technical innovation delivery in small and medium ...11… · hardie, m. (2009), ‘construction...

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TECHNICAL INNOVATION DELIVERY IN SMALL AND

MEDIUM CONSTRUCTION ENTERPRISES

By

Mary Hardie

This thesis is submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy at University of Western Sydney (UWS), Sydney, Australia.

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DECLARATION

This thesis has been prepared by me to meet the requirements of a Doctor of

Philosophy degree at the University of Western Sydney.

I declare that this thesis is my own work except where due acknowledgement is made.

It has not been submitted as a thesis or dissertation at any other institution for a

degree, diploma or any other qualification.

All possible care has been taken in the preparation of the information in this thesis

however; any liability for the accuracy and sufficiency of this information is expressly

disclaimed.

Signed

Mary Hardie

Date

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ACKNOWLEDGMENTS

The subject of this thesis is the creative effort involved by small and medium-sized

construction companies in delivering technical innovation. The time and assistance

provided by the busy managers of these companies is gratefully acknowledged, as is

the support of industry and professional bodies in the construction sector in the

identification of suitable innovative companies.

Invaluable advice in the preparation of this thesis has been provided by my colleagues

at the University of Western Sydney, most notably by my supervisors Associate

Professor Jonathon Allen, Professor Graeme Newell and Dr. Swapan Saha. Dr. Karen

Manley of Queensland University of Technology provided guidance and

encouragement, as did several former colleagues at UWS, notably Professor Alan

Jeary and Associate Professor Graham Miller.

Lastly I would like to thank my family and recognise their support. My husband

Larry Hardie provided unfailing good humour and a down-to-earth attitude which

helped to keep things in perspective. Our adult children, Alice, James and Benedict

were constant in their encouragement and understanding. My late parents, Leo and

Kathleen Roche instilled in all their children the belief that education is worth the

effort and can provide the opportunity for personal fulfilment.

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PREFACE

The work described herein was undertaken by the candidate in the School of

Engineering, UWS. The candidate was supervised by Associate Professor Jonathon

Allen, Professor Graeme Newell and Dr. Swapan Saha during the period from

January 2008 to December 2010. In addition, in the early stages, Professor Alan

Jeary supervised the candidate.

The thesis has been supported by papers that have been submitted for consideration,

accepted or published in international journals and conferences. The papers

concerned are listed below along with some citations for the early work.

Book chapters

Manley, K., Hardie, M. and Kajewski, S. (2009), ‘Innovation drivers for the built environment’, In Technology, Design and Process Innovation in the Built Environment, P. Newton, K. Hampson and R. Drogemuller Eds. Taylor and Francis, London.

Hardie, M. and Manley, K. (2008), ‘Exemplars of successful innovation delivery by small and medium construction enterprises.’ In "Clients Driving Innovation: Benefiting from Innovation", Hampson, K. ed. CRC Construction Innovation, Brisbane.

Refereed journal articles

Wong, P.S.P., Cheung, S.O., Yiu, R.L.Y. and Hardie, M. (2012), ‘The unlearning dimension of organizational learning in construction projects’, International Journal of Project Management,30 (1), 94-104.

Hardie, M. and Newell, G. (2011), ‘Factors influencing technical innovation in construction SMEs: an Australian perspective’, Engineering Construction and Architectural Management, 18 (6), 618-636.

Hardie, M. (2010), ‘Influences on innovation in small Australian construction businesses’, Journal of Small Business and Enterprise Development, 17 (3), 387-402.

Hardie, M. (2010), ‘Rainwater storage gutters for houses’, Sustainability, 2(1), 266-279.

Hardie, M. and Saha, S. (2009), 'Builders' perceptions of lowest cost procurement and its impact on quality', Australasian Journal of Construction Economics and Building, 9(1), 1-8.

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Refereed conference papers

Hardie, M. (2009), ‘Construction industry culture and innovation: An Australian perspective’, Global Innovation in Construction Conference, Loughborough University, UK. pp 106-116.

Hardie, M. and Manley, K. (2008), ‘Enabling factors for innovation in small business.’ Third International Conference of the Cooperative Research Centre for Construction Innovation Clients Driving Innovation: Benefiting from Innovation’, CRC Construction Innovation, Surfers Paradise, Queensland, 12 - 14 March 2008.

The following publications derived from research in the area of construction

innovation undertaken before enrolment for this thesis:

Refereed journal articles

Hardie, M., Miller, G., Manley, K. and McFallan, S. (2006), ‘Innovation performance and its impact on profitability among different sectors in the Australian construction industry.’ Australian Journal of Construction Economics and Building, 6(1), 1-11.

Refereed conference papers

Hardie, M., Miller, G., Manley, K. and McFallan, S. (2005), ‘Experience with the management of technological innovations within the Australian construction industry.’ Proceedings of PICMET '05 Conference, Portland, Oregon, USA.

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The publications mentioned above have received the following citations in refereed

publications:

For PICMET paper 2005

Gambatese, J.A. and Hallowell, M. (2011), 'Factors that influence the development and diffusion of technical innovations in the construction industry ', Construction Management and Economics 29 (5), 507-17.

Son, H., Kim, C., Kim, H, Han, S.H., and Kim, M.K. (2010), ‘Trend analysis of research and development on automation and robotics technology in the construction industry’ KSCE Journal of Civil Engineering 14 (2), 131-139.

Manley, K., McFallan, S., and Kajewski, S. (2009), ‘Relationship between Construction Firm Strategies and Innovation Outcomes’, Journal of Construction Engineering and Management-ASCE, 135 (8), 764-71.

Manley, K. and McFallan, S. (2008), ‘Business Strategies Supporting Effective Implementation of Innovation by Project-Based Firms’, Academy of Management 2008 Annual Meeting, Anaheim, U.S., August 8 to 13

Correa, C. L., Yepes, V., and Pellicer, E. (2007), "Determinant issues and proposals for the management of innovation in construction companies." Revista ingeniería de construcción, 22(1), 5-14.

Manley, K. and McFallan, S. (2005), The Relationship between Business Strategies and Successful Innovation TASA Conference 2005, University of Tasmania, 6-8 December 2005. Available at: http://www.tasa.org.au/conferencepapers05/papers%20(pdf)/work_manley.pdf

For CRC conference paper 2008

Colesca, S.E. and Dobrin, C. (2009), 'A review of the literature on the determinants of innovation', Review of International Comparative Management, 2, 763-68.

Construction Engineering and Management Group UNB CEM Project: NSCSC-1 (2010), 'Functional Information Technology Phase 1 Detailed Analysis', Department of Civil Engineering, University of New Brunswick, New Brunswick, Nova Scotia.

http://www.tasa.org.au/conferencepapers05/papers%20(pdf)/work_manley.pdf

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TABLE OF CONTENTS

TECHNICAL INNOVATION DELIVERY IN SMALL AN D MEDIUM CONSTRUCTION ENTERPRISES ................................................................. I

DECLARATION ......................................................................................................... ii

ACKNOWLEDGMENTS .......................................................................................... iii

PREFACE ................................................................................................................... iv

TABLE OF CONTENTS ........................................................................................... vii

LIST OF FIGURES .................................................................................................. xiv

LIST OF TABLES ................................................................................................... xvii

LIST OF ABBREVIATIONS ..................................................................................... xx

EXECUTIVE SUMMARY ...................................................................................... xxi

CHAPTER 1 INTRODUCTION ............................................................................. 1

1.1 Background .......................................................................................................... 1

1.2 Research aim and objectives ................................................................................ 4

1.3 Significance ......................................................................................................... 5

1.4 Research methodology ......................................................................................... 6

1.5 Structure of the thesis .......................................................................................... 6

1.6 Limitations ........................................................................................................... 8

1.7 Conclusion .......................................................................................................... 9

CHAPTER 2 THE RESEARCH CONTEXT ...................................................... 11

2.1 Construction industry culture and innovation .................................................... 11

2.1.1 Is construction unique? .......................................................................... 12

2.1.2 Importance of the construction industry ................................................ 14

2.1.3 The need for change .............................................................................. 15

2.2 Resistance to change .......................................................................................... 18

2.2.1 Many very small businesses and independent workers ......................... 19

2.2.2 Insecurity of employment ...................................................................... 20

2.2.3 Tacit nature of industry knowledge ....................................................... 20

2.2.4 Lack of human resource management expertise ................................... 21

2.2.5 Risk shifting .......................................................................................... 22

2.2.6 Project-based nature of the industry ...................................................... 22

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2.2.7 Lowest price procurement ..................................................................... 23

2.2.8 Supply chain complexity ....................................................................... 23

2.2.9 Resistance to standardisation ................................................................. 24

2.2.10 Industry self-perception – the theory of construction............................ 25

2.3 Theories of invention and innovation ................................................................ 26

2.3.1 The significance of the individual inventor/innovator .......................... 28

2.3.2 The significance of the entrepreneur ..................................................... 29

2.3.3 Technology leadership .......................................................................... 29

2.3.4 Innovation funding ................................................................................ 30

2.4 Innovation definitions and statistics .................................................................. 31

2.4.1 The Oslo Manual and its scope ............................................................. 31

2.4.2 Products versus services ........................................................................ 32

2.4.3 Firm level focus ..................................................................................... 32

2.4.4 Technological versus other kinds of innovation .................................... 33

2.4.5 ‘New to the firm’ innovation diffusion ................................................. 33

2.4.6 Technical and organisational innovation ............................................... 34

2.4.7 Australian Bureau of Statistics Survey .................................................. 34

2.4.8 BRITE Survey ....................................................................................... 37

2.5 SME definition in the Australian context .......................................................... 38

2.5.1 Construction SME contribution to GDP ............................................... 40

2.5.2 Characteristics of construction SMEs ................................................... 42

2.6 Taxonomy of construction innovation ............................................................... 43

2.7 Construction innovation literature ..................................................................... 45

2.7.1 Five major categories of factors affecting technical innovation ........... 47

2.8 Company resources ............................................................................................ 48

2.8.1 Personal motivation ............................................................................... 49

2.8.2 Available financial resources ................................................................ 50

2.8.3 Available time ....................................................................................... 50

2.8.4 Available skill levels ............................................................................. 51

2.8.5 Insurance/risk ........................................................................................ 52

2.9 Client and end-user influences ........................................................................... 53

2.9.1 Procurement systems ............................................................................. 54

2.9.2 Client characteristics ............................................................................. 56

2.10 Project-based conditions .................................................................................... 57

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2.10.1 Supply chain relationships ..................................................................... 58

2.10.2 On site problem solving ........................................................................ 59

2.10.3 Occupational health and safety (OH&S) improvement......................... 59

2.11 Industry networks .............................................................................................. 60

2.11.1 Professional and industry associations .................................................. 61

2.11.2 Research organisations and universities ................................................ 63

2.12 Regulatory climate ............................................................................................. 64

2.12.1 Performance-based standards ................................................................ 64

2.12.2 Industry standards .................................................................................. 66

2.12.3 Local government regulations ............................................................... 66

2.13 Summary of results from the literature review .................................................. 67

CHAPTER 3 RESEARCH METHODOLOGY ................................................... 70

3.1 Mixed methodology research ............................................................................. 70

3.1.1 Debate over quantitative research in construction management ........... 71

3.1.2 ‘Paradigm wars’ .................................................................................... 72

3.1.3 The case for mixed methods in a developing discipline........................ 73

3.2 Mixed method strategies .................................................................................... 74

3.2.1 Evaluation of strategies ......................................................................... 76

3.3 Selection of qualitative method ......................................................................... 77

3.3.1 Structured interviews ............................................................................. 77

3.3.2 Ethnographic studies ............................................................................. 78

3.3.3 Grounded theory .................................................................................... 79

3.3.4 Action research ...................................................................................... 79

3.3.5 Content analysis techniques .................................................................. 80

3.3.6 Case studies ........................................................................................... 80

3.4 Selection of quantitative method ....................................................................... 81

3.4.1 Statistically representative questionnaires ............................................. 81

3.4.2 Computer simulations ............................................................................ 82

3.4.3 Goal-oriented decision-making ............................................................. 82

3.5 Methodology for evaluating convergence in the data sets ................................. 82

CHAPTER 4 DECISION MAKING METH ODOLOGIES ............................... 84

4.1 Decision making problems ................................................................................ 84

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4.2 Multi Criteria Decision Making (MCDM) methodologies ................................ 87

4.2.1 Ranking methodologies ......................................................................... 88

4.2.2 Cut-off methodologies ........................................................................... 90

4.2.3 Prioritizing of alternatives methodologies ............................................ 90

4.2.4 Scoring methodologies .......................................................................... 91

4.2.5 Elimination methodologies .................................................................... 92

4.2.6 Ideal solution methodologies ................................................................. 94

4.2.7 Weighted comparison methodologies ................................................... 94

4.2.8 Alternative preference methodology ..................................................... 95

4.3 Selection of AHP methodology ......................................................................... 99

CHAPTER 5 SURVEY OF TECHNICAL INNOVATORS IN CONSTRUCTION SMES ............................................................................. 101

5.1 AHP Value Tree ............................................................................................... 101

5.2 Selection of survey respondents ...................................................................... 103

5.3 Characteristics of survey respondents .............................................................. 104

5.4 Patents on technical innovations ...................................................................... 107

5.5 Detailed methodology for survey .................................................................... 109

5.5.1 Step 1: The decision hierarchy ............................................................ 112

5.5.2 Step 2: Data collection ........................................................................ 114

5.5.3 Step 3: Estimates of weightings .......................................................... 114

5.5.4 Step 4: Aggregation of results ............................................................. 116

5.6 Survey data analysis software .......................................................................... 116

5.7 Inconsistency in survey response ..................................................................... 116

5.8 ANOVA for sample sub-groups ...................................................................... 118

5.9 Regression and correlation ............................................................................... 118

5.10 Other information collected at the time of the survey ..................................... 120

5.11 Survey process and time-frame ........................................................................ 123

5.12 Face-to-face surveys ........................................................................................ 128

CHAPTER 6 ANALYSIS OF FACTORS AFFECTING INNOVATION DELIVERY ..................................................................................................... 131

6.1 Survey results for the whole sample ................................................................ 131

6.2 Sub-factor weightings ...................................................................................... 134

6.3 Sub-groups within the overall sample ............................................................. 138

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6.4 Small versus medium business results ............................................................. 138

6.5 Building product versus building process innovators ...................................... 143

6.6 Patent holders versus non-patent holders ......................................................... 148

6.7 Preliminary results summary ........................................................................... 152

6.8 ANOVA ........................................................................................................... 152

6.9 Correlation and regression ............................................................................... 160

6.10 Correlations for sample sub-groups ................................................................. 164

6.11 Regression analysis .......................................................................................... 176

6.12 Summary of statistical results .......................................................................... 181

6.13 Survey respondents open-ended comments ..................................................... 181

6.14 Limitations of the data derived from the AHP study ....................................... 187

6.14.1 Inconsistency factor in AHP ................................................................ 189

6.14.2 Some possible reasons for inconsistency in the survey results ........... 200

CHAPTER 7 SELECTED CASE STUDY EXEMPLARS OF INNOVATION DELIVERY ..................................................................................................... 202

7.1 Case study purpose statement .......................................................................... 202

7.1.1 Explanation of case study significance................................................ 203

7.1.2 Case study information ........................................................................ 203

7.1.3 Case study identity disclosure ............................................................. 204

7.2 Case study 1: Rapid setting volumetric concrete ............................................. 206

7.2.1 Slaughter’s taxonomy .......................................................................... 211

7.2.2 Strategies that support successful innovation delivery ........................ 211

7.2.3 Innovator comments ............................................................................ 213

7.2.4 Lessons from this experience .............................................................. 213

7.3 Case Study 2: Lightweight impervious concrete block ................................... 214





7.4 Case Study 3: Under floor water storage bladders .......................................... 224




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7.5 Case Study 4: Cylindrical concrete formwork tubes ....................................... 229





7.6 Case Study 5: Salt-removing sacrificial render to restore deteriorating masonry

walls ................................................................................................................. 233





7.7 Case Study 6: Rollover warning system for articulated construction plant ..... 238





7.8 Case Study 7: Dry wall noise barrier ............................................................... 241





7.9 Case study innovation results and implications ............................................... 244

7.10 Vectors affecting technical innovation ............................................................ 251

CHAPTER 8 A MODEL OF SME TECHN ICAL INNOVATION DELIVERY .......................................................................................................................... 255

8.1 Convergence of methodologies at factor level ................................................ 255

8.1.1 Regulatory climate............................................................................... 255

8.1.2 Client and end-user influences ............................................................ 256

8.1.3 Industry networks ................................................................................ 256

8.1.4 Project-based conditions ...................................................................... 257

8.1.5 Company resources ............................................................................. 257

8.2 Convergence of methodologies at sub-factor level .......................................... 257

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8.2.1 Client characteristics ........................................................................... 258

8.2.2 Improving Occupational Health and Safety ........................................ 258

8.2.3 Performance-based standards .............................................................. 259

8.2.4 Professional and industry associations ................................................ 259

8.2.5 Research organisations and universities .............................................. 259

8.2.6 Supply chain relationships ................................................................... 260

8.2.7 Personal motivation ............................................................................. 260

8.2.8 Procurement systems and solving problems on site ............................ 261

8.2.9 Available skill levels ........................................................................... 261

8.2.10 Remaining sub-factors ......................................................................... 261

8.3 Innovation delivery model ............................................................................... 262

CHAPTER 9 CONCLUSIONS AND RECOMMENDATIONS ...................... 267

9.1 A matter of pre-existing resources? ................................................................. 267

9.2 Findings for aspiring innovators in SMEs ....................................................... 269

9.3 Findings for industry bodies and professional organisations ........................... 270

9.4 Findings for researchers ................................................................................... 271

9.5 Findings for governments and regulators ........................................................ 272

9.6 Contribution of this research ............................................................................ 274

9.7 Summary of outcomes from the research objectives ....................................... 277

9.8 Future research directions ................................................................................ 278

9.9 Conclusion ....................................................................................................... 279

REFERENCES ........................................................................................................ 281

APPENDICES ......................................................................................................... 314

Appendix 1 – Survey Script ...................................................................................... 314

Appendix 2 - Participant Information Sheet ............................................................. 322

Appendix 3 – Participant Consent Form ................................................................... 324

Appendix 4 – International definitions of SMEs ...................................................... 325

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LIST OF FIGURES

Figure 1.1 Diagrammatic relationship between innovation and invention ........... 2

Figure 1.2 Proportion of businesses undertaking new goods and services

innovations ........................................................................................... 4

Figure 2.1 Taxonomy of theories of invention (Based on Kaiserfledt 2006 p.6) 27

Figure 2.2 Percentage of Innovation Active Businesses by sector 2006-2007

(ABS 2008a) ...................................................................................... 35

Figure 2.3 Percentage of Goods and Services Innovation Active Businesses by

sector 2006-2007 (ABS 2008a) ......................................................... 36

Figure 2.4 Percentage of Operational Process Innovation Active Businesses by

sector 2006-2007 (ABS 2008a) ......................................................... 37

Figure 2.5 Slaughter’s taxonomy of innovation (Based on Slaughter 1998,

p.229) .....................................................................................................

...............................................................................................................

........................................................................................................... 44

Figure 3.1 Concurrent Triangulation Strategy: Convergence Model .................. 77

Figure 5.1 Value Tree of factors affecting technical innovation in construction

......................................................................................................... 102

Figure 5.2 Sample survey question ................................................................... 109

Figure 5.3 Pair-wise comparisons from the Value Tree .................................... 110

Figure 5.4 General form of a hierarchical structure .......................................... 113

Figure 6.1 Mean weighting for Value Tree factors with 5% error bars ............ 134

Figure 6.2 Mean weighting for Value Tree sub-factors with 5% error bars ..... 135

Figure 6.3 Bar chart of small and medium-sized business average response on

factors with 5% error bars ................................................................ 140

Figure 6.4 Bar chart of small and medium-sized business average response on

sub-factors with 5% error bars ......................................................... 142

Figure 6.5 Bar chart of product and process innovators average response on


Figure 6.6 Bar chart of product and process innovators average response on sub-


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Figure 6.7 Bar chart of patent holders and non-patent holder’s average response

on factors with 5% error bars ........................................................... 150

Figure 6.8 Bar chart of patent holder’s and non-patent holder’s average response

on sub-factors with 5% error bars .................................................... 151

Figure 6.9 Scatter plot and linear trend line for ‘Personal motivation’ versus

‘Available time’ ............................................................................... 179

Figure 6.10 Scatter plot and linear trend line for ‘Available skill levels’ versus

‘Available finance’ .......................................................................... 179

Figure 6.11 Scatter plot and linear trend line for ‘Professional and industry

associations’ versus ‘Research organisations and universities’ ....... 180

Figure 7.1 Volumetric concrete mixer with separate bins for cement, sand and

aggregate .......................................................................................... 208

Figure 7.2 Mixer getting ready to pour ............................................................. 208

Figure 7.3 Pour has commenced ....................................................................... 209

Figure 7.4 Pour complete and slab being finished off ....................................... 209

Figure 7.5 Resin-based curing compound being sprayed on slab ..................... 210

Figure 7.6 One hour after the pour, the mixer truck is driven onto the new slab....

......................................................................................................... 210

Figure 7.7 Industry Open Day demonstrations held every few months ............ 212

Figure 7.8 Industry demonstrations of related products .................................... 212

Figure 7.9 Block dimensions ............................................................................. 216

Figure 7.10 Block details ..................................................................................... 217

Figure 7.11 Lightweight impervious concrete block ........................................... 218

Figure 7.12 Cut block showing polystyrene bead interior ................................... 218

Figure 7.13 Retaining wall to garage not requiring waterproofing ..................... 220

Figure 7.14 Upper storey walls under construction ............................................. 220

Figure 7.15 Block wall under construction showing closer blocks ..................... 221

Figure 7.16 Internal wall face to be finished with plasterboard .......................... 221

Figure 7.17 Building design to incorporate sub-floor water bladders ................. 226

Figure 7.18 Water bladder compartments in sub-floor space .............................. 226

Figure 7.19 WaterCell® being installed .............................................................. 227

Figure 7.20 Full WaterCell® in place ................................................................. 227

Figure 7.21 Formwork tube being put in place ................................................... 230

Figure 7.22 Formwork tube being removed ........................................................ 231

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Figure 7.23 Fort Denison in Sydney Harbour ..................................................... 234

Figure 7.24 Salt affected stonework .................................................................... 234

Figure 7.25 Elizabeth Farmhouse in Parramatta, NSW (c 1790), one of the oldest

European structures in Australia ...................................................... 235

Figure 7.26 Sacrificial render in place at Elizabeth Farmhouse and later being

peeled off ......................................................................................... 235

Figure 7.27 Rollover management system .......................................................... 239

Figure 7.28 Cut away model of QuietWave® wall .............................................. 242

Figure 7.29 QuietWave® compared to other sound reducing walls in current use ...

......................................................................................................... 242

Figure 7.30 Vectors of SME technical innovation .............................................. 252

Figure 8.1 A model of technical innovation by construction SMEs ................. 264

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LIST OF TABLES

Table 2.1 Numbers of businesses in construction .............................................. 39

Table 2.2 Construction industry contribution to Industry Value Added (IVA)

2006-2007 (ABS 2008b) .................................................................... 41

Table 2.3 Construction industry contribution to sales and service income 2006-

2007 (ABS 2008b) ............................................................................. 41

Table 2.4 Occurrence of construction innovation themes.................................. 46

Table 4.1 Comparison of methodologies (Ranking methodologies, cut-off

methodologies, prioritising of alternatives methodologies)............... 97

Table 4.2 Comparison of methodologies (Scoring methodologies, elimination

methodologies, ideal solution methodologies, qualitative data

methodologies, alternative preference methodologies) ..................... 98

Table 5.1 Source of survey respondents .......................................................... 106

Table 5.2 Classification of survey respondents ............................................... 107

Table 5.3 Descriptions of innovations studied ................................................. 108

Table 5.4 The fundamental scale verbal descriptions of pair-wise comparisons

in AHP ............................................................................................. 111

Table 5.5 Descriptors for survey open-ended comments ................................. 122

Table 5.6 Synonyms/prompt words/explanations for Value Tree factors ....... 124

Table 5.7 Synonyms/prompt words/explanations for Value Tree sub-factors of

company resources ........................................................................... 125


client and end-user influences .......................................................... 126


project-based conditions .................................................................. 126


industry networks ............................................................................. 127


the regulatory climate ...................................................................... 127

Table 5.12 AHP studies based on selected expert samples ............................... 129

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Table 6.1 AHP weightings for factors affecting SME technical innovation

delivery ..................................................................................................

......................................................................................................... 132

Table 6.2 Technical innovation delivery multi-criteria decision-making priority

summary ........................................................................................... 136

Table 6.3 AHP weightings: small versus medium-sized businesses ............... 139

Table 6.4 AHP weightings: product versus process innovators ...................... 144

Table 6.5 AHP weightings: patent holders versus no patents .......................... 149

Table 6.6 Results from ANOVA on factors by company size ......................... 153

Table 6.7 Significant results from ANOVA on factors by innovation type .... 154

Table 6.8 Significant results from ANOVA on factors by patent .................... 155

Table 6.9 Results from ANOVA on sub-factors by company size .................. 157

Table 6.10 Results from ANOVA on sub-factors by innovation type ............... 158

Table 6.11 Results from ANOVA on sub-factors by patent holding ................. 159

Table 6.12 Correlations between factors for the whole sample ......................... 161

Table 6.13 Correlations between sub-factors – whole sample........................... 162

Table 6.14 Correlations between factors for the small and medium business sub-

groups ............................................................................................... 165

Table 6.15 Correlations between factors for the product and process innovator

sub-groups ........................................................................................ 166

Table 6.16 Correlations between factors for patent holder and no patent sub-

groups .....................................................................................................

...............................................................................................................

......................................................................................................... 167

Table 6.17 Correlations between sub-factors for the small business sub-group 170

Table 6.18 Correlations between sub-factors for the medium business sub-group

......................................................................................................... 171

Table 6.19 Correlations between sub-factors for the product innovator sub-group

...............................................................................................................

......................................................................................................... 172

Table 6.20 Correlations between sub-factors for the process innovator sub-group.

...............................................................................................................

......................................................................................................... 173

Table 6.21 Correlations between sub-factors for the patent holder sub-group .. 174

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Table 6.22 Correlations between sub-factors for the non-patent holder sub-group.

...............................................................................................................

......................................................................................................... 175

Table 6.23 Regression values for factor pairs .................................................... 177

Table 6.24 Regression values for sub-factor pairs ............................................. 178

Table 6.25 Common economic themes in the open-ended comments by survey

respondents ...................................................................................... 183

Table 6.26 Common relationship themes in the open-ended comments by survey

respondents ...................................................................................... 184

Table 6.27 Common structural themes in the open-ended comments by survey

respondents ...................................................................................... 186

Table 6.28 Inconsistency factors ........................................................................ 190

Table 6.29 Standard Deviation of AHP factor weightings ................................ 192

Table 6.30 Standard Deviation of AHP subfactor weightings ........................... 193

Table 6.31 Standard Deviation of AHP factor weightings for small and medium

sized businesses ............................................................................... 194

Table 6.32 Standard Deviation of AHP sub-factor weightings for small and

medium sized businesses ................................................................. 195

Table 6.33 Standard Deviation of AHP factor weightings for product and process

innovators ......................................................................................... 196

Table 6.34 Standard Deviation of AHP sub-factor weightings for product and

process innovators ............................................................................ 197

Table 6.35 Standard deviation of AHP factor weightings for patent holders and

non-patent holders ............................................................................ 198

Table 6.36 Standard Deviation of AHP factor weightings for patent holders and

non patent holders ............................................................................ 199

Table 7.1 Comparison of blocks with alternatives available ........................... 222

Table 7.2 Case study company characteristics................................................. 245

Table 7.3 Case study innovation characteristics .............................................. 246

Table 7.4 Descriptive innovation categories .................................................... 248

Table 7.5 Prime reason for successful innovation delivery ............................. 249

Table 7.6 Case study descriptions .................................................................... 250

Table 7.7 Drivers of SME technical innovation development ......................... 253

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LIST OF ABBREVIATIONS

ABS Australian Bureau of Statistics

AHP Analytic Hierarchy Process

AIB Australian Institute of Building

AIQS Australian Institute of Quantity Surveyors

ASTM American Society for Testing and Materials

ATS Australian Technology Showcase

BRANZ Building Research Australia and New Zealand

BRITE Building Research on Innovation Technology and Environment

CCF Civil Contractors Federation

CRC CI Cooperative Research Centre for Construction Innovation

CSIRO Commonwealth Scientific and Industrial Research Organisation

EA Engineers Australia

GDP Gross Domestic Product

MBA Master Builders Association

MCDM Multi Criteria Decision Making

NATA National Association of Testing Authorities

OECD Organisation for Economic Cooperation and Development

OH&S Occupational Health and Safety

SBA United States Small Business Administration

SME Small and Medium-sized Enterprise

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EXECUTIVE SUMMARY

This study investigates occurrences of technical innovation successfully delivered by

Small and Medium Enterprises (SMEs) in the construction industry in the Greater

Sydney area. A literature search identified five factors that potentially affect the

delivery of technical innovation. These can be summarised under the headings:

• Company resources;

• Client and end-user influences;

• Project-based conditions;

• Industry networks;

• The regulatory climate.

Under each factor, several related sub-factors were also identified.

Mixed method research

Because the management of innovation essentially involves a human element, it was

decided that a mixed methods approach would be taken. Any convergences that

emerge in the results from the different research strategies can be seen as equating to

robustness in the conclusions that may be drawn.

Purposive sampling was used to identify potential respondents to a quantitative

survey. The main eligibility criterion was a proven track record in delivering a

significant technical innovation in the construction market. As the surveys were

carried out face-to-face, respondents were restricted to locations in the greater Sydney

region and the western hinterland as far as Bathurst in regional NSW. The

information contained in the surveys was de-identified for ethical reasons and only

aggregate data is presented in this thesis.

Seven illustrative case studies which represent the storylines of successful innovation

delivery are presented in this thesis. All the technical innovations studied involve

significant measurable improvements which may be measured in economic,

environmental or social terms and some represent improvements in multiple fields.

The case studies were chosen because they represent unique examples of a relatively

rare phenomenon; that is, the successful delivery of a high-level technical innovation

xxii

by a SME construction company. Information on the seven case studies was gathered

from multiple sources including trade literature, industry-focused magazines,

company websites and personal observation. The case studies were classified by

descriptive innovation categories depending on whether the innovation was

considered to be proactive or reactive, bounded or unbounded, and intuitive or

analytical.

Research contribution

The principal finding of this research is that specific areas of expertise beyond that of

construction technology are essential to the successful delivery of a technical

innovation in construction. In other words, superior technical skills are a necessary,

but not a sufficient, condition for the effective delivery of a technical innovation.

Soft-skills relating to people management and networking are critical to the delivery

process, as are a high degree of economic understanding, marketing and business

planning skills. A great idea for a technical innovation is not enough in itself to

produce a delivered technical innovation. The great idea needs to be supported by

adequate investment, effective research development and testing, strong linkages with

intra-industry groups and timely delivery into the market. The successful innovators

studied in this research have all managed in one way or another to acquire this

diversity of skill-sets. This is potentially useful information for policy-makers, as

well as for those individuals seeking to improve his or her company’s innovation

performance.

1

CHAPTER 1 INTRODUCTION

Chapter 1 describes the history of innovation theory and its importance to economic

performance. It reports on the relative lack of current research attention given to

small and medium enterprises (SMEs) in Australian construction. The significance

and value of the issue of improving innovation performance in construction SMEs is

explained. Finally, the chapter gives an outline of the objectives and structure of the

remainder of the thesis.

1.1 Background

Although the term ‘innovation’ is often used loosely in general discourse, there is an

extensive and specific body of literature on the topic in academic journals.

Nevertheless, as Drucker (2007) pointed out, many people and even many businesses

equate innovation with inspiration, and entrepreneurship with good luck (Drucker

2007 p.xv). This thesis will address the discipline of innovation from the perspective

of established economic and management theory rather than popular culture. Afuah

(2003) defined general technological innovation as the application of knowledge

about tools, materials, processes and techniques to problem solving. Innovation is

widely recognised as an iterative process rather than a singular event; the process

involves an extended set of activities that translate new knowledge into something of

value (Bessant and Venables 2008). In market economies, technological innovation

creates economic value by allowing firms to use their resources more efficiently, as

well as, meeting people’s needs in ways they were not met before (Shane 2008).

Technical innovation in industries like construction represents a sub-set of broader

technological change in the larger economy. As described by Slaughter (1998),

technical innovation in construction is ‘the actual use of a non-trivial change and

improvement in a product, process or system’ (Slaughter 1998, p.225). An innovation

does not have to be an invention; that is, it does not necessarily involve a detailed

design that is novel with regard to existing knowledge and practice. Incremental

innovation and innovations that cannot be closely defined as an object or process are

classified as innovation, even though instances may be difficult to identify as discrete

2

events. Innovation includes patented inventions if they are successfully delivered, but

if original inventive ideas remain unrealised, they are not classified as innovations.

The scope of innovation is, therefore, considerably broader than invention in the sense

that it includes changes that are simply new to the institution developing the change,

rather than unique and new to the whole world. The term invention applies to unique

and original ideas with demonstrably practical implications. There are many reasons

why an invention may never be successfully realised in the marketplace. These may

relate to cost, competition, timeliness and its interoperability with existing systems.

The intersection between invention and innovation consists of new and unique ideas

successfully delivered in a real life context: the ‘inventive innovation’ or the

‘innovative invention’ depending on classifier emphasis. This relationship is

illustrated in Figure 1.1 below. As Bessant and Venables have explained:

“... innovation is a process − an extended set of activities that

translate new knowledge into something of value. It isn’t ... simply a

matter of a ‘Eureka!’ moment, but rather a long and painstaking

process of translating the initial idea into something useful − and

used” (Bessant and Venables 2008 p.3).

Figure 1.1 Diagrammatic relationship between innovation and invention

3

The effectiveness of innovation theory as both a generator and a supporter of business

success has been noted in the wider economic literature for many decades (Tidd and

Bessant 2009). The practice of fostering innovative activity as a way of improving

business performance and maintaining growth has long been an acknowledged part of

market economics, stemming from the pioneering work of J.A. Schumpeter in the first

half of the twentieth century (Schumpeter 1934; Schumpeter 1942). Schumpeter

observed a circular flow (‘kreislauf’ in the original German) to be the underlying

pattern of economic life. A degree of constancy in this circular flow pattern is

achieved, because the action of the law of supply and demand tends toward a state of

equilibrium. Schumpeter declared that “Economic activity may have any motive,

even a spiritual one, but its meaning is always the satisfaction of wants.” (Schumpeter

1934, p.10). It is the harnessing of a combination of productive forces including

natural resources and human labour that produce economic benefit. Innovation is the

spontaneous and discontinuous change which alters the previously existing

equilibrium of circular flow. Schumpeter (1942) described this process as the “gales

of creative destruction” that supplant outdated practices and introduce new and more

efficient modes of operation. Winch (1998), wryly and more circumspectly,

described the process in residential construction, as one of “zephyrs of creative

destruction”. Whatever the perceived impact, the process must be one of continual

adjustment, because as wants are satisfied intensity of desire or ‘demand’ lessens.

The primary incentive for entrepreneurial activity and innovation is that it provides

the opportunity for participating in economic gain as a result of the disturbance of the

pre-existing equilibrium flow.

There remains some general resistance to innovation theory in some areas of industry

and commerce generally. This resistance is mainly based around industry culture,

learning behaviour and absorptive capacity (Henderson and Ruikar 2010; Morton and

Burns 2008; Walker and Peansupap 2003). Nevertheless, the manufacturing sector

has adopted the theory and practice of innovation with considerable enthusiasm over

several decades (Bessant and Grunt 1985; Nonaka and Takeuchi 1995; Tushman and

Moore 1988; Tushman and Anderson 2004). The construction industry, however, has

been relatively slow to incorporate innovation as an industry goal, despite some early

prompting in that direction by economists like Bowley (1960). This

underperformance on measures of innovation is illustrated in the Australian context

4

by an Australian Bureau of Statistics Report from 2005 which produced the graph

shown as Figure 1.2 (ABS 2005). It is partly due to the perception that construction is

innately different from other industries and partly due to a continuing level of

conservatism about change initiated from outside the industry (Reichstein et al. 2005;

Winch 2003).

Figure 1.2 Proportion of businesses undertaking new goods and services innovations

(Source: ABS 8163.0 Patterns of Innovation in Australian Businesses 2005)

Nevertheless, in the last few decades, researchers such as Nam, Tatum, Slaughter and

Gann have sought to interpret innovation theory in the context of the construction

industry (Gann 1997; Gann 2001; Nam and Tatum 1992; Slaughter 1993; Tatum

1984).

1.2 Research aim and objectives

The main research aim of this thesis is to perform a systematic study of successful

construction SME innovations and the strategies adopted for their delivery, with the

intention of yielding useful lessons for other businesses wishing to improve their own

innovation performance. The research question is that will be addressed is “What are

5

the factors which affect technical innovation by construction industry SMEs?”. In

addition, this thesis has the following specific objectives:

• Identify a series of possible factors which impact on the successful delivery of

a technical innovation by a construction SME;

• Prioritise those factors via a structured survey of successful SME innovators;

• Illustrate the survey outcome by descriptive case studies of successful

innovation delivery;

• Provide encouragement for interested parties such as other construction SMEs

who are considering introducing a technical innovation;

• Provide advice for government bodies, professional and industry associations

who wish to foster a culture of innovation in the construction industry;

• Indicate possible strategies for universities and other research institutions on

how they can best contribute to SME innovation.

These objectives will be addressed in this thesis by means of a systematic study of the

holistic storyline of instances of successful innovation delivery.

1.3 Significance

The intended contribution of this thesis is to address the, as yet, under-researched area

of technical innovation in Australian construction industry SMEs. In doing so, the

thesis will generate some insights into the complexity of the innovation delivery

process. As Tidd and Bessant (2009) report, innovation is important, not only for its

critical contribution to the survival of individual firms, but also for the ongoing

prosperity of national and global economies. Priority areas which have the most

impact on a successful innovation delivery will be identified in this thesis. This

knowledge is useful to the successful innovators themselves, as an affirmation of their

strategies and processes. The dissemination of such knowledge provides

encouragement for potential innovators who are able to see the pathways taken by

SME innovators in the past. It can also provide guidance for others with an interest in

improving the overall performance of the construction industry sector in the national

economy.

6

1.4 Research methodology

As construction management research involves the observation of human activity, it

cannot be readily reduced to a strictly quantitative research problem. The subject of

this research process is the actions of successful innovators. It is, therefore, important

that multiple methods of data collection are used in the observation. It is also

important to ensure that the research methodology takes account of potential

strategies such innovators may use to influence the research outcome (Leiringer and

Cardellino 2008). In order to do this, a mixed method strategy involving both

quantitative and qualitative methodologies is employed. The methodological options

considered are discussed in detail in Chapter 3. Mixed methods research aims to

achieve triangulation of the research subject by addressing it from multiple

viewpoints. If convergences are detected in the findings from the different

methodological strategies, this can equate to robustness in the findings of the

research.

1.5 Structure of the thesis

This study will attempt to determine the major enabling factors that allow some

Australian SMEs in construction to generate or adopt technical innovations. Mixed

methodology techniques involving both quantitative and qualitative strands will be

used to approach the research question from differing points of view. It is contended

that an approach that mixes an anonymous statistical survey with qualitative named

case studies of specific technical innovations is likely to generate a fuller picture of

factors impacting on technical innovation delivery, than would result from either

approach by itself.

Chapter 2 of this thesis examines the research context of this study. Major

impediments to change in the industry have been identified. Factors that may have an

impact on the delivery of technical innovation are discussed in a review of the

scholarly literature on the topic.

7

The case for mixed methods research in construction management is made in Chapter

3. Several methodologies that were considered are evaluated for their fitness to

answer the research question and the preferred strategies are explained.

It is considered that the choice of whether or not to adopt a technical innovation can

be considered as a classic ‘decision-making’ problem. This is especially true in small

businesses where an individual chief decision maker has to evaluate many competing

and incommensurate factors when deciding to generate or to adopt a technical

innovation. Numerous quantitative methodologies exist under the heading of Multi

Criteria Decision Making for addressing such situations and these are studied and

evaluated in Chapter 4.

The validity and relative importance of the factors identified from the literature

review was tested by a statistical survey of independently acknowledged successful

innovators in Australian construction SMEs using the identified methodology. The

survey format is reported in Chapter 5 along with an explanation of the selection

criteria for the participants.

Analysis of the survey participants’ responses comprises the topic of Chapter 6. The

collected data forms the basis of a critical evaluation of alternate strategies for

supporting innovation activity. Factor priorities are established by aggregation of the

survey data, both for the whole sample and for sub-groups within the sample.

Statistical tests were undertaken to assess the significance and the validity of the

derived priorities.

Qualitative case study examples of selected innovation delivery are described in

Chapter 7. The case studies provide accessible storylines of the innovation process in

order to qualitatively substantiate the data collected in the quantitative study. They

are descriptive and elucidatory in nature, in order to meet the research objective of

providing indicative strategies for those companies wishing to improve their

performance. In a sense, the case studies represent a triangulation of the results

gleaned from the literature review and the statistical survey.

Chapter 8 analyses convergences between the results of the quantitative survey and

the qualitative case studies. A simplified model of successful technical innovation

delivery by construction SMEs is introduced. The model represents an attempt to

8

explain the essential characteristics of successful technical innovation by SME

construction companies.

Finally, Chapter 9 gives the research conclusions and recommendations of the

appropriate course of actions both for SMEs who wish to lift their innovation

performance, as well as for government bodies and industry organisations hoping to

foster an increase in innovation delivery and diffusion. Strategies have been

evaluated from the point of view of a business wishing to raise its innovation level,

but also from the perspective of industry associations, professional bodies and

government regulators who may want to actively foster innovative performance.

Potential avenues for further research which could be tested in a larger and more wide

ranging study have been suggested.

1.6 Limitations

Much of the currently published work on innovation and construction in small

businesses has come from researchers at the University of Salford in the United

Kingdom (Abbott et al. 2006; Barrett and Sexton 2006; Sexton and Barrett 2003a;

Sexton and Barrett 2003b; Sexton and Barrett 2004; Sexton et al. 2006). Their

research has noted that “Small construction firms have their own distinctive

characteristics, which are profoundly different from those of large construction firms”

(Sexton and Barrett 2003, p.623). One of the questions addressed was the external

and internal events that trigger innovation activity in the small construction firm. The

importance of owners’ attitudes, as well as the need for incremental exposure to new

systems, has been suggested as important areas for consideration. Changing client

needs and unanticipated project conditions were identified as triggers for innovation

activity in small construction firms. Other researchers from Salford have used action

learning techniques to assist construction SMEs to tackle problems and develop

solutions (Davey et al. 2004). In addition, Hari et al. (2005) have used a grounded

theory approach, as defined by Glaser and Strauss (1967), to study knowledge capture

in UK construction SMEs. In the United States, the relationship between residential

builders and technical innovation has been closely observed (Toole 1998; McCoy et

al. 2008; McCoy et al. 2009; McCoy et al. 2011).

9

To date, no large, comparable body of research into small construction businesses and

innovation in Australia has been uncovered, other than some notable exceptions in the

work of Manley (2008) and Thorpe et al. (2009). As a result, this research is

necessarily explorative in nature. It examines successful instances of technical

innovation within a limited period bounded by the greater Sydney metropolitan area

and its hinterland. The sample of innovators studied may not prove to be typical of

SME innovation throughout Australia. It can only be said to represent a systematic

collection of data from a limited place and time. The suitability of the results for

broader generalisation will be subject to the outcome of future comparative studies.

1.7 Conclusion

The research presented in this thesis represents a substantial and original contribution

to the study of innovation delivery in SMEs in the Australian context. This author has

worked for several decades in small and medium-sized construction businesses in

Australia and consequently sees the possibilities and pitfalls of such businesses from

an insider’s perspective. Research aimed at acquiring a better understanding of the

factors that encourage small construction firms to innovate can be anticipated to have

economic, environmental and social benefits.

Innovation theory has been broadly acknowledged as both a generator and a supporter

of industry performance over many years. Encouraging the rate of innovative activity

in order to improve profitability and quality of output has been an axiom of market

economics since the previously mentioned work of Schumpeter (Schumpeter 1934;

Schumpeter 1942). The manufacturing sector in most market-based economies has

wholly adopted the theory and process of innovation. The construction industry,

however, has a tendency to resist economic theory generated in other areas and often

sees itself as a unique case which cannot be appropriately compared to other sectors

(Reichstein et al. 2005; Winch 2003). This is partly due to the fragmented, combative

and project-based nature of the industry, but also to a strong innate tendency to avoid

unnecessary change. Several authors have addressed the issue of innovation in

construction internationally (Gann 1997; Gann 2001; Nam and Tatum 1992; Nam and

Tatum 1997; Slaughter 1993; Slaughter 1998; Slaughter 2000; Tatum 1984; Tatum

1987). In Australia, this work has been taken up by several researchers at the

10

Australian Cooperative Research Centre for Construction Innovation (CRCCI);

notably Hampson, Sidwell, Manley and Thorpe (Hampson and Tatum 1997; Manley

and McFallan 2006; Manley 2008; Sidwell et al. 2001; Thorpe et al. 2009; Walker et

al. 2003).

As a result, there exists a significant body of scholarly literature concerning matters

affecting the theory and practice of construction innovation. This existing body of

work is the subject of the literature review in Chapter 2 of this thesis. With some

notable exceptions, this literature has tended to concentrate its study on large

construction projects and large construction enterprises. Relatively little attention has

been paid to small and medium-sized construction companies, despite this sector

forming the greater part of the industry in terms of employment and a significant

component in terms of market value. It is surprising, given both the significance of

the industry and the high percentage of SMEs that it contains, that there has not been

a great deal of research into the factors that enable construction SMEs to survive,

prosper and grow into successful and innovative enterprises. An extensive review of

papers on construction innovation covering the past two decades in scholarly journals

has identified more than 500 refereed journal articles dealing with innovation in

construction. Only twelve of these have dealt specifically with small business

innovation. It is this identified gap in the transfer of the value of innovation theory to

the Small and Medium Enterprise in construction that is to be addressed by this

research.

While the history of every company which achieves successful adoption and delivery

of an innovative practice is clearly different in detail, it is speculated that there are

some features which such firms have in common. The identification of these

common features is useful to the firm itself as a validation of their own choices and

practices but, more importantly, it can provide some suggestions for other companies

wishing to lift their performance. Government and industry bodies may also benefit

from the knowledge of the factors that are likely to increase innovation activity, so

that they are able to foster ‘innovation friendly’ practices throughout the SME sector.

11

CHAPTER 2 THE RESEARCH CONTEXT

Chapter 2 examines the context of the construction industry with respect to innovation

theory. It defines the terms of the study and discusses existing impediments to

innovation. Factors that are likely to be significant in the delivery of technical

innovation are identified from a literature review and are grouped in clusters of

potential relationships.

2.1 Construction industry culture and innovation

A business strategy focussing on innovation and continual improvement has long

been identified as an effective means of ensuring ongoing financial success for

enterprises operating in a market economy (Schumpeter 1934; Schumpeter 1942;

Tushman and Moore 1988; Utterback 1994; Audretsch 1995; Keen 1997; Baumol

2002; Tushman and Anderson 2004; Dodgson et al. 2005; Fagerberg et al. 2005; Tidd

et al. 2005; Chesborough et al. 2006; Isaksen and Tidd 2006; Bessant and Tidd 2007;

Drucker 2007; Malerba and Brusoni 2007; Dodgson et al. 2008; Shane 2008;

Audretsch et al. 2009; Malerba and Vonortas 2009; Weick 2009). Increasingly,

openness to innovation is also associated with improved environmental and social

performance in many sectors of the economy in the worldwide context (Fussler and

James 1996; Elkington 1997; Johansson and Magnusson 1998; Tushman 2004;

Elkington and Hartigan 2008; Hubbard 2009).

However some sectors, such as the construction industry, are widely reported to have

mainly failed the challenge to adopt new attitudes and modes of operation and are

said to remain largely ‘low tech’, traditional and craft-based (Pavitt 1984; Nam and

Tatum 1989; Reichstein et al. 2008; Sundqvist 2004). Over a long period of time, the

construction industry has been broadly criticised as slow to absorb both new

management practices and new technologies (Bowley 1966; Latham 1994; Egan

1998; Fairclough 2002; Woudhuysen and Abley 2004). Indeed, among the general

public, there is an often-reported perception of the construction industry as being

‘dirty, dodgy and dangerous’. In other words, it can sometimes be regarded as rife

12

with corruption and given to doubtful safety practices which lead to injury and loss of

life on project sites. In the Australian context, this belief was widely voiced in

submissions to the Cole Royal Commission into the Building and Construction

Industry (Cole 2003). The Royal Commissioner, in his “Summary of Findings and

Recommendations” listed as his first report outcome, that there was “an urgent need

for structural and cultural reform” in the construction industry (Cole 2003, p.3). In

particular, the position of small contractors, sub-contractors and independent workers

was identified as highly vulnerable to disruption and intimidation because of their

dependence on continuous and undelayed work to maintain essential cash flow and

liquidity. Cole also identified “an unwillingness within industry leadership to

recognise the long term advantages of structural and cultural change, accepting

instead a short term project driven profit process” (Cole 2003, p.13). In this context,

the industry culture is widely perceived as belligerent, fractious, excessively

competitive and even inwardly destructive. Risk shifting and blame shifting are

reportedly commonplace and the smaller and more vulnerable end of the industry can

be forced to carry the majority of the risk associated with introducing any new or

improved practice. Significantly, the current contractual and governance system

tends to assume this background environment of disputation, intimidation, lack of

openness and barriers to information access. The available remedies for the resulting

disputes tend to be expensive and time-consuming legal ones and unfortunately

smaller businesses often lack the economic capacity to defend their interests in the

courts. As a result, change from the bottom-up may be stifled and a large part of the

industry is deflected from the prospect of improving their individual situations

through the introduction of an innovation strategy. Of course, the problems

mentioned here have by no means universal coverage among construction companies.

It is acknowledged that many firms have management structures in place to avoid

such difficulties. Nevertheless, Cole (2003) did find significant and widespread

cultural impediments to positive change in the construction industry.

2.1.1 Is construction unique?

Some degree of explanation for the perceived dearth of construction innovation is a

function of the unique structure of the industry and the way its boundaries are

currently defined. Nam and Tatum (1988) have described how the products of

construction differ in scope, complexity, costliness, durability and in potential for

13

social consequences from manufactured products. Winch (2003), for example, has

pointed out that the motor vehicle manufacturing industry is considered to be separate

from the car repair industry for statistical purposes and consequently vehicle

manufacturing can demonstrate a higher level of innovation as it is not held back by

the more mundane processes of maintenance and repair. In the case of the

construction industry, however, repair and maintenance functions are often counted as

part of the same industry leading to a lower overall industry rate of delivered

innovation. Certainly, porous boundaries exist between the construction industry and

related areas of engineering, product manufacturing, building maintenance,

demolition, project management and facilities management. As a result, Winch sees

the ‘Complex Product Systems’ model as a more appropriate description of the

industry’s situation than the classical perspective of industry development (Winch

1998, p.269). The construction industry is made up of many and diverse

interconnecting elements. It often encompasses complicated hierarchies, non-linear

progressions and a high degree of user involvement in the overall process. In this

sense, construction is not directly comparable to any other industry, although it has

features in common with several other project-based industries.

Bresnen and Marshall (2001) have stated that the question as to whether construction

is essentially different in nature from other industries is probably unanswerable and

should be avoided in favour of analysis of how knowledge and ideas are diffused in

practice in the industry. Other authors have pointed out difficulties with the direct

transfer of management ideas from manufacturing to construction due to the

established practice patterns of the industry (Cheung et al. 2003; Gann 2001; Jaafari

1996; Jørgensen and Emmitt 2008; Loosemore and Tan 2000; Santos and Powell

2001). The project-based structure of the industry means that groupings of discrete

businesses temporarily coalesce and then separate around the delivery of relatively

short term projects. Although some continuity is provided by the tendency to work

with groups where there is some connection from a previous project, the temporary

nature of the relationship can lead to suspicion, or at least caution, about the sharing

of information and experience. This is not an atmosphere conducive to the diffusion

of successful innovations. This is a problem not only for the industry itself, but also

for the wider economy because of the importance of construction as a driver of

14

economic performance in most national economies. As will be demonstrated, this is

certainly true in Australia.

2.1.2 Importance of the construction industry

Although the construction industry continues to form a significant slice of national

economies throughout the developed and the developing world, definitions and

estimates can vary widely as to the extent of this economic importance. Construction

sector contribution to national Gross Domestic Product (GDP), as reported in a large

study by Walsh et al. (2005), varies between 3.5% and 24.7%, with a mean

contribution of 10.7%. The financial value is not the full extent of the influence,

however, as construction has a significant impact on the socio-economic development

process and is able to stimulate growth in other sectors because of its complex and

extensive linkages with other parts of the economy. In the Australian context, Royal

Commissioner Cole noted that the significance of the industry is much greater than its

strict economic definition because “Every Australian business and every Australian

citizen use the built environment” (Cole 2003, p.3). This relationship was clearly

recognised by the Australian government under former Prime Minister Kevin Rudd

(2007-2010). It formed the basis of the economic stimulus package introduced in

2009 to ameliorate the effects of the global financial crisis.

The nature of the industry is also evolving and in the developed world, there is less

emphasis on new and ‘green-field’ construction and more emphasis on upgrading,

renewal, achieving sustainability and delivering complex projects. A longitudinal

global study by Pietroforte and Gregori (2003) observed a decline in the importance

of the overall construction sector over the period from the late 1960s to the 1990s in

developed countries. At the same time, however, a rise was observed in the

significance of renovation and refurbishment and an increase in the importance of

services as opposed to manufacturing inputs to construction. The observed decline

may largely be due to other sectors making significant gains in their productivity,

while construction lagged behind in structural reorganisation. In addition to this,

particularly in the developed world, the character of the construction industry is

changing, with less emphasis on new construction and a rise in the more complex

system projects. Construction remains a crucial sector of the global economy, but the

increasing diversity of activity within the sector means that its character is more

15

varied than in the past. The need for innovation to maintain the industry’s status as an

economic driver is therefore all the more pressing.

Consequently, the debate over how to maintain and improve industry performance has

been the subject of widespread discussion among industry groups themselves, as well

as government policy makers and academic researchers. Creating an atmosphere

conducive to continuous innovation is seen as important, both for individual

organisations and for the industry as a whole (Hampson and Manley 2001; Dainty et

al. 2007). Gann (2003) has described a process of intensification that is occurring as

construction firms strive to maintain profitability, while addressing newly important

priorities such as the environmental and social consequences of action in the built

environment. This is evidenced by the increasing interest in the theory and practice of

innovation among governments, industry bodies and the research community (Abbott

and Allen 2005; Bossink 2007; Keast and Hampson 2007; Lim et al. 2010; Manley

2006; Manley 2008; Manley and McFallan 2006; Manseau and Seaden 2001; Miozzo

and Dewick 2004; Pellicer et al. 2010; Stewart and Fenn 2006; Taylor and Levitt

2008; Yin 2006). The translation of this interest into widespread practice is

problematic because of the inertia created by current industry structure and because of

the qualities which have been widely seen to characterise standard industry practice

for many years; in other words, informal industry culture and structure.

2.1.3 The need for change

In a ground-breaking study of the British construction industry based on data gathered

over the preceding eighty year period, Bowley (1966) identified five fundamental

problems affecting the industry’s performance:

• Low-level of competence of prospective building owners to make an

informed choice between competing contractors;

• Lack of mechanisms to foster innovative solutions;

• Absence of design and construction integration;

• Lack of economic input into design decision making;

• Poor quality of production and low efficiency levels in the housing sector.

16

Many of these factors have been recognised to have much broader coverage than the

UK building industry. Internationally, the industry has changed a great deal in the

intervening period since the identification and formulation of these issues; however,

some difficulties have proved less easily managed than others. In the forty years

since Bowley’s insights, many public sector and other repeat clients have specifically

sought to improve their technical competence when it comes to making evaluative

judgements about construction procurement (Manley 2006). Nevertheless, lack of

capacity to evaluate contractor options remains a problem for first time or one-off

clients. The rise of ‘Design and Construct’ and ‘Package Deal’ procurement and of

the input to the process from the quantity surveying profession have at least partly

addressed two other of Bowley’s areas of concern. Quality of production, though an

ongoing issue, has been addressed via both regulation and through quality assurance

perspectives and management strategies. The establishment of mechanisms to foster

innovative solutions, however, has proved a more intractable problem. There will

likely always be a tension between regulation and innovation. This tension is centred

on risk and responsibility. The entrenched avoidance of risk has proven to be a

significant long term barrier to the development of a construction industry culture

which promotes and embraces innovation.

Some four decades after Bowley, an extensive international study using grounded

theory, Fox and Skitmore (2007) found eight key factors which are associated with

construction industry development:

• Industry-led better practice and culture;

• Financial resources and investor confidence;

• Human skills and a culture of transparency;

• Government policies and strategies supporting construction business;

• Research and development for construction;

• Self-reliant construction culture;

• Institutional support;

• Supportive attitudes from aid agencies.

The need for cultural change is emphasised along with the provision of appropriate

support structures to encourage and manage change. The focus of interest has shifted

17

towards the management of knowledge and the delivery of appropriate human

resource allocation, along with the prudential management of financial resources.

The importance of education and a process of questioning of assumptions have been

identified as necessary conditions for a change in industry culture. Kumaraswamy et

al. (2002) stressed the importance of this change process being internally driven by

the industry, with emphasis on value-oriented procurement and collaborative working

arrangements. In particular, there is a need to persuade the industry of the advantages

of information technology for their productivity (Betts 1999; Peansupap and Walker

2006). Stewart et al. (2004) identified continuing barriers to the adoption of

information technology in the Australian construction industry, which are only likely

to be overcome by strong leadership and the example of the major industry

participants. El-Ghandour and Al-Hussein (2004) made similar findings in the North

American context and emphasised the value of integration between different IT tools.

A study by O’Connor and Yang (2004) investigated the extent to which the adoption

of new technologies contributes to project performance. Both information sharing

and automation of processes were studied. Scheduling benefits were noted to be more

closely associated with technology usage than were cost benefits. In an extensive

follow-up study of capital facility projects in Taiwan, Yang (2007) found a strong link

between overall project performance and electronic information transfer and storage.

With the increasing availability of IT tools in construction, this result indicates that

those who do not adapt to this situation may find that they are increasingly outbid by

information technology users.

Advanced business practices have also been shown to improve performance for those

construction industry firms who elect to adopt them. The wider management

literature has established the utility of such practices for business performance (Tidd

et al. 2005). The industry lead-users of strategic business plans, quality certification,

incentives, computerised record keeping, online marketing, multimedia

communication and relationship contracting have seen significant benefits to their

market share and overall profitability (Goulding and Alshawi 2002; Kululanga et al.

2001; Manley and Marceau 2001).

Despite the widespread evidence for the need to reform both industry culture and

industry practice, there remains considerable resistance to change in many areas. The

18

causes of this resistance are both structural and resource-based. Careful analysis of

the factors resisting change is necessary if industry performance is to be significantly

improved.

2.2 Resistance to change

The academic literature on factors which result in resistance to change in the

construction industry is extensive. In order to set the context for this thesis, the

academic literature which deals with problems in the construction industry was

studied to identify known causes of industry underperformance. Two kinds of factors

were widely mentioned; resource-based factors and structural factors. Resource-

based factors centre on the lack of appropriate skills and financial backing to apply to

complex construction projects, while structural factors deal with the innate nature of

the industry and its context. For the purposes of this thesis, resource-based factors

which have been identified as contributors include:

• The proliferation of many very small businesses who have difficulty

surviving let alone growing and investing in improvements (Abbott et al.

2006; Dainty et al. 2007; Koksal and Arditi 2002; Love and Irani 2004;

Sexton and Barrett 2003b; Winch 2000);

• Insecurity of much employment in the industry (Campbell 1996; Walker

et al. 2001; Green and May 2003; Forde et al. 2009);

• The tacit and individualised nature of much of industry experience, skills

and knowledge (Fernie et al. 2003; Hari et al. 2005; Larsen and Ballal

2005; Love et al. 2000; Love et al. 2005; Tombesi 2006; Vakola and

Rezgui 2000);

• Lack of expertise in, and value placed on, human resource management

(Bossink 2004; Druker et al. 1996; Kangari and Miyatake 1997; Keegan

and Turner 2002; Loosemore et al. 2003; Searle and Ball 2003);

• Contractual risk shifting towards those who can least afford to bear the

cost (Hinze 1994; Langford et al. 2000; Loosemore 1999; Loosemore

2005; Zaghloul and Hartman 2003).

19

Structural factors which have been identified as impediments to change and

innovation in the construction include:

• Its temporary project-based nature (Dubois and Gadde 2002; Towill

2003; Reichstein et al. 2008);

• Procurement systems which stress lowest price rather than best value

(Wong et al. 2000; Salter and Torbett 2003; Turner 2004; Williamson et

al. 2004);

• The complexity and lack of integration in existing industry supply chains

(Dainty et al. 2001; London and Kenley 2001; Love et al. 2004; Briscoe

et al. 2004; Kumaraswamy et al. 2004);

• Resistance to standardisation and modularisation because of the inherent

diversity of industry participants (Fox et al. 2001; Gibb 2001; Gibb and

Isack 2003; Blismas et al. 2006; Blismas and Wakefield 2009);

• Self-perceptions of the industry’s nature which limit both top-down and

bottom-up innovation (Koskela and Vrijhoef 2001).

Each of these preceding ten factors will be discussed in detail below.

2.2.1 Many very small businesses and independent workers

Koksal and Arditi (2002) in an extensive study of construction business failure data in

the USA, cite insufficient profits, heavy operating expenses and burdensome

institutional debt as the most significant factors affecting business survival. While

this might seem an obvious conclusion which could apply to any business in any

industry, it is important to note that the proliferation of such undercapitalised and

overstretched businesses is a feature of the construction industry in most parts of the

world. Such firms have difficulty achieving a survival mode and are in a poor

position to innovate.

Abbott et al. (2006) stressed the importance of firm size in the innovation process and

noted that, although it is possible for small firms to manage and drive change, they do

so in circumstances which differ widely from those of large companies. Small firms

need to gradually develop an innovation capability which enables them to become

more adventurous in their change management processes.

20

In recounting the history of the construction industry in the UK, Winch (2000a) noted

that continued strong reliance by large and medium firms on self-organising groups of

workers for actual production means that many construction organisations can fail to

develop and maintain their core competencies. The historic shift from an

employer/employee relationship to a contractor/sub-contractor relationship has

resulted in a strict focus on cost, rather than on sensible allocation of resources to

allow continuity of employment and maintain a skills base. A detailed discussion of

this matter is outside the scope of this thesis, however, it remains an important part of

the day-to-day context in which small and medium-sized construction firms exist.

2.2.2 Insecurity of employment

The proliferation of small business sub-contractors has also increased overall

insecurity of employment in an industry that was already characterised by unstable

employment practices (Green and May 2003). Walker et al. (2001) have reported on

the traditional adversarial approach to industrial relations, which was common until

recently on most Australian construction projects. Such adversarial attitudes and time

lost due to disputes can be correlated with the perception of insecurity experienced by

those whose future employment is uncertain and who, therefore, seek to maximise

their current returns at the expense of project quality and value (Campbell 1996).

This ‘everyone for himself’ attitude is a major impediment to a more co-operative

industry culture and a more innovative industry. Interestingly, Forde (2009) has

noted a developing tendency for a blurring of the line between employee and sub-

contractor which may result in attitudinal change.

2.2.3 Tacit nature of industry knowledge

A further factor which tends to exasperate the deep-seated adversariality in the

construction industry is the fact that much industry knowledge and skill is tacit,

uncodified and resides in the minds of individuals who have acquired their knowledge

through experience over time and on diverse projects (Loosemore et al. 2003; Love et

al. 2005; Vakola and Rezgui 2000). In addition, the rationale for decisions is often

not written down or recorded in any way, making it difficult for the organisation as

opposed to the individual to learn from project experience (Tombesi 2006).

21

This highly personalised nature of construction knowledge means that the ability to

make sensible decisions is very difficult to teach or transfer to others (Fernie et al.

2003b; Thorpe et al. 2009). Promising new technologies may be rejected simply

because they challenge existing norms and standard practice (Zhang and Yang 2006).

The socialisation process is often given scant resourcing in construction firms with a

resultant breakdown in the transfer of knowledge between different project teams and

employee generations. Hari et al. (2005) looked specifically at this transfer process in

small and medium construction enterprises and found a specific lack of awareness of

the issues of knowledge transfer within a firm. When these issues were managed

well, it tended to be because of the vision and flair of the organisation’s owners rather

than through any systematic process (Hari et al. 2005, p.555). Consequently, the

greater part of the industry, especially the small firms, has no effective strategy for

knowledge transfer from project experience. Szulanski (1996) described such issues

through the concept of ‘internal stickiness’ and found that problems with knowledge

transfer were often related to the recipient’s lack of absorptive capacity or to

relational difficulties between the knowledge source and the recipient.

2.2.4 Lack of human resource management expertise

Construction firms tend to be led by people with technical expertise and often there is

an associated lack of human resource management skills (Druker et al. 1996).

Construction industry education has also tended to neglect the softer human skills in

favour of technical capacities. Kangari and Miyatake (1997) point out that in contrast

to western countries, management culture in Japan is quite proactive in incorporating

‘people skills’ in technical enterprise management. Collaborative attitudes,

systematic information gathering and a reliance on reputation are regarded as essential

components of a management structure which is friendly to innovation. Bossink

(2004) identifies the manager’s leadership style as an important issue in the

progression of innovative ideas in the Dutch construction industry. He reports that

training for such managers has tended to avoid issues of human resources in favour of

technical skills, resulting in a lack of expertise in many parts of the industry and the

inability to benefit from newer management ideas and practices. Similarly

Tzortzopoulos and Sexton (2007), in researching case studies, found that a ‘learning’

approach rather than managerial ‘command and control’ structure was more likely to

favour improved construction industry performance.

22

2.2.5 Risk shifting

Similarly, lack of awareness of more progressive management theory has led many

parts of the industry to persist with adversarial risk shifting and blame shifting

strategies (Loosemore 1999). The practice of shifting risk down the contractual chain

to the smaller players was identified by Hinze in the early nineties (Hinze 1994).

Langford et al. (2000) noted the adverse impact this has on safety on construction

sites, as it can leave responsibility for safety with those with the least resources to

manage the problem. The pull of productivity bonuses and other incentives can lead

sub-contractors to compromise on safety issues if head contractor managers do not

intervene to prevent this situation. This represents a serious impediment to

progressive change. Kay (2010) has asserted that potential risk and uncertainty have

acted together to stifle much needed innovation in the construction industry.

A study undertaken in the Canadian construction industry demonstrated that lack of

trust between the contracting groups on projects can lead to a hard line reliance on the

letter of the contractual law to apportion blame, rather than to solve the problem

(Zaghloul and Hartman 2003). This lack of trust was shown to be ultimately

counterproductive for all the parties concerned. Nevertheless, it remains the common

context of much of industry interaction.

2.2.6 Project-based nature of the industry

Construction activity is essentially carried out by teams who come together for short

term projects. Linkages between companies are often temporary and unstable.

Dubois and Gadde (2002) have described the difficulties associated with a ‘loosely

coupled’ system as such a project-based industry inevitably is. The strong project

focus inherent in such an industry structure makes coordination with those outside the

project difficult and even pointless (Dubois and Gadde 2002, p.629). Seymour and

Rooke (1995) noted that stereotypes abound in the construction industry because they

facilitate transitory relationships. However, these stereotypes tend to impede the

formation of the longer-lasting and personalised relationships that characterise

effective working in teams. Small firms particularly can suffer from a lack of

strategic alignments which broaden their resource base (Hua 2007). Unlike some

other project-based endeavours like, for example, the movie industry, the construction

industry produces artefacts which are usually very long-lived and continue to impact

23

on the environment and on society for many years after their production. This

combination of short-lived project teams with long-lived effects is one of the essential

problems for the delivery of quality project outcomes. Towill (2003) has stated that a

focus on implementation, not just on the early phases of process mapping and process

redesign, is necessary if construction is to gain the benefits that an integrated industry

like manufacturing currently enjoys.

2.2.7 Lowest price procurement

In addition to the temporary nature of the industry structure, construction also suffers

from an overdependence on cost, as opposed to value, as the means of determining

the distribution of work. It has been demonstrated that a multi-criteria contractor

selection process has many advantages over simple lowest cost selection (Wong et al.

2000; Williamson et al. 2004). However, at times, the experience, skill-base, safety

record and appropriate capitalisation of bidders can tend to be ignored in favour of a

low tender price from a less reputable firm that may be ultimately undeliverable.

Along with this attitude is a short-sighted tendency to under resource the design time

allocation for a project in order to cut costs (Salter and Torbert 2003). As a result, the

various design alternatives may not be fully explored because of the need to restrict

design costs and the end result may not be the ‘best for project’ solution.

Turner (2004) pointed out that the information available on the parameters of a

construction project is inevitably incomplete at the time a contract is awarded. In

these circumstances, a reliance on tender price as the only measure of selection is

particularly problematic. The broader assessment approach taken by some

relationship procurement methods is likely to be much more effective in the long term

but, as previously noted, these methods are currently mostly restricted to the large

national and multi-national business end of the construction industry.

2.2.8 Supply chain complexity

Since the Egan Report (1998) in the UK pointed out the need to integrate the project

delivery process, there has been a strong move towards such supply chain integration

worldwide. Dainty et al. (2001), however, have shown that sub-contractors are often

sceptical of the value of supply chain integration, seeing it as a way of limiting their

scope for profit and their potential for independent operation. As a result, there has

24

been very little uptake by the small and medium-sized construction firms of the more

collaborative forms of project delivery.

London and Kenley (2001) have described the tension between the integration of the

construction supply chain and the nature of a project-based industry. It is clear that

theories developed in the context of the manufacturing industry may need some

significant adjustment in the context of the more complex and diversified construction

industry. The nature and extent of competition, as well as the power relationships

between firms of different sizes, can be important barriers to the efficiencies of closer

integration.

As Briscoe et al. (2004) have pointed out, clients can be potential drivers of industry

performance improvement by supporting the appropriate integration of the supply

chain through their procurement policies. Love et al. (2004) have supported this

notion and stressed the importance of communication, co-operation and learning

within the project team and incorporation of design within the delivery process rather

than separate from it. Collaborative decision making within the supply chain received

further support from Kumaraswamy et al. (2004b). ‘Acceptable rules of engagement’

need to be set out in order for industry groupings to negotiate information-sharing,

risk allocation and reward-sharing in an industry that has traditionally relied on

competition rather than co-operation.

2.2.9 Resistance to standardisation

There are many possible benefits from standardisation of building products and these

have been known for many years. Nevertheless, the structure of the industry tends to

resist pre-assembly, pre-fabrication and modularisation of components (Gibb 2001;

Gibb and Isack 2003). A new component has to win acceptance, not only from the

owner or ultimate purchaser, but also from the variety of consultants, contractors and

tradespeople who will need to integrate the new component into their own operations.

Some benefit needs to accrue to each part of the delivery chain or the change is likely

to be resisted (Blismas et al. 2006; Blismas and Wakefield 2009).

Although construction has tended to be a bespoke industry because of its scale of

operation and the complexity of its inputs, there is an increasing place for

standardised and modularised buildings and the economies they produce. This is

25

particularly true of standardised components for onsite fabrication (Fox et al. 2001).

Input from the builder at the design stage is essential if such standardised components

are to achieve widespread acceptance. In the field of manufacturing, user input for

products in heterogeneous markets is being encouraged (Von Hippel and Katz 2002).

This move may well have some relevance for the construction industry which has a

clear need to balance standardisation savings with customised performance.

2.2.10 Industry self-perception – the theory of construction

Finally, Koskela and Vrijhoef (2001) suggest that the most fundamental barrier to

improved performance in the construction industry is the industry’s own self-

perception. The current accepted theoretical model of the industry is one of

‘transformation’ where the inherent uncertainty and interdependence of operations are

ignored. Top-down changes often fail because of the absence of feedback

mechanisms from site-based workers to design originators, or because the strong

emphasis on process limits the possibility for change. Bottom-up changes are limited

by the inability of the individual to comprehend all aspects of the problem given the

limited access they have to a whole project perspective. There is also structural

resistance to ideas that come from areas other than management. Koskela (2006)

called for a debate on an appropriate theory of construction that will aid in achieving

the efficiencies already gained by the manufacturing sector and produce a ‘Lean

construction’ equivalent of Toyota’s ‘Lean production’ system. It may be that this

will prove to be a helpful avenue, but by no means all researchers agree with the

proposition. Green (1999) noted that the Lean Production system is not without its

critics, in the manufacturing sector where it originated. Furthermore, there are

potential adverse consequences, if it is accepted without a careful, balanced appraisal

of its suitability in the construction industry context (Green 2002; Green et al. 2008a).

Green et al. (2008b) called for a complex understanding of human actions and the

construction industry context in which they occur. Winch (2006) also stressed the

need for further development of the concepts involved, particularly, in terms of a

broader definition of the concept of ‘value’. Consequently, a widely accepted theory

of production in construction is still far from being established.

26

Each of the preceding ten factors amounts to a barrier to change to a greater or lesser

extent. Construction industry culture produces a level of inertia which discourages

the development of new solutions to community problems because of the associated

risk. The competitive and adversarial industry structure exacerbates the problem.

Working together, industry culture and industry structure combine to produce an

unfriendly atmosphere towards the fostering of innovation and continual

improvement. These circumstances are not restricted to the construction industry;

however, a determined resistance to change does appear to characterise some parts of

the industry. The situation is not entirely negative, however, as recent decades have

seen many genuine efforts at reform by individual firms and sector groupings. There

remain many areas where change has not taken root. The case, therefore, needs to be

made that the encouragement of innovative practice will benefit all sections of the

industry and improve the outcomes for those who work in the industry, as well as

those who use its products.

2.3 Theories of invention and innovation

At this point, it may be useful to describe a brief history of the theories of innovation

and invention over the past two hundred years. This will assist in understanding

where the issue of technical innovation in construction fits into the much larger

picture of the theoretical basis for the development and delivery of inventions into the

marketplace as innovations. These matters have been carefully explained in a report

by Kaiserfledt (2006). In a thoughtful discussion of “how new stuff comes about”,

Kaiserfledt (2006, p.2) makes it clear that many researchers in the area stress the

difference between ‘invention’ and ‘innovation’. Innovation is generally

distinguished by the successful delivery to the market of a new idea (Tidd et al.

2005). In this sense, invention usually precedes innovation. Many inventions may be

generated, but never successfully make the transition to the marketplace. Despite this,

inventions are a necessary precondition for technical innovation and there are grey

areas in definition between innovation and invention (Baumol 2002). Kaiserfledt

(2006) presents a taxonomy of theories of invention as depicted in Figure 2.1.

27

Figure 2.1 Taxonomy of theories of invention (Based on Kaiserfledt 2006 p.6)

According to this explanation, Schumpeter’s theory is located in the top right-hand

quadrant of the invention theory spectrum, as it stresses the importance of the

individual entrepreneur and his or her ability to bring together diverse resources to

derive advantage in the marketplace (Schumpeter 1934). Neo-classical theories of the

economy (mainstream economics) by contrast stress the social environment as

represented by market forces before the influence of the individual and problem

solving before access to resources (Weintraub 2002). Neo-classical theories are

therefore located in the lower left hand quadrant. Evolutionary models are placed in

the central upper half of the range, because they equally stress both problems and

resources (Nelson and Winter 1982). Schumpeter (1942) saw the ‘entrepreneur’ or

successful businessperson as the personification of innovation and gave support to the

belief that it is large companies that drive innovation, because they have acquired the

resources to do so. Under the classical Schumpeterian perspective, the inventor of a

technical innovation is unlikely to be the person who will successfully deliver the

innovation to market (Hagedoorn 1996). Similarly, classical Schumpeterian

economics sees small businesses as unlikely innovators because of their lack of

resources. Other economists have countered this argument and demonstrated that

small businesses in many areas can indeed be highly innovative (Acs and Audretsch

28

1990; Acs 1999). This thesis will investigate contrary examples to the classical

Schumpeterian theory. It will deal with episodes where construction industry SMEs

have successfully managed both to generate and deliver a building product or building

process improvement. As explained by Bessant and Tidd (2007), innovation delivery

has three stages:

• Generating new ideas;

• Selecting the useful and practical ones;

• Implementing them.

This thesis considers all three stages, but the emphasis is on the third stage - that of

implementation or delivery.

2.3.1 The significance of the individual inventor/innovator

The role of the individual inventor in the history of technological development has

been given particular research attention. Bijker (1995) describes how an unusual

combination of knowledge in a specific field often gives birth to a radical innovation

in a different field. A seminal example that is given is the Wright Brother’s

knowledge of bicycle mechanics enabling them to solve the problems of steering

aeroplanes. A generalisation of this idea is that creative problem solving can occur

when there is interaction between individuals with different knowledge sets (Freeman

and Golden 1997). In the second half of the 19th century, Thomas Edison and his

associates effectively invented the ‘Scientific Research Centre’ based on this principle

(Altshuller 1984). Edison established teams or workshops which broke down

technical problems into a series of tasks and each workshop simultaneously tested

many variants of particular solutions. This is the origin of the Scientific Research

Institute as it is known today. It has proved to be a very effective way of solving

specific technical problems, but it is clearly an option not available to smaller

businesses with their limited resource base. Such businesses must employ other

strategies if they wish to participate in the benefits of innovation.

29

2.3.2 The significance of the entrepreneur

Small business managers need to be able to gather together the knowledge of many

participants via networking both within and outside of their industry group. Nobel

Prize winner K.J. Arrow referred to this as ‘social knowledge’ and saw it as essential

to the innovation delivery process (Arrow 1994). Inventors may themselves become

entrepreneurs, or they may form associations with sympathetic entrepreneurs. In

either case, an understanding of ‘entrepreneurship’ is reported as essential to the

successful delivery of significant innovation (Drucker 2007; Audretsch et al. 2009;

Acs et al. 2009). Entrepreneurial activity is centred round the identification and

exploitation of opportunity. Shane (2003) defines entrepreneurship as activity that

involves the discovery, evaluation and exploitation of opportunities to introduce new

goods and services by organising efforts in ways not previously achieved. This thesis

will concentrate on SME construction firms led by individuals who have had success

in addressing this challenge.

2.3.3 Technology leadership

Nam and Tatum (1992) promoted the idea that a ‘proactive technology leadership’

strategy was both feasible and desirable in the construction industry. The industry did

not have to be exclusively subject to ‘demand side pull’ factors initiated by

clients/owners, but could actively develop its own technological solutions. In a

seminal study of ten innovative projects, Nam and Tatum (1992) demonstrated that

some owners were quite willing to accept innovative solutions to problems that

develop on site (called the ‘Problem needs solution model’) and some were also open

to solutions proposed by contractors as a result of their previous technical experience

(described as the ‘Technology guides problem model’). In other words, it was shown

not to be the case that owner’s specifications or the demand side strictly controlled the

outcome in construction. Rather, the contractor or the supply side could significantly

influence the success of the project outcome by the application of their technical

expertise in developing new technological solutions. Nam and Tatum’s findings were

in contrast to the work of innovation theorist von Hippel in the manufacturing sector,

where end-users were shown to clearly dominate the innovation process (von Hippel

1976; von Hippel 1988). As a result, Nam and Tatum exhorted the industry to

30

proactively pursue innovation as a goal which supports better practice rather than

simply a reactive response to problems in project delivery.

2.3.4 Innovation funding

The difficulty of financing innovation has been addressed in the broader economic

context stemming from Schumpeter (1942) and laid out by Arrow (1962). It can be

difficult for smaller companies to obtain external financing because of the gap

between the rate of return and the cost of capital (Hall 2008). Hall concludes that

government policy intervention is usually required in this area. The question of how

best to fund the research needed to develop innovations that result in improved

quality, profitability and competitiveness in construction was directly addressed by

Gann (1997). Gann described the traditional linear model of innovation, where

scientific research generates ideas which are later developed in an applied context by

non-scientists resulting in new products and processes that generate economic growth

(Gann 1997, p.258). This model, however, does not fit well with industries like

construction that have only a slight and passing relationship with the classical

scientific method. It is reported that in such industries, up to 90% of innovations arise

from the adaptation of pre-existing technology and not from academic science or

abstract research. The term ‘research’ is not, however, restricted to theoretical

research, as it also incorporates strategic research, applied research and experimental

development.

In project-based industries like construction, where comparatively little formal

Research and Development (R&D) is performed, there is nevertheless a need to adapt

and appropriate the findings of R&D undertaken by component manufacturers and by

other industries. The particular expertise of builders is called upon both to integrate

ideas from elsewhere and to manage compliance with the regulatory requirements

under which they operate. Gann (1997) reports that builders make many small, ad

hoc changes in the delivery of projects and often these changes are critical to the

success of the project outcome and its budget or schedule. Large changes in

materials, components or equipment tend to come from other parts of the supply

chain, specifically component manufacturers and design consultants. Consequently,

funding for research should be a joint responsibility of both government agencies in

the interests of the public good, as well as private industry in the interests of

31

economic growth and development. This thesis focuses on innovation and

construction SMEs. Without some level of external support, SMEs in particular find

it difficult to generate or adopt innovative practices.

2.4 Innovation definitions and statistics

As governments contribute either directly or indirectly (through tax subsidies) to

research and innovation, they necessarily feel the need to collect standardised

statistical information on the effectiveness of their investments. This has been the

impetus behind the Oslo Manual developed by the Organisation for Economic Co-

operation and Development (OECD/Eurostat 2005). The manual proposes guidelines

for collecting and interpreting technological innovation data. It deals with industry in

the broad definition and is not specific to construction. The premise of the data

collection effort is that the world is currently experiencing a major technological

revolution with the introduction and roll-out of information technology, but the

benefits of this technology are being harnessed unevenly and resultant productivity

growth is mixed. Governments and policy makers have seen the benefits of an

innovation focus in specific industries and would like to see a more widespread use of

the management strategies that encourage continuous improvement and innovation.

The Oslo Manual is seen as supporting the concept of the ‘innovation dynamo,

meaning the background and process factors which enable innovation in industry

through its monitoring of the level of innovation that currently occurs’ (OECD 2005,

p.6). Innovation is acknowledged as a complex and diversified process, which

requires an appropriate level of analysis in order for its occurrence to be understood

and the application and adaptation of exemplars to be made possible (Gray and

Davies 2007).

2.4.1 The Oslo Manual and its scope

The Oslo Manual’s scope is defined as follows (OECD 2005, p.7):

• The Manual covers innovation in the business enterprise sector only. It

does not deal with public services such as health or education;

• It deals with innovation at the level of the firm rather than at industry or

national level;

32

• It concentrates on technological product and process (TPP) innovation,

with optional guidelines for other forms such as organisational change;

• It covers diffusion down to the ‘new to the firm’ level.

2.4.2 Products versus services

While innovation in services and service industries is important and some discussion

in the Oslo Manual is devoted to how to collect statistics in this area, this remains a

field for future detailed definition and research and is largely outside the scope of this

thesis. The distinction between service and product is important for this study,

because, to some degree, construction is a service-providing, as well as, a product-

generating industry. A particular area where overlap between technical and service

innovation is likely to occur in the construction industry, is the area of occupational

health and safety (OH&S) initiatives. In general, OH&S innovations will only be

included in this study if they include a product, process or equipment innovation.

Awareness-raising or other information and education provision activities will not be

included. These matters are more properly classified as organisational rather than

technical innovation.

2.4.3 Firm level focus

The Oslo Manual focuses on innovation delivery within the individual firm, rather

than larger and more complex regional clusters or industry-wide groupings. This

study proposes a similar focus, because decisions made at individual firm level

generate the aggregate performance of the industry. It is suggested that the

innovation enabling factors described at firm level by successful innovators, if

adopted broadly, would lead to improved industry efficiency and performance.

When defining a construction firm, this study seeks to identify independent and

responsible entities which operate in the competitive marketplace. Definitional issues

exist with regard to boundaries between firms, especially large and multi-national

corporations and their subsidiary companies. Complex corporate law in different

jurisdictions defines the ‘business’ or ‘firm’ in a variety of ways to do with

employment and structure. The construction industry unfortunately has more than its

fair share of ‘shelf companies’ and ‘phoenix operations’. In the former case, these are

firms who exist in name only and in the latter case, firms that go through repeated

33

death and re-birthing processes to avoid responsibility for previous poor performance.

This study will endeavour to exclude firms that are fully controlled instruments of

larger entities and, therefore, not able to act independently, as well as firms with a

limited and temporary focus which have no interest in long-term improvement

strategy.

2.4.4 Technological versus other kinds of innovation

Afuah (2003) defines technological innovation as the application of knowledge about

tools, materials, processes and techniques to problem solving. In the Oslo Manual

definition (OEDC 2005), purely subjective changes in a product’s appearance or style

are regarded as marketing rather than technical or functional innovation, and are

considered as a separate category in proposed data collection. It will also be

necessary to exclude innovations that are superficial in nature and, therefore, do not

result in any significantly improved functional performance. For illustration purposes

for this thesis, a new colour range for concrete roof tiles would not be considered a

technical innovation, but a new tile pattern which improved water-shedding

performance would be included. While marketing innovations can have a positive

effect on profitability, it is difficult to define any positive change that they make to

performance. Technical innovation must, by definition, result in improved

performance or else it is simply change not innovation.

2.4.5 ‘New to the firm’ innovation diffusion

The Oslo Manual includes the study of innovations which are not internally

generated, but simply observed and transferred to a firm’s operation. This is a much

broader definition than previous studies which restricted themselves to innovations at

higher levels of novelty such as ‘new to the industry,’ ‘new to the country,’ or ‘new to

the world.’ The reason for this apparent ‘lowering of the bar’ with regard to the

definition of what can be considered as innovation is that the diffusion of a

technological innovation throughout an industry is the main source of its economic

impact. If new ideas are generated in a small number of innovative firms who then

jealously guard the commercial advantage of the innovation, overall industry

performance fails to improve and general prosperity is not benefited. The size and

scope of the construction industry, as well as its ability to impact on the lives of most

human beings, mandates that successful innovations are diffused throughout the

34

industry wherever they are useful and become available for the benefit of all people

who depend on the built environment.

2.4.6 Technical and organisational innovation

A further distinction that is made in the 2005 edition of the Oslo Manual, but was not

included in the earlier 2002 edition, is the difference between organisational and

technical innovation. Technical innovation concentrates on significant improvements

in products, processes and equipment. It involves ideas that have an overtly physical

manifestation. Organisational innovation, on the other hand, may be primarily

thought-driven or activity-driven. Organisational innovations include such things as

changes to business practices, communication systems, human resources and

knowledge management. These innovations may result in significantly improved firm

performance and, indeed, they may provide critical support for technical innovation.

Marketing innovation is considered a separate category of innovation by the OEDC,

and while it is an area worthy of study it is not part of this thesis. Specifically

technical innovation is the area covered by this thesis. Organisational and marketing

innovation will only be included insofar as they support or enable technical

innovation and not as an end in themselves.

2.4.7 Australian Bureau of Statistics Survey

The Australian Bureau of Statistics published an extensive study into innovation rates

in Australian businesses in 2003 (ABS 2003) and a follow-up survey was published in

2008, dealing with the 2006-2007 financial year statistical collection (ABS 2008a).

Data was collected across 16 industry sectors, one of which was the construction

industry. The survey determined a base rate of innovation active businesses as shown

in Figure 2.2 overleaf. This overall innovation rate incorporates goods and services

innovation, operational process innovation, organisational/managerial innovation and

marketing method innovation. The first and second categories include those

innovations which can be defined as technical innovation. It should be noted that

construction is the poorest performing sector under the overall category.

35

0.0

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Figure 2.2 Percentage of Innovation Active Businesses by sector 2006-2007 (ABS 2008a)

Although the construction industry performs relatively better when the two technical

innovation categories of goods and services innovation and operational process

innovation are considered, it nevertheless remains in the relatively ‘low achiever’

category in both types of technical innovation compared with the level in other

industry sectors. Part of the explanation for this lies in the diversity of industry

sectors and how they define what they regard as technical innovation. It is possible

that there was some under-reporting of technical innovation in construction, because

there is a sense in which all buildings are innovative because they are unique and

cannot be produced as a series of identical objects on an assembly line. However, the

survey respondents would have been aware that what is measured in terms of

innovation is some level of breaking away from ‘business as usual’. How great this

step needs to be is a question that is difficult to define and is likely to vary from

Per

cent

age

36

industry to industry because of operational differences. As construction is a technical

industry, it is possible that construction respondents defined the step at a higher level

than other industries. There is insufficient evidence at the moment to determine

whether or not this is the case.

When looking at goods and services innovation (Figure 2.3 below), the construction

industry no longer fills the bottom slot, but it is among the low-level innovators along

with mining, transport and real estate. On the whole, these four industries do not

provide many ‘small ticket items’ and this may partially explain their relatively low

goods and services innovation rate. The cost of change is greater if the item or

process being altered is expensive, and consequently innovation rates can tend to be

lower in ‘large ticket item’ industries.

0.0

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Figure 2.3 Percentage of Goods and Services Innovation Active Businesses by sector 2006-2007 (ABS 2008a)

Per

cent

age

37

The area of operational process innovation (Figure 2.4 below) reveals a similar

pattern. Construction is among the low rated innovators, despite operational

processes being an area where it could be expected that technological industries

would excel. Only seven of sixteen industry sectors achieved operational process

innovation rates of greater than 15%. This may be at least partly due to the cost of

operational change in industries that are not capital intensive.

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Figure 2.4 Percentage of Operational Process Innovation Active Businesses by sector 2006-2007 (ABS 2008a)

2.4.8 BRITE Survey

Apart from the ABS survey, the other significant attempt to measure innovation rates

in construction in recent years is the Building Research on Innovation, Technology

Per

cent

age

38

and Environment (BRITE) survey conducted in 2004 for the Australian Cooperative

Research Centre for Construction Innovation (Manley 2005). The survey dealt with

the road and construction industry, so its findings are not directly comparable to the

innovation rates for the construction industry in the ABS Innovation survey. The

BRITE survey found a ‘new to industry’ rate of technological innovation of 18%

which is a higher level of innovation than might be anticipated from the ABS results.

The survey sample was much smaller than the ABS study, but the survey

questionnaire was designed specifically for the industry, so it is possible to use it as

evidence that innovation in construction may be under-reported in the larger survey.

It is not proposed that this thesis seek to verify or to dispute innovation rates as

recorded in the ABS or BRITE surveys; that would be a statistical task requiring very

considerable resources beyond the scope of a research thesis. Instead, this thesis will

examine the reasons why some construction companies are able to innovate at a much

higher level than the sector average. It is envisaged that this could lead to useful

guidelines and advice for those firms who wish to lift their own innovation rates.

Furthermore, it is suggested that such advice could have particular relevance to SME

construction businesses and that this is an area where there is considerable potential

for improved innovation performance.

2.5 SME definition in the Australian context

The introduction of the Goods and Services Tax (GST) in Australia in 2000 involved

a system of national registration for all businesses delivering or using goods and

services. The system involves the registration of the trading unit by an Australian

Business Number provided by the Australian Taxation Office. Only businesses who

earn total revenue of less than $50,000 a year are exempt from this requirement and

some of them have an ABN nevertheless, because it enables them to claim back GST

amounts they have paid out to other businesses. As a result, there are very reliable

figures about the extent of business activity and a relatively small informal sector. In

its Counts of Australian Businesses 2007, the ABS found that the construction

industry had 308,405 businesses operating at the end of the financial year 2006-2007

(ABS 2008 p.10). This figure would include sole operators, ‘own account workers’

and multiple trading identities operated by the same individual.

39

Since 2003, the ABS has specifically been collecting information on innovation in

Australian business. In these data sets, they define a business somewhat more rigidly

than the Counts of Australian Business model. Businesses are only included in the

innovation survey if they lodge Pay As You Go (PAYG) instalments with the

Australian Tax Office. This means that sole traders who operate as a business with a

separate business bank account from which they pay themselves wages are included

in the survey. Sole operators who accept payment for work and deposit the receipts in

their own private account are not included, whether or not they later submit quarterly

Instalment Activity Statements (IAS) or Business Activity Statements (BAS). There

is a resultant large discrepancy in the number of businesses listed as operating in the

construction industry in the Counts of Australian Businesses and in the Innovation in

Australian Business Survey. For 2007, the figures are 308,405 and 124,000

respectively. It can be seen that more than half the businesses in the greater

construction industry operate in a fairly informal manner and employ few people.

The breakdown of the 124,000 businesses in the scope of the construction survey is as

follows in Table 2.1 below.

Table 2.1 Numbers of businesses in construction

Category Number of Employees Number of businesses

Micro-business 0-4 91,000

Small business 5-19 30,000

Medium business 20-200 4,000

Large business > 200 < 1,000

Therefore, the Australia-wide population of formal, non-micro SMEs in construction

for the calendar year 2007 is 34,000 businesses. Of these, approximately one third, or

40

11,000, are in New South Wales and slightly more than half of that number (6000),

are located in the Greater Sydney metropolitan area. This represents the population of

all potential businesses to be studied in this thesis. The total incorporates many

businesses that primarily operate as labour-only subcontractors. These are not the

focus of this research, however, as it is intended to study only those firms within this

population that have successfully delivered a recent technical innovation with a high-

level of originality. The primary qualification for eligibility for the study will be

having received some form of peer recognition as a successful innovator from

industry or professional organisations. This technique is classified as a form of

‘purposive sampling’ or non-probability sampling (Teddlie and Yu 2007). It will be

discussed further in Chapter 5 of this thesis.

2.5.1 Construction SME contribution to GDP

The ABS Annual Reports on Australian Industry itemise industry sector contributions

to Industry Value Added as a measure of relative sector performance (ABS 2008b).

As recorded in Table 2.2 overleaf, the statistics show that the construction industry

contributes approximately 10% of national Industry Value Added (IVA) and that

construction SMEs contribute just over 80% of the industry total, or 8% of the

national total. The construction industry also accounts for 11% of total sales and

service income, and SMEs contribute 77% of the industry total sales and service

income (see Table 2.3 overleaf). These percentages are considerable, especially when

the amount of attention sometimes given by policy makers to the views of the large

construction companies is taken into account. Construction SMEs clearly have the

potential to generate economic impact well beyond their restricted size. As such, they

represent a suitable area for ongoing study.

41

Table 2.2 Construction industry contribution to Industry Value Added (IVA) 2006-2007 (ABS 2008b)

Business size Total industry

value added

($m)

Construction

industry selected

industry value

added ($m)

Percentage

contribution to

total industry VA

(%)

Small 249,506 45,245 18

Medium 168,036 13,516 8

Large 294,489 14,127 5

Total 712,030 72,888 10

Table 2.3 Construction industry contribution to sales and service income 2006-2007 (ABS 2008b)

Business size Total sales and

service income

($m)

Construction sales

and service income

($m)

Percentage

contribution

to total

industry SSI

(%)

Small 691,169 116,872 17

Medium 518,833 57,484 11

Large 893,998 51,830 6

Total 2,103,999 226,185 11

These percentages for the contribution made by construction SMEs are considerably

higher than for the other industry sectors recorded. Taken together, these statistics

42

indicate the potential economic benefit to the nation of improved performance in

SME construction. This serves to emphasise the significance of a research focus on

SME construction as an area that can result in significantly improved economic

performance if barriers to effective change are addressed.

2.5.2 Characteristics of construction SMEs

There are some known areas where SMEs are distinctly different from other industry

participants. Typically, they often have very limited financial resources, both in terms

of capital and borrowings. As a consequence, they often have little spare capacity to

plan for change. Frequently, they have to contend with higher levels of competition

than larger businesses (Manley 2008b). SMEs may be less able to monitor their

competitors than large business. Consequently, keeping an up-to-date technology

watch may be beyond their resources, unless they can do so through an industry

network. Finally, some SMEs may be motivated to simply survive rather than to

grow (Abbott et al. 2006). Both the risk and the cost of change may be too great for

SMEs to attempt.

It has been decided to concentrate on SMEs who are not in the micro-business

category, precisely because the micro-business category is likely to suffer from the

restrictions listed above to a greater extent than even slightly larger businesses. This

is not meant to imply that micro-businesses are an unsuitable area for an academic

study, but simply that due to their very small size they are likely to have less

consistency as a class and to be far more subject to the constraints of individual

capacity and fortune.

On the positive side, many SMEs are headed by very able individuals, who have

chosen not to work in large business because of the brake that a large bureaucratic

organisation can put on individual creativity. Such individuals have the potential to

be leaders of industry change and generators of new systems and products. Nam and

Tatum (1997) refer to them as ‘champions’ of innovation. Dulaimi et al. (2005)

found that the role of such champions can be crucial in innovation delivery. The fact

that the industry is characterised by many small businesses is, therefore, both its

strength and its weakness. It does lead to restrictions on capacity and resources, but it

also enables creative individuals to move quickly in new directions and develop new

solutions to industry problems. It is this potential that justifies this research into

43

enabling factors for non-micro SME construction companies. It is also possible that

creative individuals in SMEs can lead reform in industry practice in terms of

improving the environmental and social outcomes of construction processes.

2.6 Taxonomy of construction innovation

Slaughter (1993) looked in detail at the kinds of innovations developed by builders as

opposed to component manufacturers and found that builders were not only more

innovative in general, but that they generated the great majority of innovations that

related to the connection or integration of component parts. In Slaughter’s study, 34

innovations in stressed skin panels for housing construction were examined and 84%

of these innovations were generated by the builders rather than the panel

manufacturers. As a result, it can be suggested that there exists a de facto design

partnership between the component manufacturer and the builder which can lead to

effective innovation delivery, if both sides recognise the necessity of acknowledging

the constraints that affect the other’s operations. Slaughter went on to develop a

taxonomy of construction innovation, based on the degree to which the individual

innovation required changes in the systems and products around it (see Figure 2.5).

In ascending order from small change to major change in the surrounding

components, Slaughter classified innovations as Incremental, Modular, Architectural,

Systems and Radical (Slaughter 1998). Using this taxonomy, the developers of

innovations can become more aware of the changes that need to occur to deliver their

innovation and consequently understand the level of intra-industry cooperation

needed for successful adoption of a good idea in construction.

44

Although the classifications represent a useful framework for discussing innovation, it

should be remembered that innovation delivery is a complex process. An innovation

that may be modular for one company in a supply chain may require systemic

innovation for the users of the innovation (Harty 2008). This complexity has been

described by Afuah and Bahram (1995) as “The hypercube of innovation”. There are

several other efforts to classify innovation in the literature. These include the

decision making typology of Mitropoulos and Tatum (1999) which sorts innovation

into two major categories; strategic/proactive versus project-based/reactive. There is

also Gopalakrishnan and Bierly’s typology based on knowledge characteristics which

has three general categories: Tacit/explicit; Systemic/autonomous; and

Complex/ordinary (Gopalakrishnan and Bierly 2001). This taxonomy, however, was

explicitly created for organisational rather than technical innovation and as such is not

strictly relevant to this study. Harty (2005) described, the essential difference

between a variety of innovation processes as consisting of whether they are bounded

or unbounded. In other words, the critical aspect is whether or not the innovation has

Figure 2.5 Slaughter’s taxonomy of innovation (Based on Slaughter 1998, p.229)

45

impacts beyond the operation of the innovator’s own sphere of activity. Lim and

Ofori (2007) taking a different tack found three classes of innovations: those that

clients are willing to pay for because of their advantages for the end-user; those that

reduce construction costs; and those produce competitive advantage through their

intangible qualities. Each of these taxonomies of innovation are valid tools and will

be used to classify the technical innovations studied for this thesis, however, it is

important to remember that technical innovation is essentially unique in each of its

occurrences. For this reason, a great deal of attention is paid to the nature of research

in construction and to the funding of research that generates innovation.

2.7 Construction innovation literature

Many authorities, such as Keeney and Raiffa (1976), recommend the use of a

literature review specifically to identify the significant attributes in the area of a

research problem. The authors explain that a literature review may be used to identify

significant factors for later testing by empirical research. In consequence of this

advice, a search was made of refereed journal articles that dealt with innovation and

the construction industry published between 1990 and mid 2008. Five international

journals dealing specifically with construction were searched initially. These were:

Building Research and Information (BRI), Construction Innovation (CI),

Construction Management and Economics (CME), Engineering Construction and

Architectural Management (CME) and Journal of Construction Engineering and

Management (JCEM). References in these articles led to a further five journals, each

with three or more articles on the topic of construction innovation. In descending

order of the number of articles discovered, these were: Research Policy (RP),

Facilities (F), Journal of Management in Engineering (JME), Australian Journal of

Construction Economics and Building (AJCEB) and International Journal of

Innovation Management (IJIM). A further 29 journals were found with one or two

articles on construction innovation.

Articles were then classified as addressing any of five identified principal themes.

The themes were: firm resources; client and end-user influences; project-based

conditions; industry networks; and regulatory climate. Many articles addressed

46

multiple themes. In addition, several sub-themes were identified under each of the

five identified primary themes.

As well as the articles referred to in Table 2.4 (below), an additional 112 articles were

identified during the initial search, which related to, but did not specifically address

the topic of construction innovation. Some of these articles are included in the

citations for this thesis.

Table 2.4 Occurrence of construction innovation themes

Journal Number of

construction

innovation

articles

Firm

resources

Client and

end-user

influences

Project-

based

conditions

Industry

networks

Regulatory

climate

CME 38 21 11 8 9 5

BRI 19 10 7 8 8 2

JCEM 17 10 2 7 5 2

CI 13 9 6 5 2 2

ECAM 13 8 3 2 3 2

RP 7 1 0 1 0 0

F 5 2 3 2 1 2

JME 4 3 1 0 1 0

AJCEB 3 2 2 2 1 0

IJIM 3 2 0 0 0 1

Other <3

in total

31 22 15 17 15 5

Total 153 90 50 52 45 21

47

Detailed discussion of each factor and identified sub-factors follows. It is not

intended to comprehensively refer to every article included in Table 2.4. Rather the

intention is to sort out and evaluate principal areas of agreement and disagreement.

Ongoing monitoring of the literature published during the course of the study was also

undertaken and further references were added from relevant newly published papers

during the time of writing of this thesis. The initial literature survey to identify

significant factors is not claimed to be definitive, it was simply the starting point

consideration of the factors involved.

2.7.1 Five major categories of factors affecting technical innovation

For this study, the published literature was surveyed with a view to dissecting the

possible factors that affect technical innovation delivery in the construction industry.

Five factors were identified as reported in the literature to be of primary importance.

The first area concerns matters that are entirely internal to the company concerned,

that is, all the available resources, both tangible and intangible, that the SME has at its

disposal, to be deployed towards the innovation process. Technical capabilities,

capital investment, liquidity, time allocation and individual enthusiasm are all part of

this complex mix of resources that may be available to a potential innovator in a

construction SME. This factor has been summarised as ‘Company resources’.

The second area concerns matters that are entirely external to the company concerned.

It deals with influences at both ends of a construction project: at the front end, there

are those who commission the project, variously known as developers, clients and

investors; and at the bottom end of the project, there are those who occupy and use the

building project, known as the customers or the end-users. Both groups ultimately

pay for building projects, and consequently they potentially have a great deal of

power to influence the building project’s progress. Because of a general lack of

technical expertise, however, these groups are largely outside the mechanics of the

project delivery process, although sometimes they can take an active role. This factor

has been summarised as ‘Client and end-user influences’.

The third area identified from the literature relates to the innate nature of construction

projects. These are complex, but temporary, activities that involve a great deal of

organisational expertise. They also have to allow for the contingency of the unknown

factors that may arise on site once work has commenced. Management of human and

48

physical resources requires careful planning as well as flexibility and responsiveness.

These matters have been summarised as ‘Project-based conditions’.

Published research has also pointed to the importance of intra-industry connections

that are not related to specific project delivery. These can be connections with

professional bodies which uphold ethical standards, or industry bodies which

represent the construction industry to the broader public. They may also include

organisations that provide independent verification and testing of new technologies.

This factor has been summarised as ‘Industry networks’.

The fifth and final factor identified related to the legal framework in which the

construction industry operates. Several areas of law have impact on the construction

industry. These include contract law, torts and professional responsibility

obligations. The major impact on building projects is, however, through building

regulation by the different levels of government. This factor is summarised as the

‘Regulatory climate’.

Each of the five factors will be discussed in detail as it relates to the published

literature. In addition, sub-factors which relate to specific areas under the influence of

the five factors will be described.

2.8 Company resources

The available resources of a firm, along with a multi-disciplinary approach to team

formation, are both widely regarded as critical for innovation success (van der Panne

et al. 2003). The ‘trial and error’ nature of much innovation requires a supportive

management structure and sufficient resource allocation if it is to deliver benefits.

The fact that builders can generate and deliver significant and valuable technical

innovations has been recognised by researchers since the 1960s (Bowley 1960;

Bowley 1966; Nam and Tatum 1992; Slaughter 1993). Motivational issues and the

value of innovation champions have also been acknowledged (Nam and Tatum 1997).

Leiringer and Cardellino (2008), however, caution that studies of innovation

champions may be subject to a bias that results from the champion practising

“impression management” by controlling the information presented to any observer.

The critical importance of the allocation of sufficient resources to deliver innovation

49

has been clearly described by several authors (Gerwick 1990; Dulaimi 1995;

Slaughter 2000; Blayse and Manley 2004; Tatum 2005). This is particularly true in

the construction small business sector which often needs to be convinced of the direct

benefits to themselves of adopting new technologies, if they are to be persuaded to

change their current practices (Andresen et al. 2000).

2.8.1 Personal motivation

The personal motivation-level of the team which generates and delivers a successful

innovation has been demonstrated to have a decisive effect on the overall process

(Hartmann 2006b). Individual contributions can be critical in several roles and at

several stages of the innovation delivery process. This is likely to be particularly true

in smaller businesses where the impact of an individual innovator is proportionally

greater. Egbu (2004) explained that any meaningful innovation strategy should have

unequivocal support from the top in order to be successful. It also needs to be

monitored and reviewed regularly. Slaughter (1998) mentioned the role of

‘gatekeepers’ who are aware of possible solutions to a given problem. These people

can also be important as evaluators of the innovation delivery process. Winch (1998)

drew on a comparison with the aviation industry to describe the importance of

‘systems integrators.’ This is a role which in construction is often split between the

principal architect or engineer and the principal contractor. Consequently, third party

brokers are sometimes needed to moderate the process of innovation delivery when

responsibility is divided. Mitropoulos and Tatum (2000) identify ‘champions’ as the

people who absorb the risk of an innovation and drive the change. Top management’s

aspirations and proactive attitude towards technology are seen as a major source of

competitive advantage. Szulanski’s study of knowledge ‘stickiness’ takes a different

view and finds that motivational factors are less important in the diffusion of

innovation than conventional wisdom might suggest (Szulanski 1996). Abbott et al.

(2006) looks specifically at small business in construction and find that their

motivation to innovate differs intrinsically from that of larger businesses as they may

not necessarily be seeking to grow. Developing an appreciation of the benefits of

innovation for these companies may require the intervention of third party

organisations such as industry bodies or larger businesses in partnership

arrangements.

50

2.8.2 Available financial resources

It has long been recognised that the traditional construction industry structure can

inhibit innovation, simply by reducing incentives to introduce technical or process

innovations (Brown 1990). Slaughter (1993) reported that builders commonly

innovate when technology is easy to modify and the costs of doing so are low. Barrett

and Sexton (2006) noted that small companies, in particular, often lack sufficient

‘slack resources’ in order to attempt innovative activities. The difficulties that small

construction businesses encounter in trying to survive, let alone innovate, have been

well documented (Sexton and Barrett 2003a; Sexton and Barrett 2003b; Sexton and

Barrett 2004; Sexton et al. 2006; Manley 2008). Such companies certainly depend

more heavily on scarce resources than do larger firms and they can often be

constrained by their financial circumstances.

An insightful paper by Pries and Jansen (1995) urged construction companies to be

more extrovert and market-oriented in order to overcome the inertia of ‘business as

usual’ type operations. Miozzo and Dewick (2002) found that contractors are more

likely to invest in new assets and their complementary knowledge if this can be

financed from reserves or cash flow rather than from borrowing. This innate risk

aversion can limit the potential for innovation. More recently, Stewart and Fenn

(2006) stressed that innovation needs to be ‘strategic’ or targeted towards a goal,

which can be profitably exploited, or else it is highly unlikely to succeed.

2.8.3 Available time

It is an industry axiom that construction companies exist under constant pressure to

deliver their projects on time and without going over budget. This can result in

avoidance of new ideas, because there is perceived to be no spare capacity to test new

products or systems. Shortage of resources contributes to a perceived lack of interest

in innovation especially in small construction firms (Davidson 2001). Veshosky

(1998) found that time constraints were a barrier to innovation in engineering and

construction firms. Even in large construction firms, groups such as designers often

feel that insufficient time is allocated to their role in the project delivery process and

consequently innovation may be stifled or curtailed (Salter and Gann 2003). This is a

short-sighted position, however, as it leads to the inability to adapt to potential

positive changes and efficiencies. Motawa et al. (2004) have looked at using

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computer scheduling to model the economic effect of iterative innovations. The

system they have developed will eventually form a useful tool for managers

modelling the possible impact of a proposed technical innovation on a company’s

available resources.

2.8.4 Available skill levels

Ling (2003) found the capabilities of people working on projects to be a significant

factor in the implementation of innovations along with level of interest, the working

environment and task groupings. Knowledge retention and transfer within

construction firms has tended to be problematic due to the competitive nature of much

construction activity. Individuals may fear the loss or devaluation of their hard-won

individual expertise. The rights of individuals need to be carefully considered if trust

is to be established. Janssen (2004) stressed the need for procedural and distributive

fairness in the implementation of innovations in order to prevent ‘burnout’ among

innovators. Participants need to be confident of receiving individual benefit from

gains they achieve for the organisation, or otherwise they will resist productivity gains

for fear of eventual job losses (Taylor and Levitt 2008). Attribution of innovations is

also important. The developing, presenting and championing of an innovation is a

stressful process which individuals are likely to abandon if the rewards are

inappropriate or insufficient (Mitropoulos and Tatum 2000). Ben Mahmoud-Jouini

(2000) has described how innovative construction products and processes can be

generated when project management skills are linked with technical skill

development. In a study of innovation in construction equipment, Arditi et al. (1997)

found that such innovations are likely to be incremental in nature. Furthermore,

technical innovations are not confined to the industry that develops the innovation;

they may cross industry boundaries. In a study of the Swedish construction industry,

Brochner (2008) found that those construction managers who diversified into the

facilities management area tended to be more proactive in identifying business

opportunities, were more collaborative in style and put a higher value on education

and training in their workforces. This skill-set enabled them to be more innovative in

their original endeavour.

When considering available skills in their broadest sense, Cohen and Levinthal (1990)

argued that the ability of a firm to recognise, assimilate and apply new knowledge can

52

be described as their ‘absorptive capacity’. This ability or skill was seen as critical

for many performance measures. Szulanski (1996) found that ‘absorptive capacity’

was a significant factor in innovation diffusion. It was shown to outweigh

motivational issues which had traditionally been seen as critical for innovation

delivery. Peansupap (2004) and Peansupap and Walker (2006) made similar findings

concerning the diffusion of ICT in the construction industry.

The ‘technology push’ versus ‘demand pull’ debate remains inconclusive (Nam and

Tatum 1992; Arditi et al. 1997; Barlow 2000; O’Connor and Yang 2004; Anderson et

al. 2004; Abbott and Allen 2005). Innovation can, and does, occur as a result of both

influences and both require the knowledge base of the innovating firm to be robust

and diversified.

2.8.5 Insurance/risk

The role of firm culture and organisation in regard to risk management and

responsible corporate strategy is an increasingly important area of study (Loosemore

and Phua 2011). A study by Pries et al. (2004) has reported that attitude change is

required in order for the construction industry to progress from its technology and

project-oriented base. The authors suggest that there needs to be more client and

market focus, and construction firms should concern themselves more with the

delivery of a successful end product, than with the intricacies of the delivery process

itself. Some may regard this approach as a softer focus; however, it can be entirely

consistent with maintaining technical excellence, simply adding an extra level of

performance requirement. Improved project outcomes when both risk and reward are

shared among project participants have recently been reported (Love et al. 2011).

Much of the construction industry, however, tends to have an over-reliance on cost-

based measures of design performance when compared to quality and constructability

issues. This amounts to a cultural barrier to innovation. The importance of design to

innovation is stressed, as is the idea that designers need to participate in the collection

and analysis of data on design articulations if full benefits are to be achieved (Ivory

2005). While an innovation needs to have measurable benefits to be successful, these

benefits may be other than strictly cost-based. A culture of innovation requires the

consideration of environmental and social goals along with economic ones and this

involves some inherent risk.

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Miozzo and Dewick (2002) discuss the issue of governance and the extent to which

strategic control is in the hands of those who allocate resources for investment in

innovation. The capacity to assess innovation risk requires both a broad knowledge

of economic conditions and a specific knowledge of the potential benefits and pitfalls

of a particular proposed innovation. At the same time that this hard commercial

assessment must be made, the potential innovation manager needs to ensure that there

is a degree of openness in the firm’s capacity to develop beneficial changes. Seaden

et al. (2003) found that, in general, innovative behaviour varies with the size of the

firm and that small firms are largely risk-averse. Nevertheless, firms that are able to

overcome this challenge are likely to achieve significant gains from innovative

practice.

In a multi-industry study which included construction, Searle and Ball (2003) found

that company policy usually rewarded non-managerial level employees for

innovating, but expected managerial staff to do so as a matter of course. This

inconsistency was a source of blockage to the implementation of new ideas. Creating

the conditions in which individuals can freely engage in innovative processes requires

a certain level of open exchange both within and between organisations. It may be

that the temporary loss of exclusive possession of a profitable idea can be

compensated for by the generation of many more profitable ideas. Creativity only

flourishes in an atmosphere of openness, and overly cautious risk aversion can stifle

the potential of innovative suggestions.

2.9 Client and end-user influences

Clients have been clearly identified as key drivers of performance improvement and

innovation (Hartmann et al. 2008). Blayse and Manley (2004) noted that clients are

key drivers of innovation because they have the ability to influence firms and

individuals involved in building and construction projects in a way that either fosters

or impedes innovation. Clients exert this influence through a number of means,

including the design and implementation of contracts, pre-qualification schemes and

regulations (Fernie et al. 2003a). It has often been pointed out that the greater the

influence of the client, the more complex is the relationship to project outcomes

(Green 1996; Sidwell et al. 2001; Walker 2002; Walker et al. 2002; Ivory 2004; Boyd

54

and Chinio 2006). Ivory (2005) has cautioned that this client influence is not always

positive for innovation, although it has the potential to be so. Barlow and Köberle-

Gaiser (2008) found similar impediments to innovation resulting from Private Finance

Initiative (PFI) agreements in the UK (Barlow and Köberle-Gaiser 2008). Client

influence may operate through the procurement structures selected or through the

level of involvement and technical competence of the client, both of which can be

included under the heading ‘client characteristics’. Each of these areas is discussed

below.

2.9.1 Procurement systems

Procurement in the construction industry can sometimes tend to favour the lowest

price options ahead of value-based options (Mahdi et al. 2002). Client-based

interventions such as the movement towards partnering and relationship contracting is

one attempt to address industry problems (Hampson and Kwok 1997; Bresnen and

Marshall 2000; Walker et al. 2000; Hampson et al. 2001; Chan et al. 2004; Cheng et

al. 2004; Sarshar et al. 2004; Turner 2004; Ingirige and Sexton 2006; Walker et al.

2002; Kumaraswamy and Dulaimi 2001; Kumaraswamy et al. 2002; Walker 2002;

Walker and Keniger 2002; Walker and Hampson 2003a&b; Hauck et al. 2004;

Kumaraswamy et al. 2004; Tawiah and Russell 2008). Such initiatives tend to be

mainly confined, however, to large and complex projects with the small and medium-

sized projects being largely uninvolved. Clients and end-users are also often the

driving force behind the use of procurement systems to propel the industry towards

more sustainable practices (Bossink 2002b; Dewick and Miozzo 2002; Dikman et al.

2005; Sterner 2001). Once again, however, this influence tends to have more effect at

the large company and large project level. The diffusion of these procurement systems

towards the SME sector of the industry is problematic, because of the mistrust that is

widely felt towards the large business sector.

Procurement systems in the construction industry influence innovation, because they

set the parameters for knowledge sharing and risk management (Khalfan and

McDermott 2006; de Valence 2010b). Systems such as alliances, specifically address

the traditional adversarial culture of construction and seek to alter its course. Alliance

contracts are themselves organisational innovations and one of their principal effects

is to encourage further innovation through a supportive environment and a fair

55

distribution of economies gained. Rezgui and Miles (2010) have proposed a new

model of alliance that is specifically tailored for SME construction contractors and

which deals with income, risk and responsibility within the alliance, as well as

behavioural and collaborative management. Drejer and Vinding (2006) found that

firms who engage in partnering arrangements are more likely to be innovative than

those who do not. Of course, experience with the implementation of new

procurement methods is variable, and some research has shown that the contractual

basis of Public Private Partnerships (PPPs) in particular can sometimes discourage

innovation (Eaton et al. 2006; Leiringer 2006). This is especially so when smaller

businesses are involved.

It is worth pointing out that the complex nature of construction procurement means

that the terms ‘clients’ and ‘customers’ are not always synonymous in the industry as

they are in some others. The client can be regarded as the initiator and financer of a

project, sometimes called the ‘developer’. Customers, on the other hand, may be the

end-users of the construction product; that is, the project’s eventual occupants. There

may be a conflict of interest between the two groups, especially if the client or

developer is a speculator with only a short term interest in the outcome of the project.

End-users have their part to play in the diffusion of technical innovations, but they are

often less likely to identified as drivers of the innovation process in construction

(Harty 2010).

Like clients, end-users or customers have the potential to drive innovation (Fagerberg

1995; Ozaki 2003). Unlike clients, however, the end-users of buildings may

sometimes be of minor economic significance to the construction contractor, as they

are somewhat removed from the direct sphere of influence. Thus, some end-users

have little capacity to influence procurement arrangements. Nevertheless, post

occupancy evaluations and similar studies present the opportunity to perform a

feedback function for construction contractors which may improve this situation

(Lowry 2002). It is possible that this process may have a greater impact in the future

as end-user evaluations become common practice in the industry.

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2.9.2 Client characteristics

In discussing ‘Client characteristics’, this research will focus on the knowledge,

experience and management skill levels of the client, rather than their personal

idiosyncrasies. Clients may be groups as well as individuals and, consequently in the

group situation, individual personality traits are less significant. The absorptive

capacity of the industry and of individual firms has been identified as an important

precondition for innovation to flourish in the economy generally (Hampson and

Tatum 1997; Gann 2001; Ling et al. 2006). Manley (2006) has demonstrated that a

high-level of technical competence in the client body is a significant enabler for

construction innovation. Both the clients’ core competences and their internal

innovation capabilities need to be maintained if they are to foster and encourage

innovative thinking at levels of contractors who have input into the construction

industry (Lindahl and Ridd 2007).

Nam and Tatum (1992) have pointed out that client values are not necessarily as

conservative as they are often depicted to be by other industry participants. Some

clients who actively foster innovation within their own organisations are able to

accept and encourage innovation in the building projects which they commission.

This openness means that technology availability can drive technical innovation

without the presence of ‘market push’ factors from the outset. In order to increase

contractor contribution to innovation and value creation, clients need to take a long

term perspective and actively encourage an innovation-friendly climate on projects.

While traditional industry structure has been demonstrated to be a barrier to

innovation at times (Barlow 2000; Sidwell et al. 2001; Dulaimi et al. 2003), new

procurement methods under the general heading of relationship contracting can

sometimes fail to address the specific concerns of smaller companies and sub-

contractors in their relationships with clients (Barlow and Köberle-Gaiser 2008). This

is particularly so if risk remains shifted downstream from clients and large contractors

to the smaller players. Erikssen et al. (2007) found that procurement methods which

affect the level of sub-contractor involvement in project integration do not necessarily

improve the level of innovation delivered. Clients can counter this tendency by

having procedures which prioritise value over simple cost measures and which share

the benefits of innovation with all the participants in the process. A collaborative

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project climate and a ‘best for project attitude’ among all project participants is only

likely to occur if the client who is the project generator values such an atmosphere

and makes support for it explicit.

The demand for a more sustainable construction industry is increasingly giving

impetus to construction innovation (Bossink 2002). This is mainly a market-pull

force directed by clients and end-users, but can also be a technology-pull force

directed by the innovation generators themselves. As Bossink (2007) has clearly

identified, sustainable project delivery is heavily influenced by the personal style of

the manager involved. As clients are increasingly expressing a general community

desire to improve the sustainability of the construction industry, they can support this

improvement by choosing project managers who combine technical competence with

the ability to coordinate knowledge exchange and cooperation among the project

participants.

The construction industry derives considerable benefit from early adopter or lead-user

clients. Involved and active clients contribute a great deal towards the efficacy of

built environment solutions. They can initiate innovations themselves, foster an

atmosphere in which innovations are able to occur, facilitate the adoption of external

innovations and encourage the diffusion of successful innovations through feedback

and publicity. Frequently, lead-users have a long-term focus which is quite different

from the primary concerns of the construction organisation. Their role is a pivotal

one in the amelioration of the construction industry problems mentioned in previous

sections. Not all clients, however, are lead-users and understanding the innovation

behaviour of differing client groups is critical to the successful diffusion of new ideas

(Hartmann et al. 2008).

2.10 Project-based conditions

Project-based industries have been demonstrated to have different priorities for

innovation than more stable industries such as manufacturing (Blindenbach-Driessen

and van den Ende 2006). The nature of project-based activity can sometimes mean

that companies lack the stability and continuity necessary to develop complex

innovations which require time and multiple iterations. The competitive tender

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structure can sometimes mean that the financial benefits of innovations produced by a

builder are usually passed on fully to the end-user rather than to the builder’s own

profit margin (McCoy 2008). The builder’s reward may be that it is possible to use

the innovation in future projects and to gain more market share as a result.

Consequently, interest in knowledge management and the capture of project-based

lessons for future use is a growing area of research (Kamara et al. 2002; Bresnen et

al. 2003; Fernie et al. 2003b). There is a clear understanding that the temporary

nature of construction project teams can lead to a loss of useful experience and

unnecessary duplication of effort. This discontinuity of effective problem solving is

also a factor in the move towards more integrated supply chains in construction

(London and Kenley 2001; Love et al. 2002; Palaneeswaran et al. 2003; Briscoe et al.

2004).

2.10.1 Supply chain relationships

A great deal of research in recent times has focussed on the benefits of integrated

supply chains for a diverse industry made up of many small players (Dainty et al.

2001a; Dainty et al. 2001b; London and Kenley 2001; Love et al. 2002b; Love et al.

2004a; Palaneeswaran et al. 2003; Zou et al. 2005; Larssen et al. 2006; McCoy et al.

2008). Along with the efficiency and productivity benefits, there is also the

possibility that a more integrated supply chain can foster innovation. Establishing

good feedback loops between manufacturers, fabricators and installers can bring their

differing perspectives together for the delivery of a higher quality product (Larsson et

al. 2006). Arditi et al. (1997) described how innovations generated by production

intensive science-based companies outside of the industry can generate technical

innovations that are useful to the construction process. Manley (2008) has shown that

manufacturers have the potential to deliver construction innovations if knowledge

flows and cooperative relationships are supported. Stable supply chain relationships

can also smooth out the disruption caused by the temporary nature of project-based

work. Robeiro and Love (2003) found that strong e-business connections with their

supply chain were particularly useful for SME construction contractors looking for

competitive advantage in the market place.

Those technical innovations classified by Slaughter (1998) as “architectural”,

“systems” or “radical” require changes which can alter operations up and down the

59

supply chain, because linkages with other parts of the construction process are

affected. Consequently, successful delivery of the innovation involves

communication, consultation and expert input from each affected member of the

supply chain (Andrews and Hahn 1998).

2.10.2 On site problem solving

Toole (2001) has identified four ‘trajectories’ or pathways which can ameliorate some

of the problems of the traditional craft-based and project-centred construction

industry. These are moving production off site; using machinery instead of labour;

using engineered materials instead of natural materials; and 'systems design'. While

this perspective is valid, the move to industrialise construction should not prevent

recognition of the fact that the site-based nature of construction can itself generate

practical innovation potential. Mitropoulos and Tatum (2000) identify ‘process

problems’ as one of the four forces which drive construction innovation. Doree and

Holmen (2004) present a case study where a significant technical innovation was

delivered by a contractor as a result of particularly severe project conditions.

Individuals as well as companies can generate innovative ideas resulting from

carefully analysing problems that occur on construction projects. A great deal of

practical knowledge is held in the minds of the individuals who work on site, yet this

experience is often not documented and may consequently be undervalued (Vakola

and Rezgui 2000). Korsvold and Ramstad (2004) have demonstrated from case

studies in the Norwegian construction industry that innovation can be fostered on

projects by using reflective practice to develop collective know-how and creativity

among project participants. This approach has the potential to improve industry

performance if adopted in a more widespread manner.

2.10.3 Occupational health and safety (OH&S) improvement

The construction industry has had long term problems with its poor safety record and

the source of the problem appears to be multi-faceted (Langford et al. 2000;

Loosemore and Andonakis 2007). Lingard and Holmes (2001) found a somewhat

fatalistic attitude to the inevitability of injury on construction sites among some small

businesses in construction. Sarshar et al. (2004) have stressed the need for better risk

mitigation, post-project reviews and improved induction programs to improve

construction project safety performance. At least in first world countries, the

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potential consequences of the largely poor OH&S record of the industry are now of

such economic importance that the need to improve safety standards is itself

becoming a push factor for construction innovation. Cultural changes favouring

hazard assessment processes and the use of safety equipment are gradually changing

the nature of work for many construction workers. The drive for a safer workplace

has in some cases led to specific technical innovations, whose main purpose is to

decrease the likelihood of workplace trauma and repetitive strain injuries (de Jong et

al. 2003).

Reichstein et al. (2005) reports on the liabilities that construction firms face with

respect to other industries in trying to deliver innovations. Despite the undeniable

difficulties inherent in a temporally organised project-based industry which produces

long-lived products, it is nevertheless possible to successfully deliver technical

innovation (Doree and Holmen 2002). The lessons learned from the exceptions to the

rule may well be useful to the industry as a whole.

2.11 Industry networks

Technical innovations, and especially inventions, may be generated by an individual

in isolation, but successful delivery to the marketplace involves the participation of

many other actors. Tatum (2005) identified the need to increase technical support for

construction innovation, while Harty (2005) pointed out the need to consider the

social and organisational context in which innovation is located. Indeed, Cohen and

Prusak (2001) claim that it is a firm’s social capital that is paramount in the efficient

operation of any business. In addition, Yin (2006) noted that innovation takes the

creative energies of many minds and therefore benefits from the free exchange of

ideas and information. Fleming and Juda (2004) reported on the advantages of

information gatekeepers building connections outside of their specific disciplines and

industries. Staber (2004) found that project-based workers with work-related social

networks outside their organisation tended to be more innovative than those without

such networks. Abbott and Allen (2005) have described how the UK Centre for

Construction Innovation has been able to facilitate both inter- and intra-organisation

cultural assessment with the aim of improving the climate for innovation. The Centre

has acted as an innovation broker, bringing together industrialists, researchers,

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academics and practitioners and fostering information exchange. The Cooperative

Research Centre for Construction Innovation (CRC CI) in Australia has filled a

similar role (Keast and Hampson 2005). Innovation brokerages have also been

successfully trialled in other Australian industries, such as mining and resources

(Dodgson and Steen 2008). While there has been some research that disputes the

efficacy of industry networks as an aid to innovation (Taylor and Levitt 2008), it is

nevertheless likely that some kind of industry facilitation will be needed in the future

to lift industry performance.

2.11.1 Professional and industry associations

Successful innovation in the building and construction industry is widely believed by

industry observers to be heavily influenced by the structure of relationships in the

industry (Reichstein et al. 2008). This is true of networking activities as well as of

integration of the supply chain. As noted in Blayse and Manley (2004), relationships

are important because they have the ability to facilitate knowledge flows via

transactions and interactions between individuals and firms. A ‘community of

practice’ approach to knowledge diffusion is also reported to be successful in

encouraging construction firms to innovate (Walker and Peansupap, 2003). The

authors found that ‘word of mouth’ is an extremely powerful means of encouraging

innovative practice. Joint problem solving is an effective framework for encouraging

the sharing of tacit knowledge and the development of trusting relationships.

‘Communities of practice’ can develop through industry organisations or through

repeat project groupings and the relationships formed can counter the short-term

project-based emphasis of much of the construction industry. In particular, the

sharing of information technology may assist in breaking down inter-firm barriers of

secrecy and mistrust (Bossink 2002).

There is evidence that the breaking down of such barriers is already occurring.

Miozzo and Dewick (2004) interviewed several large construction companies

operating across national boundaries. It was found that firms with strong inter-

relationships with related groups were most likely to prosper. Stable long-term

networks were found to be responsible for enhanced performance. The authors have

suggested that governments should encourage the formation of such long-term

industry relationships. Comet (2009) reported that small firms in the French

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construction industry have derived considerable benefit from cohesive networks

within their sphere of activity (Comet 2009). Rutten et al. (2009) looked at the role of

systems integrators who foster innovation by encouraging inter-organisational

cooperation. Within the Australian context, Manley (2003) reported on four key

approaches for construction industry relationships, namely systems, networks, value

chains and clusters. All are capable of providing the framework for innovation, but

the critical issue is their integration. Freel (2003) noted that for small firms

networking or informal association can be particularly critical for innovation delivery

and diffusion. Without such networking, the innovations developed in small firms

can sometimes fail to result in improved performance. The innovation may ‘wither

on the vine’. In addition, small firms often rely on informal networks of their peers in

order to learn of latest ‘best practice’ ideas. Informal networks, however, can only

partially resolve the difficulties and insecurities inherent for employees in loosely

connected project-based firms. More stability in inter-firm relationships is still

required to produce an industry structured to foster innovation.

Industry relationships can be contractual and based around projects or they may be of

a more general informal nature, based on long association over several years and

many projects. Some degree of stability is achieved through formal and informal

partnering relationships. Partnering relationships, usually governed by contractual

obligations, can also foster innovation provided that project knowledge and project

risk is fairly distributed. Chan et al. (2003) have described the benefits of

construction partnering as experienced in Hong Kong. A comprehensive

questionnaire revealed that under partnering arrangements, projects are more likely to

be delivered on time and on budget, and the number of conflicts and defects are also

reduced. By eliminating ‘defensive case building’, the cost of negotiating and

delivering a contract is considerably reduced. A better safety record and improved

customer satisfaction were also reported from partnering projects. The detail of the

contractual arrangements may have influenced the success of the projects studied, but

the results show a demonstrable benefit over traditional contractual arrangements.

The terms partnership, joint venture and alliance are used with varying shades of

meaning by different authors. The specific detail of the procurement relationship may

vary from project to project and some arrangements may fit into more than one

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category. As elucidated by Walker et al. (2002), project partnering and project

alliancing can result in significantly different relationships from the adversarial ones

commonly encountered in the industry. The partnering contractual relationship may

remain partially adversarial, in that the partners may be able to benefit at each others’

expense. Alliances on the other hand are predicated on sharing both risk and reward

between the parties, so that they either gain or lose together. Walker et al. (2003)

have reported that relationship-based procurement systems, notably alliances, can

foster innovation through the development of trust and the sharing of risk.

Professional bodies and industry organisations have the potential to foster multiple

connections within the industry through the informal contacts via the organisations

activities. There is some evidence that these informal contacts produce greater value

than government-sponsored formal networks aimed at improving performance

(Huggins 2001). Whichever way they are generated, these informal contacts have the

potential to encourage the level of communication necessary for parties to enter into

formal alliances and other groupings on projects.

2.11.2 Research organisations and universities

According to Barrett and Barrett (2003), integration and risk sharing needs to spread

from project firms to research institutions if a culture of innovation is to develop.

Industry is often reported as being dissatisfied with the results of research (Barrett and

Barrett 2003). It is argued that communication between those involved in research

and industry practitioners needs to improve for innovation to flourish and that

alliances may be formed which include research institutions alongside construction

firms and private consultants. Laursen and Salter (2004) found that firms with

successful open research strategies tend to have universities in their network of

contacts.

Formal and informal networks also assist in encouraging innovation through

providing a forum for discussion and through the dissemination of new ideas

(Hampson 1998). University Centres can provide this opportunity. Participation in

such networks is a good entry point for an individual firm wanting to develop a

system of innovative practice. Actually implementing such a system is likely to

involve an awareness of means of developing a culture of innovation in an enterprise

or an industry. Innovation intermediaries or ‘innovation brokers’ may be helpful in

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the development and diffusion of technological innovations (Hartmann 2006a;

Stewart and Hyssalo 2008; Winch and Courtney 2007). Universities are particularly

well placed to offer independent advice and assistance to companies wishing to adopt

new Information Technology systems and move to electronic storage and transfer of

data (Dodgson et al. 2002). There may be issues resulting from the differing

priorities of researchers and industry (Lorch 2003; Maqsood et al. 2007). The

funding of research priorities, therefore, needs to take both perspectives into account

if benefits are to flow to all participants.

2.12 Regulatory climate

The approval and regulation system under which the construction industry operates

can have the effect of either encouraging or discouraging innovative activity (Gann et

al. 1998; Campagnac 1998; Winch 2000; Slaughter and Shimizu 2000; Dewick and

Miozzo 2002a; Dewick and Miozzo 2002b). This may be due to the structure of the

industry, its ability to respond flexibly to challenges or even to more esoteric factors

such as how national culture values originality. There is an often-observed tension

between innovation and standardisation which may be difficult to resolve, but is not

necessarily without benefit for the industry (Edum-Fotwe et al. 2004).

2.12.1 Performance-based standards

Several authors have pointed to the restrictive role that planning and building

regulators may have on innovation (Oster and Quigley, 1977, Gann and Salter 2000;

Dubois and Gadde 2002; Meacham 2010). As a response, a widespread trend in

recent years in developed economies has been the move away from prescriptive

building regulation towards regulations that are ‘performance-based’. The framework

of national or local building regulations and standards as well as occupational health

and safety laws (OHS) represents a predetermined context into which successful

innovations need to fit. If it is legislatively too difficult to introduce changed practice,

then innovation can be largely stifled. Performance-based standards set the outcomes

required, but not the means of achieving those outcomes. They are open-ended and

therefore more responsive to context. There is some multi-industry evidence that this

is a successful approach (Bruneau 2004). Performance-based standards are often

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highly valued by building designers, as they are seen as enablers of flexible and

innovative solutions (Fujitani et al. 2004).

The positive impact of industry regulations on innovation in the building and

construction industry was examined in Blayse and Manley (2004). They cited

literature that pointed to the importance of government regulatory policies that

exerted an influence on demand and played an important role in moulding the

direction of technological change. It was suggested that ‘performance-based’, as

opposed to prescriptive or ‘deemed to satisfy’ industry regulations, had much more

capacity to provide the necessary conditions for innovation to occur in the building

and construction industry. A good example of such performance-based regulations

providing the opportunity for innovations is the relatively new discipline of Fire

Safety Engineering which has been developed largely in response to these standards.

It is based on providing innovative solutions in circumstances where the standard

code-driven response is inadequate or uneconomical. In particular, the application of

performance-based solutions to fire safety issues in refurbishment projects has led to

significant economies without loss of safety performance.

The trend towards introduction of performance-based standards is not without its own

difficulties. Sexton and Barrett (2005) have documented the way that performance-

based building can sometimes run counter to the business logic necessary for

innovation. In addition, performance-based standards can affect the reliability of

financial valuations of existing buildings. This is because the certainty formerly

provided by strictly enforced requirements on means of egress and fire protection has

been removed. A fire safety engineer may be able to provide a non-structural solution

in a building that would otherwise require expensive structural alterations to achieve

code compliance. Valuation is a significant issue for investors, so this problem

cannot be easily ignored. Some research in New Zealand has uncovered some

problems with building performance under flexible standards, but this research comes

from a legal perspective and may have more to do with certainty about legal rights

when standards are not met rather than with actual building performance (May 2003).

The flexibility provided by performance-based standards can sometimes be gained at

the cost of certainty, so there has been some resistance to the move to such standards

and it is clear that they do not always deliver the predicted benefits or result in greater

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innovation (Meacham et al. 2005). It is possible that more experience with the

operation of performance-based standards will settle the difficulty as innovative

performance-based solutions become standard practice.

2.12.2 Industry standards

The construction industry does not operate entirely on the basis of complying with

existing regulatory codes in all instances. With regard to new products and processes,

it may be that industry standard practice advances well ahead of building regulation.

In these cases, expert guidance and the attitudes of competitors can have a great deal

of influence. The pressing need for more stringent energy efficiency standards is

currently driving a great deal of innovation in the construction industry generally and

especially in the housing sector (Gann et al. 1998). Such innovation can be fostered

by semi-government and non-government organisations, as well as through

regulation. Both environmental performance and OH&S are areas where community

desire for improvement is pushing the industry to raise standards. Both

environmental groups and social activists are pressing the industry to change long

held cultural attitudes and improve its outcomes on these matters. Responsive

companies are achieving market gains by incorporating these ideals into their own

agenda.

2.12.3 Local government regulations

Not only is the construction industry itself characterised by many small entities, in

some countries governance and regulation is similarly diverse and local in nature. In

places like Australia where the construction approval system is not regulated by a

unitary national government but is devolved to smaller local government entities,

particular issues with consistency and verification can arise (Bell and Lowe 2000;

Brown and Furneaux 2007). This local focus also runs contrary to the move towards

market globalisation and international competition for construction projects. Local

regulations can protect sensitive local cultures, environments and practices, but their

downside is a possible failure to adapt to change and potential gains brought about

through an innovation culture.

Progressive companies can only actively improve their own performance and perhaps

hope to influence their competitors. The primary responsibility for improving

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standards lies with the industry regulators. Their input addresses issues of physical

safety, environmental effects and social consequences of construction industry

performance. The increasing trend towards performance standards, instead of

prescriptive solutions, is one that has considerable merit for encouraging innovation.

It is now generally accepted that while regulatory systems need to maintain standards,

they must be sufficiently flexible to enable the development and adoption of new

solutions. This is a difficult balance to achieve; but without it, regulators become a

brake on improvement and a barrier to innovation.

2.13 Summary of results from the literature review

The discipline of innovation management first developed in spheres of activity which

are fundamentally quite different from the construction industry. Despite this, the

literature shows that the application of innovation theory in the construction industry

can be of considerable benefit. The construction industry, at the same time, reacts to

and drives the global economy. Efficiency gains that can be made in construction

have significant flow-ons to other industries, as well as benefits for society as a

whole. Innovation is regarded as essential to the continued growth; consequently, the

construction industry needs to foster and encourage innovative practice (Hardie et al.

2006).

There is a considerable body of evidence in the literature to lead to the conclusion that

innovation requires a cooperative atmosphere and that the construction industry needs

to abandon its adversarial practices if innovation is to flourish. Despite some notable

exceptions, the traditional culture of the construction industry has produced attitudes

that are often antagonistic towards innovation and change. There is also considerable

inertia in the current system but, nevertheless, the movement towards a new culture is

already apparent in some areas. Innovation can be fostered through management

practices that encourage multi-disciplinary teams and idea sharing practices. There is

also widespread agreement that construction firms need to develop systems for

providing continuity between projects so that knowledge gained is retained and

disseminated. The equitable sharing of risk and reward through all project

participants is another measure widely believed to aid innovation.

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The changes required in current practice are not small and are likely to involve

considerable effort in their implementation. A radical overhaul of industry culture has

long been seen to be required (Pavitt 1984; Nam and Tatum 1989; Reichstein et al.

2008; Sundqvist 2004; Woudhuysen and Abley 2004). The project-based and largely

adversarial nature of construction contracts is slowly being replaced by innovative

management initiatives which share risk and foster collaboration. Already, systems of

knowledge management and empowerment of participants are providing encouraging

results for those organisations which actively pursue these goals. Robust networks of

contacts within the industry increase the likelihood of innovation generation and

innovation diffusion. Initial sources of innovative practice are many and varied.

Creative individuals can lead innovation, provided they are given an environment

conducive to the exercising of their talents. Innovations can stem from the

identification of a newly recognised need such as increased environmental

performance. A technological development itself can inspire innovation in the form

of new applications. An organisational structure that encourages monitoring of new

ideas and practices and the careful evaluation of innovations creates an atmosphere in

which further innovation is quite likely to occur.

The literature reports on considerable synergies between organisational innovations

and technological ones. They tend to occur together and result in multiple benefits.

There is much industry support for the adoption of innovation strategies, both in

organisational as well as technological matters. There remains some disagreement

about the best way to encourage innovation in those areas of the industry which

currently perceive of no benefit to themselves in partaking in the process. There is

also disagreement about who should lead the process and what structures will best

promote the necessary change.

It is, nevertheless, clear that measurable improvements in performance, quality, time

saved and in profitability can be demonstrated as having resulted from construction

innovations. A culture which favours and fosters innovation is widely regarded as

crucial to the continued growth and prosperity within the industry and the larger

economy. This thesis reports on the experience of SME construction managers who

have been recognised by their peers as having delivered successful technical

innovations. It is contended that their opinions and insights will give an indication of

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the most appropriate strategies that can be adopted by those wishing to emulate

current day innovator’s success. Chapter 3 deals with the selection of methodologies

suitable for capturing the knowledge gained by the identified successful innovators.

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CHAPTER 3 RESEARCH METHODOLOGY

Chapter 3 considers the possible methodological approaches which might be used to

address the question of ‘What lessons can be learned from instances of successful

technical innovation delivered by construction SMEs?’ The limitations of the use of

purely quantitative research approaches when dealing with human actors are

presented. The value of mixed methodology structures in construction management

research is explained and the specific methodological structure selected for this

research is presented. Several possible methods of triangulating quantitative data

with qualitative research outcomes are discussed.

3.1 Mixed methodology research

Creswell (2009) has explained how the perceived legitimacy of both quantitative and

qualitative research has resulted in an expanding trend towards mixed methodology

research. A mixed methods approach can incorporate the best features of quantitative

and qualitative research (Teddlie and Tashakkori 2009). The conclusions drawn from

the two strands can be compared and contrasted. Convergences and disagreements

between the methodological approaches may offer particular insights that either

approach alone may not provide. Of course, this is also true if two or more different

research methods are used within the overall paradigm of either quantitative or

qualitative research. The approach of using multiple viewpoints for the same research

object is referred to as ‘triangulation’ (Jick 1979). Drawing on a metaphor from the

geometry of spatial location, triangulation can be seen as a way to improve the

accuracy of research results by collecting different types of data which relate to the

same observed phenomenon.

The concept of triangulation in research methodology relies on the suggestion that the

weaknesses of any single method are likely to be counter-balanced by the

compensating strengths of another. As Jick (1979) has explained, qualitative

researchers can benefit from quantitative methods of systematising their observations,

employing sampling techniques and coding their qualitative data sets. Similarly,

quantitative researchers can learn from qualitative approaches to social observation

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strategies, interpretive fieldwork and the investigation of puzzling findings. Mixed

quantitative and qualitative methods are especially appropriate when the research

focus is on matters which involve the element of human behaviour.

3.1.1 Debate over quantitative research in construction management

Seymour and Rooke (1995) have addressed the issue of the human element in

construction management research and come down heavily on the side of the

argument that claims that purely quantitative research, which they term the ‘rationalist

paradigm’, does not effectively answer research problems in construction

management. The authors state that the distinction between subjective experience and

objective reality, which works authoritatively in the natural science disciplines, falls

down in fields that involve research into human beings, because researchers have no

way of confirming the validity of their version of events compared with that of the

participants. The metaphor often used is that ‘the dancers cannot be separated from

the dance’. Seymour and Rooke (1995) claim that the expectation implicit in the

rationalist paradigm is that research findings will be unambiguous. They further state

that such an approach is not suitable for making assessments about social processes.

The individual researcher’s own viewpoint is hard to separate from that of the people

being studied or observed. Seymour’s and Rooke’s call for a debate among

construction researchers on this subject provoked responses that included widely

varying perspectives and some outright rejection (Root et al. 1997; Runeson 1997a

and b).

The more common response to Seymour and Rooke (1995 and 1998), Rooke et al.

(1997) and Seymour et al. (1997) from other researchers has been to suggest that it is

not appropriate to characterise disagreement about the value of quantitative and

qualitative research as an ‘all or nothing situation’ (Raftery et al. 1997; Chau et al.

1998). These authors contend that there is a place for the rationalist or scientific

method approach in construction research and that it can exist alongside and in

company with qualitative and interpretive research. They argue against

‘methodological monopolies’ and ‘throwing the baby out with the bathwater’. They

note that it has always been possible to use quantitative methods in a reflective mode

and thereby lessen the likelihood that the researcher will impose inappropriate

strictures on data and the evaluation of results.

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Similarly, research methodologies have been developed which increase the rigour and

reduce the subjective nature of qualitative research such as case studies, interviews

and ethnography (Barrett and Sutrisna 2007; Dainty et al. 2000; Dey 1993; Maqsood

et al. 2007; Pink et al. 2010; Sutrisna and Barrett 2007). Dainty (2008) has recently

looked at the nature of the research type in published articles in Construction

Management and Economics and has concluded that the positivist paradigm and

quantitative methodologies still account for the great majority of construction

management research, as evidenced by the published record in this journal. Dainty

(2008) recommends ‘reflexivity’ ,where researchers openly question the effectiveness

of their methodologies and the robustness of their results as an appropriate strategy to

improve rigour in qualitative research. Following this advice and seeking reflexivity,

this researcher has sought to extend the findings of the quantitative AHP study with

qualitative research in the same subject area.

3.1.2 ‘Paradigm wars’

The methodology debate which occurred in the late 1990s in construction academia

mirrors a much larger and more disputative debate in the broad fields of the Social

Sciences and Economics over several decades and commonly referred to as the

‘Paradigm wars’ (Tashakkori and Teddlie 1998). The dichotomy is often expressed

as between various polar alternatives such as quantitative and qualitative

methodologies; deductive and inductive reasoning; and positivist and constructivist

philosophy. Positivism is a philosophy of science theory which holds that the only

authentic knowledge is that which is based on sensory experience and positive

verification. Positivist theory is founded in the traditional scientific method arising

from the approach of 17th century scholar Francis Bacon who set out the ground rules

for making meticulous observations and carrying out systematic experiments (Kuhn

1996). In the twentieth century, mathematician and philosopher Karl Popper

reconsidered the Baconian scientific method and came to the conclusion that

experimentation, however careful and however often repeated, cannot prove an

hypothesis. Repeated experimentation only serves to increase the probability of the

hypothesis being correct. On the other hand, a single case where the hypothesis fails

under experimental verification is enough to disprove it (Popper 1954; 1979). The

Popperian paradigm of Post-Positivism revitalised the scientific method and gave

new, though restricted, support to the use of quantitative experiments as a way of

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understanding problems in the physical world. Constructivism is the opposite of

Positivism/Post-positivism because it holds that scientific knowledge is constructed

by scientists and not discovered from the world. Based on the work of educational

theorist Jean Piaget, constructivism believes knowledge is created within the

individual’s own mind and cannot be transmitted objectively. Consequently, the

constructivist view is that there is no single valid methodology and qualitative

methodologies are more suitable than scientific experimentation for use in studies of

human beings.

While some researchers in particular fields continue to hold tightly to an exclusively

‘Positivist’ or an exclusively ‘Interactionist’ perspective and reject the mixing of these

approaches, there has also been strong recent growth in the area of mixed methods

where both quantitative and qualitative research strategies are used together to tackle

a complex research question (Mingers and Gill 1997; Morgan 2007; Teddlie and Yu

2007). Furthermore, it has been clearly demonstrated that qualitative research can

have structure and rigour and can be applied within established traditions of inquiry

and research which may previously have eschewed such methods (Creswell 1997).

This researcher favours the mixed approach over restrictive ideological approaches

that exclude either quantitative or qualitative methods. This is not intended to deride

or characterise as inadequate single method studies, but rather the intention is to seek

to validate results in an area of ambiguity by approaching the research question from

several different angles. As Creswell (2009) declares, “there is more insight to be

gained from the combination of both quantitative and qualitative research than either

form by itself” (Creswell 2009 p.203). This insight can been described as

methodological triangulation.

3.1.3 The case for mixed methods in a developing discipline

Love et al. (2002) discusses the suitability of methodological triangulation as a

research strategy in construction management. It is contended that the approach used

to study events and phenomena in the natural sciences is largely inappropriate in

construction management research, because the latter involves “thinking participants”

(Love et al. 2002a p.294). The separation that exists between thoughts and events in

the natural sciences does not exist when the subjects of the research have their own

thought processes. In consequence, uncertainty is created and the laws of scientific

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generalisation are violated. Triangulation as a strategy aims to get a clearer picture of

reality than a single methodological approach can generate. If the results of the

differing strategies converge or demonstrate agreement, then this can be regarded as

adding to the robustness of the conclusions. Nevertheless, convergence is difficult to

achieve, especially when the separate methodologies used are drawn from differing

fundamental world views. Researchers adopting the triangulation approach are,

therefore, cautioned that they should not adopt this approach merely for convenience

or because other efforts to close a research problem have failed (Love et al. 2002,

p.301). The adoption of a mixed methods approach is a positive step towards a

broader understanding of the research question rather than an admission of the failure

of a single methodology to produce robust conclusions.

Li and Love (1998) proposed the need for a theory of construction problem-solving

that considers not only the problem, but also the problem-solver and the industry in

which the problem occurs. In the absence of such a theory, the discipline cannot be

regarded as mature. This thesis hopes to make a contribution to the development of

the understanding of construction problem-solving and decision making by

approaching these issues with mixed method strategies in order to triangulate the

results of separate quantitative and qualitative studies. As Love et al. (2002 p.296)

have noted, construction businesses “are essentially human enterprises and cannot be

understood solely in terms of technical relations among components from a purely

scientific approach”. Consequently, it was always the intention of this researcher that

the results gained from a quantitative study would be extended by a qualitative

approach and the results evaluated against one another.

3.2 Mixed method strategies

Creswell (2008) sets out the types of mixed methods strategies which can be used

when combining quantitative and qualitative research. Such methods can be applied

either sequentially or concurrently. If the data is collected sequentially, either the

qualitative or the quantitative phase may occur first, depending on the intention of the

study. Six strategy options are identified: Sequential Explanatory Strategy;

Sequential Exploratory Strategy; Sequential Transformative Strategy; Concurrent

Triangulation Strategy; Concurrent Embedded Strategy; and Concurrent

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Transformative Strategy (Creswell 2008, pp. 211-216). The strategies’ purposes and

applicability are summarised below.

The Sequential Explanatory Strategy is suitable for researchers with strong

quantitative leanings. It involves collection and analysis of empirical data, followed

by secondary qualitative data collection to examine surprising or unexpected results.

Strong weighting is given to the quantitative data. The results from the quantitative

data inform the secondary qualitative data collection.

In the Sequential Exploratory Strategy, the two phases are reversed. Qualitative data

is collected and analysed and this informs the second phase of quantitative data

collection. This strategy is used to explain and interpret relationships and is useful for

a researcher who wants to explore observed phenomena. Generally, stronger

weighting is given to qualitative aspects.

Sequential Transformative Strategy is also a two-phase process, but it involves a

“theoretical lens” which overlays the sequential procedures and guides or shapes the

study (Creswell 2009). Equal weight can be given to both phases or, alternately,

either may predominate. It is appropriate when the researcher wishes to test an

existing theoretical perspective.

The Concurrent Triangulation Strategy involves the researcher collecting both

quantitative and qualitative data at the same time and observing any convergences or

differences in the two data sets. This can be referred to as confirmation, dis-

confirmation, cross-validation or corroboration (Creswell. 2009). The intention is to

offset the weaknesses inherent in one method with the strengths of the other.

In Concurrent Embedded Strategy, there is a primary method that guides the project

and a secondary database that plays a supporting role in the procedures. The

secondary data collection may be seeking information at a different level of analysis.

The data from the two sources is compared and contrasted in a discussion of the

results.

Finally, the Concurrent Transformative Strategy is guided by the use of a specific

theoretical perspective which is the driving force behind the methodological choices.

It is appropriate when the researcher intends to test a pre-existing ideological

framework.

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3.2.1 Evaluation of strategies

In the case of this study, sequential methods were ruled out because many of the

subjects of the research were extremely busy people who were only available for a

limited period of time and were unlikely to accept repeated return visits from the

researcher. Consequently, the survey was completed and initial qualitative

information collected at the same time in a single face-to-face interview.

Subsequently, further information was collected through demonstrations and site

visits to construction projects, at times convenient to the survey respondent’s

company. The survey was completed between February and December 2009. The

qualitative data was collected between February 2009 and April 2010. Both empirical

and descriptive data gathering were completed by April 2010.

In considering the concurrent options, Transformative Strategy was ruled out because

of the absence of an existing coherent theoretical construct which addressed the

research topic of factors affecting the delivery of innovation in SME construction.

The Embedded Transformative Strategy was ruled out, because the researcher

contends that while the weighting of the two data collection strands is not exactly

equal, nevertheless one does not dominate the other to any great extent. The

perspectives of both quantitative and qualitative data are considered necessary in

order to adequately explain the phenomenon of technical innovation delivery by SME

construction organisations. This leaves Concurrent Triangulation Strategy as the most

appropriate option. This researcher has an issue with the use of the term

‘triangulation’ to describe data collection from two (rather than three) different

perspectives as the geometric or surveying metaphor implies. Nevertheless, as the

literature review can be considered the third perspective of the research, the

Concurrent Triangulation Strategy is selected as a means of observing convergence or

disagreement in the quantitative and qualitative areas of the thesis. The design of this

methodology is set out in Figure 3.1 overleaf. The three strategies have been pursued

throughout this research into the factors affecting technical innovation delivery by

construction SMEs.

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Figure 3.1 Concurrent Triangulation Strategy: Convergence Model

Developed from Creswell and Plano Clark (2007 p.63)

The basic reasoning behind a triangulation strategy is simply that given robust

methodological application “convergence usually equates to robustness in terms of

knowledge acquisition” (Love et al. 2002 p.301). When convergence does not occur,

this signals areas that require additional investigation as unknown factors may be in

operation. Given the advantages of triangulation, it was decided that at least one

qualititative and one quantitative research method would be employed.

3.3 Selection of qualitative method

Among the qualitative techniques that were considered as potentially appropriate for

this study are: structured interviews; ethnographic studies; grounded theory; action

research; content analysis techniques and case studies. Some of the advantages and

disadvantages of each of these research methods are discussed below.

3.3.1 Structured interviews

One scenario considered was that of a series of structured interviews with selected

experts in the field of construction innovation delivery. Structured interviews have

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the advantage that they enable the researcher to control the line of questioning and

direct the participants’ responses to the critical study questions (Creswell 2009).

Participants are able to describe the history and context of their involvement in the

research area. This would enable relatively rapid collection of data on possible

critical factors for technical innovation. The information provided would, however,

be highly filtered through the perceptions of the chosen experts. The researcher’s

presence could affect the data collected, as the experts might be looking to protect

their reputations or direct future research in the area (Leiringer and Cardellino 2008).

Structured interviews with individuals who had personally been the driver of

successful technical innovation delivery within a construction industry SME were

considered to be likely to yield fresh insights into the research question. Such

individuals are likely, however, to be unable to spare a great deal of time to this

research project. It was also considered that due to time constraints, structured

interviews would necessarily cover a smaller number of the successful innovators

than a quantitative survey that could be completed in less than an hour.

Consequently, a method that involved less demand on the time of the SME innovator

was sought in order to maximise the participation rate. It remained a possibility that

unstructured comments could be collected during other data collection exercises.

3.3.2 Ethnographic studies

Deriving from the field of anthropology, ethnographic research aims to obtain a

holistic picture of the subjects studied by observing their everyday experiences in

context (Creswell 2009). The subject participants are interviewed for their own

opinions. Relevant observations are also collected from other sources. In the case of

a construction company, ethnographic research would be likely to involve a degree of

embeddedness by the researcher in the innovative company concerned. At the very

least, it would require long hours of observation within the identified company. The

time frame for this research did not permit extensive observation from within one or

more construction companies. It was also likely that access would be a problem due

to issues of commercial sensitivity. Nevertheless, the message from ethnographic

theory that the researcher should seek a holistic picture of the observed subject is well

taken.

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3.3.3 Grounded theory

Grounded theory as originally expounded by Glaser and Strauss (1967) involves the

researcher attempting to derive a generalised theory from observation and analysis of

a process, action or interaction. As such, it reverses the traditional scientific

experimental approach. Instead of propounding a theory and subsequently designing

experiments to test the validity of the original theory, grounded theory starts without

any preconceived theoretical structure. Observations are made and data is collected

with the intention that careful consideration of the information gathered will suggest a

theory. The validity of the grounded theory developed by this means should then be

judged according to its fitness, relevance, workability and modifiability (Glaser and

Strauss 1967; Glaser 1992). The developed theory may then be tested in a more

traditional manner.

It should be noted that the proponents of grounded theory do not accept its

classification as a qualitative methodology, because they assert that ‘all is data’. As a

result, the approach may be used for numerical data as much as for qualitative

observations. For the purposes of this thesis, however, it was only considered as a

means of exploring qualitative data. While suitable for exploratory research,

grounded theory method was not chosen for this study because its multi-stage

approach would, as with ethnography, involve considerable demands on the time of

the research subjects. Although Hari et al. (2005) have demonstrated that this

methodology can be useful for studying the difficulties experienced by small

construction businesses, this was in a context where the participants had an

expectation of significant improvement in their own organisation’s performance by

means of involvement in the study. It was considered that this time commitment was

unlikely to be readily available from SME innovators who were already successfully

delivering innovations.

3.3.4 Action research

Action research is a reflective process for the purposes of progressive problem

solving. The researcher works with individuals in a group or team to address the way

they approach problems and find solutions. The term was coined by Kurt Lewin in

the 1940s as part of his work on the problems of racial minority groups (Lewin 1946).

Action research may be undertaken by companies or groups with a view to improving

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their performance, practices and self-awareness. Davey et al. (2002) has proven the

efficacy of this technique for small construction companies. Even more so than

grounded theory, however, this approach would involve a strong commitment from

the participating SMEs and it was therefore not chosen for this thesis.

3.3.5 Content analysis techniques

Computer-aided qualitative data analysis software (CAQDAS) can be used to analyse

information from multiple sources with a view to coding and identifying patterns in

qualitative data (Veal 2005). The most commonly used software package for these

purposes is Nvivo™. The software assists in the shaping of large amounts of text and

other data into coded groupings which are then able to be used to test intuitive

assumptions about the meaning of the aggregated data. This software was accessed

too late in the research process for it to be used for this thesis. It is envisaged that this

methodology will be used to code and re-analyse the data collected during this thesis

with a view to deriving more value from the research study.

3.3.6 Case studies

The case study as a research methodology can be defined as the intensive analysis of

the occurrence of an individual event or phenomenon when observed in its temporal

and spatial context. Case studies may be selected because they are typical instances

of the event studied, or because they are unusual and may therefore shed light on the

extent or nature of the phenomenon being observed (Fellows and Liu 2008). As Yin

(2009) explains, case study research is suitable when the number of contextual

variables is so numerous that traditional experimental design would be unworkable

due to the number of data points required. Case studies are also suitable when the

primary data collection technique is participant observation. In order to enhance the

validity of the information gained from case studies, it is recommended that multiple

sources of evidence are used and that a case study database is developed as part of the

methodology (Fellows and Liu 2008).

The case study methodology enabled a process whereby the researcher could collect

multiple information sources relating to instances of technical innovation by

construction SMEs without making unreasonable demands on the time of the

individual innovators. Data could be accessed from the innovators themselves by

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interview, but also from published academic and trade literature, professional

association reports, site visits and post occupancy evaluations. This approach

lessened the likelihood that the innovators could manipulate the dialogue with the

researcher to their own advantage as suggested by Leiringer and Cardellino (2008).

Case study methodology allowed the observation of multiple instances of technical

innovation by construction SMEs and therefore facilitated access to a variety of

different kinds of successful innovation. For this reason, case studies were selected as

the methodology most likely to yield useful results within the projected timeframe of

the thesis study.

3.4 Selection of quantitative method

Quantitative methods considered for use in this study into the delivery of technical

innovation in construction include: statistically validated questionnaires; computer

simulations; and goal-oriented decision-making.

3.4.1 Statistically representative questionnaires

A questionnaire used to survey a statistically significant proportion of the population

of construction SMEs in the study area was initially considered as a means of

determining the drivers and inhibitors for technical innovation. Such questionnaires

could be composed using Likert scale questions. This would yield large amounts of

numerical data which could then be analysed with standard statistical tests.

The population of construction industry SMEs as recorded by the Australian Bureau

of Statistics is in the region of 125,000 (ABS 2008, p.10). This presents a difficulty

in that the population of construction SMEs is so large that it would be beyond the

resources of a PhD candidate to contact and receive responses from a statistically

significant sample. Such surveys are rightly the province of the ABS. Consequently,

it was decided to narrow the focus of the research to successful SME technical

innovators. These would then be contacted and data collected by several means in

order to record their experience.

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3.4.2 Computer simulations

In recent years, computer game software has been developed which mimics the

operation of a construction enterprise and simulates the decision making processes

that occur on construction projects. It would be possible to set up a scenario where a

technical innovation was proposed for development and deployment within an SME.

Chief decision makers from such companies could potentially be invited to work

through the issues involved via the game simulation. The game would score the

success of the simulation decisions numerically. This might well yield useful insights

into the delivery process for technical innovation. It would be more useful, however

if employed as a follow-up methodology once a well structured scheme of decision

making priorities had been determined. Therefore, it was not selected for this thesis,

but is suggested as a future research methodology to extend this research.

3.4.3 Goal-oriented decision-making

It was considered that in order to achieve a high response rate from successful SME

innovators, it would be necessary to demonstrate to them a research tool that might

prove useful in their future operations. The term goal-oriented decision-making

describes a variety of research tools that give individuals and firms a structure for

decisions that they might otherwise make in an ad hoc or intuitive manner. There are

numerous methodologies that come under the general heading of Multi Criteria

Decision Making (MCDM). These are considered in Chapter 4 and the preferred

option is given. The value of this methodology for this study lay in the rigour of its

mathematical basis combined with its ease of use. The technical innovators who are

the subject of this research may not all be particularly prone to self-analysis. They

might also be not especially articulate about the process that they have been through.

MCDM methodologies enable the capture of a quantitative structure behind the series

of choices that are made when delivering a technical innovation.

3.5 Methodology for evaluating convergence in the data sets

Having identified the appropriate methodologies for addressing the research question

as qualitative case studies and a quantitative Multi Criteria Decision Making survey, it

is then necessary to consider how it might be possible to aggregate the results from

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the two methodological viewpoints. Love et al. (2002) cautions against the use of

methodological triangulation for the sake of convenience. It is unlikely that randomly

chosen different methodologies will result in the ‘closure’ of a research problem or

the imposition of an overall unifying theory on diversely collected data. Any

convergences in the findings will, therefore, require interpretation. Love et al. (2002

p. 301) counsel the researcher that “to understand the world of meaning one must

interpret it”. The researcher needs to look beyond the simple outputs of different

methodologies adopted and offer constructions that attempt to explain holistically

how the results relate to the initial study object. Therefore an interpretivist approach

is taken to the aggregation of the results from the mixed methods study. This

interpretivist outcome is presented in Chapter 8 of this thesis.

Tashakkori and Teddlie (1998) have described mixed methodology or mixed model

research as having a clear focus on the research question, rather than on the prevailing

discipline paradigm or world view. As a result, mixed model research, used either

sequentially or concurrently, is able to address areas of study that are in their relative

infancy in terms of formal research. Mixed model research is able to break new

ground by validating research conclusions from the differing perspectives of

quantitative and qualitative studies. The intention in this thesis is that three research

strategies are used to triangulate the results on the general research question of “What

are the factors which affect technical innovation by construction industry SMEs?”

The three strategies are literature review, the quantitative methodology of an MCDM

study and the qualitative methodology of descriptive case studies. It is intended that

the three approaches give a multi-faceted view of the research question and permit

somewhat more generalisation from the findings than any of the individual three

strategies may have entailed separately. The three different approaches involve:

‘casting the net widely’ in the literature review to determine the factors to be tested;

undertaking prioritisation of those factors using an anonymous survey of successful

innovators; and illustrating the variety and extent of possible SME technical

innovation strategies via the case studies.

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CHAPTER 4 DECISION MAKING METHODOLOGIE S

Chapter 4 makes the case that the choice of whether or not to introduce an innovation

can be seen as a classic decision making problem. It then analyses the various

methodologies which come under the category of Multi Criteria Decision Making

(MCDM) Models and selects Analytic Hierarchy Process (AHP) as the most

appropriate method for the quantitative section of this study.

4.1 Decision making problems

Rogers (2003 p.168) describes “the innovation-decision process” as comprising of

initial knowledge, the forming of an attitude, the decision to adopt or reject, the

implementation of the innovation and finally, the confirmation of the decision. In

SMEs, this process is often undertaken by an individual who is the chief decision

maker for the firm. In larger firms, the structure of the decision making process may

be much broader. When the organisational structure is multi-faceted and diverse, the

use of decision making methodologies would be inappropriate. In smaller firms,

however, it is quite likely that the choice to invest in change may well be made by one

or two individuals. At both ends of the spectrum, decision making in some form has

long been regarded as being a core skill at the heart of all business management

processes (Arrow and Raynaud 1986; Simon 1957; Simon 1983; Hammond et al.

1999). The making of selections among different courses of action, which may

include the choice of ‘no change’ or maintaining the current position, is definitely a

complex process, but it is not necessarily without structure. Decision making theory

relies on the assumption that all decision makers desire to make rational choices

whether or not they actually achieve this objective (Buede and Maxwell 1995). It is

certainly true that some decision making is ad hoc or unconscious. If this were the

major mode of operation for a business, it would make MCDM unsuitable. Selecting

the highest valued available alternative for a particular set of evaluation criteria,

however, is the goal of the rational decision maker. While this assumption of

rationality cannot be claimed to hold true for all categories of human decision

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making, decision making theory nevertheless represents a methodology for requiring

the decision maker to make any tacit priorities explicit. As such, it introduces some

level of precision and reliability to the assessment of alternative courses of action.

When the decision being considered requires considerable investment of time or

capital most responsible decision makers would aim to have some rational basis for

their choices. As McCoy et al. (2009) have noted that in the last six decades, decision

making research:

“has demonstrated that model-based decision support, can leverage a

decision maker’s intelligence, remove emotional biases and make

tradeoffs that are too complex or too computationally burdensome for

an individual or an organisation to make.”

Furthermore, Weick (2001) noted that decisions made in organisations have public

consequences and, therefore, need to be justified. While this may be less true for

small and medium businesses than it is for large ones, there is nevertheless, a general

requirement for public accountability in decision making, from those individuals who

employ other people, or expend investors’ funds.

Arrow and Raynaud (1986) caution that every decision making problem necessarily

involves two steps: the identification of potential factors; and the processing of that

information. At either stage, approximations may be made that result in inaccuracy.

Indeed, it may not be possible to avoid some level of inaccuracy or inconsistency in

human judgements. It is, therefore, of crucial importance that the methodology

chosen is suitable for the problem being studied. Hammond et al. (1999, p.6)

proposed eight keys to effective decision making. These are:

• Work on the right problem;

• Specify the objectives;

• Create imaginative alternatives;

• Understand the consequences;

• Grapple with the trade-offs;

• Clarify the uncertainties;

• Think hard about risk tolerance;

• Consider linked decisions.

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This represents a structured and systematic evaluation of subjective and unbounded

problems, which the authors call the ProACT approach. It is not intended to make

difficult decisions easy, but rather to give order to the process of solving difficult

problems. Shane (2009) has presented a guide for decision makers looking to pursue

an innovation project in circumstances of uncertainty. The uncertainty may relate to

any or all of the following areas: technical matters; markets; finance; and

competitiveness. The guidelines can be summarised as:

• Focus on high return opportunities;

• Minimise investment in non-salvageable assets;

• Maintain flexibility;

• Re-allocate uncertainty to those better able to deal with it.

It can be seen that the decision maker is expected to juggle conflicting and competing

priorities while maintaining standards of ethical behaviour. The management

decisions faced by construction companies often entail precisely this sort of complex

mixture of competing priorities and values. The study of decision making theory has

the potential to shed new light on the most effective ways of handling such problems.

The problem faced by an SME construction manager who has to decide whether or

not to introduce to the marketplace new products, processes or equipment is likely to

have three characteristics. Firstly, there are likely to be several goals, decision criteria

or attributes that are involved in the problem. Secondly, there is probably conflict

among the various criteria. Thirdly, there are probably incommensurable units

associated with the different criteria. The field of Multi Criteria Decision Making

(MCDM) methods has developed in an attempt to introduce the rigour of a scientific

approach to the assessment of such problems. This is commonly performed by

assigning decision weightings to the relative importance of each criteria and

expressing the problem in a matrix format. There are many specific methodologies

that come under the category of MCDM. Several of these methodologies are

currently being used to support the evaluation of critical economic and social

alternatives in government and industry (Buede and Maxwell 1995). Some have wide

applicability, while others are suitable only in specific circumstances. Some

methodologies are only suitable when attempting to select the best option in a specific

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case, but others are also suitable when the aim is to tease out general deciding factors

and priorities from the collective opinions of a group of experts. This is the option

taken in Chapter 5 of this thesis.

4.2 Multi Criteria Decision Making (MCDM) methodologies

MCDM methodologies can be classified according to the type of data they use

(Triantaphyllou 2002). The data may be deterministic, stochastic or fuzzy and it can

also be combinations of these categories. Deterministic data involves physically

measured quantities. Stochastic data involves statistically or probabilistically

estimated quantities. Fuzzy data involves consideration of uncertainty and

imprecision arising from phenomena which are neither random nor deterministic

(Chen and Hwang 1991; Yoon and Hwang 1995).

MCDM methods can also be classified according to whether they involve individual

or group decisions. This study will concentrate on decisions made by the owner or

principal of an SME construction company, so group MCDM methods are outside the

scope of the thesis. Multi Attribute Decision Making (MADM) methods are a sub

category of MCDM, where the number of alternatives has been predetermined. These

are cases where the most promising alternative needs to be selected from a standpoint

of limited resources. MADM methods include:

• Dominance;

• Maximin;

• Maximax;

• Conjunctive method;

• Disjunctive method;

• Lexicographic method;

• Lexicographic semi-order;

• Weighted Sum Model (WSM) also called Simple Additive Weighting (SAW);

• Weighted Product Model (WPM);

• Technique for Order Preference by Similarity to Ideal Solution (TOPSIS);

• Elimination By Aspect (EBA);

• Elimination et Choice Translating Reality (ELECTRE);

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• Analytic Hierarchy Process (AHP);

• Linear programming techniques for Multi-dimensional Analysis of Preference

(LINMAP).

This list is by no means comprehensive and there are several variations in the

definition and the detailled application of each listed method. Choosing the best

method for a particular MADM problem involves careful analysis of the nature of the

problem and of the kinds of information that is available (Ho 2000).

Chen and Hwang (1991) present three taxonomies of Multi Attribute Decision

Making (MADM) methods derived from earlier work by Hwang and Yoon (1981).

The first is based on the type of information from the decision maker and the salient

feature of that information. The second classifies methods according to the solution

aimed at; either screening or prioritising. The third is based on the data type

involved: Yes-No data; Ranking data; and Numeric data.

The three approaches are summarised in Table 4.1 (p.97) and Table 4.2 (p.98). The

fourteen methodologies listed above will be discussed in terms of their suitabilit y for

addressing particular kinds of problems in construction management. It is not

proposed to reproduce an extensive mathematical basis for each methodology, but

rather to descriptively present the advantages and disadvantages of each as

acknowledged by the principal authors in the field. Illustrative examples from the

construction industry will be suggested of the possible applicability to the

construction industry of each methodology.

4.2.1 Ranking methodologies

The first three methodologies, Dominance, Maximin and Maximax are used when no

information is provided by the decision maker. In other words, they are appropriate

when no pre-conditions are set by the decision maker. All three are non-

compensatory, meaning that each attribute must stand on its own (Yoon and Hwang

1995).

Dominance is a screening methodology which involves ranking data. An alternative

is considered dominated if there is another option which surpasses it in one or more

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attributes and equals it in the remaining attributes. The chosen solution is the one

remaining when all dominated alternatives are discarded.

EXAMPLE: Simple lowest price tender selection for construction projects

operates in a manner similar to this methodology. The lowest price is the

one chosen, provided that other criteria such as predicted construction

time, sureties provided and insurance cover held are not considered

dominated by other bids.

This is a simple and easily understood process, but the disadvantage is that some

screened out alternatives may in fact be better on balance than some of the non-

dominated alternatives. For example, the lowest price may contain errors or

omissions due to the inexperience of the estimator and consequently later problems

may result if this tender is selected.

Maximin relies on the logic of the aphorism ‘a chain is only as strong as its weakest

link’. All attributes must be measured on a common scale. Only one attribute is

considered for a particular alternative and all other attributes are ignored.

EXAMPLE: The strength of a structural steel space frame is dependent on

the weakest structural steel element in the frame, because if one member

fails under load, the frame fails progressively.

There is an inherently pessimistic outlook to this strategy, as it makes decisions on the

basis of the worst case; however especially when safety is involved, such an attitude

may be quite appropriate.

Maximax involves selecting an alternative by its best attribute. The best attribute is

selected for each alternative and the alternative with the maximum overall best value

is chosen. Like Maximin, this method requires commensurable units, numeric data

and only one attribute is chosen to represent an alternative. However, unlike

Maximin, there is an optimistic outlook to this strategy.

EXAMPLE: The finishes selected for a high prestige building may be

chosen on the basis of superior appearance above all other attributes such

as cost, durability and maintenance requirements.

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4.2.2 Cut-off methodologies

Conjunctive and Disjunctive methods are both screening methodologies which

involve cut-off levels and use numerical data. These are sometimes known as

‘Satisficing’ Methods. ‘Satisficing’ is a portmanteau word derived from the

combination of ‘satisfying’ and ‘sufficing’. Coined by Herbert Simon in the 1950s,

the term refers to decision making strategies based on criteria for adequacy rather than

on the identification of the optimal solution (Simon 1957). In the Conjunctive

Method, an alternative which does not meet the minimal acceptable level for all

attributes is rejected.

EXAMPLE: A sub-contractor may be selected based on having passed the

accepted competency certificate levels in a series of skills. Failure to have

a competency certificate in one area outweighs high performance in the

remaining competencies.

Trade-offs between competencies are not allowed and, hence, this is non-

compensatory methodology.

The Disjunctive Method is the mirror image of the Conjunctive Method. A minimum

acceptable level for each attribute is specified. The option chosen is the one which

exceeds the desired performance level by the greatest amount. In other words, the

choice is made on the basis of the best attribute for each option.

EXAMPLE: The members of a project design team may be selected on the

basis of outstanding talent in any one of the following areas: design,

communication skills, technical skills, services integration and

documentation. Team members are not expected to excel in all areas.

The disadvantage of this system is that an option that is good in all categories, but not

outstanding in any, will not be chosen. In other words, the steady, competent all-

rounder is likely to miss out. Once again, this method is non-compensatory.

4.2.3 Prioritizing of alternatives methodologies

The Lexicographic Method and the Lexicographic Semi-order Method are used when

it is necessary to evaluate and prioritise the best option from a series of alternatives.

They are both methodologies that can involve Yes-No data, ranking data or numerical

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data. The Lexicographic Method applies in situations where a single attribute seems

to predominate.

EXAMPLE: When selecting building materials for a low-budget, fully

utilitarian project choose the cheapest option from among the alternatives;

only look at other attributes if price is equal.

Attributes must be ranked in terms of importance and they are considered non-

compensatory.

The Lexicographic Semi-order Method is a slightly more discriminating method. It is

used when one attribute seems to predominate, but bands of imperfect discrimination

are allowed so that one alternative is not chosen simply because of a slightly higher

value on the principal attribute. The attributes must be ranked in terms of importance

and a tolerance value must also be specified for each attribute. This indicates the

difference from the best value which is not considered significant.

EXAMPLE: When selecting building materials choose the cheapest, but

only if cheaper by a specified amount. If the specified amount is not

exceeded, look at the next important attribute, say durability, and compare

the best price within the tolerance options with the standard for durability.

If both are still within the tolerance range move to the next attribute, say

colour range. Continue comparing attributes until a difference outside the

tolerance range is found, and a preferred option can be chosen.

As in the previous methodology, attributes remain non-compensatory.

4.2.4 Scoring methodologies

The next sub-group of decision making methodologies are those that involve some

form of scoring of attributes. In such problems, an alternative in a decision making

problem is viewed as a vector which has multiple elements. Scoring methodologies

aim to transform the vector into an appropriate scalar value so that the alternative with

the highest value or utility can be selected (Yoon and Hwang 1995, p.31). Two

varieties of methodology are based on the decision maker assigning weights to the

attributes. These are Weighted Sum Model (WSM), also called Simple Additive

Weighting (SAW) by some authors (Chen and Hwang 1991), and Weighted Product

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Model (WPM). In the WSM methodology, the overall score of an alternative is

computed via the weighted sum of the attribute values. Each attribute is scored by

multiplying its rating by its importance weighting. The attributes must be capable of

being expressed numerically and they must be comparable. Unlike the previously

mentioned methodologies, trade-off among attributes is compensatory.

EXAMPLE: An item of construction plant or equipment may be chosen by

identifying the important attributes, say capital cost, maintenance cost,

anticipated lifespan and safety rating. These attributes are given a

numerical weighting to reflect their importance to the decision maker. The

possible alternatives are rated for each attribute. The score for each

alternative is the sum of the products of each attribute’s rating multiplied

by its importance weighting.

Weighted Product Method penalises alternatives with some poor attribute values more

heavily than WSM by using the product rather than the sum of the weighted values

across the attributes.

EXAMPLE: If the decision maker for the previous example (the purchase of

plant and equipment) decided that maintenance costs were particularly

important then this priority could be emphasised by scoring the

alternatives for each attribute and multiplying rather than adding each

score to form the end value for each option.

This has the effect of increasing the importance of outlying values for individual

attributes. A low score on an individual attribute has more effect on the outcome

value than it does with WSM.

4.2.5 Elimination methodologies

In Elimination by Aspects (EBA), alternatives are compared one attribute at a time

and are considered eliminated if they fail a Yes–No question or a minimum

acceptable level. Minimum cut-offs are specified for each attribute. Attributes are

ranked in terms of discrimination power and are processed in order until only one

attribute is left.

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EXAMPLE: A construction manager may set up a series of yes-no criteria

for the engagement of a sub-contractor to perform work on an hourly rate

basis: Can you deliver your services at our specified maximum hourly

rate? Can you start at two weeks’ notice? Do you have the required

competency certificates? The available contractors could be screened on

the basis of their answers to the yes-no questions.

The disadvantage of this is that an alternative with one unacceptable attribute will be

screened out, even if it has very high scores in the other attributes.

A development of simple elimination by aspects is Elimination et Choice Translating

Reality or ELECTRE (the acronym is a hybrid translation from the original French

version). This methodology also uses the concept of the outranking relationship.

Pair-wise comparisons of alternatives are made under each criterion separately.

Alternatives are considered dominated if there is another alternative which excels

them in one or more criteria and equals them in the remaining criteria. Choices are

made at the decision maker’s discretion. Even though two alternatives do not

dominate each other mathematically, the decision maker accepts the risk of regarding

one as almost certainly better than the other. The trade-off among attributes is

compensatory and the information contained in the decision making matrix is fully

utilised.

EXAMPLE: A construction manager may be faced with many available

options with regard to selection of a supplier for a common building

material, say pre-mixed concrete. Perhaps he decides that there are only

three important criteria for selection: cost per m³ delivered to site;

capacity of concrete that can be delivered in a given time; and lead time

between order and delivery. By making successive comparisons of the

alternatives and discarding the dominated alternatives, it is possible to

arrive at the likely best option.

This method is particularly useful when there are relatively few criteria and many

alternatives. The consecutive assessment of out-ranking relationships does not

necessarily yield the most preferred alternative. It may only provide a number of

equally rated leading alternatives.

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4.2.6 Ideal solution methodologies

Some decision making processes rely on the presumed existence of an ideal solution

to the problem at hand. An ideal solution is defined as a collection of ideal ratings in

all attributes considered (Yoon and Hwang 1995, p.38). Developed by Hwang and

Yoon (1981) as an alternative to ELECTRE, the Technique for Order Preference by

Similarity to Ideal Solution or TOPSIS uses the rationale that the best alternative is

the one which has the shortest distance to the ideal solution and the farthest distance

from the negative ideal solution. Attributes must be both numerical and comparable.

Trade-off among attributes is compensatory. The method assumes that each criterion

has a one dimensional effect on the utility of the choice.

EXAMPLE: It is possible to describe an ideal or perfect materials

handling system for a construction site. The required performance can be

specified in terms of attributes which all relate directly to cost: initial

capital outlay; running costs; predicted downtime for maintenance and

repair; expected serviceable lifespan etc. The available market options can

then be compared to the ideal solution and its direct opposite, the negative-

ideal solution attribute by attribute. The option with the least distance

from the ideal solution is selected.

In reality, the ideal solution is generally unattainable, but it is often possible to

construct the ideal solution hypothetically and select the available option that is

closest to it.

4.2.7 Weighted comparison methodologies

Developed by Dr. Thomas Saaty over the decades since the 1970s, the Analytic

Hierarchy Process or AHP is a combination of the eigenvector method based on

matrices and the Weighted Sum Method (Golden et al. 1989; Saaty 1977; Saaty 1980;

Saaty 1994a; Saaty 1994b; Saaty 1996; Saaty 2006; Saaty and Vargas 1991; Saaty

and Vargas 1994; Saaty and Vargas 2001).

Some authors have elected to classify AHP as simply a variant of WSM or SAW

(Chen and Hwang 1991), but others see it as sufficiently different in scope to merit

classification as a separate system (Yoon and Hwang 1995). AHP operates by

decomposing a problem into a series of hierarchies and constructs a matrix m x n

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where m is the number of alternatives and n is the number of criteria (Saaty 2006). A

feature of the method is that it is applicable to situations where the criteria are in non-

commensurate quantities. The problem is set up in the form of a Value Tree which

contains criteria and sub-criteria. The decision maker is asked to make pair-wise

comparisons across the range of the selection criteria and across the sub-criteria

sections also. This breaks the problem down into a series of small decisions, which

are then evaluated in matrix format.

EXAMPLE: The selection of heavy plant or equipment for a construction

project involves soft factors such as the manager’s convenience,

operational efficiency, likely progress delays and work safety issues

alongside hard capital and running costs. With AHP, these factors are

given weightings via pair-wise comparisons of each factor on the same

level. This enables the alternative options to be ranked in terms of their

desirability and any internal discrepancies in the weighting are made

apparent and can be debated and decided.

AHP as a research methodology has found an enthusiastic reception in many

discipline areas with refereed journal papers (and special journal issues) published

using the methodology in extensive fields of endeavour. This will be discussed more

fully in Section 4.3 of this chapter.

4.2.8 Alternative preference methodology

LINMAP stands for Linear programming techniques for Multidimensional Analysis of

Preference. The decision maker is required to indicate a preference between

alternatives. This is a much more complex task than choosing between attributes.

This is because multiple factors have to be evaluated at the one time. LINMAP

requires both the assessing of weights for attributes, as well as locating the ideal

solution. The ideal point is assumes to exist in n-dimensional space. Once this ideal

point is located, the alternative with the least distance to the ideal solution is chosen.

EXAMPLE: The credit worthiness of potential joint venture construction

partners could be assessed using LINMAP methodology. This would

involve fuzzy assessment of a number of attributes including reputation,

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project record, known commitments, trustworthiness and insurance cover.

Several judgement calls have to be made in assessing the alternatives.

LINMAP methodology was designed to capture information on reasons for consumer

choice rather than for making a decision. As such, this methodology exceeds the

needs of this study. Similarly, an examination of the growing field of fuzzy data

analysis is beyond the scope of this thesis, because of the imperative to keep the

methodology simple enough to allow inclusion of those decision makers who may be

technically highly competent in their field, but who do not have a great deal of formal

education and who may be intimidated by terminology that appears complex and

esoteric.

Tables 4.1 and 4.2 (p.97 and p.98) summarise the comparison of the decision making

methodologies listed above. For the purposes of this thesis, AHP has been

determined to be the most suitable methodology, because it has the appropriate level

of complexity, it is user-friendly and it is able to deal with problems that have several

competing criteria. A fuller explanation of the selection of AHP methodology is

given in Section 4.3 of this chapter.

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Table 4.1 Comparison of methodologies (Ranking methodologies, cut-off methodologies, prioritising of alternatives methodologies)

Methodology Data type

Information received from the decision maker

Salient feature of information

Compensatory or Non-compensatory attributes

Dominance Yes-No

Rank

Numeric

None Not applicable

Non-compensatory

Maximin Numeric None Not applicable

Non-compensatory

Maximax Numeric None Not applicable

Non-compensatory

Conjunctive method Numeric Information on attributes

Standard level

Non-compensatory

Disjunctive method Numeric Information on attributes

Standard level

Non-compensatory

Lexicographic method

Yes–No

Rank

Numeric

Information on attributes

Ordinal Non-compensatory

Lexicographic semi-order

Yes–No

Rank

Numeric

Information on attributes


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Table 4.2 Comparison of methodologies (Scoring methodologies, elimination methodologies, ideal solution methodologies, qualitative data methodologies, alternative

preference methodologies)

Methodology Data type

Information received from the decision maker

Salient feature of information

Compensatory or Non-compensatory attributes

Weighted sum model WSM

Numeric Information on attributes

Cardinal Compensatory

Weighted product model WPM



Elimination by aspects EBA

Yes-No Information on attributes


ELECTRE Numeric Information on attributes


TOPSIS Numeric Information on attributes


Analytic Hierarchy Process AHP



LINMAP Fuzzy Information on alternatives

Pair wise Preference

Compensatory

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Ranking methodologies (Dominance, Maximin and Maximax) are unsuitable for this

exploratory study because they fail to include consideration of all available

information on alternatives. Cut-off methodologies (Conjunctive and Disjunctive

Methods) and Prioritising of Alternatives methodologies (Lexicographic method and

Lexicographic semi-order) are unsuitable for this study because they are non-

compensatory and do not allow trade-off between aspects. Such trade-offs are

desirable in problems that have conflicting criteria. Scoring methodologies (WSM

and WPM) do have the effect of introducing a level of compensation between the

attributes, but they have difficulty in comparing attributes which are measured in

entirely different units. This can be become a case of “adding apples and oranges”

(Triantaphyllou 2002 p.7). Elimination methodologies (Elimination by Aspects and

ELECTRE) are also compensatory, but the effect of one unacceptable attribute may

be to rule out an otherwise well scored alternative. Ideal solution methodology

(TOPSIS) assumes that an ideal solution exists and can be mathematically described.

Furthermore, each alternative has a calculable linear relationship to the preferred

solution. TOPSIS applies to problems where all attributes are numerical and

comparable (Chen and Hwang 1991 p.39), so it is not suitable for this study.

LINMAP requires the decision maker to make comparisons between the available

alternatives rather than between the attributes of those alternatives. As such, it

involves a higher level of discrimination than is needed for this study. This leaves the

Weighted Comparison methodology, AHP, as the option which makes use of all

available information on attributes, incorporates trade-offs and enables comparing of

non-commensurate and non-numerical attributes.

4.3 Selection of AHP methodology

The effectiveness of AHP methodology has led to its current widespread use in

disciplines as disparate as ecology (Ananda and Herath 2008), economics

(Büyüközkan et al. 2008; Shahin and Mahbod 2007), education (Melón et al. 2008),

engineering (Hwang 2004; Wang et al. 2008) manufacturing (Shi et al. 2008; Wang et

al. 2004) and medicine (Ahire and Rana 1995; Liberatore and Nydick 2008). In the

field of property, which is closely related to this research, its use is also widespread

(Ball and Srinivasan 1994; Bender et al. 2000; Chan 2002; Ho et al. 2005; Ho et al.

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2006; Hutchison et al. 2005; Kauko 2003; Ong and Chew 1996; Newell and Seabrook

2006; Schniederjans et al. 1995; Yang and Lee 1997). AHP has been employed to

study various complex decision making areas including: factors which influence

investment decision making; investment strategy; and assessing commercial office

building quality.

Recent years have seen the development of the use of the methodology to address a

wide variety of problems in construction management (Abudayyeh et al. 2007; Al-

Harbi 2001; Al Khalil 2002; Bayazit et al. 2006; Cheng and Li 2004; Cheung et al.

2002; Chung and Skibniewski 2007; Dias and Ioannou 1996; Doloi 2008; El-Sawalhi

et al. 2007; El-Sayegh 2009; Gunhan and Arditi 2005; Lin et al. 2008; Shapira and

Goldenberg 2005; Skibniewski and Chau 1992; Wu et al. 2007). In the construction

management field, AHP has been used to study the areas as diverse as: contractor

selection; site location selection; improving construction productivity; equipment

selection for construction projects; Total Quality Management (TQM); and evaluating

accessibility in buildings.

While the ubiquity of the AHP method is not proof of its efficacy, it is a strong

indication that many scholars have found the methodology useful for the study of

diverse and complex problems. These problems tend to have competing and

conflicting parameters and often the different attributes being evaluated are measured

in units that are incommensurate. AHP represents a systematic method for breaking

down the decision making process into a series of simple pair-wise comparisons. It is

based on a well defined mathematical structure of consistent matrices to generate

approximate weights (Forman and Gass 2001). As such, the problem is given

structure and the degree of discrimination required is reduced, as the decision maker

is only required to consider the relative importance of two attributes at any given

time. The result of the process is a mathematically validated guide to the preferred

option. The methodology is not, however, confined to use in determining a specific

course of action. When the same decision making problem framework in AHP is then

repeated by a number of experts with experience in the issue concerned, the resulting

data can be aggregated and analysed for patterns of agreement and disagreement,

which represent the current collective knowledge on the issue of the sample of experts

chosen. This is the methodology of the study reported in Chapter 5 of this thesis and

analysed in Chapter 6.

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CHAPTER 5 SURVEY OF TECHNICAL INNOVATORS IN CONSTRUCTION SMEs

Chapter 5 reports on the construction of a value tree from the literature review. AHP

methodology is then used in a survey of chief decision makers in SME construction

companies in the Greater Sydney metropolitan area and nearby New South Wales.

The defining qualification for survey participants is some form of peer recognition for

the successful delivery of technical innovations. The statistical characteristics of the

survey group and sub-groups are described.

5.1 AHP Value Tree

It is possible to construct a Value Tree hierarchy for a decision making problem by

several means. Some authors have used individual experts or small numbers of

experts in group discussion to construct the Value Tree for a decision making problem

(Al -Harbi 2001; Al Khalil 2002; Ball and Srinivasan 1994; Cheng and Li 2001; El-

Sayegh 2009; Hwang 2004; Ong and Chew 1996; Schniederjans et al. 1995; Shahin

and Mahbod 2007; Skibniewski and Chao 1992; Yang and Lee 1997). Others have

relied upon the literature of previously published studies to construct a hierarchy for a

research problem (Büyüközkan et al. 2008; El-Sawalhi et al. 2007; Kauko 2003;

Wang et al. 2008). As mentioned at the start of this chapter, the latter approach has

been taken here.

The identified factors discussed in thesis sections 2.8 to 2.12 have been summarised

in a Value Tree presented as Figure 5.1 (overleaf). A Value Tree is a hierarchical

structure that demonstrates simple functional dependence of one element of a system

on another. Such structures are useful as a means of decomposing a complex problem

into its component parts, in order to aid understanding (Saaty 1994a). The Value Tree

presented here is drawn from the targeted literature review and forms the basis of the

empirical study described in this chapter.

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Figure 5.1 Value Tree of factors affecting technical innovation in construction

A Value Tree is an integral part of Decision Analysis. It represents an attempt to

classify and codify relationships between multiple factors in a logical and consistent

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manner. There can always be argument about the content and definition of the Value

Tree elements; however, as a tool for analysing a problem, it has the advantage of

giving form to a problem that may otherwise be considered too large or too complex

to tackle.

5.2 Selection of survey respondents

Purposive sampling techniques (Teddlie and Yu 2007) were used to select suitable

candidates to respond to the research survey for this thesis. The intention was to

identify a select group of successful SME innovators and determine if they had any

commonalities between them. The principal criterion for eligibility to respond to the

survey on factors influencing technical innovation in construction was a verifiable

track record in successfully delivering a significant technical innovation. A

significant technical innovation is defined in these circumstances as one that has

received recognition by peers in the Australian construction industry. The potential

survey respondents were identified from several sources, which included public

databases, industry awards and other peer recognition processes. Two public

databases were used. These were Australian Technology Showcase (ATS) and the

Building Research Innovation, Technology and Environment (BRITE) National

Innovative Contractor Database. The ATS website is maintained by three Australian

state governments (Queensland, New South Wales and Victoria), and is a national

networking program aimed at promoting and developing export markets for

innovative technology based products. In NSW, it is managed through the

Department of State and Regional Development. The website covers products

produced by SMEs from many industries, including more than 80 in construction. To

be eligible, companies must provide two independent referee reports, a current

business plan with a commercialisation strategy and they must demonstrate that their

technology is:

• Clearly innovative;

• Scientifically credible;

• Significantly local in content;

• Commercially attractive;

• Demonstrably marketable and exportable;

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• Socially and environmentally beneficial (ATS 2008).

The BRITE National Innovative Contractor Database was established as a result of a

research project at the Australian Cooperative Research Centre for Construction

Innovation (CRCCI) in response to calls from the construction industry for a ‘Yellow

Pages’ directory of innovative contractors. The purpose of the database is to help

facilitate networking between industry participants and innovative contractors across

Australia (Manley 2006). The database contains more than 80 listings of contractors

and specialist contractors. This database is not restricted to SMEs and in fact contains

many large companies, but there are some SMEs among the identified high

innovators. To qualify, businesses completed a survey dealing with the novelty and

impact of their innovations. Answers were scored and the top 25% of respondents

were included in the database.

A third source of potential interviews was the annual awards lists of professional

organisations and industry umbrella bodies covering the period of 2005 to 2009.

Awards which mentioned innovation, either specifically, or by implication, were

selected. Organisations canvassed were Australian Institute of Building (AIB),

Masters Builders Association of NSW (MBA), Housing Industry Association (HIA),

Engineers Australia, Civil Contractors Federation (CCF) and Panasonic Australian

Business Awards. All awards considered were based on competitive nominations.

They are all awarded after scrutiny and assessment by expert panels to ensure the

integrity of the award process.

Finally, featured inventions from the last five years on the Australian Broadcasting

Commission’s television program “The New Inventors” were also included, if they

involved construction industry contractors. This program undertakes an extensive

screening process for potential featured inventions by experts in the specific field of

endeavour for each invention. The screening experts come from both industry and

academia. Selection of inventions featured on the program is highly competitive.

5.3 Characteristics of survey respondents

After sorting through these four sources of potential survey respondents, a

spreadsheet was assembled of 38 possible eligible interviewees located in an area that

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was within a day’s travel by car of the researcher’s university home campus

(approximately 150 km radius). While this geographic limitation could be seen as

somewhat arbitrary, it should be noted that this region encompasses more than a fifth

of the Australian construction industry by number of enterprises and, as such, may be

regarded as a significant section of the national industry. It is not, of course, a

random sample of the entire Australian construction sector, but this simply limits the

generalisability of the results. It does not invalidate the usefulness of the sample as a

view of opinions in a particular geographic zone.

Checks were then made to ensure that the potential interviewees fitted the category of

SME. Six short-listed companies were removed at this point, as they proved to be

sub-sections or subsidiaries of large construction companies. Another four were

removed, because they were largely manufacturers or suppliers to the construction

industry, rather than contractors operating in the industry. This left 28 possible

interviewees. Of these, 21 completed the survey for a satisfactory response rate of

75%. In every case, the person approached for an interview was the owner, director,

manager or department head with the responsibility for company decision making

which would affect innovation delivery. The sources of the eligible survey

participants are shown in Table 5.1 overleaf. It is worth noting that the highest

response rate from the survey respondent sources was 100% from both the BRITE

Innovative Contractor Database and the New Inventors. These contractors are clearly

engaged in promoting their technical innovations widely. The lowest response rate

was from those potential survey respondents identified from industry awards, but this

rate was still more than half of those approached.

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Table 5.1 Source of survey respondents

Source BRITE

Innovative

contractor

database

Australian

Technology

Showcase

Industry

awards

New

Inventors

Total

Qualified potential

survey respondents 4 10 9 5 28

Completed survey

interviews 4 7 5 5 21

Percentage 100% 70% 56% 100% 75%

The breakdown of the 21 respondents’ company sizes and the nature of their

innovation type are shown in Table 5.2 overleaf. For small businesses, the total

employee number was between 5 and 19 including part-time employees. Medium

businesses had between 20 and 200 employees including part-time employees. This

information was given by the participants and whenever possible confirmed from

other sources such as industry website listings.

Product innovations were concerned primarily with goods or components that are

installed or incorporated in buildings. Process innovations were primarily concerned

with the actions needed for installation or incorporation of goods in a building, or in

other words building techniques. Tidd et al. (2005) describe the difference between

the two as a product consists of “what we offer the world”, while a process consists of

“how we create and deliver that offering” (Tidd et al. 2005 p.23). This is a definition

that is easier to recognise on a case by case basis than it is to describe in the abstract.

In simple terms, building products are things, and building processes are ways of

incorporating these things in buildings. There is some degree of overlap between the

two categories, as new products usually require some new means of installation to

some extent, but all the innovations studied in practice appeared to fall reasonably

clearly into one category or the other. As a point of clarification, the term process

innovator here is taken only to mean those who have delivered a new building process

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or building technique. It does not, for the purposes of this thesis, refer to the broader

area of business process innovation. This is a form of organisational innovation and

is outside the scope of this thesis.

5.4 Patents on technical innovations

A patent can be defined as a government-granted monopoly that precludes others

using an invention for a stated period of years (Shane 2009). Patents are only granted

for inventions that the national Patent Office determines are novel, non-obvious and

useful. The survey respondents stated whether or not they held patents on their

innovation and this was confirmed by checking the Scopus database (Elsevier 2010).

Both Australian and international patents were considered, and most respondents held

multiple patents on their invention. To maintain the confidentiality of the survey

response, patents are not referenced in this thesis, except where the innovation is

discussed in Chapter 7 as a case study. Separate AHP analyses will be carried out to

assess for significant differences between the two groups for each of business size,

innovation type and patent holdings.

Table 5.2 Classification of survey respondents

Business size Innovation type Patents

Small 10 (48%) Product 13 (62%) Patent

holders

14 (67%)

Medium 11 (52%) Process 8 (38%) Non-

patented

7 (33%)

A brief, randomised and non-identifying description of the technical innovations

delivered is shown in Table 5.3 overleaf.

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Table 5.3 Descriptions of innovations studied

Product innovations Process innovations

• Solar powered, rainwater collecting hot water system

• High performance membrane noise barrier for thin wall structures

• Lightweight slate roofing system for domestic roofs

• Weather sealing for temporary repair to storm damage

• Safety guard for floor penetrations during construction

• Under floor rainwater storage bladders

• Eco-friendly replacement for Portland cement

• Temporary formwork for concrete columns

• Interlocking lightweight and waterproof concrete block

• Early warning monitoring system designed to prevent mobile plant roll over

• Road pavement repair and profiling machinery

• Roof tile fixing system

• Evacuated tube solar hot water systems

• Long-span post tensioned steel roof system for column free internal space

• Salt removing poultice to restore masonry building components deteriorating due to rising damp

• Heavy lift tower crane system suitable for restricted sites

• Increased use of recycled concrete as road base and aggregate in civil projects

• Long-span, lightweight, customised roof systems, allowing for double curvature

• Energy efficient heat exchanger air conditioning installations

• Sheet piling for emergency repairs

• Electricity co-generation installations

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5.5 Detailed methodology for survey

In accordance with the procedures of Analytic Hierarchy Process (AHP), survey

respondents were asked to make pair-wise comparisons of the elements in the Value

Tree, which was generated from the literature review in Chapter 2 of this thesis (see

Figure 5.1, p.102). Comparisons were made on a seventeen point scale between 9 at

either end of the scale for extremely preferred element distributed around a neutral

point of 1 where both elements are equally preferred. This is the standard scale

derived by Saaty (1980) and is used in Expert Choice™ software as illustrated in

Figure 5.1. Such pair-wise comparisons were made between each element grouping

in the Value Tree as illustrated in Figure 5.2 below. The system allows for

comprehensive assessment of the different factors and sub-factors identified in the

Value Tree. Each first level factor is compared to all other factors and each sub-

factor (or second level factor) is compared to all others in its own group.

Figure 5.2 Sample survey question

For the Value Tree presented in Figure 5.1, this amounts to 28 pair-wise comparisons

in the format of Figure 5.1 in order to cover all possible combinations among the first

level factors (ten pair-wise comparisons) and among each sub-grouping in the second

level factors (18 pair-wise comparisons). This is illustrated in Figure 5.3 overleaf.

The robustness of the methodology stems from the comprehensiveness of the

judgements made and the level of inbuilt redundancy. The maximum number of sub-

factors in a sub-grouping was five. Consequently, at no stage were respondents asked

to make relative judgements over more than five individual elements, that is, ten pair-

wise comparisons. As such, the quantity of judgements made, is considered well

within the capacity of a competent decision maker.

Thinking of your most successful technical innovation which was more important in assisting the delivery process: Company resources or Client and end-user influences?

Company resources Client and end-user influences 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9

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Figure 5.3 Pair-wise comparisons from the Value Tree

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One of the basic premises of decision making theory was reported by Miller in the

1950s. Miller refers to the “magic number of seven plus or minus two” (Miller 1956).

This represents the contention that most human beings only have the capacity to

discriminate between a limited number of variables at any one time, that being 7±2.

As previously explained, in this study, five is the maximum number of variables that

are contained in any comparative grouping. This is well within an individual decision

maker’s capacity to judge.

Under the standard procedure established by Saaty (1996), an intensity scale of

importance for the numbered comparisons is explained in verbal terms to reduce

variability in answers to the pair-wise comparisons. This is shown in Table 5.4. As

human beings are much more capable of making relative judgements rather than

absolute ones, pair-wise comparisons of the full range of possibilities in each

grouping enables a level of built-in redundancy which assists reliability (Forman and

Selly 2001).

Table 5.4 The fundamental scale verbal descriptions of pair-wise comparisons in AHP

Intensity of Importance Definition Explanation

1 Equal importance Two elements contribute equally to the objective

3 Slightly more importance of one over the other

Experience and judgement slightly favour one element over another

5 Moderate importance of one over the other

Experience and judgement strongly favour one element over another

7 Strong importance of one over the other

An element is strongly favoured and its dominance is demonstrated in practice

9 Absolute importance of one over the other

The evidence favouring one element over another is of the highest possible order of affirmation

2,4,6,8 Intermediate values between the two adjacent judgements

When compromise is needed

Source: Saaty (1996)

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The validity of the AHP method stems from its three primary functions: structuring

complexity; measurement; and synthesis (Forman and Gass 2001). This is the basis

of the method’s broad applicability to the study of many different kinds of decision

making problems. Zahedi (1986) sets out the standard procedure for the use of AHP

in decision making in four steps. These are:

Step 1 Setting up the decision hierarchy by breaking down the

decision problem into a hierarchy of interrelated decision

elements;

Step 2 Collecting input data by pair-wise comparisons of decision

elements;

Step 3 Using the ‘eigenvalue’ method to estimate weights of decision

elements;

Step 4 Aggregating the relative weights of decision elements to arrive

at a set of ratings for potential outcomes.

Each step involves specific procedural protocols to ensure the validity of the collected

data. These are discussed below.

5.5.1 Step 1: The decision hierarchy

A typical hierarchical structure for a decision making problem is presented in Figure

5.4 overleaf. For the purposes of this thesis, the literature review reported in Chapter

3 was used to accomplish Step 1, setting up the hierarchical Value Tree of potential

factors and sub-factors relating to the goal of successful technical innovation delivery

(Figure 5.1). The five factors were selected under the following criteria:

• Each factor needed to be distinctly different from every other factor;

• It needed to be possible to make relative judgements about the importance of

each factor. In other words, fully intangible elements could not be included;

• As far as possible, the factors should cover the items of major significance in

the innovation delivery process, but repetition should be avoided.

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Figure 5.4 General form of a hierarchical structure

Source: Adapted from Saaty (1994a)

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5.5.2 Step 2: Data collection

Data was then collected from the 21 eligible survey respondents to complete Step 2.

This took place over a period of nine months in 2009. All survey respondents

qualified under the criteria set out earlier in this chapter, and no respondents were

added to the eligibility list in an ad hoc manner, or due to ‘word of mouth’

recommendation. Survey respondents were provided with a Participant Information

Sheet and a Participant Consent Form as required by the University of Western

Sydney Ethics Committee under national guidelines for ethical research involving

human beings (see Appendices 2 and 3). All respondents read and signed the consent

form. The data was stored on a laptop computer, backed up on the university network

and in hard copy. According to the university policy, the data was de-identified and

will be retained for a period of five years for verification purposes.

5.5.3 Step 3: Estimates of weightings

Step 3 involves the computation of weighting estimates for each of the factors and

sub-factors in the Value Tree using the standard AHP eigenvalue technique. In the

eigenvalue technique, the reciprocal matrices of pair-wise comparisons are

constructed. Using these pair-wise comparisons, the weighting parameters can be

estimated (Saaty 1980; Forman and Gass 2001). The method recognises that a

common way for human beings to deal with complexity is via the hierarchical

structuring of complexity into groups of relatively homogeneous factors (Forman and

Gass 2001). The method is robust because all possible pairings in a sub-group or

family are investigated. In addition, the methodology contains an in-built check for

internal consistency. This enables a researcher to determine whether or not it may be

necessary to discard some respondents’ answers. This matter will be discussed more

fully in Chapter 7, when the limitations of the study are considered.

In classical AHP methodology, the right eigenvector of the largest eigenvalue of

matrix A (see Equation (1) overleaf) constitutes the estimation of relative importance

of attributes or factors.

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where bi is the importance or desirability of decision element i.

In the AHP approach, the eigenvector is scaled to add up to 1 to obtain the weights.

AHP methodology allows for simple checking of the internal consistency of the

judgements made. It should be noted that the matrix A represented in Equation 1, is a

reciprocal matrix with the diagonal equating to unity, and the right top triangle of the

matrix being equal to the left bottom triangle. Based on the properties of reciprocal

matrices, a consistency ratio (CR) can be calculated. Saaty (1977) has shown that the

largest eigenvalue, , of a reciprocal matrix A is always greater than or equal to n

(number of rows or columns). If the pair-wise comparisons do not include any

inconsistencies, then equals n. The more consistent the comparisons are, the

closer the value of computed to n. A consistency index (CI), which measures

the inconsistencies of pair-wise comparisons is given in Equation (2).

CI = ( - n) / (n -1) (2)

A CR, given in Equation (3), measures the coherence of the pair-wise comparisons.

CR =100(CI / ACI) (3)

where ACI is the average CI of the randomly generated comparisons.

The comprehensive consideration of alternatives, along with checking for

inconsistency, is the basis of the methodology’s robustness.

(1)

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5.5.4 Step 4: Aggregation of results

It is possible to aggregate results via several methods. These include: aggregation

using the arithmetic means of the separate survey responses; aggregation by use of the

median scores for the dataset; and aggregation by use of the geometric mean (Fellows

and Liu 2008). Use of the arithmetic mean for the sample is recommended, whether

the data set is large or small. It is generally the most representative of a series or

distribution. It is necessary, however, to check for outlying responses which may

skew the result. The median response is only suitable when there are few outliers

which affect the overall response. It is not suitable for small numbers of responses.

The geometric mean is suitable for small samples and to assess the relative changes

between responses (Fellows and Liu 2008).

In this case, the arithmetic mean of all the factors and sub-factors is calculated for the

full sample of survey respondents, as well as for sub-groupings within the sample.

Consideration will also be given to the effect of outlying answers in the survey

response. These results are presented in Chapter 6 of this thesis.

5.6 Survey data analysis software

The results obtained from the survey respondents were entered into Expert Choice™

software to enable rapid analysis of the priorities. Expert Choice is the accepted

standard software package for AHP analysis (Zapotera et al. 1997; Ishizaka and Labib

2009). A weighting for each factor was then computed using the ‘eigenvalue’ method

in AHP taking into account each of the pair-wise comparisons as described above.

The data sets were completed for each of the 21 respondents in this way. The

software returns a rating for each factor and sub-factor in decimal form. For

convenience of understanding, the rating factors were converted to percentages and

are presented as such in the results section of this thesis.

5.7 Inconsistency in survey response

The purpose of the study is an exploratory one, and the research aim is to gather

information on the collective experience of the expert respondents. In these

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circumstances, some level of inconsistency is expected and may even be elucidatory

of the complex process undertaken. Consequently, the decision was taken before the

survey commenced, that respondents would not be given the opportunity to address

any inconsistencies in their answers to the AHP survey. Expert Choice™ software

does allow this facility, as ratings are calculated on the spot, and the consistency

ratios can be immediately obtained. If the intention was to select a concrete

alternative, or to establish a decision making model, then it would be appropriate to

allow those respondents with high inconsistency in their answers to opt to amend their

responses. Since neither of these situations applied, it was decided to simply gather

the raw response even if the CR was high.

Inconsistent survey responses may result from several sources. Clerical error is the

simplest and may be, in fact, be the most common source of inconsistency. In the

case of pair-wise comparisons, the reverse of what is intended may be mistakenly

entered, particularly on the 17 point scale. People are also quite likely to respond to

the same questions differently at different times. Concentration level may drop and

the respondent may become distracted. Wikman (2005) has found that greater

inconsistency is likely to occur when people are asked to make judgements as

opposed to providing descriptions. In addition, terminology used in a survey may

have ‘fuzzy boundaries’ either semantically or in terms of specific context. When the

areas being considered are not strictly quantifiable and require judgement, it is highly

unlikely that inconsistency can be completely eliminated. Furthermore, in terms of

this study as it was carried out face-to-face, revealing the inconsistencies to the survey

respondent may have made it more likely that the researcher could influence the

results. Avoiding this possibility was a prime reason why only the raw response was

collected and not a modified response after consideration of the CR (these matters are

further discussed in Section 6.14). As Wikman (2006 p.104) points out, inconsistency

does not result solely from deficiencies in the measuring instrument, but may stem

from the innate uncertainty of human perception. Furthermore, Ganzac (1994) found

that in multi attribute judgements, inconsistency does not increase the level of

‘extremity’ of the judgements or the extent to which they deviate from the mean. In

other words, internally inconsistent results may still give good approximations of true

values (Ganzac 1994 p.193). In particular, the priorities derived from an AHP study

using the eigenvector method are likely to be robust, even when the numerical values

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are less so (Forman and Gass 2001). This is because the method contains enough

redundancy, to make the priorities reliable. As Forman and Gass have put it:

“If consistency does not hold, and in general it does not, error analysis

shows that the eigenvector still produces a set of priorities that are a

very acceptable approximation of the true (unknown in most cases)

values, under the reasonable assumption that the DM is not making

random comparisons” (Forman and Gass 2001).

Putting aside these reservations about consistency, the raw data as provided by the

survey respondents will be analysed for statistical significance using multiple tests as

established by standard statistical techniques.

5.8 ANOVA for sample sub-groups

Analysis of variance (ANOVA) is a statistical method which represents the ratio of

variance between groups to the variance within groups. The larger the between-

groups variance relative to the within groups-variance; that is, the larger the

calculated value of F value, the more likely it is that the mean differences represent

true effects, rather than random ones. In other words, the more likely it is that the

groups studied are distinct populations and not simply variability within an

amorphous group (Fellows and Liu 2008). When performing ANOVA calculations

using tables of the F-distributions and the appropriate degrees of freedom (df), if the

calculated value of F is greater than the critical F value (Fcalc.> Fcrit..), then the null

hypothesis, that there is no significant difference between the groups can be rejected.

In other words, the groups are significantly different. F-tests were carried out for the

three separate sub-group pairs in the survey sample: small and medium enterprises;

product and process innovators; and patent holders and non-patent holders. These

results are presented in Chapter 6 of this thesis.

5.9 Regression and correlation

Regression and correlation are usually considered together when expressing a

relationship between two variables. They can establish that a statistical relationship

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exists, but they do not establish causality. Scatter plots were prepared for each survey

factor against the other factors and the linear regression trend line calculated. The

regression line or the ‘line of best fit’ through the data points, uses the criterion of

least squares. The equations to find this line of best fit are:

(4)

(5)

where: b = slope of the line of best fit (estimate/regression) line

x = values of the dependent variable

y = values of the hypothesised or dependent variable

= mean of the values of x

= mean of the values of y

n = number of data points (pairs of values of the variables x, y)

a = y-intercept

The coefficient of determination measures the strength of a linear relationship

between two variables. It can be calculated directly in Microsoft’s Excel® or other

software such as IBM’s Statistics Package for the Social Sciences (SPSS). It is

calculated using the following equation given overleaf:

120

(6)

where: b = slope of the line of best fit (estimate/regression) line

x = values of the dependent variable

y = values of the hypothesised or dependent variable

= mean of the values of y

n = number of data points (pairs of values of the variables x, y)

a = y-intercept

Pearson’s Coefficient of Correlation between two variables is defined as the

covariance of the two variables divided by the product of their standard deviations.

Based on a sample of paired data (Xj, Yj), the sample Pearson’s Correlation

Coefficient is:

(7)

where

v is the sample score

is the sample mean

is the sample standard deviation

The results of this analysis of regression and correlation for the survey data will be

reported in Chapter 6.

5.10 Other information collected at the time of the survey

At the same time as the survey interview, information was collected on the number of

employees at each SME, the nature of the most successful innovation delivered in the

last five years and whether or not patents were held on the innovation concerned.

121

Extensive patent searches were later performed to confirm this information. This

information allowed the respondents to be classified as either small or medium-sized

businesses, as either product or process innovators and as patent holders or non-patent

holders (see Table 5.2, p.107). At the end of the survey, the respondents were given

the opportunity to advise of any factors that they considered significant in their own

story and which might be of assistance to others. This information was recorded in

the researcher’s notes. In addition, many of the survey respondents provided the

researcher with technical, trade and promotional material on the nature of their

innovation. Others also offered the opportunity for the researcher to attend

construction sites where the innovation was being currently utilised. A randomised

and de-indentified table showing the respondents’ characteristics is given in Table 5.5

overleaf. These descriptors will be used later in this thesis when quoting from, or

referring to, the open-ended responses given by the survey respondents.

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Table 5.5 Descriptors for survey open-ended comments

Respondent Small or

medium-

sized

company

Product

or process

innovator

Patent holder or

no patent

Descriptor

R1 Medium Product Patent holder R1_M.Prod.Pat

R2 Small Product Patent holder R2_S.Prod.Pat

R3 Medium Product No patent R3_M.Prod.NoPat

R4 Medium Process No patent R4_M.Proc.NoPat

R5 Small Process No patent R5_S.Proc.NoPat


R7 Small Process Patent holder R7_S.Proc.Pat

R8 Medium Process Patent holder R8_M.Proc.Pat














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5.11 Survey process and time-frame

The survey was conducted between March and December 2009. Interviews were

carried out on a face-to-face basis in the interviewees’ offices at a time that was

convenient to them. Participant consent forms and information sheet pro formas were

provided to the interviewees in accordance with the ethics approval process (copies of

these are included in the Appendices 2 and 3 of this thesis). Each survey interview

took between 30 minutes and one hour. The responses were either entered directly

into a laptop computer by the researcher during the interview or entered by hand onto

a paper version of the survey, depending on the convenience and preference of the

interviewee. Responses from the hard copy surveys were entered into the laptop

immediately after returning from the interview to the researcher’s office.

Initially, it was considered that some surveys could be done via email, but a pilot of

this methodology with two interviewees proved to be unsuccessful, as surveys were

not returned, even after several promptings. Making an appointment and using the

face-to-face format ensured a more inclusive response from the targeted group of

successful SME technical innovators. Because the nature of this study is primarily

exploratory rather than definitive, it was decided to allow for elaboration and

explanation of the terms in the survey during the interview (Suchman and Jordan

1990). The interviewee was informed at the start of the session that it was

permissible to ask questions if the survey terminology was unclear. A list of

synonyms, prompt words and explanations for the terms in the Value Tree was

prepared ahead of the interviews and used if the interviewee queried the terminology,

or hesitated for a significant period before answering. This list is included in Tables

5.6, 5.7, 5.8, 5.9, 5.10 and 5.11 (p.124 to p.127).

Strictly speaking, a survey where this level of interaction between the interviewer and

interviewee is permitted, is open to the charge of the interviewer leading the

interviewee to the desired responses. In order to limit the potential bias introduced by

this procedure, the list was simply used as an aid when respondents had some

definitional difficulty with the terms used. In the great majority of instances, the list

was not necessary and was not used at all. The first column of prompt words was

used on eight occasions and the second column was used only twice in total during

the twenty-eight question survey for the twenty-one interviewees. By far, the

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majority of the interviewees expressed no difficulty with understanding the

terminology or with definitional matters relating to the scope of the terminology.

Table 5.6 Synonyms/prompt words/explanations for Value Tree factors

Value Tree

item

Prompt words if

interviewee hesitates

or asks for

clarification

Examples to be suggested if prompt

words do not assist;

Questions if still unsure

Company

resources

Internal firm resources;

Available slack

resources

Do you ask the question “is a particular

innovation a realistic prospect for your

firm?”

Client and end-

user influences

Influence of project

initiator;

Influence of the

customer

Effect of owners/developers, project

commissioners and users/occupiers;

Essentially this item deals with people

who are outside the construction project

team but may be influential at the start or

the end of the project delivery

Project-based

conditions

Project unknowns;

Issues that arise once a

project has commenced;

On site variability

Construction planning and scheduling

issues; site-based incidents; site accidents

Industry

networks

Relationships external

to your firm; Industry

umbrella bodies; Other

industry players

Partners; Consultants; Collaborators;

Competitors

Regulatory

climate

Authorities; Building

codes; Approvals

systems; Certification

Are the Authority’s you deal with

generally willing to consider new

products or systems?

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Table 5.7 Synonyms/prompt words/explanations for Value Tree sub-factors of company resources

Value Tree

item

Prompt words if

interviewee asks for

clarification


words do not assist; Questions if still

unsure

Motivation Enthusiasm; Personal

drive; Ability to motivate

others

How significant for innovation is the

personality of the leader?

Available

finance

Effort versus return;

Payback period

Long and short term perspectives;

Venture capital; Was your innovation

funded through borrowing or from

capital resources?

Available

time

Time pressure; Other

priorities in your life

Did your innovation take longer to

deliver than you anticipated?

Available

skill levels

Your own and your

employees’ skills levels;

Tacit knowledge

Skill shortages; Confidence in staff

ability to deliver; Degree of dependence

on individuals

Insurance

and risk

Availability of insurance;

Supportive backers

Does the perception of risk prevent you

developing some possible innovations?

126

Table 5.8 Synonyms/prompt words/explanations for Value Tree sub-factors of client and end-user influences

Value Tree

item

Prompt words if


clarification



unsure

Procurement

systems

Contractual relationships;

Tender system; Pre-

qualification systems

Alliances; “Best for project” attitudes;

Does your firm do work for public or

private clients mainly?

Client

characteristics

Experienced or new;

Actively involved or

preferring to delegate

Technical competence of client; How

much do they understand of the

construction process? How useful is

their input?

Table 5.9 Synonyms/prompt words/explanations for Value Tree sub-factors of project-based conditions

Value Tree

item

Prompt words if


clarification



unsure

Supply chain

relationships

Your upstream

associations

Materials suppliers; Plant and equipment

hire firms; Construction product

manufacturers; Labour hire firms

Solving

problems

that occur on

site

Quality assurance

measures; Defects

remediation

Avoiding the cost and time delays

associated with rework; “Get it right

first time”

Improving

OH&S

Construction safety record;

Cost of construction

injuries

Proactively preventing accidents;

Designing out safety hazards

127

Table 5.10 Synonyms/prompt words/explanations for Value Tree sub-factors of industry networks

Value Tree

item

Prompt words if


clarification



unsure

Professional

and industry

associations

Building, construction or

specialist organisations

Australian Institute of Building;

Engineers Australia; Association of

Civil Contractors

Research

organisations

and

universities

Testing; Verification;

Developmental research

Commonwealth Scientific Industrial

Research Organisation (CSIRO);

National Association of Testing

Authorities (NATA)

Table 5.11 Synonyms/prompt words/explanations for Value Tree sub-factors of the regulatory climate

Value Tree

item

Prompt words if


clarification



unsure;

Performance-

based

standards

Flexible open-ended

building standards

Building Code of Australia

Local

authority

regulations

Council building approvals

process

Local Council attitudes and processes;

Local building inspectors’ attitudes

Industry

standards

Standard industry practice;

“Business as usual”

Standards Association of Australia

(SAA); “Deemed to satisfy” solutions

128

5.12 Face-to-face surveys

As previously mentioned, face-to-face interviews were adopted as the means of

survey delivery because this was speculated as likely to produce a high response rate

from the eligible survey group. This prediction proved to be correct. People who

manage SMEs are almost invariably very busy people with many demands on their

time. The researcher asked for, and made, an appointment with each respondent at

their offices and at a time convenient to the interviewee. This is the reason for the

high response rate for a construction industry survey of 75% of the targeted group.

Survey response rates of between 15 and 20% are considered reasonable by some

researchers in the Australian construction industry (Manley 2005). Those rates

would, however, only be satisfactory for a significantly larger sample size than was

possible in this study. A target response rate of over two-thirds of the eligible

respondents was set and achieved for this study in order to strengthen the validity of

the results because of the small size of the survey target group. As Doloi (2008)

points out, “one of the major advantages of AHP is that the analysis does not always

require a statistically significant sample size” (Doloi 2008 p.842). The

comprehensiveness of the pair-wise comparisons assures the method’s reliability. As

an indication of widespread acceptance of this approach, Table 5.12 overleaf shows

some examples of published AHP studies in several fields that have involved

relatively small, but carefully selected, survey samples.

While a low response rate can invalidate a survey because of the likelihood of sample

bias, it does not necessarily follow that a high rate removes this possibility. The bias

may have been in the selection criteria themselves. It was, therefore, given a high

priority that the qualifications for eligibility be clearly defined and no interviewees

were added to the list in an ad hoc manner. No self-nominations or informal third

party recommendations were accepted.

129

Table 5.12 AHP studies based on selected expert samples

Reference Study area AHP sample size

Shapira and Simcha (2009) Construction equipment 19

Doloi (2008)

Construction productivity 19

Kaka et al. (2008)

Construction culture 51

Lam, Lam and Wand (2008)

Quality management 12

Melón, Aragonés Beltran and Carmen González Cruz (2008)

Technical education 14

Newell and Seabrook, (2006)

Property investment 15

Shahin and Mahbod (2007)

Key performance indicators 10

Gunhan and Arditi (2005)

International construction 12

Kauko (2003)

Property valuation 25

Chan (2002)

Property assessment 40

Dias and Ioannou (1996)

Project evaluation 14

130

Face-to-face surveys have their own associated potential biases due to the essential

nature of human interaction. As Suchman and Jordan (1990) have explained, there is

often an unresolved tension between the survey interview as an interactional event

and as a neutral measurement instrument (Suchman and Jordan 1990, p.232). The

interviewer may give unconscious indications of the expected answers via body

language, facial expressions and verbal responses to comments made by the

interviewee. The interviewees themselves may be trying to impress, seeking to give

the anticipated ‘correct’ answers or those which will display their companies in the

best light. These possibilities were addressed by assurances that the survey responses

would be de-identified and only data on average responses published at the end of the

survey. Individual responses were not to be reported on in any way that could

identify the original source. In addition, the integrity of the answers was also aided

by the fact that the interviewees were, in fact, the primary experts on their particular

technical innovation and so were unlikely to be intimidated or directed in their

responses by the interviewer. The survey does not deal with matters that are personal,

emotional or which might impinge on the individual’s privacy. Therefore, the

inclusion of a small level of elaboration in the wording of the questions during the

interview can be considered to have no significant effect on the validity of the results.

All of the above quality control measures ensured the integrity of the interview

process and the quality of the survey materials collected.

131

CHAPTER 6 ANALYSIS OF FACTORS AFFECTING INNOVATION DELIVERY

Chapter 6 analyses the quantitative results of the AHP survey in order to identify

those factors considered by the expert respondents to be most significant in assisting

the delivery of technical innovations. Recurring themes are reported and evaluated in

the context of SME construction businesses. Sub-groups within the sample are

analysed for significant differences.

6.1 Survey results for the whole sample

The survey response displayed a robust diversity amongst the respondents on

priorities for both the identified factors and sub-factors that influence technical

innovation delivery. Some observations can be made about the raw data responses.

Significantly, none of the identified factors were rejected as irrelevant by a large

number of the respondents. There was scattered support for all factors from at least

some of the respondents and this can be regarded as an indicator of the validity of the

identified factors in the Value Tree. These findings show that there is strong support

for the inclusion of all five factors in the Value Tree as at least some respondents

rated each of the five factors as very important.

Mean weightings and priorities given by the survey respondents for factors and sub-

factors are displayed in Table 6.1 overleaf. Four of the five factors were ranked

closely (ranging within ±0.8% of the mean of the four weights) with only ‘Company

resources’ receiving a significantly lower rating than the others (14.1%). ‘Project-

based conditions’ (22.6%) was the highest ranked factor, albeit by a small margin

from ‘Client and end-user influences’ (22.2%). ‘Regulatory climate’ (21.5%) and

‘Industry networks’ (19.6%) were rated next, followed by ‘Company resources’

(14.2%).

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These AHP results indicate three levels of importance:

• Level 1: project-based conditions and client influences (> 22%),

• Level 2: regulations and networks (< 22% and > 18%),

• Level 3: company resources (< 18%).

Table 6.1 AHP weightings for factors affecting SME technical innovation delivery

Factors Factor weight

Sub-factors Sub-factor weight

Sub-factor rank

1. Project-based conditions

22.6% Improving OH&S 10.4% 3

Supply chain relationships 7.2% 6

Solving problems that occur on site

5.5% 8

2. Client and end-user influences

22.2% Client characteristics 12.4% 1

Procurement systems 5.8% 9

3. Regulatory climate 21.5% Performance-based standards

11.2% 2

Industry standards 4.7% 11

Local authority regulations 4.4 12

4. Industry networks 19.6% Professional and industry associations

9.4% 4

Research organisations and universities

8.2% 5

5. Company resources

14.1% Personal motivation 6.9% 7

Available skill levels 5.3% 10

Available finance 3.9% 13

Available time 3.4% 14

Insurance and risk 1.9% 15

TOTAL 100% 100%

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The first two factors together accounted for nearly 45% of the total factor weightings.

It should be noted that both these factors relate to project-specific matters. These are

matters that do not persist beyond individual construction projects. This is evidence

for the primacy of construction project organisation on construction company

performance. The second pair of factors are related to regulations and networking.

These are matters that persist beyond individual projects and are at least partially

outside the control of the individual SME. The third level, or least important factor,

was found to be matters internal to the firm; that is, its resource base.

The AHP survey of factors found that there was no rejection of any of the individual

factors as insignificant. There was, however, no support for the contention that one or

other of the five factors completely dominates the others in the minds of technical

innovators. It is only possible to indicate a slight preference for the four highest rated

factors over the remaining one, that being ‘Company resources’.

The low weighting for ‘Company resources’ was somewhat unexpected, as there is

much published literature coming from the UK, in particular, which describes this

factor as being of critical importance to construction innovators in small and medium-

sized firms (Abbott et al. 2006; Barrett and Sexton 2006; Sexton and Barrett 2003a;

Sexton and Barrett 2003b; Sexton and Barrett 2004; Sexton et al. 2006). It is said to

be a reason why small businesses are unlikely to deliver innovations at a rate

comparable to large businesses. They are suggested to have too few slack resources

to devote time to innovation. Indeed Schumpeter, the principal founder of innovation

theory in economics, believed that innovation was likely to remain the province of

large businesses for this reason (Schumpeter 1942). The results of this study run

counter to this widely held opinion. The small and medium-sized business operators

in this study did not report that company resources were a significant factor in the

delivery of their innovations. It can be speculated that this is due to the fact that the

survey took place among successful innovators only. These innovators had solved

any potential problems with their resource base, in order to bring their innovation

successfully to market, and therefore, they did not rate the factor highly. It may also

be that the innovators were keen to present themselves and their businesses in the best

light and, consequently, did not wish to admit to any inadequacies in matters relating

to internal company resources. A study amongst potential innovators, or those

134

considering embarking on an innovation delivery process, may have given very

different results.

Because of the closeness of the first four factor weightings, confidence levels were

calculated for the average responses. These are illustrated by the 5% error bars in

Figure 6.1. At a 95% confidence level, the top three factors cannot be said to be

markedly different, as illustrated by overlapping error bars.

Figure 6.1 Mean weighting for Value Tree factors with 5% error bars

The major finding on the AHP factor ratings is, therefore, that the survey group of

high performing technical innovators did not rank internal company resources as

important in the delivery of their innovation. This finding is contrary to traditional

innovation theory as delineated by Schumpeter (1942).

6.2 Sub-factor weightings

Sub-factor weightings covered a considerably greater range than the factor

weightings. There was a greater than six-fold difference between the rating of the

highest and lowest rated sub-factor.

This is illustrated by Figure 6.2 with the inclusion of 5% error bars for the sample. At

the 95% confidence level, there is considerable difference between the average

responses on sub-factor weightings.

135

Figure 6.2 Mean weighting for Value Tree sub-factors with 5% error bars

The AHP results indicate three levels of sub-factor importance:

• Level 1(major importance): client characteristics, performance-based

standards, improving OH&S, professional and industry associations and

research organisations and universities. (Weighting: > 8%);

• Level 2 (moderate importance): supply chain relationships, personal

motivation, procurement systems, solving problems on site, available skill

levels, industry standards and local authority regulations. (Weighting: > 4%

and <8 %);

• Level 3 (minor importance): available finance, available time and

insurance/risk. (Weighting < 4%).

136

These priorities are illustrated as a potential priority model for technical innovation by

SME construction firms in Table 6.2.

Table 6.2 Technical innovation delivery multi-criteria decision-making priority summary

Level Factors Sub-factors Driver/

outcome

First Client and end-user influences

Client characteristics Driver

Regulatory climate Performance-based standards

Driver

Project-based conditions Improving OH&S Driver/

outcome

Industry networks Professional and industry associations

Driver

Industry networks Research organisations and universities

Driver

Second Project-based conditions Supply chain relationships Driver

Company resources Personal motivation Driver

Project-based conditions Solving problems that occur on site

Driver

Client and end-user influences

Procurement systems Driver

Company resources Available skill levels Driver

Regulatory climate Industry standards Driver/

outcome

Regulatory climate Local authority regulations Driver

Third Company resources Available finance Driver

Company resources Available time Driver

Company resources Insurance and risk Outcome

137

Table 6.1 (p.132) shows that there was a distinctly greater difference of opinion on

the sub-factors generally when compared with the fairly uniform response to the

factors. The highest ranked sub-factor ‘Client characteristics’ was given a rating of

six times the lowest ranked sub-factor ‘Insurance and risk’. This is a larger difference

than was anticipated. It is mainly accounted for by the relatively low importance

ascribed to the five sub-factors which relate to a company’s resources; in other words,

the internal characteristics of the business arrangements.

The survey of the sub-factors in the Value Tree strongly supported the contention that

client characteristics, as well as performance-based building standards, assist

technical innovation. To a lesser extent, it also found that the assistance of

professional bodies and research organisations was considered by many innovators to

be very important in the delivery process. Each of these findings is useful to the

industry as a whole and to related groups such as building procurers.

Among the sub-factors, ‘Improving OH&S’ (3rd in total priority order) was rated more

highly than previous innovation studies have indicated. It was also regarded as

almost twice as important as the other two ‘Project-based conditions’ sub-factors.

This finding may be related to a recent strong push from both government and large

construction companies to improve the Australian industry performance in this area.

Several individual innovators in this study gave very high priority to OH&S issues

generally, and some reported it as the driving motivation for their innovation.

The sub-factor ‘Client characteristics’, was regarded as twice as important as

‘Procurement systems’, which was the other factor in its sub family. This is a

surprising result as it indicates that personal factors to do with the clients’ choices,

their competence or their behaviour outweigh contractual and legal issues in the

minds of the innovators surveyed. As this matter was not raised in any of the

informal comments at the end of the survey, any explanations offered are necessarily

speculative. It may be that the personal factors are exaggerated in some

circumstances and these occasions are likely to be remembered when reflecting on

past experience for this survey. It is not possible to determine from the data collected

whether or not this is so.

‘Professional and industry organisations’ and ‘Research organisations and

universities’ were given fairly similar ratings by the survey respondents with the

138

former being only slightly favoured over the latter. It is possible that different kinds

of technical innovation focus either on verification by independent testing, or

verification by acceptance of the innovation within the industry. The first group

would place more importance on universities and the second on industry

organisations. This is a matter for further investigation.

Finally, ‘Performance-based standards’ were regarded as twice as important as the

other two sub-factors relating to the ‘Regulatory climate’. This indicates strong

support from the innovators for the move towards performance-based regulation of

building.

6.3 Sub-groups within the overall sample

The AHP survey data was also sorted to display the responses of the sub-groups in the

sample: small versus medium businesses; product versus process innovations; and

patent holders versus non-patent holders. The results for small versus medium are

displayed in Table 6.3 overleaf; product versus process innovation in Table 6.4

(p.144); and those for patent holders versus non-patent holders in Table 6.5 (p.144).

The sub-groups were not equal in numbers: ten small versus eleven medium-sized

businesses; thirteen building product innovators versus eight building process

innovators; and fourteen patent holders versus seven non-patent holders. Some

significant differences between the mean responses at 95% confidence level were

noted and these have been listed in the last column of Tables 6.3, 6.4 and 6.5.

6.4 Small versus medium business results

The average responses for both small and medium enterprises in the sample are

considerably less uniform than the average responses for the whole group. This is an

indicator that significant differences exist between the two groups. All five factors

and fourteen of fifteen sub-factors were given different priority ranks by the two

groups.

139

Table 6.3 AHP weightings: small versus medium-sized businesses

Weights

Small

businesses Factor rank

Medium businesses

Factor rank

Sig.

Factors

Company resources 12.5% 5 15.5% 5 Yes

Client and end-user influences 27.0% 1 19.5% 3 Yes

Project-based conditions 17.7% 4 25.6% 1 Yes

Industry networks 18.6% 3 20.5% 2 No

Regulatory climate 24.4% 2 18.9% 4 Yes

Sub-factors

Personal motivation 4.5% 12 7.9% 5 Yes

Available finance 4.1% 13 3.3% 13 Yes

Available time 3.5% 14 2.7% 15 Yes

Available skill levels 4.6% 11 5.4% 10 Yes

Insurance and risk 0.7% 15 3.0% 14 Yes

Procurement systems 5.8% 6 = 5.7% 8 No

Client characteristics 15.8% 1 8.8% 4 Yes

Supply chain relationships 5.3% 9 7.8% 6 Yes

Solving problems that occur on site 5.8% 6 = 5.5% 9 No

Improving OH&S 7.7% 5 13.6% 1 Yes

Professional and industry associations 8.2% 4 11.9% 2 Yes

Research organisations and universities 10.5% 3 7.4% 7 Yes

Performance-based standards 13.1% 2 10.2% 3 Yes

Industry standards 4.9% 10 4.2% 11 Yes

Local authority regulations 5.8% 6 = 3.6% 12 Yes

Significance is taken here to represent significant difference between means of small and medium-sized business factor/ sub-factor weights allowing for 5% error.

140

As a general observation, it can be seen that ‘Client and end-user influences’ is rated

much more importantly by small companies than it is by medium-sized companies.

This probably reflects the relative importance of an individual client to a small

business. Conversely, medium-sized businesses rate ‘Project-based conditions’ much

more importantly than do small businesses. This may indicate that the medium-sized

businesses are involved in more complex projects where site conditions assume more

significance. On the other hand, there is little difference in the average response of

the two groups on ‘Industry networks’. Both small and medium businesses in the

survey on average see industry networks as important, but not critical, to their

innovation delivery process. Figure 6.3 illustrates the differences between the two

groups’ averages on factors along with 5% error bars.

Figure 6.3 Bar chart of small and medium-sized business average response on factors with 5% error bars

Some useful points can be noted here. Although the average difference between the

groups on the factor ‘Industry networks’ is not significant, there are sub-factor

averages relating to this factor which do contain significant differences. The inverted

priority between small and medium businesses, on the factors ‘Client and end-user

141

influences’ and ‘Project-based conditions’, has already been commented upon. It may

be a result of differing levels of reliance on individual clients and differing positions

in the contractual hierarchy.

Curiously, ‘Company resources’ is rated as more important by medium-sized

businesses than by small. The literature would tend to indicate that that this should be

reversed (Abbott et al. 2006; Barrett and Sexton 2006; Sexton and Barrett 2003a). It

may be that the medium-sized businesses in the survey are generally engaged in larger

contracts and, therefore, more pressed for resources. This response may also be due

to the larger wage and salary commitments of the medium-sized businesses.

The sub-factors exhibit a greater degree of difference in average response than the

factors do (Tables 6.11 p.159 and 6.12 p.161). Thirteen of fifteen sub-factors exhibit

significant differences between the two groups. There is reasonably close agreement

between the two groups on ‘Procurement systems’ and ‘Solving problems that occur

on site’. Otherwise, there is considerable disagreement in the ratings derived from the

average response. The four largest differences are on ‘Client characteristics’,

‘Improving OH&S’, ‘Personal motivation’ and ‘Professional and industry

associations’.

Individual clients are proportionately more important to small businesses than to

medium-sized businesses, as they are likely to represent a greater proportion of

income for the small business. Indeed, sometimes small businesses may be very

dependent on one or two individual clients, and therefore, they can be very vulnerable

to changes of opinion by their important clients. Medium-sized businesses are less

likely to be in this situation, because their size is likely to mean that they have a

spread of potential clients.

142

Figure 6.4 Bar chart of small and medium-sized business average response on sub-factors with 5% error bars

The next biggest difference between the two groups was on ‘Improving OH&S’,

where medium-sized businesses gave this sub-factor considerably higher priority.

This may be evidence of medium-sized companies taking up the push towards

improving industry performance on OH&S which has in recent years been driven by

government and by large companies in the Australian construction industry.

Medium-sized businesses are possibly more likely to be engaged as sub-contractors

on large projects for government clients or where the head contractor is one of the top

200 industry enterprises. Consequently, the medium sized business manager may be

more aware of OH&S as a driver of industry change. Since medium sized businesses

143

employ more people, they also have more vulnerability to be liable for the cost of

injury and death on construction sites.

It is unclear why ‘Personal motivation’ should be seen as more important by medium-

sized businesses than by small ones. Generally, this researcher has observed a high-

level of personal motivation among those respondents at both levels of business size.

It may be that for small businesses ‘being a self-starter is a given’ (comment by

R13_S.Prod.Pat), and consequently, they failed to rate the attribute highly. It is

simply considered a prerequisite for running a small business in a competitive

industry like construction.

It is also somewhat difficult to explain why medium-sized businesses in the sample

rated ‘Professional and industry associations’ much more importantly than small

businesses. It may be that, for this sample, the kinds of services and opportunities

currently provided by professional organisations are more closely geared to the needs

of medium-sized businesses. This is a potential area for future research.

6.5 Building product versus building process innovators

The second pair of sub-groups in the sample is product innovators compared to

process innovators. As the term implies, product innovators have generated a distinct

physical product, either a building component or a piece of plant or equipment for use

on construction projects. Process innovators on the other hand have developed a new

or substantially different construction process which is not bounded by an individual

building component. The average responses for both groups in the sample are, once

again, considerably less uniform than the average responses for the whole group.

This is an indicator that significant differences exist between the two groups. All five

factors and eleven of fifteen sub-factors were given different priority ranks by the two

groups.

144

Table 6.4 AHP weightings: product versus process innovators

Weights

Product innovators

Factor rank

Process innovators

Factor rank

Sig.

Factors

Company resources 13.0% 5 15.9% 4 Yes



Industry networks 22.0% 3 15.6% 5 Yes


Sub-factors

Personal motivation 4.9% 11 8.5% 4 Yes



Available skill levels 5.0% 10 5.1% 10 No


Procurement systems 5.4% 9 6.2% 8 Yes



Solving problems that occur on site 5.7% 6 = 5.6% 9 No





Industry standards 5.7% 6 = 2.6% 14 Yes

Local authority regulations 4.7% 12 4.5% 11 No

Significance is taken here to represent significant difference between means of product and process innovator factor/ sub-factor weights allowing for 5% error.

145

As can be seen from Table 6.4, process innovators rated ‘Project-based conditions’

much more highly than product innovators did. For product innovators, ‘Client and

end-user influences’ were rated most important of the five factors. This confirms

anecdotal impressions of the two groups. Building process innovators are more likely

to be head contractors or major sub-contractors. As a result, they are often driven by

solving problem situations that occur during the delivery of construction projects

(Slaughter 1993a; Slaughter1993b). They are more likely than product innovators to

have supervision responsibility for other participants in the construction project

delivery process. In other words, they are more likely to be ‘integrators’ and problem

solvers. Product innovators, on the other hand, are likely to be more dependent on a

sympathetic attitude from project funders who may opt for the conservative approach

and be unwilling to try anything new. Consequently, product innovators rate the

client or the end-user as being of critical importance in the delivery of their

innovation.

The differences on average between product and process innovators in the sample

were significant for each of the five factors as can be seen in Figure 6.5 (overleaf)

where error bars for 5% value are shown. The average differences between product

and process innovators are greater than for either of the other pairs of sub-groups in

the sample. This is a somewhat unexpected finding. Small and medium-sized

businesses were expected to exhibit the biggest differences between the sub-groups as

the unique position of small businesses has been much reported (Abbott et al. 2006;

Barrett and Sexton 2006; Sexton and Barrett 2003). It may be that for this sample, it

is the level of project integration which the innovator has responsibility that is the

critical factor in revealing the story of how technical innovation is delivered. This is a

suitable area for future research.

146

Figure 6.5 Bar chart of product and process innovators average response on factors with 5% error bars

A similar attitude can be seen to be confirmed by the ratings given to the fifteen sub-

factors by each group. Product innovators once again saw the ‘Client characteristics’

as easily the matter of most importance. This indicates their dependence on the client

opting for a change from standard practice in the adoption of an innovative product.

Clients would probably have more say in the selection of products than they would in

the adoption of innovative processes, as this may be decided by the builder or head

contractor.

147

Figure 6.6 Bar chart of product and process innovators average response on sub-factors with 5% error bars

Process innovators, however, rated ‘Improving occupational health and safety’ as

being the sub-factor of the highest level of importance and this was considerably more

important to them than to product innovators. The process innovators in the sample

were more likely to have responsibility for integrating the construction process and

consequently, they were more likely to see construction safety as of prime importance

to their innovative process solutions.

It is unclear why process innovators rated personal motivation considerably higher

than did product innovators. It may be that the delivery of a new building process

requires more negotiation and the convincing of other players in the project delivery

148

system and consequently, the process innovators are more dependent on personal

drive to manage this negotiation.

For the sub-factors ‘Research organisations and universities’ as well as ‘Industry

standards’, product innovators were considerably more enthusiastic than process

innovators. It could be that once again this is about the need to convince the

appropriate people of the value of a new product or process. Independent verification

and the attitude of competitors both seem to be more important for product

innovators.

The bar chart for the sub-factors averages (Figure 6. 6) illustrates the significant

differences between product and process innovators on eleven of the fifteen factors.

This is an indication that they may represent quite distinct populations within the

sample.

6.6 Patent holders versus non-patent holders

The third pair of sub-groups in the sample was patent holders compared with non-

patent holders. The sample contained fourteen patent holders and seven respondents

who did not hold patents on their innovation. Three of five factors and fourteen of

fifteen sub-factors were given different priority ranks by the two groups. As Table

6.5 illustrates, patent holders rated ‘Client and end-user influences’ much higher than

did non-patent holders. This is further support for the need for open-minded

individuals funding projects when new and innovative solutions are proposed. Other

than on this factor, there were few notable differences between the two groups on

factors. There was little difference in the average responses on ‘Company resources’

or ‘Industry networks’ between the two groups. The group differences on the factors

of ‘Project-based conditions’ and ‘Regulatory climate’ were minor.

149

Table 6.5 AHP weightings: patent holders versus no patents

Weights

Patent holders

Factor rank

Non-patent holders

Factor rank

Sig.

Factors

Company resources 14.5% 5 13.2% 5 No



Industry networks 19.5% 4 19.7% 3 No


Sub-factors

Personal motivation 6.0% 6 = 6.9% 7 Yes



Available skill levels 4.9% 10 5.3% 9 = No


Procurement systems 6.0% 6 = 5.2% 11 Yes



Solving problems that occur on site 5.8% 9 5.3% 9 = No





Industry standards 4.0% 13 5.5% 8 Yes

Local authority regulations 4.5% 11 4.9% 12 No

Significance is taken here to represent significant difference between means of patent holders and non-patent holder’s factor/ sub-factor weights allowing for 5% error.

150

Figure 6.7 Bar chart of patent holders and non-patent holder’s average response on factors with 5% error bars

On sub-factors, as displayed in Table 6.5, there were generally fewer significant

differences on average than for the other two sub-group pairs. Only the sub-factor

‘Client characteristics’ revealed a fairly large difference on average. This is a similar

result to the one for the factor ‘Client and end-user influences’ and probably stems

from the same source. The bar chart illustrated in Figure 6.7 shows the relatively

minor differences in average response to the survey by patent holders and non-patent

holders. This is a somewhat unexpected finding as patent holders are generally

regarded as very unusual in the construction industry. Compared to the

manufacturing sector, the construction industry generates relatively few patents. As a

result, it might be expected that the patent holders in the sample would form a

distinctly different group. However, as all the respondents were selected on the basis

of having achieved peer recognition as a significant innovator, it is likely that the

whole sample represents a distinctly different group from the average construction

company rather than the patent holders being specially delineated.

Minor differences were noted on ‘Personal motivation’, which was rated more highly

by process innovators than by product innovators. This may be due to the higher

level of integration and communication skills needed by those delivering innovations

that may require other parties in the construction process to change their standard

151

practices. Conversely ‘Research organisations and universities’ were more important

on average to product innovators than they were to process innovators. This

difference may relate to the need for independent testing of products before their

delivery in the marketplace.

Figure 6.8 Bar chart of patent holder’s and non-patent holder’s average response on sub-factors with 5% error bars

In general, the average responses of these two groups on sub-factors does not exhibit

large enough difference to be confident that these are two distinct groups as opposed

to one group without distinctly different characteristics.

152

6.7 Preliminary results summary

Generally, the preliminary descriptive analysis of the three pairs of sub-groups in the

sample has revealed that there may be significant differences between product and

process innovators on the factors that assist their innovation delivery. Similarly,

while the results demonstrate that there may be some important differences between

small and medium-sized businesses, these are generally less than was anticipated

before the survey was undertaken. Only minor differences between patent holders

and non-patent holders in the survey response were exhibited.

It is also noteworthy that all of the ten small businesses in the sample were patent

holders, while only four of the eleven medium-sized businesses held patents. This

indicates that the protection afforded by a patent may be critical for small business

technical innovation delivery. This would particularly be likely in the establishment

phase of the innovation delivery.

So far, the analysis of the sub-group response has looked only at the difference

between the group means. Statistical tests are available to more closely examine both

variance and correlation within the data set of group responses.

6.8 ANOVA

The analysis of variance (ANOVA) concept starts from the premise that the

individual items of information being studied are not all the same and may vary

according to a significant pattern (Black 2008 p.409). One-way ANOVA can be used

to compare the relative sizes of the total variation in the group to the error variation

(which is due to individual differences within the group). ANOVA was completed in

Statistical Package for the Social Sciences (SPSS) for each of the three pairs of

identified sub-groups in the sample against each of the factors and sub-factors. This

test can be expressed as:

Along with consideration of degrees of freedom, the calculated F value can be

compared with critical F values for 0.05 probability. If the calculated F value exceeds

153

the critical value for a particular treatment, then the null hypothesis is rejected and the

variances between the samples are significant. Tables 6.6, 6.7 and 6.8 reveal the

ANOVA results for the five factors for each of three sub-groups: small versus

medium-sized companies; product innovators versus process innovators; and patent

holders versus non-patent holders.

Table 6.6 Results from ANOVA on factors by company size

Small versus medium-sized companies

Sum of Squares df

Mean Square F Sig.

Company resources

Between Groups

47.114 1 47.114 0.330 0.572

Within Groups 2710.058 19 142.635

Total 2757.172 20

Client and end-user influence

Between Groups

425.572 1 425.572 2.239 0.151

Within Groups 3610.790 19 190.042

Total 4036.363 20

Project-based conditions

Between Groups

459.710 1 459.710 1.887 0.186

Within Groups 4629.901 19 243.697

Total 5089.611 20

Industry based networks

Between Groups

23.582 1 23.582 0.106 0.748

Within Groups 4218.720 19 222.038

Total 4242.303 20

Regulatory climate

Between Groups

155.792 1 155.792 0.439 0.515

Within Groups 6739.674 19 354.720

Total 6895.467 20

Where df represents the degree of freedom for the sample and Sig. represents the calculated

significance level.

No significant differences compared with F Critical of 2.970 (Black et al. 2009).

154

Table 6.7 Significant results from ANOVA on factors by innovation type

Product versus process innovators Sum of Squares df

Mean Square F Sig.

Company resources

Between Groups

42.176 1 42.176 0.295 0.593

Within Groups 2714.996 19 142.895

Total 2757.172 20


Between Groups

79.391 1 79.391 0.381 0.544

Within Groups 3956.972 19 208.262

Total 4036.363. 20


Between Groups

591.927 1 591.927 2.501 0.130

Within Groups 4497.684 19 236.720

Total 5089.611 20


Between Groups

206.400 1 206.400 0.972 0.337

Within Groups 4035.903 19 212.416

Total 4242.303 20

Regulatory climate

Between Groups

56.090 1 56.090 0.156 0.697

Within Groups 6839.377 19 359.967

Total 6895.467 20


significance level.


155

Table 6.8 Significant results from ANOVA on factors by patent

Patent holders versus no patents Sum of Squares df

Mean Square F Sig.

Company resources

Between Groups

8.961 1 8.961 0.062 0.806

Within Groups 2748.211 19 144.643

Total 2757.172 20


Between Groups

111.394 1 111.394 0.539 0.472

Within Groups 3924.969 19 206.577

Total 4036.363 20


Between Groups

38.477 1 38.477 0.145 0.708

Within Groups 5051.134 19 265.849

Total 5089.611 20


Between Groups

0.174 1 0.174 0.001 0.978

Within Groups 4242.129 19 223.270

Total 4242.303 20

Regulatory climate

Between Groups

48.000 1 48.000 0.133 0.719

Within Groups 6847.466 19 360.393

Total 6895.467 20


significance level.


As can be seen from Table 6.7, only one of the five factors demonstrated significant

difference between the product and process innovator respondents in the ANOVA

test. The ‘Project-based conditions’ factor was significantly more important to

156

process innovators than to product innovators. This is a reasonably expected result, as

process innovators are likely to be more involved with the detailed delivery of their

technical innovation on site. Product innovators may or may not be so involved,

depending on whether they are heavily involved in the product’s on-site installation.

The ANOVA results for the other two pairs of sub-groups revealed no significant

differences on factors affecting technical innovation (Tables 6.6 and 6.8). This is, in

itself, an interesting result. A possible interpretation may be that the sample

represents a reasonably coherent group of high-level innovators in construction

SMEs. The characteristic for which they were selected, that is, successful delivery of

a high-level technical innovation, would appear to dominate other differences within

the group. Company size, technical innovation type and whether or not they hold

patents on their particular innovations, all appear to have less impact on their ratings

of the factors that affect technical innovation delivery, than does their membership of

the group overall. Since successful delivery of a technical innovation by a

construction SME is still a comparatively rare event, it is perhaps unsurprising that

this fact dominates other company characteristics. It was never anticipated that these

firms represented typical construction firms. Indeed, they were chosen for an

achievement which is atypical. The lack of differentiation by sub-group can be said

to give more weight to the priorities and weights of the overall sample, as listed in

Table 6.1.

ANOVA tests were also performed for each of the fifteen sub-factors by the three

pairs of identified sub-groupings. These results are given in Tables 6.9, 6.10 and

6.11. For 95% confidence, the F Critical value should be 2.970 (Black et al. 2009).

No calculated value of F exceeded this figure. Therefore, no significant differences

were found, so the null hypothesis must be retained. In other words, the proposed

sub-groups do not represent two distinct populations within the sample. As with the

ANOVA tests for factors, it should be concluded that membership of the survey group

of high-level technical innovators dominates membership of the potential sub-groups

based on company size, innovation type and patent holding. This supports the

validity of the sub-factor priorities given in Table 6.1, as being an accurate reflection

of high-level technical innovator group opinion. Further statistical tests were carried

out in order to search out patterns in the data set and these are reported in the next

section of this chapter.

157

Table 6.9 Results from ANOVA on sub-factors by company size

Small versus medium-sized companies Sum of Squares df

Mean Square F Sig.

Personal motivation

Between Groups 40.060 1 40.060 1.084 0.311 Within Groups 701.963 19 36.945 Total 742.023 20

Available finance Between Groups 1.955 1 1.955 0.128 0.725 Within Groups 291.305 19 15.332 Total 293.260 20

Available time Between Groups 3.414 1 3.414 0.195 0.663 Within Groups 331.878 19 17.467 Total 335.291 20

Available skill levels


Insurance and risk


Procurement Between Groups 8.424 1 8.424 0.205 0.656 Within Groups 781.201 19 41.116 Total 789.626 20

Client characteristics


Supply chain relationships


Solving problems on site


Professional and industry organisations




Improving OH&S


Performance-based standards


Industry standards

Between Groups .118 1 .118 .005 .942 Within Groups 407.365 19 21.440 Total 407.483 20

Local authority regulations

Between Groups 27.165 1 27.165 .355 .558 Within Groups 1452.127 19 76.428 Total 1479.291 20

158

Table 6.10 Results from ANOVA on sub-factors by innovation type

Product versus process innovators Sum of Squares df

Mean Square F Sig.

Personal motivation






Insurance and risk













Improving OH&S




Industry standards




159

Table 6.11 Results from ANOVA on sub-factors by patent holding

Patent holders versus no patent Sum of Squares df

Mean Square F Sig.

Personal motivation






Insurance and risk Between Groups 6.326 1 6.326 0.661 0.426 Within Groups 181.701 19 9.563 Total 188.027 20












Improving OH&S Between Groups 23.926 1 23.926 0.154 0.699 Within Groups 2956.084 19 155.583 Total 2980.010 20



Industry standards Between Groups 16.974 1 16.974 0.826 0.375 Within Groups 390.509 19 20.553 Total 407.483 20


Between Groups 0.549 1 0.549 0.007 0.934 Within Groups 1478.743 19 77.829

Total 1479.291 20

160

6.9 Correlation and regression

Correlation analysis was carried out using Pearson’s Coefficient of Correlation to

determine if any specific relationships exist between the variables of the survey

response. Significant results were returned for both the factors and the sub-factors.

Results for the factors are displayed in Table 6.12. Results for the sub-factors are

presented in Table 6.13.

Three factor pairings exhibited significant negative correlations: ‘Client and end-user

influence’ with ‘Regulatory climate’; ‘Project-based conditions’ with ‘Regulatory

climate’; and ‘Project-based conditions’ with ‘Industry networks’. The first two

factors are fully external to the SME innovator’s company and are items over which

the innovator has little or no control. To an extent, they are also external to the

project delivery process. The negative correlation is evidence that the innovators in

the study see these two factors as working in opposite directions to each other when it

comes to fostering innovation. The second factor pair is evidence of the somewhat

disputative relationship between building regulators and those who have

responsibility for dealing with unforeseen occurrences that can occur on a

construction site. The third factor pair both relate to industry-centred matters, not

entirely in the control of the SME innovator, although it may be possible to exercise

influence. Nevertheless, these factors are also seen by the survey innovators to be

acting counter to each other. It may be that the innovators were split into those who

largely focussed on delivering their own projects, or those who aimed at convincing

the industry to take up their innovation. This represents a dilemma for those

contractors who successfully deliver a technical innovation. Do they remain in the

area of construction project contractor or do they become essentially a supplier of

their innovation to the larger industry? The innovators who responded to this survey

involved companies who were headed in either direction, as well as those who were

continuing to take both roles. Either path may prove to be suitable for some kinds of

innovation and for some company types which embark on the innovation delivery

process. The study undertaken for this thesis was not able to determine a single most

appropriate course for the potential construction innovator.

161

Table 6.12 Correlations between factors for the whole sample

Company

resources

Client and

end-user

influence

Project-

based

conditions

Industry

based

networks

Regulatory

climate

Company

resources

Pearson

Correlation

1

Client and

end-user

influence

Pearson

Correlation

-0.139 1

Project-

based

conditions

Pearson

Correlation

-0.105 0.084 1

Industry

based

networks

Pearson

Correlation

-0.080 -0.355 -0.518* 1

Regulatory

climate

Pearson

Correlation

-0.374 -0.472* -0.451* -0.017 1

* Correlation is significant at the 0.05 level (2-tailed).

A table of sub-factor correlations is presented overleaf (Table 6.13). Both positive

and negative correlations were exhibited between the sub-factors. The correlations

include some which were of a high order of significance. These are shown

highlighted in the tables.

162

Table 6.13 Correlations between sub-factors – whole sample

Non-patent holder sub-factor correlations

N = 21

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform

ance-based standards

Industry standards


Personal motivation

1

Available finance

0.505* 1

Available time

0.720** 0.369 1


0.642** 0.761** 0.501* 1

Insurance and risk

0.662** 0.217 0.323 0.561** 1

Procurement

-0.076 -0.150 -0.124 -0.310 -0.089 1


-0.192 -0.257 0.064 -0.190 -0.054 -0.086 1


-0.158 -0.206 -0.110 -0.187 -0.238 0.407 0.078 1


-0.491* -0.365 -0.484* -0.405 -0.384 0.011 0.327 0.309 1

Improving OH&S

0.013 -0.174 -0.076 -0.088 -0.137 0.005 0.070 0.040 0.402 1


-0.251 -0.213 -0.320 -0.399 -0.060 0.085 -0.360 -0.023 -0.079 -0.281 1


-0.161 0.152 -0.087 -0.221 -0.276 0.064 -0.453* -0.298 -0.414 -0.480* 0.737** 1


-0.268 -0.126 -0.252 0.098 0.029 -0.393 -0.102 -0.343 0.151 -0.205 -0.141 -0.157 1

Industry standards

-0.328 -0.249 -0.256 -0.268 -0.182 -0.315 0.312 -0.025 0.019 -0.220 -0.052 0.009 0.096 1


-0.251 -0.118 -.205 -0.179 -0.156 -0.023 -0.182 -0.097 -0.304 -0.361 -0.064 0.265 0.046 0.259 1

* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).

163

Twelve pairs of sub-factors exhibited significant correlation. Eight of these were

positive correlations and four were negative. Six pairs were correlated at 99%

confidence level and six at 95% confidence level. The strongest correlation was

between ‘Available skill levels’ and ‘Available finance’ and this may simply denote

that if sufficient finance is available skill levels can probably be acquired. Strong

correlations (in descending order of magnitude) were also noted between:

‘Professional and industry organisations’ and ‘Research organisations and

universities’; ‘Personal motivation’ and ‘Available time’; Personal motivation’ and

‘Insurance and risk’; ‘Personal motivation’ and ‘Available skills levels’; and

‘Available skills’ and ‘Insurance and risk’. The first two of these pairs relates to

external contacts which may verify or promote the innovation. The remaining three

pairs are all internal company matters relating to the firms resources. Although these

matters were given relatively low priority by the survey respondents, their high

positive correlations suggest that they ‘hang together’ in the minds of the survey

group. A certain level of interdependency is indicated. As previously mentioned, the

survey group is atypical among the construction SME population, because they have

largely solved their resource based problems, in order to successfully deliver their

technical innovations to the market.

The remaining six pairs of factors with significant correlation at the 95% confidence

level are:

• ‘Personal motivation’ and ‘Available time’;

• ‘Available time’ and ‘Available skills’;

• ‘Personal motivation’ and ‘Solving problems on site’ (negative correlation);

• ‘Available time’ and ‘Solving problems on site’ (negative correlation);

• ‘Improving OH&S’ and ‘Research organisations and universities’ (negative

correlation); and

• ‘Client characteristics’ and ‘Research organisations and universities’ (negative

correlation).

164

The first two pairs relate to the previously mentioned resource base of the SME. The

next two pairs relate a resource based matter to solving problems that occur on

building sites. This is an interesting negative correlation because it appeared to the

researcher that most of the survey respondents were very focussed on solving

practical problems. That their motivation and time allocation was negatively

correlated with ‘Solving problems on site’ indicates a possible trade-off between this

focus and the allocation of individual and company resources. The last two

negatively correlated pairs relate to ‘Research organisations and universities’. The

relationship suggests that when an innovation involves an OH&S problem, or when

clients are particularly demanding, independent verification form universities is

unlikely to be sought. Universities and other research organisations can provide

assistance in these matters, but it seems that the innovators in this sample were not

often availing themselves of this option.

6.10 Correlations for sample sub-groups

Pearson’s correlation coefficients were also calculated for each of the six sub-groups

in the sample: small businesses (10); medium businesses (11); product innovators

(13); process innovators (8); patent holders (14); and non-patent holders (7).

Remembering the caveat that these are small sample sizes, it may be that some

interesting insights can be gained from these statistics. The results for the factors are

presented in Tables 6.14 to 6.16. The results for the sub-factors follow in Tables 6.17

to 6.22.

165

Table 6.14 Correlations between factors for the small and medium business sub-groups

Small business response N = 10

Company resources


Project-based

conditions

Industry based

networks Regulatory

climate

Company resources 1


-0.156 1

Project-based conditions -0.264 0.360 1

Industry based networks 0.159 -0.512 -0.549 1

Regulatory climate -0.422 -0.609 -0.362 -0.027 1

Medium business response N = 11

Company resources


Project-based

conditions

Industry based

networks

Regulatory climate

Company resources 1


-0.045 1


Industry based networks -0.263 -0.210 -0.536 1

Regulatory climate -0.310 -0.504 -0.409 0.010 1

No correlation is significant at the 0.05 level (2-tailed).

No significant correlations were found between the factors for either small or medium

sized businesses. The nearest to a significant correlation was the small businesses’

ratings of ‘Project-based conditions’ compared to ‘Industry based networks’. It may

be that the small business innovators are particularly likely to focus their attention on

either on projects or on industry networks to a greater extent than medium-sized

businesses. A similar negative correlation was observed in the responses of product

innovators and this was statistically significant (Table 6.15 overleaf).

166

Table 6.15 Correlations between factors for the product and process innovator sub-groups

Product innovator response N = 13

Company

resources

Client and

end-user

influence

Project-

based

conditions

Industry

based

networks

Regulatory

climate

Company resources 1

Client and end-user

influence

-0.077 1



Regulatory climate -0.468 -0.566* -0.301 -0.099 1

Process innovator

response

N = 8

Company

resources

Client and

end-user

influence

Project-

based

conditions

Industry

based

networks

Regulatory

climate

Company resources 1

Client and end-user

influence

0.199 1

Project-based conditions -0.214 -0.030 1



* Correlation is significant at the 0.05 level (2-tailed).

There were no significant correlations between patent holder and non-patent holder

responses (Table 6.16 overleaf). Once again this serves to signal the individual nature

of the innovation delivery process because respondents were quite diverse in their

factor ratings whether or not they held patents on their innovation.

167

Table 6.16 Correlations between factors for patent holder and no patent sub-groups

Patent holder response N = 14 Company

resources

Client and

end-user

influence

Project-

based

conditions

Industry

based

networks

Regulatory

climate

Company resources 1

Client and end-user

influence

-0.105 1




Non-patent holder

response

N = 7

Company

resources

Client and

end-user

influence

Project-

based

conditions

Industry

based

networks

Regulatory

climate

Company resources 1

Client and end-user

influence

0.255 1



Regulatory climate -0.090 -0.696 -0.405 -0.143 1

No significant differences

Correlation calculations were completed for the six sub-groups in the sample on the

innovation sub-factors. Once again, some significant differences were found on a

relatively small number of sub-factors. Small business innovators returned significant

positive correlations for four pairs of factors:

• ‘Personal motivation’ and “Available time’;

• ‘Personal motivation and ‘Insurance and risk’;

• ‘Available finance’ and ‘Available skill levels’; and

• ‘Research organisations and universities’ and ‘Professional and Industry

associations’ (Table 6.17).

168

The strong correlation for the first three of these sub-factor pairs, however, is

tempered by the fact that these sub-factors were rated fairly low in the overall priority

list of sub-factors (see Figure 6.3). The remaining strong positive correlation is for

the external organisations which small businesses are likely to depend on for support

and guidance. It is therefore, unsurprising that these correlate highly. The only

strong negative correlation for small business respondents was between ‘Client

characteristics’ and ‘Research organisations and universities’. Remembering that

small businesses rated ‘Client characteristics’ much higher than did other groups, it

might be speculated that this is a result of small business high dependence on

individual clients to have their innovation accepted in the marketplace (see Figure

6.3).

Medium-sized business respondents returned significant correlations for ten separate

sub-factor pairs (Table 6.18). All significant correlations were positive. Eight

correlated pairs referred to sub-factors of the factor ‘Company resources’. This

indicates the close inter-relationships between these matters, which were, however,

given fairly low ratings overall. The two other sub-factor pairs with high positive

correlation are: ‘Professional and industry organisations’ and ‘Research organisations

and universities’; and ‘Solving problems on site’ and ‘Improving OH&S’. The first

of these indicates a strong preference by medium-sized business innovators for

multiple networks within the larger industry sector. The second indicates an

association in the innovators’ minds between site issues generally, and the specific

issue of site safety. This is a positive finding as it indicates that there is a growing

awareness among leading innovators in medium-sized businesses of the importance of

dealing thoroughly with safety matters on construction sites.

Product innovators returned positive correlations for eight sub-factor pairs and two

negative correlation pairs (Table 6.19). Seven of the positive correlations were within

the ‘Company resources’ area. As previously mentioned these were relatively lowly

rated overall (Figure 6.6). The remaining positive correlation was for ‘Professional

and industry organisations’ and ‘Research organisations and universities’. The two

negative correlations were between ‘Personal motivation’ and ‘Solving problems on

site’; and between ‘Client characteristics’ and ‘Research organisations and

universities’. This may be an indication of two streams within the product innovators:

169

those who focus on the outcome of their innovation; and those who are deeply

focussed on the innovation process itself.

Building process innovator responses showed six positive correlation pairs and one

negative (Table 6.20). They were the only sub-group to identify a high correlation

between ‘Procurement’ and ‘Supply chain relationships’. It is perhaps surprising that

other innovators did not rate these sub-factors higher, but it may be that the process

innovators dealt with more complex procurement and supply situations than did other

innovators. Process innovators were the only sub-group to display a high correlation

between ‘Insurance and risk’ and ‘Performance-based standards’. This may be due to the

complexity of the approvals process for a new building process. This may also explain

the negative correlation between ‘Procurement’ and ‘Industry standards’ as process

innovators may be seeking to change industry standards, and consequently may require

more flexible procurement options.

170

Table 6.17 Correlations between sub-factors for the small business sub-group


Small businesses sub-factor correlations

N = 10

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform


Industry standards


Personal motivation

1

Available finance

0.517 1

Available time

0.791** 0.259 1


0.602 0.916** 0.470 1

Insurance and risk

0.655* 0.217 0.369 0.164 1

Procurement

0.079 -0.211 -0.255 -0.347 0.628 1


-0.243 -0.443 0.112 -0.300 -0.060 -0.234 1


0.348 0.012 0.211 0.170 0.000 0.116 0.040 1


-0.513 -0.281 -0.493 -0.335 -0.283 -0.208 0.393 0.034 1

Improving OH&S

-0.386 -0.283 -0.256 -0.060 -0.151 -0.042 0.490 -0.028 0.160 1


-0.107 -0.295 -0.315 -0.370 0.258 0.462 -0.459 -0.248 0.151 -0.073 1


0.123 0.185 -0.065 0.036 0.278 0.399 -0.798** -0.367 -0.373 -0.404 0.727* 1


-0.233 -0.014 -0.237 -0.107 -0.473 -0.524 -0.182 -0.433 0.227 -0.195 0.031 -0.048 1

Industry standards

-0.604 -0.418 -0.337 -0.543 -0.452 -0.193 0.574 -0.196 0.274 0.042 -0.408 -0.460 0.127 1


-0.326 -0.105 -0.199 -0.230 -0.419 0.148 -0.194 0.147 -0.287 -0.332 -0.287 0.097 -0.147 0.457 1

171

Table 6.18 Correlations between sub-factors for the medium business sub-group


Medium businesses sub-factor correlations

N = 11

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform


Industry standards


Personal motivation

1

Available finance

0.727* 1

Available time

0.891** 0.678* 1


0.695* 0.585 0.616* 1

Insurance and risk

0.704* 0.494 0.630* 0.803** 1

Procurement

-0.124 -0.124 -0.010 -0.275 -0.159 1


0.002 0.173 -0.214 0.054 0.198 -0.014 1


-0.407 -0.479 -0.377 -0.423 -0.371 0.571 0.324 1


-0.524 -0.586 -0.497 -0.491 -0.572 0.206 0.256 0.532 1

Improving OH&S

0.082 -0.087 0.118 -0.151 -0.277 0.066 -0.095 0.004 0.640* 1


-0.440 -0.093 -0.332 -0.481 -0.237 -0.118 -0.137 0.017 -0.304 -0.499 1


-0.255 0.118 -0.170 -0.405 -0.334 -0.152 -.362 -0.247 -0.489 -0.487 0.851** 1


-0.279 -0.366 -0.322 0.315 0.166 -0.320 -0.082 -0.308 0.064 -0.200 -0.254 -0.263 1

Industry standards

-0.204 -0.103 -0.219 -0.077 -0.177 -0.387 0.094 0.041 -0.190 -0.329 0.161 0.246 0.075 1


-0.173 -0.229 -0.302 -0.070 -0.117 -0.343 0-.458 -0.353 -0.397 -0.508 0.390 0.558 0.402 0.065 1

172

Table 6.19 Correlations between sub-factors for the product innovator sub-group


Product innovator sub-factor correlations

N = 13

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform


Industry standards


Personal motivation

1

Available finance

0.493 1

Available time

0.931** 0.626* 1


0.665* 0.854** 0.714** 1

Insurance and risk

0.870** 0.234 0.745** 0.552 1

Procurement

0.029 -0.171 -0.123 -0.341 -0.028 1


-0.353 -0.401 -0.413 -0.275 -0.134 -0.150 1


-0.266 -0.247 -0.324 -0.112 -0.195 -0.165 0.136 1


-0.557* -0.408 -0.546 -0.456 -0.449 -0.185 0.540 0.362 1

Improving OH&S

-0.034 -0.291 0.021 -0.074 0.002 0.026 0.438 0.080 0.158 1


-0.125 -0.314 -0.190 -0.306 0.026 0.258 -0.354 0.054 0.077 -0.179 1


-0.197 .0134 -0.124 -0.176 -0.346 0.397 -0.654* -0.338 -0.275 -0.431 0.577* 1


-0.251 -0.018 -0.205 -0.085 -0.225 -0.470 -0.020 -0.308 0.185 -0262 -0.054 -0.001 1

Industry standards

-0.270 -0.294 -0.304 -0.296 -0.275 -0.326 0.326 0.200 0.032 -0.253 -0.205 -0.104 0.019 1


-0.279 -0.105 -0.258 -0.234 -0.251 0.183 -0.152 0.078 -0.227 -0323 -0.345 0.134 -0.107 0.248 1

173

Table 6.20 Correlations between sub-factors for the process innovator sub-group


Process innovator sub-factor correlations

N = 8

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform


Industry standards


Personal motivation

1

Available finance

0.909** 1

Available time

0.615 0.354 1


0.650 0.407 0.438 1

Insurance and risk

0.208 -0.060 -0.011 0.720* 1

Procurement

-0.226 -0.179 -0.128 -0.312 -0.314 1


0.278 0.011 0.591 0.009 0.072 -0.028 1


-0.149 -0.084 -0.070 -0.368 -0.377 0.938** 0.102 1


-0.373 -0.241 -0.563 -0.251 -0.156 0.293 -0.108 0.262 1

Improving OH&S

-0.117 0.030 -0.244 -.0157 -0.365 0.001 -0.098 -0.083 0.801* 1


-0.393 -0.118 -0.377 -0.628 -0.459 -0.075 -0.480 -0.046 -0.351 -0.307 1


-0.012 0.164 0.004 -0.335 -0.331 -0.243 -0.313 -0.208 -0.698 -0.493 0.894** 1


-0.307 -0.473 -0.288 0.450 0.760* -0.329 -0.238 -0.376 0.107 -0.171 -0.246 -0.337 1

Industry standards

-0.433 -0.482 -0.192 -0.203 0.189 -0.727* 0.116 -0.667 -0.074 -0.049 0.264 0.188 0.458 1


-0.189 -0.214 -0.237 0.046 0.440 -0.434 -0.312 -0.511 -0.596 -0.622 0.557 0.628 0.392 0.500 1

174

Table 6.21 Correlations between sub-factors for the patent holder sub-group


Patent holder sub-factor correlations

N = 14

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform


Industry standards


Personal motivation

1

Available finance

0.439 1

Available time

0.781** 0.311 1


0.655* 0.868** 0.564* 1

Insurance and risk

0.719** 0.109 0.411 0.269 1

Procurement

0.071 -0.131 -0.191 -0.286 0.125 1


-0.366 -0.457 -0.028 -0.364 -0.198 -0.229 1


-0.112 -0.185 -0.061 -0.023 -0.180 -0.119 0.089 1


-0.499 -0.336 -0.537* -0.365 -0.314 -0.259 0.376 0.316 1

Improving OH&S

0.220 -0.105 0.038 0.213 0.172 -0.044 0.088 0.007 0.094 1


-0.331 -0.323 -0.406 -0.486 -0.022 0.338 -0.296 0.033 0.202 -0.252 1


-0.224 0.167 -0.188 -0.143 -0.236 0.418 -0.521 -0.372 -0.302 -0.496 0.643* 1


-0.368 -0.051 -0.319 -0.211 -0.336 -0.463 -0.034 -0.251 0.231 -0.341 0.089 0.101 1

Industry standards

-0.586* -0.422 -0.404 -0.570* -0.331 -0.174 0.639* -0.082 0.272 -0.213 -0.256 -0.230 0.241 1


-0.293 -0.104 -0.217 -0.241 -0.224 0.154 -0.096 0.049 -0.255 -0.345 -0.247 0.146 -0.066 0.490 1

175

Table 6.22 Correlations between sub-factors for the non-patent holder sub-group


Non-patent holder sub-factor correlations

N = 7

Personal

motivation

Available

finance

Available tim

e

Available skill

levels

Insurance and risk

Procurem

ent

Client

characteristics

Supply chain

relationships

Solving

problems on

site

Improving

OH

&S

Professional

& industry

organisations

Research

organisations &

universities

Perform


Industry standards


Personal motivation

1

Available finance

0.925** 1

Available time

0.786* 0.886** 1


0.657 0.577 0.782* 1

Insurance and risk

0.699 0.665 0.819* 0.966** 1

Procurement

-0.349 -0.322 -0.321 -0.349 -0.223 1


0.722 0.657 0.470 0.364 0.405 0.064 1


-0.312 -0.258 -0.261 -0.440 -0.362 0.917** 0.180 1


-0.482 -0.564 -0.715 -0.488 -0.509 0.344 0.155 0.337 1

Improving OH&S

-0.391 -0.353 -0.555 -0.461 -0.444 0.061 0.126 0.049 0.883** 1


-0.087 0.160 0.143 -0.278 -0.171 -0.135 -0.534 -0.144 -0.617 -0.358 1


-0.047 0.107 0.067 -0.326 -0.286 -0.259 -0.542 -0.196 -0.639 -0.457 0.932** 1


-0.092 -0.317 -0.056 0.542 0.385 -0.324 -0.241 -0.484 0.034 -0.095 -0.492 -0.425 1

Industry standards

-0.010 0.077 0.275 0.020 -0.146 -0.383 -0.026 -0.029 -0.282 -0.267 0.095 0.256 -0.065 1


-0.049 -0.189 -0.165 -0.012 -0.066 -0.356 -0.646 -0.480 -0.489 -0.512 0.440 0.616 0.327 -0.085 1

176

The patent holder sub-group displayed seven positive correlation sub-factor pairs and

three negative pairs (Table 6.21). In addition to those pairs already discussed, patent

holders positively correlated ‘Client characteristics’ and ‘Industry standards’. This is

hard to explain, other than to state that ‘Industry standards’ are perhaps partly

determined by what the client is willing to pay for. There were two negative

correlations with ‘Industry standards’: these being ‘Personal motivation’ and

‘Available skill levels’. The remaining negative correlation was between ‘Available

time’ and ‘Solving problems that occur on site’. This probably reflects the underlying

industry issue of tight project scheduling leaving relatively little contingency time for

problem solving.

Lastly, among the non-patent holders there were nine significant positive correlation

pairs and no negative ones (Table 6.22). These results differed from the patent holder

results in that non-patent holders closely correlated ‘Procurement’ and ‘Supply chain

relationships’ as well as ‘Solving problems on site’ and ‘Improving OH&S’. It may

be that the non-patent holder innovators were, like the process innovators, involved in

more complex construction project types.

6.11 Regression analysis

Regression analysis was undertaken to establish if any linear relationship exists

between the variables in the survey factors and sub-factors. Regression analysis was

performed for all possible pairs of factors as well as for all possible pairs of sub-

factors in the sample for a total of 115 individual tests. The results of this analysis are

presented in Tables 6.23 and 6.24. Only three pairs, where R² value was greater than

0.5, were found. The positive results were for the following sub-factor pairs;

‘Personal motivation’ versus ‘Available time’; ‘Available finance’ versus ‘Available

skill levels’; and ‘Professional and industry associations’ versus ‘Research

organisations and universities’. Scatter plots for these results are displayed in Figures

6.9, 6.10 and 6.11 (pp.179-180). These illustrate the strength of the relationship by

the steepness of gradient of the ‘line of best fit’ R² value.

177

Table 6.23 Regression values for factor pairs

Regression for factor pairs (R²)

Company resources



Industry networks

Regulatory climate

Company resources

1.000


0.000 1.000


0.047 0.008 1.000

Industry networks

0.007 0.147 0.246 1.000

Regulatory climate

0.140 0.287 0.161 0.000 1.000

No significant values

178

Table 6.24 Regression values for sub-factor pairs

Regression R² for sub-factor pairs

Personal

motivation

Available finance

Available tim

e

Available

skill levels

Insurance and risk

Procurem

ent system

s

Client

characteristics

Supply chain

relationships

Solving

problems

that occur on site

Improving

OH

&S

Professional

and industry associations

Research

organisations and

universities

Perform

ance-based

standards

Industry standards

Local authority

regulations

Personal motivation

1

Available finance

0.2555 1

Available time 0.519* 0.136 1


0.4128 0.5786* 0.2512 1

Insurance and risk

0.4379 0.0472 0.104 0.3143 1

Procurement systems

0.0058 0.0225 0.0155 0.0958 0.0079 1

Client- characteristics

0.0368 0.0662 0.0041 0.036 0.0029 0.0074 1


0.025 0.0426 0.0121 0.0348 0.0567 0.1656 0.006 1


0.2413 0.1334 0.2346 0.1638 0.1471 0.1656 0.1068 0.0955 1

Improving OH&S

0.0002 0.0302 0.0058 0.0078 0.0188 0.00002 0.0048 0.0016 0.1618 1

Professional and industry associations

0.0628 0.0454 0.1024 0.1588 0.0036 0.0072 0.1298 0.0005 0.0062 0.0787 1


0.0261 0.0231 0.0076 0.049 0.076 0.004 0.2055 0.0886 0.1717 0.23 0.5427* 1


0.0717 0.016 0.0636 0.0096 0.0008 0.1544 0.0104 0.1179 0.0227 0.0421 0.0198 0.0246 1

Industry standards

0.1078 0.062 0.0655 0.0719 0.0332 0.0994 0.0972 0.0006 0.0004 0.0482 0.0027 0.00008 0.0092 1


0.063 0.0139 0.0419 0.0319 0.0244 0.0005 0.033 0.0094 0.0923 0.1301 0.0041 0.0703 0.0021 0.0669 1

*Significant R² values

179

Figure 6.9 Scatter plot and linear trend line for ‘Personal motivation’ versus ‘Available time’

Figure 6.10 Scatter plot and linear trend line for ‘Available skill levels’ versus ‘Available finance’

180

Figure 6.11 Scatter plot and linear trend line for ‘Professional and industry associations’ versus ‘Research organisations and universities’

That these particular three pairs of sub-factors should demonstrate a relationship is an

interesting finding. ‘Personal motivation’ and ‘Available time’ are both matters

centred on the individual innovator. The more that personal motivation is regarded as

important, the more likely it is that finding sufficient time to devote to the potential

innovation will also be important. These sub-factors were not prioritised at the first

level (Table 6.2), but their close relationship does signal the importance of the

individual leader in the process of technical innovation delivery by an SME.

‘Available finance’ and ‘Available skill levels’ are both strongly in a company’s

resource capacity. The necessary skills can often be acquired, if appropriate financial

resources are available to do so. The greater the financial resources that are available,

the more high quality skills can be assigned to the innovation delivery process.

Finally, ‘Professional and industry associations’ and ‘Research organisations and

universities’ are both networking factors fully external to the innovating company.

The positive relationship indicates that those innovators who value contacts with one

group are likely to value association with the other. Both these sub-factors were

given first level priority in the survey sample (Table 6.2).

181

The inter-relationships between the survey factors and sub-factors could be

investigated more fully with a larger sample of construction SMEs with more varied

experience in innovation delivery and innovation diffusion.

6.12 Summary of statistical results

The statistical analysis of the survey data has provided some insight into factors that

affect technical innovation delivery by construction SMEs. It does not, however,

provide a template for undertaking such innovation processes. There is much

variation among the survey responses. This indicates that the individual nature of

each innovation delivery should be emphasised, ahead of any commonalities.

Furthermore, the differences found between the identified sub-groups were less than

anticipated. This is especially true of small and medium-sized company sub-groups

in the sample. Much existing literature on small businesses in construction stresses

the importance of internal resources to the small firm (Abbott et al. 2006; Sexton and

Barrett 2003a; Sexton and Barrett 2003b; Sexton and Barrett 2004; Sexton et al.

2006; Manley 2008). The survey sample did not support this belief. This particular

sample of construction SMEs were not typical of other companies in the sector. The

characteristic which qualified them for the sample, having delivered a recognised

successful technical innovation, made them necessarily atypical. High-level technical

innovators may represent a distinct group among construction companies. The

experience of having successfully delivered a high-level technical innovation was

seen in the survey sample to largely outweigh expected differences in terms of

company size, innovation type and patent holdings.

In order to learn more about the technical innovation delivery process, further

investigation of the individual experience is required. Qualitative data collection is,

therefore, an appropriate avenue to pursue.

6.13 Survey respondents open-ended comments

At the completion of the survey the innovators were asked if they had any comments

to add on the basis of their experience with technical innovation delivery. Care was

182

taken to avoid interview bias by allowing the survey respondents to take the lead with

their open-ended responses (Kvale 1996). These open-ended responses have been

sorted into three broad categories: economic, relational and structural issues. Tables

6.25, 6.26 and 6.27 (pp.183-186) illustrate the number and type of interviewees who

made comments under each category.

The innovators who raised economic issues mostly stressed that economic reform was

needed if industry performance was to be improved. The importance of the larger

economy to SMEs was mentioned by three innovators. It was also pointed out that

the current state of the national and the global economy can impact on the importance

rating for each of the factors in the survey. The Global Financial Crisis was reported

to have had a strong effect on supply chains in construction by those medium-sized

businesses who worked on international projects:

“Last year we had difficulty getting what we wanted from our

suppliers but the downturn overseas has made things easier”

(R4_M.Proc.NoPat).

The effectiveness of Australian government stimulus packages was commented upon

favourably by two innovators:

“The Building Education Revolution (BER) program is very

good for us because school communities are keen to have more

sustainable building practices” (R18_S.Prod.Pat).

Other innovators raised the issue of “off balance sheet assets” such as intellectual

property, business processes, reputation and market understanding. These form a

large part of the innovator’s investment in an SME

Lack of recognition of this situation results in difficulties for those seeking to generate

and deliver innovation. This is supported by the wider management literature (Keen

1997). It was reported as particularly true in the early stages of innovation delivery.

183

Table 6.25 Common economic themes in the open-ended comments by survey respondents

Comment Survey respondents who raised this

matter (Descriptive codes explained in

Table 5.4)

State of the economy R4_M.Proc.NoPat; R8_M.Proc.Pat;

R5_S.Proc.NoPat;

Finance in the planning stages R1_M.Prod.Pat; R10_S.Prod.Pat; R16_M.Prod.Pat;

R2_S.Prod.Pat; R12_S.Prod.Pat; R20_S.Prod.Pat;

Government stimulus packages R16_M.Prod.Pat; R18_S.Prod.Pat;

Cost of patents R11_S.Prod.Pat; R13_S.Prod.Pat;

R12_S.Prod.Pat;

Industry unwilling to pay for IP R5_S.Proc.NoPat;

Market knowledge R3_M.Prod.NoPat; R14_M.Proc.NoPat;

R11_S.Prod.Pat; R19_M.Proc.NoPat;

Proven performance R1_M.Prod.Pat; R6_M.Proc.NoPat;

R2_S.Prod.Pat; R9_M.Prod.Pat;

The cost of acquiring and defending patents was raised by three innovators. Although

patents are expensive to acquire and to defend, banks and other lenders do not usually

recognise a patent as an asset. A business, particularly a small business, often cannot

find finance as a result of holding a potentially profitable patent even if they have a

viable business plan. . As one small business innovator put it:

“It is very difficult to fund a technical innovation because the

banks do not regard a patent as an asset. You have to have

established cash flow before you can borrow to develop a

product” (R11_S.Prod.Pat).

The cost of patent litigation is a widespread problem internationally, especially in the

United States, where it has the potential to force some smaller businesses out of

research on product development (Lerner 1999). In addition, one innovator reported

that:

184

“The Australian construction industry is largely unwilling to pay

for the use of intellectual property. They understand the need to

pay for the products of innovation, but not for the know-how

involved in problem solving” (R5.S.Proc.NoPat).

Four innovators declared that a thorough knowledge of the market being serviced is

essential for any successful innovation delivery process. A further four reported that

in the end, it is proven performance in comparison to existing practice, which allows

an innovation to become accepted in the construction market. These unprompted

comments indicate the importance placed on business management skills by the

successful innovators.

Table 6.26 Common relationship themes in the open-ended comments by survey respondents



Table 5.4)

Disputes with industry organisations

R1_M.Prod.Pat; R18_S.Prod.Pat;

R16_M.Prod.Pat;

Competitor sourced misinformation

R1_M.Prod.Pat; R15_M.Proc.NoPat;

R2_S.Prod.Pat;

In house training R1_M.Prod.Pat; R3_M.Prod.NoPat;

Shifting the risk R4_M.Proc.NoPat;

End-user misunderstanding R2_S.Prod.Pat;

Community involvement R9_M.Prod.Pat; R17_S.Prod.Pat;

R14_M.Proc.NoPat;

Professional association’s lobbying power

R1_M.Prod.Pat; R6_M.Proc.NoPat; R17_S.Prod.Pat;

R2_S.Prod.Pat; R9_M.Prod.Pat; R21_M.Proc.NoPat;

The innovators who raised relationship issues talked about the need for more

cooperation within the industry and the need to reduce time wasted in intra-industry

185

disputation. Three reported that some industry organisations resist innovation as it

can be seen as a threat to their area of expertise. Three innovators gave examples of

misinformation put out by established competitors. This can severely restrict those

innovators trying to acquire a share of the market.

Two innovators reported their positive experience with staff training. They found that

training staff ‘in-house’ in the use of an innovative product or process had been more

effective than relying on traditional trade training which is sometimes inflexible. One

innovator reported that large companies often try to shift risk downwards to smaller

businesses through sub contract arrangements. This is widely supported in the

academic literature (Hinze 1994; Langford et al. 2000; Loosemore 1999; Zaghloul

and Hartman 2003).

One innovator reported difficulty with end-user misunderstanding of product

operation. Lack of technical expertise may lead potential clients to avoid an

innovative product because of inability to judge the long term benefits of a ‘new to

market’ innovation. Three innovators explained how involvement in their local

community encourages positive public perceptions of innovative companies:

“The local council and the people in this area are very

supportive of local businesses” (R9_M.Prod.Pat).

This is a useful strategy for potential innovators to follow. A total of six innovators

stated that industry and professional organisations are particularly useful to them as

lobbyists on government legislation and Australian Standards. Such organisations can

also play a useful role as monitors of changes in the regulatory environment for

SMEs. Small businesses, in particular, rely on industry associations to represent their

interests with government and provide feedback to the members on potential

government policy changes. Unlike large businesses, they are usually not able to deal

with these matters directly because of limited influence on the national stage.

186

Table 6.27 Common structural themes in the open-ended comments by survey respondents



Table 5.4)

The significance of various factors changes over the course of innovation delivery

R3_M.Prod.NoPat; R15_M.Proc.NoPat; R16_M.Prod.Pat;

R7_S.Proc.Pat; R18_S.Prod.Pat;

Independent performance testing R1_M.Prod.Pat; R17_S.Prod.Pat;

R2_S.Prod.Pat;

International verification R7_S.Proc.Pat;

Environmental issues drive innovation

R2_S.Prod.Pat; R11_S.Prod.Pat; R17_S.Prod.Pat; R19_M.Proc.NoPat;

R6_M.Proc.NoPat; R14_M.Proc.NoPat; R18_S.Prod.Pat; R21_M.Proc.NoPat;

Circuit breakers to ‘business as usual’

R2_S.Prod.Pat; R16_M.Prod.Pat;

R12_S.Prod.Pat;

Those innovators who raised structural issues mostly said that processes needed

streamlining in order to assist delivery of new ideas. They pointed out that the needs

of SME innovators vary according to the stage of innovation delivery. A great deal of

assistance from government and research organisations would be useful in the early

stages of innovation delivery. This tends to be the time however, when assistance is

largely unutilised because the effort and compliance paperwork involved in qualifying

for assistance deters small businesses.

Independent performance verification and testing can be an expensive investment, but

it is often essential to the delivery of a new construction product or process. Three

innovators pointed out that relationships with research bodies and universities could

be improved in this area. One innovator related the situation where, in attempting to

deliver a technical innovation internationally, the process of proving the value of the

innovation must begin again ‘from scratch’ in each jurisdiction. Internationally

recognised verification standards would assist with this matter.

187

Six innovators said that environmental issues are currently the main drivers of

construction innovation:

“There are a lot of good intentions out there. Environmentally

friendly products have a ready-made market if it’s done

properly” (R14_M.Proc.NoPat).

This is power of environmental issues to drive innovation is supported in the

academic literature by Bossink (2004a). Two innovators reported that they believed

this to be an accelerating trend.

Finally, three innovators reported on the widespread need for ‘circuit breakers’, in

order to persuade industry to move away from ‘business as usual’ as a mode of

operation. External events such as accidents, natural disasters, recessions and credit

droughts have the potential to create the impetus for innovative construction products

and processes. Sometimes SMEs are best placed to meet these challenges.

The issues raised in the open-ended comments have the potential to shed much light

on the way technical innovations are delivered in the construction industry. As many

of the issues raised are subjective and case-related, it is necessary to explore the

matter of construction innovation delivery through qualitative as well as quantitative

methods.

6.14 Limitations of the data derived from the AHP study

There are always pitfalls when future predictions are made from empirical research

that is very much situated in the present day. As referred to in Chapter 1 of this

thesis, the seminal work of Marian Bowley in the 1960s did much to elucidate the

construction industry’s dilemma in the delivery of a more efficient built product

(Bowley 1960, 1966). The work represented a pioneering contribution to the study of

construction innovation. However, one of technologies lauded by Bowley in her 1960

book “Innovations in building materials: An economic study” was asbestos cement

sheeting for housing construction. With the perspective of the current day and our

knowledge of the mortality, disease and distress caused by this product when it is

disturbed by construction processes, a different evaluation must be made. There is no

188

intention here to deride Bowley’s work as the damage done by asbestos was not

known at the time and the evaluation done at the time was correct according to the

existing state of knowledge about asbestos fibre. The example is simply raised as an

illustration of the perils of making predictions based on any data that is necessarily

limited and subject to change. In a sense, all knowledge includes this unknown factor

but it is particularly true when the research question involves the impact of human

beings and their actions in the environment.

As reported in Chapter 4 of this thesis, Analytic Hierarchy Process is a methodology

that has been applied in many fields to address many complex and divergent decision

making processes. The value of the methodology chiefly resides in the fact that it can

deal with problems that require the evaluation of non commensurate criteria or

quantities. It is therefore a suitable method to use for a survey addressing the

question of the factors that have most influence on the successful delivery of technical

innovation by construction SMEs. Useful insights have been generated through

reflective analysis of the data collected by the survey. It was not, however, the

intention of this researcher to produce a statistically validated rating system for

predicting those factors that have the most effect on potential technical innovator

performance. The sample size is much too small for this and the individual instances

of technical innovation delivery far too diverse. Rather, the intention of the survey

was exploratory. It was intended to shine a light on any commonalities of attitude or

of strategy that could be deduced from the survey respondents’ answers. Such

commonalities, as well as any divergences, are capable of revealing insights into the

process of technical innovation delivery and of indicating possible useful strategies

for potential innovators. However, it is not possible from this kind of research to

draw broad generalisations about the innovation process which can be expected to

have universal application. The survey reports on aggregated attitudes from a group

of successful innovators in a particular place and at a particular time. It would be

inappropriate to claim it represents more than a useful perspective on the research

question as opposed to an empirically validated answer to it. This does not invalidate

the survey, or the priorities derived from it, but it serves to temper its ability to be broadly

generalised. It has been pointed out that:

189

“Being consistent is often thought of as a prerequisite to clear

thinking. However, the real world is hardly ever perfectly consistent

and we can learn new things only by allowing for some inconsistency

with what we already know” (Forman and Selly 2001 p.46).

Furthermore, there are other issues with the use of the AHP data set to assess or

predict the likelihood of innovation success in SMEs generally. Keeney (1996) points

out the importance of a consideration of values in the decision making process. If a

problem is reduced to a choice between predetermined alternatives, other possible

approaches are necessarily excluded. This represents a freely acknowledged

limitation to this study. There is a human factor in the operation of construction

projects which cannot be validly ignored. This was clearly brought home to the

researcher when it was noticed that a particular survey respondent had rated ‘personal

motivation’ very lowly in his list of comparative weightings. This seemed to be an

anomaly as the survey respondent appeared to the researcher to be someone who was

characterised by a very high level of personal motivation and enthusiasm for his

innovation. When queried on this matter, the respondent replied that he was “always

motivated and therefore it was not of any significance in the delivery of his

innovation” (R1_M.Prod.Pat). The logical inconsistency which some may see in this

answer can be regarded as symptomatic of the effect of the human element in the

survey response. Self efficacy, or the belief in one’s own ability to perform a task, is

likely to be very strong in those who undertake entrepreneurial activity to deliver an

innovation (Shane 2003).As the previously mentioned example illustrates, however, the

individual may not be in a position to objectively judge his or her own level of self

efficacy or motivation.

6.14.1 Inconsistency factor in AHP

The question of inconsistency is specifically addressed in the formulation of the AHP

methodology (Saaty 1980, 1994). Inconsistency arises when a decision maker ranks

criteria in a self contradictory manner. In the most severe case, this would mean X is

more important than Y, Y is more important than Z, but Z is more important than X.

More commonly, inconsistency arises from the weighting or amount by which one

criterion is said to be preferred over another. AHP methodology assumes that such

inconsistencies are likely to occur and provides a measure of the level of such

inconsistency using the consistency ratio. Table 6.28 shows the inconsistency factors

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for each of the 21 survey respondents randomly sorted so that individuals cannot be

identified (Equation given in Chapter 5, p.115).

Depending on the intended aim of the decision making process, different levels of

inconsistency may be acceptable. Particularly when the aim is to explore a process

using multiple respondents, a relatively high level of inconsistency is to be expected

and does not nullify the results of the priority rating. Relatively high inconsistency,

however, does suggest the need for finer grained, qualitative research into the reasons

behind the inconsistencies.

Table 6.28 Inconsistency factors

Respondent Respondent Respondent

A 0.13 H 0.57 O 0.25

B 0.17 I 0.30 P 0.42

C 0.07 J 0.46 Q 0.11

D 0.26 K 0.26 R 0.42

E 0.17 L 0.21 S 0.10

F 0.40 M 0.12 T 0.11

G 0.20 N 0.33 U 0.23

Average inconsistency factor – 0.28

Saaty (2003) specifically states that an inconsistency factor of greater than 0.1 for the

data set leaves the result open to question. He is, however, referring to the situation

where an individual decision maker has used the process to determine a specific

course of action or where some empirical conclusion is to be drawn from a data set of

several decision makers. This is not the case in the study undertaken for this thesis.

Newell and Seabrook (2006) reported that a consistency ratio of less than 0.2 is

considered acceptable in AHP studies, such as those used to compile an index of

specific priority ratings in fields such as property investment (Newell and Seabrook

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2006 p.286). Forman and Selly (2001) note that higher than usual standard levels of

inconsistency may be tolerated in some circumstances, particularly when the data

gathering intention is descriptive rather than definitive. This thesis does not propose

to produce a specific priority guideline on the factors which affect technical

innovation in construction. The priorities detected here are simply indicators of the

directions that a specific number of successful innovators have followed. As such, the

descriptive intent allows for a more flexible approach to inconsistency in the data.

Ozdemir and Saaty (2006) have gone so far as to suggest that this matter of

inconsistency can be addressed by including an additional criterion labelled ‘the

unknown’ in the value tree. The unknown would then be ranked against the other

criteria in the standard way with all Analytic Hierarchy Process studies. This is

proposed as a technique for avoiding inconsistencies. The technique is not adopted

here as it was considered likely to antagonise some respondents and lead to

incomplete survey responses.

Doloi (2008) in his AHP study on improving construction productivity states that an

appropriate test for consistency when using AHP with survey data is that “75% of the

data set must lie within the range of average ±2 standard deviations” (Doloi 2008

p.845). This condition can be met by the data set for this thesis, as is demonstrated by

Tables 6.29, 6.30, 6.31, 6.32, 6.33, 6.34, 6.35 and 6.36 (commencing overleaf p.191).

Confidence intervals were also calculated for the whole sample and the three sub-

group pairs. F tests were performed in Excel spreadsheets for each of the sub-group

pairs and no significant differences were found compared with critical F test values

from tables (Black et al. 2009). While the standard deviations of the survey responses

can be characterised as relatively high, indicating that the survey group is diverse in

its attitude to the factors and sub-factors, there is no statistically significant difference

in the sum of squares calculations for any of the three identified sub-group pairs in the

sample. Consequently, it can be argued that the inconsistency levels of the responses

are unlikely to have skewed the results in any particular direction. As previously

mentioned, Ganzac (1994) found that internally inconsistent results may still give

good approximations of real or ‗true‘ values (Ganzac 1994 p.193). For this reason,

the decision was taken that those responses which exhibited higher levels of

inconsistency would be retained in the sample, given that a descriptive and

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exploratory approach was taken to the research topic of the factors affecting technical

innovation delivery by construction SMEs.

Table 6.29 Standard Deviation of AHP factor weightings

Factor Standard Deviation

for 21 survey

responses

Company resources 11.658 %

Client and end user influences 14.1139 %

Project based conditions 15.9688 %

Industry networks 16.2019 %

Regulatory climate 18.751 %

As Table 6.29 (above) shows, the confidence intervals are somewhat similar for all

factors with only ‘Regulatory climate’ showing a larger disparity of response than the

other factors. For the sub-factors (Table 6.30 overleaf) only two items have significantly

larger confidence intervals than the others. These are ‘Performance-based standards’ and

‘Improving OH&S’. Qualitative research investigations may be able to shed further light

on these issues.

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Table 6.30 Standard Deviation of AHP subfactor weightings

Sub Factor Standard Deviation

for 21 survey

responses

Personal motivation 6.1688 %

Available finance 3.8368 %

Available time 4.0911 %

Available skill levels 5.2679 %

Insurance and risk 3 0746 %

Procurement systems 5.3252 %

Client's characteristics 9.7552 %

Supply chain relationships 6.7816 %

Solving problems that occur on site 4.0054 %

Improving OH&S 12.1778 %

Professional and industry associations 8.8375 %

Research organisations and universities 0.092128

Performance based standards 11.9688 %

Industry standards 4.4076 %

Local authority regulations 8.5780 %

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Table 6.31 Standard Deviation of AHP factor weightings for small and medium sized businesses

Factor Standard deviation for small businesses

Confidence interval for 95% confidence level

Standard deviation for small businesses


Company resources 11.51 7.14 12.32 7.28

Client and end-user

influences

16.11 9.99 11.29 6.67

Project-based conditions 11.46 7.10 18.57 10.97

Industry networks 13.24 8.21 16.25 9.60

Regulatory climate 19.21 11.91 18.48 10.92

F tests revealed no significant difference in variability between the two groups for each factor at 5% level (Black et al. 2009).

Confidence intervals are naturally larger when the sub-groups are considered because of

the smaller sample size but no significant difference in variability between the sub-groups

of small and medium sized enterprises was found.

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Table 6.32 Standard Deviation of AHP sub-factor weightings for small and medium sized businesses

Sub-factor SD small businesses


SD for medium sized businesses


Personal motivation 4.98 3.09 6.92 4.09

Available finance 5.01 3.11 2.55 1.51

Available time 5.14 3.19 3.06 1.81

Available skill levels 5.64 3.49 5.18 3.06

Insurance and risk 0.75 0.47 3.99 2.36

Procurement systems 5.70 3.53 6.99 4.13

Client characteristics 12.09 7.49 6.04 3.57

Supply chain relationships 4.56 2.83 8.27 4.89


4.57 2.83 3.69 2.18

Improving OH&S 8.71 5.40 14.52 8.58


8.23 5.10 9.29 5.49


7.98 4.94 10.30 6.09


12.48 7.74 12.46 7.37

Industry standards 3.69 2.29 5.23 3.09


11.51 7.14 5.27 3.12


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Table 6.33 Standard Deviation of AHP factor weightings for product and process innovators

Factor Standard deviation for product innovators


Standard deviation for process innovators



Client and end-user

influences

12.98 7.06 16.62 11.52

Project-based

conditions

11.60 6.31 20.29 14.06




As for the small and medium sized company sub-groups, confidence intervals are

naturally larger when the sub-groups are considered because of the smaller sample

size, but no significant difference in variability between the sub-groups of building

product and building process innovators was found.

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Table 6.34 Standard Deviation of AHP sub-factor weightings for product and process innovators

Sub-factor Standard deviation for product innovators


Standard deviation for process innovators




Available time 2.76 1.50 5.64 3.91






6.05 3.29 7.82 5.42


4.43 2.41 3.55 2.46

Improving OH&S 8.20 4.46 16.49 11.42


8.05 4.38 10.24 7.09


8.39 4.56 10.59 7.34


11.22 6.10 14.56 10.09



10.17 5.53 5.96 4.13


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Table 6.35 Standard deviation of AHP factor weightings for patent holders and non-patent holders

Factor Standard deviation for patent holders


Standard deviation for non-patent holders



Client and end-user

influences

14.52 7.60 14.06 10.41

Project-based

conditions

14.45 7.57 19.74 14.62




Once again, confidence intervals are naturally larger when the sub-groups are

considered compared with the whole sample, because of the smaller sample size.

Nevertheless, no significant difference in variability between the sub-groups of patent

holders and non-patent holders was found. Non-patent holders being the smallest

sub-group in the sample, exhibit the largest variability in their response and, therefore,

the largest confidence intervals.

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Table 6.36 Standard Deviation of AHP factor weightings for patent holders and non patent holders

Sub-factor Standard Deviation for patent holders


Standard Deviation for non-patent holders




Available time 2.05 1.08 1.38 1.02






7.43 3.89 8.32 6.16


4.97 2.61 3.96 2.94

Improving OH&S 9.55 5.00 16.59 12.29


9.20 4.82 9.85 7.30


9.68 5.07 11.63 8.62


7.60 3.98 15.31 11.34



1.26 0.66 6.33 4.69


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In addition, as previously stated in the case of this thesis, no strictly numerical

conclusions are to be drawn and no rating scheme is to be established. The data was

collected for the purposes of elucidating a process about which not a great deal is

known. Consequently inconsistency can be tolerated, particularly as the survey data

collection will be accompanied by qualitative exploration to determine some of the

reasons behind the inconsistencies.

6.14.2 Some possible reasons for inconsistency in the survey results

Forman and Selly (2001) identify clerical error as a common cause of inconsistency in

AHP survey responses. Particularly, they have noted that reversing the intended

preference for a pair of factors has been observed as a relatively common mistake to

make (Forman and Selly 2001, p.47). The researcher observed that some of the

respondents corrected themselves while entering their responses for the survey. They

were focussing on the numerical weighting of a particular factor, and almost ticked

the wrong side of the seventeen point scale compared to their verbal response. There

may have been cases that were not picked up. The researcher was, however, aware of

this tendency and when possible, asked for clarification if an answer appeared

ambiguous or contradictory to that which had been previously stated. In addition,

when the survey respondent opted to fill out the survey on paper rather than through

the laptop computer, the researcher entered the spoken responses on another copy of

the survey at the same time as the respondent. This picked up some potential clerical

errors and these were amended on the spot.

Another explanation for inconsistency in the survey results was raised in an

unprompted manner by nine of the twenty-one respondents during the face-to-face

survey interviews. It can be summarised as the matter of the temporal nature of the

factor ‗importance‘. A common comment was that the importance of the factors

varies over time, and in accordance with where you are in the innovation delivery

cycle. In an example frequently cited by the survey respondents, during the early

stages of development and testing, company resources are often critical, but they tend

to become less so as the innovation achieves market acceptance. The survey

respondents had all passed through this early stage and had achieved the delivery of

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their innovations to the market at the time of the survey. The respondents were

specifically asked to give their current ratings for the factors, not their importance at a

time in the past. Psychologically, this is hard to do for a complex process and

individuals may tend to remember somewhat erratically particular incidents in the

past when they answer some weighting questions and revert to the present day with

regard to other weightings. Inconsistency of weighting therefore results.

A difference of interpretation between the researcher‘s and the respondent‘s

understanding of the terminology used may be another possible explanation for

inconsistencies in the factor weightings. As some of the terms relate to complex

concepts, it may simply be that the respondent was thinking of different aspects of the

term at different times during the survey. Certainly, the survey prompted virtually all

the respondents to recount specific instances of the effect of a nominated factor on

their innovation process. They did this by way of explanation of their answer to the

survey question. The researcher noted down these comments at the time. On

reflection, the recounting of anecdotes during the survey could well result in

inconsistency of weighting because the flow of thought process is interrupted. As the

intention of the survey was to record the successful innovator‘s experience, it is

considered that it was useful to allow these interruptions to occur and to record their

nature for use in the selected case studies which form the basis of Chapter 7 of this

thesis.

The Analytic Hierarchy Process as represented in Expert Choice™ software does signal

inconsistencies in the data in real time and thereby allows the decision maker to address

any such inconsistencies. An individual decision maker can decide whether or not they

wish to change their weighting to avoid inconsistency. This would be particularly

appropriate when the process is undertaken in order to select an appropriate course of

action. In the case of this survey, however, the researcher opted to simply collect the raw

data in terms of weightings from the respondents without giving them the option to

address any inconsistencies.

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CHAPTER 7 SELECTED CASE STUDY EXEMPLARS OF INNOVATION DELIVERY

Chapter 7 reports the storyline of seven representative exemplars of successful

technical innovation delivery by SME construction contractors. The case studies

have been chosen because they are elucidatory of both the development process and

the actual realisation and delivery of a technical innovation in construction. They are

all high-level innovations which can be classified as ‘new to the country’ or ‘new to

the world’.

7.1 Case study purpose statement

The case studies presented in this chapter represent a collection of bounded delivery

process stories of technical innovation in the construction marketplace by

construction SMEs. These narratives of innovation delivery serve to contextualise

and enrich the data gathered in the AHP study. Seven specific examples of technical

innovations that have been successfully delivered are described and analysed for

convergent themes. All the technical innovations involve significant measurable

improvements to standard industry practice for the specific product or process

concerned. The improvements may be economic, environmental or OH&S based, and

some represent improvements in multiple fields. All have received peer recognition

as significant technical innovations from industry awards or via inclusion on the

innovation databases used in Chapter 5 to select participants for the AHP study. The

innovations may be ‘new to the world’ or ‘new to the country’ level of originality as

described in the Oslo Manual (OECD 2005). This represents a form of purposive

sampling known as revelatory case sampling (Teddlie and Yu 2007). The case

studies are chosen because they represent unique examples of a relatively rare

phenomenon; that is, the successful delivery of a high-level technical innovation by a

SME construction company. Collectively, they serve to illuminate the innovation

delivery process for construction SMEs.

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7.1.1 Explanation of case study significance

Yin (2003a & b) has explained that case studies can have several functions ranging

from exploration of individually varying circumstances to elucidation of typical

processes or features that are likely to recur. Manley (2008a) has demonstrated the

usefulness of case studies in the small construction enterprise context, as well as for

manufacturers subcontracting to construction projects (Manley 2008a; Manley

2008b). Leiringer and Cardellino (2008) are correct in cautioning about the potential

bias which may result from the innovator seeking to manage the outcome of the

research study for self-promotion. Neverthelesss, for the purposes of this thesis, the

case studies are intended to illustrate the variety and quality of innovations delivered

by SME firms in a limited region of the Australian construction industry based in the

greater Sydney and the surrounding area. It is not intended that these case studies

comprise the range of all potential types of technical innovation. Nor is it suggested

that the selected case studies represent the extent of achievement by elite performers

in innovation delivery by SMEs. Rather, the case studies are intended as exemplars

of successful innovation delivery which may be of interest to potential innovators

seeking encouragement from the achievements of others in the industry. As well as

these elucidatory storylines, some common factors may be present in several case

studies and these will be discussed in the last section of this chapter. It is intended

that the case studies provide useful examples of strategies and ‘best practice’ options

that can assist the delivery of technical innovation. The case studies may represent

useful storylines for encouraging less innovative sections of the industry to improve

their performance and consider trying new ideas.

7.1.2 Case study information

Several illustrations are included for each innovation case study, because

communication in the construction industry is primarily visual in nature and pictures

provide a significant amount of information that cannot readily be transmitted by

means of text only. This is particularly true as the intention of this chapter is to

describe the nature of technical innovations that have been successfully delivered to

market. Photographs of construction innovations often involve inclusion of some

individual workers involved in the process, but every effort has been made to ensure

that the individual’s privacy is not invaded, by using photographs that do not show

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recognisable individuals. All photographs are captioned as either by the author of this

thesis, or provided by the technical innovator. Trade names are used in this chapter in

order to recognise the considerable contribution made by the individual developers of

technical innovations to research in this field of applied endeavour, rather than to

publicise the individual innovation. The researcher has no financial or other interest

in any of the innovations presented as case studies. They have been chosen as

representative of some of the different kinds of technical innovation described by

Slaughter’s taxonomy of technical innovation (Slaughter 1998) as described in Figure

2.5 on p.44 of this thesis. The case studies have also been selected on the basis of

their peer recognition as successful high-end innovations and on the participant’s

willingness to assist with the research aim of presenting successful exemplar

storylines in order to encourage other potential innovators.

7.1.3 Case study identity disclosure

Information on the seven case studies was gathered from several sources including

trade literature, industry focused magazines, company websites, testimonials, site

visits and personal observation. An interpretive approach was taken to the case

studies and the researcher’s aim, following Seymour and Rooke (1995), is to report on

the perspectives of the participants in their particular settings. For this reason, trade

names are identified in the case study chapter, although they were not used in the

AHP study. The author gratefully acknowledges the assistance of the innovating

firms in the preparation of this chapter.

Yin (2003) discusses the question of whether case studies should be “real or

anonymous” (Yin 2003a p.157). He concludes that the most desirable course is to

disclose the identities of the case studies. This has the advantage of allowing the

reader to recall any previous information he or she may have learned about the case

from other sources and thus integrate the case study with previous research

knowledge. Even more significantly disclosure allows for the cases to be more

readily peer reviewed and for appropriate criticisms to be raised about the

interpretation of the case studies. The use of real company names in this

circumstance thus aids the intellectual rigour of the study, because it is possible for a

reader to repeat the case study research and either confirm or dispute its conclusions.

Anonymity is only required for case studies where there is some area of privacy or

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delicacy involved for an individual participant. The names of individual company

leaders are not given in this thesis as this would be considered an unnecessary breach

of privacy. Company names, however, do not involve similar privacy issues. In the

case studies presented here, the companies are actively involved in publicising their

innovation and were supportive of the academic publication of their stories. The case

studies focus on the building product or process and not on the individual people who

responded to the AHP survey or their private opinions. The case studies were

selected from the innovations delivered by some of the respondents to the AHP study,

but due to ethical considerations it is not possible to match the case studies with any

individual responses given to the AHP study. As previously mentioned, the

individual responses in the survey have been de-identified to ensure anonymity and

only aggregated data is presented. Each of the seven case studies will now be

discussed individually.

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7.2 Case study 1: Rapid setting volumetric concrete

Volumetric Concrete® mixing combined with RapidSet™ cement is a radical system

change which has potential to replace a significant proportion of the agitator type

rotary mixer concrete trucks that produce most concrete in all but remote areas today.

It can also replace on-site mixing as still used on remote sites where ready-mixed

concrete is not available. Ready-mix concrete has taken up an increasing percentage

of the Australian market since it was first offered in a widespread manner in the

1960s. It is an efficient system for delivery of concrete to building sites, but relies on

accurate estimating of the amount of concrete required for a particular job. Over

ordering can often result in significant wastage. Volumetric concrete mixers include

all mixing devices that measure the raw materials using volume rather than weight to

produce a concrete mix. The volumetric system studied here involves custom-made

trucks which carry three separate bins for aggregate, sand and cement in dry form plus

a water tank. There is also an integral chain fed conveyor belt under the bins to feed

the chute where all the mixing happens. The mixes are measured with great accuracy

by the machine, and an onboard computer allows the operator to vary the mix via the

control panel. Concrete is only mixed as it is used, so there is no over-ordering and

virtually no wastage. Only the small amount of concrete in the enclosed three metre

long chute as the pour finishes would ordinarily be wasted. One truck can service

several sites a long distance apart without any concern about the mix going off in the

truck, or the need to add plasticisers or other additives which decrease the quality of

the concrete. Rear discharge volumetric concrete mixers were originally developed in

the United States (Cooper 2006). They are regarded as the new generation in concrete

mixers, but constitute a ‘new to the country’ innovation in Australia (Volumetric

Concrete Australia 2010).

In addition to the savings in avoiding waste, the system has the added advantage of

being able to economically produce rapid setting concrete. The rapid setting cement

used contains no chlorides, accelerators or water reducing additives. The use of rapid

setting concrete means that repair work or critical tasks can be performed with

considerable time savings. This is demonstrated by the fact that a slab poured using

this system develops sufficient strength to be trafficable within a few hours of being

poured rather than a few days (see Figs. 7.1 to 7.6). Such speed of operation makes

the system particularly suitable for road and runway repairs and extensions, as the

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time between concrete pour and functional operation is greatly reduced. Reductions

in material wastage and time savings in many cases make the use of the more

expensive rapid setting cement a viable proposition.

This was illustrated by repairs completed to the Qantas Domestic Terminal apron at

Sydney Airport in early 2009. Demolition and replacement of sections of cracked

concrete was undertaken during the airport curfew hours of 11pm to 4am. The

replacement slab was trafficable by 6am. Consequently, there was no need for partial

closure of the airport facility and resultant delay and rescheduling costs were avoided

(Volumetric Concrete Australia 2010). Conventional concrete delivery could have

required a week-long shutdown of the area concerned. The flow-on cost to the

economy of any sort of airport shutdown has been demonstrated during recent

extreme weather events experienced in several parts of the world in 2010. While this

system does not address closures of that sort, it does avoid minor shutdowns for

maintenance work on aging infrastructure which could be both costly and disruptive.

This market niche of ‘rapid repair’ is the immediate area of useful application for the

volumetric concrete delivery system; along with small volume concrete jobs and

remote location concrete. It is believed by the innovator that increasingly the system

will prove competitive with standard ‘ready-mix’ concrete delivery for a wide variety

of applications.

The photographs in Figures 7.1 to 7.8 were taken by the researcher at an industry

open day in April 2010. The system was demonstrated by the pouring and finishing

off of a small slab followed by a one hour break after which the concrete truck was

driven onto the recently poured slab. No defects were observed in the new slab

despite careful inspection by the assembled interested parties.

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Figure 7.1 Volumetric concrete mixer with separate bins for cement, sand and aggregate

Figure 7.2 Mixer getting ready to pour

Photos Hardie

209

Figure 7.3 Pour has commenced

Figure 7.4 Pour complete and slab being finished off

Photos Hardie

210

Figure 7.5 Resin-based curing compound being sprayed on slab

Figure 7.6 One hour after the pour, the mixer truck is driven onto the new slab

Photos Hardie

211

Dust extractor technology is being developed and has been recently added to the

system in order to ameliorate any adverse effects on concrete workers of the dispersal

of small particles of dry cement dust during the concrete mixing process. The system

has additional OH&S benefits in that it does not require unsafe speeding up of

concrete pours when the mix is close to going off.

7.2.1 Slaughter’s taxonomy

This is a ‘Radical’ innovation under Slaughter’s terminology. It involves a new

approach which is likely to lead to major changes in the industry. It enables repair

and replacement of concrete structures in a much faster time frame than is possible at

present. Its current most appropriate applications are in civil works; particularly road

and runway repair and duplication. The speed with which the resulting slabs develop

their full working strength will have significant consequences for construction

scheduling and the economic benefit of the material waste reduction will require those

who stick with the existing system of concrete batching plants and agitator type

delivery trucks to find efficiencies of their own in order to compete. This is a

‘shooting star’ type innovation which breaks new ground for the construction industry

and opens up a plethora of new possibilities.

7.2.2 Strategies that support successful innovation delivery

Regular open day demonstrations at the innovator’s premises are used to explain the

technology to industry representatives and potential users. Such demonstrations are

carried out in combination with associated companies who wish to display their own

innovations to interested potential contractors and clients. The innovator in this case

puts a great deal of time and effort into networking within the industry and with

government and commercial client groups. An innovation which involves significant

changes in attitudes from current standard practice needs to court lead-users, and

especially large clients, whose projects are likely to get wide exposure in the industry

through technical magazines and industry publicity. Industry awards are also actively

sought by this innovator and several have been received from the Civil Contractors

Federation.

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Figure 7.7 Industry Open Day demonstrations held every few months

Figure 7.8 Industry demonstrations of related products

Photos Hardie

213

7.2.3 Innovator comments

The innovator sees the major benefits of this system-changing innovation as the

following: a reduction in truck movements and waiting times on site; resultant

reductions in carbon emissions due to fewer truck trips; less wastage of concrete

particularly in hard to estimate jobs involving excavation; and no unstable cold joints

as a result of waiting for concrete deliveries to arrive. While monetary savings are the

strongest driver of this innovation, efficiency savings, time schedule savings and

reductions in pollution from concrete construction are also significant. OH&S

concerns relating to concrete dust released to the atmosphere on the work site are

being closely monitored and addressed by careful work site supervision and practice.

7.2.4 Lessons from this experience

The delivery of this innovation has been supported by conscious and organised

attempts to spread awareness of the system throughout the industry, including among

potential clients and competitors. Networking with other businesses is fostered

through the regularly scheduled open day demonstrations and the contacts that are

made there. Careful follow up is practised of queries raised during the

demonstrations. Surveys are taken at each open day and these results as well as open-

ended comments are analysed and receive follow up if necessary.

This innovation delivery process is a clear example of placing great importance on

communication and market research. Knowing that it would be necessary to

overcome entrenched attitudes about the superiority of the existing system of concrete

delivery, the innovator in this case has adopted a very open strategy with technical

information about the new system. Attendees at the open days are encouraged to

voice any scepticism about the innovation and where possible technical responses are

given. This openness to industry scrutiny is a necessary process for an innovation

which seeks to change standard practice in an established field. If lead-users in large

companies or in government procurement agencies can be convinced of the

effectiveness of the innovation, then adoption of the innovation is likely to be

relatively rapid.

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7.3 Case Study 2: Lightweight impervious concrete block

Benex Blocks™ are lightweight concrete blocks with superior acoustic properties, fire

rating and impact resistance when compared with other lightweight concrete blocks.

They are impervious to water and require no vapour barrier or tanking when used as

basement walling. The blocks contain expanded polystyrene beads in a concrete

medium. This produces the lightweight and waterproof characteristics which are the

principal innovative feature of the block. Construction time is rapid, no applied finish

is necessary and minimal clean up is required. The system reverses the ratio of

skilled to unskilled labour required for construction of masonry walls. The base

course for any wall is laid in mortar in the same manner as traditional block-work

and, as such, requires experienced and skilled block-layers to accurately set out the

walls. Subsequent courses are laid in adhesive and are locked in place by the integral

connecting lugs on the joining surfaces (these are illustrated in Figures 7.9 and 7.10

pp.216-217). These courses can be completed by unskilled labourers with

comparatively brief training and a high standard of finish can be produced (Bennett

2006, 2007). In the current industry climate, this means that the widespread shortage

of tradesmen bricklayers/block-layers can be addressed by using less skilled labour to

produce an outcome of a similar standard in a faster timeframe.

With the aid of specially designed hardware that fits over the core openings, the

blocks can be core filled in both the horizontal and the vertical dimensions. This

enables detailed engineering of walls for heavy load situations or reactive sites.

Typically, every fourth core is filled vertically and a horizontal tie beam is poured in

one course in every story. Blocks can readily be cut with a diamond tipped saw and

nails and screws can fix directly into the block-work. Special lintel blocks and wall

closer blocks are available in the same material as the standard block.

The blocks have been tested for fire rating, water penetration, thermal resistance,

acoustic properties, resistance to salt attack and structural strength by various testing

authorities including Commonwealth Scientific and Industrial Research Organisation

(CSIRO). The reports and certificates mentioned below are available on the company

website (Benex Technologies 2008). The blocks have achieved a fire rating (Fire

Resistance Level) of 240/240/240 for structure/integrity/insulation (CSIRO test

certificate 2042, 2007). Water penetration tests were based on ASTM E514-06 which

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is known as “Standard Method for Water Penetration and Leakage through Masonry.”

This test is normally terminated after four hours, as masonry generally fails the test

well before the four hour period has concluded. The innovator’s block wall did not

fail within the 4 hour period, so it was decided to continue the test for a total of 24

hours. The block had not allowed any water to pass through at the end of the 24 hour

period. The wall was untreated and the standard block and adhesive were used. No

special installation methods were adopted. CSIRO experts concluded that a properly

built wall from these blocks can resist the conditions imposed by the ASTM water

permeability test for more than 24 hours, without failure (CSIRO Report on Job

number JK13ATS346 8).

Thermal resistance has been shown to be equal to or superior to that of other concrete

block products (BRANZ Report no.EC 1310, 2007). Sound Transmission Class

(STC) and Weighted Sound Reduction Index (Rʷ) were tested and found to meet or

exceed BCA requirements (CSIRO Report TL474, 2007). CSIRO testing also

confirms that the blocks can be used in a saltwater environment without failure or

deterioration.

Finally, the block’s structural qualities are equal to that of competing concrete block

walls and much stronger and more impact resistant than Autoclaved Aerated Concrete

blocks (commonly known by the trade name Hebel™ blocks). It is not within the

scope of this thesis to confirm these technical tests on the block’s performance. It is

merely reported here to explain that testing has been performed by the appropriate

authorities and the blocks have been shown to perform well. It is likely that they

equal or exceed the performance of the existing hollow concrete blocks that are their

main competitor in most areas.

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Figure 7.9 Block dimensions Image Benex

Figure 7.9 above illustrates the integral connecting lugs that are used to locate the

block courses and to ensure the finish quality of the completed block-work wall. The

narrowness of the vertical joints between the blocks is also illustrated. This results

from the blocks being bonded with adhesive rather than traditional mortar. The result

is an acceptable finish without an additional cladding or lining, although lining

internally with plasterboard is optional should that be the desired finish.

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Figure 7.10 Block details

Image Benex

Figure 7.10 above further illustrates the block with isometric and end views. It may

be noted that the blocks have a larger percentage of void space than traditional

concrete blocks. This is achieved without any subsequent loss of strength. Along

with the inclusion of the expanded polystyrene beads this feature what makes the

blocks lightweight and relatively easy to manage and handle, even by inexperienced

block-layers.

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Figure 7.11 Lightweight impervious concrete block

Photo Benex

Figure 7.12 Cut block showing polystyrene bead interior Photo Hardie

219


Under Slaughter’s taxonomy, this is a ‘Systems’ innovation. There are multiple

changes within the blocks themselves when compared to standard concrete blocks, as

well as significant changes to the other construction systems that connect to the block-

work. The need for tanking in underground situations is removed, enabling the

elimination of a problematic wet trade from the construction process. The amount of

reinforcement required and the number of columns which need to be poured are both

reduced when compared with standard concrete blocks.


In order to achieve market recognition, this innovation has been presented on

television (Australian Broadcasting Commission’s The New Inventors), as well as at

various trade fairs and through conferences of professional organisations such as the

Australian Institute of Building. The company provides training packages for other

builders who want to use the product, as well as training unskilled labour to lay the

blocks. This is done with the aid of several government income support and job

readiness schemes for the long-term unemployed.

Some resistance to the increasing market share of the product has come from existing

producers of concrete blocks. There are reports that competitors have spread

misinformation about the performance of the blocks to local building inspectors in

some areas. This has to be countered by the dissemination of verified performance

test results from respected authorities such as CSIRO and NATA. The blocks can

produce a 4 hour fire rated wall without filling all the cores, whereas standard

concrete blocks meet this standard only when all cores are filled. This represents a

significant saving on existing concrete block-work.

Feedback from early installers indicated that a standard glue gun applicator could not

deliver the large quantity of adhesive necessary to lay a block wall at the speed that

workers could put the blocks in place. Consequently, a purpose-designed large

volume applicator (made initially from 100mm poly pipe) was developed and is

delivered as part of the installation system.

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Figure 7.13 Retaining wall to garage not requiring waterproofing

Figure 7.14 Upper storey walls under construction

Photos Hardie

221

Figure 7.15 Block wall under construction showing closer blocks

Figure 7.16 Internal wall face to be finished with plasterboard

Photos Hardie

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The innovator described the main advantage of his construction system as being a

very rapid construction method, requiring very little worker training to produce a high

quality finish. Exceptional performance is achieved at a competitive price. Owner

builders have shown considerable interest in the product. The innovator is seeking

larger projects such as public buildings, in order to lift the profile of his product, so

that it will be considered as an alternative throughout projects where load bearing

masonry is currently used. Largely as a result of their thermal properties, the blocks

have been used for the Green Skills Trade Centre at Orange TAFE College in western

NSW in 2010. A comparison of the relative cost and time properties of the blocks

compared with their major competitors was supplied by the innovator. This is shown

in Table 7.1.

Table 7.1 Comparison of blocks with alternatives available

Feature Benex Block™ H600 core filled

Standard core filled, fire rated concrete block

Hebel Block 200 mm Thermoblock™

Finished cost/sq m (unpainted) March 2010

$140-$160 $180-$210 $125

Fire rating – Structural/Integrity/Insulation (hours)

240/240/240 240/240/240 240/240/240

Installation speed in m² per day

25-30 9-12 15-20

Dampcourse and moisture barrier required for water resistance

No Yes Yes

Additional finishing material required (external render or internal plasterboard)

No No Yes

Freight cost for delivery to site Low Medium Low

Screw fix direct to wall surface Yes No Yes

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As the Table 7.1 illustrates the Benex block system is quicker than both other

alternative options listed. It is more cost effective than standard concrete blocks and

is comparable in cost to Hebel block when the need for additional finishing material is

added.


The reduction in the need for skilled labour to produce a quick and high quality result

is a feature of this innovation and the source of much of its economic

competitiveness. While the blocks have not yet achieved a slice of the market which

affects the prospects of traditional brick- and block-laying, they have the potential to

do so. As Seymour and Rooke (1995) have noted, innovation often leads to old skills

becoming redundant. Whether these blocks and other interlocking masonry products

will have this kind of impact remains to be seen.

Whatever the long term impact will be, this kind of block is significantly different

from its current competitors in the market, so it has been necessary for the product

innovator to invest in a great deal of independent testing to verify claims that are

made about the product. The test certificates are available on the product web pages

(Benex Technologies 2008) in order to reassure potential customers of the reliability

of the product.

The development of this innovation involved the study and usage of processes

developed in other industries. The process used for temperature control and curing

the concrete blocks is adapted from conveyor systems used in food processing.

Learning lessons from other industries is not often done in construction, but it is a

largely untapped source of potential innovations.

Large institutions such as universities often have a regular building program to

expand and upgrade their existing facilities. Targeting property managers from such

institutions with information about innovative products can prove a useful strategy to

spread the word about new construction systems. This is particularly true for

innovations that are attempting to gain market share in an area already well serviced

by existing technologies.

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7.4 Case Study 3: Under floor water storage bladders

WaterCell™ is a series of under floor water bladders connected to roof water

collection pipes. It is used as either partial or full replacement for mains water. Many

Australian cities and towns have experienced severe water shortages in recent years

and it is widely believed that this is an ongoing problem due to the combined effects

of population increase and global warming. The water storage bladder system

comprises an engineered, high volume rainwater harvesting, storage and reticulation

system which forms an integral part of a new building and can, in some cases, be

retrofitted to an existing one (Ball 2006).

The WaterCell™ system is entirely contained within the building footprint and

according to the producer; the components are accessible, serviceable, maintainable,

replaceable, recyclable and affordable. The storage cell is manufactured using

recyclable polyethylene which complies with both US and European standards for

food contact and drinking water storage. The technology delivers an immediate clean

water supply for a project, simultaneously eases the demand on the existing

centralised water supply system, extends the life of existing stormwater infrastructure,

and significantly reduces the cost of new stormwater infrastructure for the lifetime of

the installation. It can deliver a potable water supply at a reasonable and sustainable

cost to all kinds of buildings. Researchers at the University of Newcastle, Australia

have established that such water supply systems can provide safe, high quality water

to complement mains water supply (Kuczera 2008; Coombes and Kuczera 2003).

The system is normally located in the sub-floor space, but can be situated in any area

that can be allocated to the storage of water. It is competitively priced compared to

other water storage systems such as water tanks and water storage gutters.

A storage cell is a non-structural element, which takes the shape of its container. The

typical storage cell is 6 metres x 4 metres x 0.7 metres deep and has a storage capacity

of 16,000 litres. Each storage cell is a welded, closed bag, manufactured from thin,

flexible, impermeable, non-toxic, hygienic material and fitted with integral inlet and

outlet spigots. Any number of storage cells can be connected in series. The plumbing

system allows additional storage cells to be added in series at any time, and can allow

any particular storage cell or cells to be isolated, removed or replaced when required.

Each empty cell weighs 28 kilograms and is warehoused and transported in a

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cardboard box measuring approximately 1 m x 1 m x 0.2 m. This can be handled by a

single person with the use of a light trolley (VisionWater 2008). There are several

companies producing water storage bladders in various forms but the WaterCell®™

version is an integrated system that is easily transportable and is designed to reduce

the use of mains water in climatic conditions such as that of the greater Sydney area

by up to 85% compared to normal water usage (Coombes 2002). It is covered by

international patents (Ball 2006).

Ease of transportation is a major benefit of these water bladders over precast concrete,

plastic or galvanised steel water tanks that are in common use in Australia. Tanks of

similar capacity to the bladders need to be transported on large trucks and require site

access that is not available in some narrow streets or on steeply sloping sites. As the

individual bladders can be easily handled by one person, they can be placed in

position even when access is restricted by confined site layout and existing building

structures. For the same reason, it is also possible to use the bladders in some retro-fit

situations where tanks are unsuitable. Potential manual handling injuries from lifting

during installation are also avoided because of the light weight and compact nature of

the bladders compared to steel and concrete tanks.

Because the bladders are installed in out-of-sight locations under floors of houses,

they do not have the visual impact of water tanks which some residents find

objectionable. This is an issue in some residential areas where existing residents may

oppose the installation of tanks because they are perceived to be an eyesore. Attitudes

of this type may be changing with greater environmental awareness among the

broader community but the issue is circumvented if the bladders are used rather than

tanks. If a new technology can be designed to have minimal aesthetic impact on the

existing built environment, then this is likely to assist in the adoption process.

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Figure 7.17 Building design to incorporate sub-floor water bladders

Figure 7.18 Water bladder compartments in sub-floor space

Images WaterCell®

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Figure 7.19 WaterCell® being installed

Figure 7.20 Full WaterCell® in place

Photos WaterCell®

228


This is a ‘Systems’ innovation according to Slaughter, as it involves large changes to

the element itself (water storage units) as well as multiple changes to its linkages with

other elements. The floor space of the building needs to be designed in modular

compartments which can accommodate the water bladders. The roof plumbing of the

building needs to be connected to the bladders and the water stored in the bladders

needs to be piped to particular outlets such as toilet cisterns and garden hose cocks.


The marketing strategy for the product targets end-users with desire to build

sustainably and who nevertheless want a cost effective solution to the provision of

fresh water in an environment, where the rainfall falling on a property is regarded as a

resource that can no longer be ignored. The system comes with advice about applying

for Government rebates and is supported by local council authorities in the

innovator’s region.


The innovator stressed the potential of the water bladders to replace mains water

consumption as a significant contribution to likely water shortages as a result of

climate change. Particularly in coastal NSW, where rain falls in irregular patterns but

often in significant amounts at individual rain events, it is possible to greatly reduce

pressure on the available potable water supply with the use of this innovation.

Ongoing monitoring of completed projects is being undertaken to insure the validity

of these claims. It is preferable that the water bladder storage is used for regular

draw-down purposes such as toilet flushing and washing machine operation. If the

intention is to use the water only for landscaping purposes, the water can remain

unused for long times during rainy periods. This results in a sub-optimal usage.


Close alignment with the strategies espoused by public utilities which provide

services to new development can assist the delivery of a technical innovation. This

innovator also had close ties with a regional university in the area which assisted in

modelling of the potential benefits of the system, as well as verification of the

effectiveness of the delivered system.

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7.5 Case Study 4: Cylindrical concrete formwork tubes

Ezytube™ is a spiral, lined formwork tube for off-form finished round concrete

columns. The tubes consist of multiple layers of thin water resistant paper and high

tensile strength plastic coated mesh. The tubes are light-weight which saves on

cranage costs, as tubes of up to 4.5m long by 600mm diameter can be safely handled

by a single worker in most cases. The tubes are weatherproof and can be stored easily

on construction sites. They save labour due to their fast and simple installation

requirements, as well as through the rapid removal process using an inbuilt ripcord.

They are very safe to use and no grinders or electric tools are required to trim, remove

or cut the tubes before placing in waste bins, as would be the case with metal form

tubes. The strong multilayer structure, nevertheless, provides flexibility and ensures

improved impact resistance when compared with single seam spiral tubes. During

transportation, the tubes may at times become distorted or ‘out of round’. According

to the producer, this is not a significant problem, as the tubes can normally be pushed

back into shape prior to fitting. Even if this cannot be done, the tube will attain a

round form when filled with concrete despite being slightly distorted prior to filling.

The tubes can be transported in either a vertical or horizontal position. In order to

contain freight costs, each of the different diameter tubes fit within the internal

diameter of the next larger size. In other words, 400mm fits inside 450mm, which fits

inside 500mm and so forth (Ezytube Pty. Ltd. 2009).

The particular advantage of these tubes over other removable formers available on the

market is the ease of stripping from the completed column. Forms are often left in

place until just before hand over of the building as they can prevent scratching and

other damage during construction and fit out of the building. When required they can

either be stripped with a knife or by using the ripcord feature installed for some of the

tubes.

When the ripcord function is not installed, after sufficient curing time has elapsed, the

base supports are removed and a Stanley knife (or similar implement) is used to

perform a straight vertical cut from the top of the tube to the base. An additional cut is

then made around the full circumference of the tube approximately 100mm from the

soffit or support beams. The two sections are pulled apart and the form can be easily

slid from the concrete column. One person can perform this operation, generally in a

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few minutes per column. For best finished results with lined tubes, the form should

be cut in line with the marks on the outside of the tube which indicate the location of

the internal plastic join. When the ripcord feature is used, the process is even quicker.

Somewhat similar products are available internationally, but the features of this

particular system make it unique in the current construction market as indicated by

international patents held by the innovating company (Adams and Villaescusa 2005;

Adams and Villaescusa 2009).

Figure 7.21 Formwork tube being put in place

Photo Ezytube

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In Slaughter’s taxonomy of construction innovation, this would be regarded as an

‘Architectural’ innovation with relatively small changes to the element that enable

considerable change to the efficiency of the concrete pour process and, therefore, the

project delivery.

Figure 7.22 Formwork tube being removed

Photo Ezytube

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The delivery of this product innovation is strongly dependent on long experience in

the concrete formwork industry, along with thoroughly organised feedback loops

between the product supplier and its on-site installers. This is an innovation

conceived and generated by individuals with practical experience of the quality

assurance and timing issues involved in concrete form-working. Considerable effort

has gone into training packages for workers using the product for the first time.

Instructional CDs are provided and these give particular emphasis to site safety as

well as to quality assurance.


The innovator stressed that the inspiration for this product was the need to provide

safer and more economic methods of forming concrete columns. Emphasis on ease of

operation, complying with limits for manual lifting and the designing out of potential

injury hazards from the system were critical factors inspiring the delivery of this

innovation. OH&S matters are receiving increasing attention in the concrete forming,

pouring and stripping processes because of a history of frequent musculo-skeletal

injuries to workers in this area. The attention is unsurprising given that the

construction industry’s hospitalisation rate for injured workers is significantly higher

than the hospitalisation rate for all other industries. It is currently running at over 100

more hospitalisations per 100,000 workers than the average for all industry employees

(Australian Safety and Compensation Council 2008). Manual handling issues are the

most common cause of workplace injury for concreters. It is likely that such statistics

will drive further innovation in construction products and processes aimed at reducing

the frequency and impact of significant injury on construction sites.


Effort spent informing the workers who actually use an innovative product of its

benefits is considerably more effective than providing this information to designers

and product specifiers. This tends to be overlooked by many technical innovators and

can result in the failure of a good idea to achieve market penetration. The actual

delivery process for the innovative product is reliant on the level of understanding of

those who deploy it, rather than those who select the product, but who are not

involved in responsibility for checking the end result.

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7.6 Case Study 5: Salt-removing sacrificial render to restore

deteriorating masonry walls

Cocoon™ desalination poultice is a sacrificial render that can be sprayed or trowelled

on to a masonry wall in order to remove the accumulated salt build up caused by

rising damp. This build up is a significant cause of deterioration in historic and

heritage masonry buildings. Indeed a UK specialist in the repair and conservation of

historic building has stated that:

“Soluble salts are a principal agent of decay in porous building

materials and a source of great frustration to those involved in the

conservation of historic buildings.” (Woolfit 2000).

In such buildings, there may have been inadequate provision for a Damp Proof

Course (DPC) to prevent capillary action, causing salt-laden ground water to be

absorbed into the soft masonry fabric of old brick or stonework (Cooper 1999).

In order to remove these salt deposits a render coat is applied to the affected surface

area. The render consists of an 8mm to 10mm thick layer of creamy paste in a

distilled water medium. It has a PH of 8 and contains no reactive chemical

compounds. The active constituent is pharmaceutical grade filter paper pulp.

Diatomaceous earth particles in the pulp have fine fibres which attach to the salt

particles in the masonry wall. The normal practice is to apply a first render coat

which is left in place for two weeks to allow the salt particles to be absorbed by the

render. The first coat is then easily peeled off and another coat applied and also left

for two weeks. After this, the second coat is removed. The end result is that almost

all the deposited salt on the masonry surface is removed and deterioration of the

fabric due to salt damage is either greatly reduced or halted altogether. The

applications result in a dramatic improvement in the appearance of the masonry and

do not need to be repeated for several decades under normal circumstances. The

product was first developed for the restoration of the convict-built structure in Sydney

Harbour known as Fort Denison (see Figures 7.23 and 7.24 overleaf). Located in a

tidal area, the sandstone structure had been subject to damage from dissolved salt

from salt water for over a hundred and fifty years. The salt removing poultice

performed more successfully than any other potential solution available at the time.

This led to its use on other historically significant buildings such as Elizabeth

234

farmhouse in Parramatta, NSW (see Figures 7.25 and 7.26, p.233). The system has

also since been used on heritage buildings in many parts of the world, some of which

were of considerable antiquity (Westox Building Products 2010). An example of

these is the Duomo in Pisa, Italy where marble friezes have been successfully treated.

Figure 7.23 Fort Denison in Sydney Harbour

Figure 7.24 Salt affected stonework

Photos Westox

235

As can be discerned from Figure 7.24, salt damage to historic masonry buildings is

more than just cosmetic in nature and can lead to long-term deterioration in the

strength of the wall, as well as, unsightly surface erosion. This damage builds up over

long periods of time, but the two stage treatment with the sacrificial render can

provide a building with many additional years of functional life, while restoring an

acceptable level of finish to the masonry surface.

Figure 7.25 Elizabeth Farmhouse in Parramatta, NSW (c 1790), one of the oldest European

structures in Australia

Photos Westox

Figure 7.26 Sacrificial render in place at Elizabeth Farmhouse and later being peeled off

Photos Westox

236


This innovation would be regarded as ‘Modular’ according to Slaughter. The actual

element itself, the sacrificial render, is a big departure from previous practice. The

render system is patented and represents a means of successfully treating a problem

previously considered intractable (Cooper 1999). It does not, however, require any

significant modifications to any other building processes involved with the restoration

of old masonry structures. It is essentially a fully-bounded innovation as defined by

Harty (2005).


Since this is a highly specialised area of building, successful delivery of the

innovation requires that people responsible for decision making about historic

building restoration know of the potential of the salt removing treatment. This has

been done primarily through a web site that contains an animated explanation of how

the process works plus numerous case studies of its successful application. ‘Word of

mouth’ is highly significant in the dissemination of information about this innovation.

A process like this one, however, needs to be global in its approach and the internet is

the primary way of achieving international product recognition for the process.


This innovation was driven by the innovator’s investigation of what was widely

regarded as an intractable problem; namely the disfiguring build-up of dissolved salts

on the surface of masonry. As a plasterer by trade, who had come to specialise in the

restoration of masonry surfaces in heritage buildings, he actively sought possible

existing solutions before experimenting with a potential solution of his own devising.

He also had a quantity of pharmaceutical grade filter paper available due to an

unrelated business deal, so he determined that it might be possible to use something

that he had available to solve a problem that he commonly encountered. Considerable

research, development time and expense were required to bring the initial idea to the

market as a successful solution to the problem. Similar poultice-based systems have

been suggested by conservationists, but effective solutions are not commercially

available to any great extent (Woolfit and Arbrey 2000). The issue is commonly

treated on a small-scale case-by-case basis.

237


In order to achieve acceptance for this process in building conservation circles, the

innovator has found it necessary to ‘start from scratch’ in each new country where the

system is introduced. Reports of previous success in other countries appear to carry

very little weight with the guardians of heritage buildings. In each new market, the

system needs to be extensively re-tested under local conditions before gaining

acceptance.

Often alliances and partnerships need to be formed with local companies in order to

have the process approved in the national jurisdiction. This has had to be accepted as

a condition of the business environment. Each new regulating authority is approached

and taken through the process of verifying the safety and effectiveness of the system

according to its own building and heritage standards.

Due to the highly specialised nature of the process, information about the system on

the company website is offered in ten languages in an attempt to address the

international communication issue. Video footage of several case studies employing

the process, both in Australia and internationally, have been made available on the

website (Westox Building Products 2010). The website also provides a very clear

explanation of how the process works in animated cartoon form. Such

communication and awareness raising measures are likely to be required for any

technical innovation which has a market in heritage buildings, because there is a long

history of poor and ineffective restoration processes which showed early promise of

delivering positive outcomes. Innovators need to be aware of the precautionary

approach that is usually taken by heritage guardians to any new process. Care needs

to be taken when building treatments are not reversible. Consequently, new solutions

are necessarily greeted with a fair degree of scepticism in matters that affect heritage

buildings. It is up to the innovator to reassure regulators and provide solid evidence

of the efficacy of any change.

238

7.7 Case Study 6: Rollover warning system for articulated

construction plant

ROPS2™ is an early warning and function management system designed to reduce

the risk of mobile plant rollover. The system monitors axial machine angles and

warns the operator of impending dangerous angles. If the operator persists, the lock

out function is activated and the system immobilises the equipment. Developed for

vibrating rollers, the system is capable of being fitted to most mobile construction

plant. The system is needed, because operator perception can often be inaccurate

when assessing the risk of rollover. This is especially true for articulated vibrating

rollers that oscillate at their articulation joints. In most cases, the operator station is

fitted to the rear of the machine and the vibrating drum to the front section. When

working on uneven ground, the operator does not always move with the front section

of the unit. In other words, there can be an angle variation between the two sections

of the roller. When the machine is reversing and the operator is looking in the

direction of travel, the drum would not normally be in the operator’s field of vision.

The ROPS2™ system fitted to the front of the machine warns the operator with both

visual and audible alarms when the roller drum is at an unstable angle. The lock out

function of the system reduces the risks associated with operator error, complacency,

panic and slow reaction time. An additional safety feature is a seat belt sensor that

maintains park brake application and prevents travel unless the seat belt is engaged

(Ibrahim 2007). Appropriate operator training is still required, but the system greatly

reduces the margin for accident and injury caused by operator error (Conplant Pty.

Ltd. 2008). While plant rollover is not among the most common causes of worker

injury in the construction industry, when an incident does occur, it is comparatively

more likely than other incidents to result in a fatality. There were 16 recorded

fatalities in Australia in 2007-2008 from rollover incidents involving farming, mining

or construction machinery (Safe Work Australia 2010).

This case study represents another example of an innovation focussed on improving

OH&S outcomes in the construction industry. The innovator comes from a medium-

sized company which is delivering its innovation nation-wide, with the aim of

improving the industry’s safety record. While there are many rollover prevention

239

systems available, the salient feature of this one is the lock out function which is

activated when the operator persists with moving the vehicle at an unsafe angle.

Figure 7.27 Rollover management system

Images ConPlant

240


This is a ‘Modular’ innovation under Slaughter’s taxonomy. It involves large changes

to the element concerned, but has little impact on the surrounding components other

than a reduction in time loss due to accidents. The innovation amounts a simple

substitute for similar plant and equipment, but the propensity for rollover is greatly

reduced.


The equipment has been demonstrated at trade shows and is also promoted via means

of a plant hire system where contractors try out potentially useful machinery without

the expense of outright purchase. For equipment items with high capital cost, this is

an important way of acquiring market share.


The innovator commented that his firm liked to have control of operator training in

order to be confident that correct procedures were carried out. They did not feel

entirely confident about relying on third party certification of machinery operation

skills. The system was motivated by the need to design out operator error and

intransigence. This was primarily a risk management strategy resulting from potential

liability due to OH&S laws. Removing the opportunity for potentially dangerous

operator decisions addresses a major risk on construction sites during the hazardous

excavation and site-forming phases of a building project.


A technical innovation often needs to be supported by marketing and management

strategies that make the benefits of the innovation known. OH&S can be a driving

force behind inventive solutions to common construction problems. The evidence

from this case study is that safety is a primary concern for those construction SMEs

who use large plant and machinery, as well as a frequently changing workforce of

semi-casual employees. The emphasis is placed on reducing or removing the

potential hazard rather than on relying on the judgement of individual workers.

241

7.8 Case Study 7: Dry wall noise barrier

QuietWave® is a high performance, dry wall noise barrier which is able to deliver

excellent sound attenuation due to its patented constrained layer membrane system.

The 1.2mm thick visco-elastic membrane is lightweight and can be readily installed

by one person. When combined with vibration damping, it easily exceeds Building

Code of Australia (BCA) noise reduction requirements for separating walls between

apartments, townhouses and other attached dwellings. It is also suitable when a high-

level of acoustic privacy is required, such as between offices, teaching spaces or other

institutional buildings. It is particularly successful at attenuating noise from

electronic entertainment sources for adjacent occupancies. The membrane has self

healing properties and can be penetrated without significant degradation in

performance. The finished wall system has a solid feel and when impacted upon,

sound resonates in a similar manner to that of a masonry wall. The system is space

saving, as it produces a 50% reduction in the width of the wall against other

comparable 6 star rated acoustic wall systems. This equates to a gain of 1m² of floor-

space for every 6.6m length of wall (Acoustica 2010).

The wall system comprises:

• One 13mm thick plasterboard sheet

• One 1.2mm thick visco-elastic membrane


• 64mm staggered studs in a 92mm track

• 50mm thick insulation batt


• One 1.2mm thick visco-elastic membrane


This is illustrated in Figure 7.28 overleaf.

242

Figure 7.28 Cut away model of QuietWave® wall

Image QuietWave®

Figure 7.29 QuietWave® compared to other sound reducing walls in current use

Image Spec Net

243

The system provides what is currently regarded as the highest possible acoustic

performance for the thinnest available wall section. In addition, the membrane has

environmental benefits due to the fact that it is produced from organic waste products

including gelatine, glycerine and a filler material (Doneux and Takacs 2005a, 2005b,

2006).


Under Slaughter’s five heading taxonomy of building innovations, QuietWave®

would best fit the category of ‘Modular’ innovation. It involves a large change to the

separating wall itself, but has little impact on other building components around the

wall. It is a closely bounded innovation in Harty’s terms (Harty 2008). The only

impact is that of space saving due to the comparatively narrow width of the wall.

This may result in more planning flexibility in some circumstances, such as in retrofit

projects.


In the case of an innovative product which has no closely comparable competitors in

performance, it is necessary that a great deal of effort is put into making designers,

builders and clients aware of the product’s potential. Due to the highly original nature

of the innovation involved in the design of this wall system, marketing strategies have

played an important part in the successful delivery of the product.

Demonstrations of the effectiveness of the wall system on television programs such as

The New Inventors and Better Homes and Gardens were used to create public interest

and awareness. Endorsement on public websites such as the SMART 100 Index and

Australian Technology Showcase has further lifted the public profile of the product.

Recognition through awards such as the Small Business Ventures Excellence Awards

has also been pursued to increase market awareness of the quality of the product.


This innovation was inspired by a need to improve the acoustic performance of noise

barriers in residential and commercial construction. This is an ongoing problem

which creates many acrimonious disputes between neighbours and some considerable

social disruption between people of different lifestyle habits and age group usage

patterns. There are other ways of reducing noise transmission between adjacent

244

building areas, but this system was driven by the need to demonstrate the superior

performance that could be achieved using a product made from an environmentally

sustainable organic based product. It is likely that ongoing interest in green building

strategies will assist the growing market acceptance for this product. The innovator

sees this trend as the real potential for his innovation, because it is produced from

sustainable organic by-products which would otherwise be wasted.


The technical superiority of an innovative product is not of itself sufficient to ensure

the rapid uptake of a product by the construction industry. Builders and designers

may prefer to stick with products that they are familiar with rather than risk change.

In order to overcome this, the innovator in this case targets market leaders in their

fields and specifically stresses originality and environmental benefits in the

information that the company disperses to architects and major property companies.

The more original the technical innovation, the more likely it is that an active

marketing campaign will be needed to persuade industry and end-users of the benefits

of change.

7.9 Case study innovation results and implications

All the case studies were of technical innovations of high-levels of originality, as

defined in the OEDC’s Oslo Manual, either new to the country or new to the world

(OEDC 2005). This does not mean that the products or processes have no

competitors or no available alternative solutions. Rather, it means that the products or

processes are significantly different in technical detail from the currently available

alternative options. The case studies highlighted the positive side of SME innovation.

245

Table 7.2 Case study company characteristics

Innovation Small or

medium-sized

company

Product or

process

Patent holder

1 Rapid-setting volumetric

concrete

Medium Process No

2 Lightweight impervious

concrete blocks

Medium Product Yes

3 Under floor water storage

bladders

Small Product Yes

4 Cylindrical concrete

formwork tube

Small Product Yes

5 Salt removing sacrificial

render

Small Process Yes

6 Rollover warning system

for articulated

construction plant

Medium Product Yes

7 Dry wall noise barrier Small Product Yes

246

Table 7.3 Case study innovation characteristics

Innovation Novelty level

(OECD Oslo Manual

definition)

Slaughter’s

taxonomy

1 Rapid-setting volumetric

concrete

To the country Radical

2 Lightweight impervious

concrete blocks

To the world Systems

3 Under floor water storage

bladders

To the world Systems

4 Cylindrical concrete

formwork tube

To the country Architectural

5 Salt removing sacrificial

render

To the world Modular

6 Rollover warning system

for articulated construction

plant

To the country Modular

7 Dry wall noise barrier To the world Modular

Many SMEs are headed by very able individuals who have chosen to avoid working

in large businesses, because of the restrictions that a large bureaucratic organisation

can place on individual creativity. Such individuals have the potential to be leaders of

industry change and generators of new systems and products. Nam and Tatum (1997)

refer to them as ‘champions’ of innovation. The fact that the construction industry is

characterised by many small businesses has both positive and negative aspects. It

does lead to restrictions on capacity and resources, but it also enables creative

individuals to move quickly in new directions and develop new solutions to industry

problems. It is this potential that justifies this research into factors that affect

technical innovation for non-micro SME construction companies.

247

The breakdown of the characteristics of the case study innovations is shown in Table

7.2 and 7.3 on previous pages. As with the AHP study, innovations are regarded as

either product or process-based innovations, depending on whether or not they

primarily involve a physical object (product) or a method of work delivery (process).

The novelty level is either ‘new to the country’ or ‘new to the world’ as defined by

Manley in the BRITE Report 2005. Finally, Slaughter’s taxonomy of technical

innovation in construction, as described in Figure 2.5 (p.44) of this thesis, is used to

classify each innovation according to its degree of internal change, along with

changes involved in connecting construction products or processes.

As a further level of analysis, the innovations were classified according to three sets

of alternative characteristics described in the literature: These are ‘Project-based/

Reactive/Bottom-up’ compared with ‘Strategic/ Proactive/ Top-down’ as described by

Winch (1999); ‘Unbounded/ Systemic’ compared with ‘Bounded/ Autonomous’ as

defined by Harty (2005); and according to the decision making practices as described

by Mitropoulos and Tatum (1999) as Intuitive/ Behavioural as opposed to Analytical/

Rational. Although there was some cross over between the alternatives, most of the

innovations appeared to fall significantly, if not entirely, into one or other category.

The results of this analysis are shown in Table 7.4 overleaf.

The choice between strategic or proactive innovation types is largely revealed by the

history of the innovation generation. If the innovation resulted directly from a

perceived problem, it was regarded as reactive, but if it was more speculative in the

sense of looking for greater efficiencies in general delivery of a project, it was

regarded as proactive. Unbounded innovations affect the systems around them

significantly, whereas bounded innovations largely affect only themselves. The

choice between intuitive or analytical innovations mainly relates to the amount of

systematic testing that took place during the innovation generation. The analytical

approach starts with no particular solution in mind and scientifically eliminates

alternatives. The intuitive approach starts with a specific idea that is then tested for

its suitability and performance. Successful technical innovations have been recorded

as deriving from either process.

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Table 7.4 Descriptive innovation categories

Innovation Strategic/

Proactive/T

op-down

Project-based/

Reactive/ B

ottom-up

Bounded/

Autonom

ous

Unbounded/

System

ic

Analytical /R

ational

Intuitive/ B

ehavioural

Rapid setting volumetric

concrete

Lightweight impervious

concrete blocks

Under floor water storage

bladders

Cylindrical concrete formwork

tube

Salt removing sacrificial render

Roll over warning system for

articulated construction plant

Dry wall noise barrier

Table 7.5 (overleaf) shows how the innovations rate under Lim and Ofori’s three way

classification relating to the reason for the innovation’s successful adoption (Lim and

Ofori 2007). Although the innovations may be seen as fitting multiple categories,

only the primary, or driving one, is selected here. The case studies are evenly spread

between the three prime driving factors. This variety in driving factors supports the

contention that the case studies represent a sample of the diversity exhibited by high-

level technical innovations in construction.

249

Table 7.5 Prime reason for successful innovation delivery

Innovation

Innovations the

market is w

illing to

pay for

Innovations that

reduce builders’ costs

Innovations with

intangible benefits

producing competitive

advantage

Rapid setting

volumetric concrete

Lightweight

impervious concrete

blocks

Under floor water

storage bladders

Cylindrical concrete

formwork tube

Salt removing

sacrificial render

Roll over warning

system for articulated

construction plant

Dry wall noise

barrier

250

Table 7.6 Case study descriptions

Technical innovation case study

description

Com

pany holds patents on the invention

Involves trademark protected

intellectual property

Degree of novelty (O

EC

D O

slo M

anual)

Com

pany size by direct em

ployment (A

BS

)

On demand concrete mixing system that

reduces waste and can be used for rapid

setting concrete

* High Medium

Lightweight interlocking concrete block,

impervious to water that does not require

tanking in retaining wall situations

High Medium

Under floor rainwater storage bladders

connected to outlets within the building to

replace a percentage of mains water usage

High Small

Temporary formwork for round columns

with quality finish and easy removal Medium Small

Salt removing poultice to restore

appearance and strength to masonry

building components deteriorating due to

salt deposits resulting from rising damp

High Small

Early warning and function management

system designed to reduce the risk of

mobile plant roll over

Medium Medium

Lightweight, high performance dry wall

noise barrier that is easily installed and

takes up minimal floor space

High Small

*Company holds southern hemisphere licenses for the patented invention

251

In Table 7.6 (on previous page), the originality of the case study innovations is

confirmed by checking on which innovating companies hold patents for the product

or process described. Six of seven do so and the remaining company holds licenses

for the patented process for the southern hemisphere. All seven innovations involve

trademarked intellectual property. The innovations are classified as high or medium

level innovations, according to the definitions set up in the OECD’s Oslo Manual

(OEDC 2005). No low-level innovations were included, because the selection criteria

for the case studies involved peer recognition for having delivered a ‘significant’

innovation’. Company sizes are based on the ABS definitions of 5 to 19 employees

for a small company and 20 to 200 employees for a medium company.

7.10 Vectors affecting technical innovation

Deriving from the case study observations, a pattern can be observed in the factors

that affect technical innovation delivery by construction SMEs. This is different in

detail from the factors initially identified from the literature review and tested via the

AHP survey. A set of seven vectors affecting technical innovation has been

identified. The seven vectors are illustrated in Figure 8.30 overleaf. The items are

properly described as vectors because they have both magnitude and direction. In

individual cases they may operate in either a push or a pull mode. In other words, the

direction of the affect may be either way. None of the innovators studied, operated

entirely in the ‘Open innovation’ mode as described by Chesborough (2003 and

2006). All exhibited concern about protecting their intellectual property and

commercial viability. From the findings of this study, however, technical innovation

in construction does not appear to be entirely focussed on economic motives.

Innovation may have primarily environmental (Bossink 2007) or social foci

(Loosemore and Phua 2010). Several other factors as described in Figure 7.30

(overleaf) can at times be the driving impulse for new building products and processes

252

Figure 7.30 Vectors of SME technical innovation

The vectors are: contractor creativity; economic efficiency; solving problems on site;

OH&S benefits; end-user or social focus; environmental performance and client

demands. None of the case studies demonstrated being affected by all the listed

vectors; however, there was evidence for each vector from multiple case studies. This

is illustrated in Table 7.7 overleaf.

The company’s publically available information about their innovation, as well as

reviews and comments by the innovator and other industry authorities, have been

taken into account in determining the significance of each vector to the delivery of the

individual technical innovation.

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Table 7.7 Drivers of SME technical innovation development

Contractor creativity was a factor in all cases, unsurprisingly, as this is partly the

reason for the case study selection in the first place. Of the other factors, the

overcoming of site/project-based problem was a factor for six of the seven case

studies. This result accords with the findings of Mitropoulos and Tatum (2000) who

found ‘process problems’ as one of the four forces which drive construction

innovation. An economic focus and an OH&S focus were each noted for five of the

seven case studies. The construction industry is inherently practical and delivery

focused. Economic benefits are the most powerful driver of change diffusion

Innovation

Innovation generated by contractor creativity

Client dem

and driven

Driven by overcom

ing site/project based problem

s

Environm

ent focus

Econom

ic focus

OH

&S

focus

End-user/social focus

Rapid setting volumetric concrete

Lightweight impervious concrete blocks

Under floor water storage bladders

Cylindrical concrete formwork tube

Salt removing sacrificial render

Roll over warning system for articulated construction plant

Dry wall noise barrier

254

throughout the industry, but they are not always the primary motivation for those who

generate that change, even though economic factors can never be ignored in an

applied industry like construction. Environmental and social focuses were noted for

three of the case studies each. These areas may become greater push factors as public

awareness and government regulation increase. Client demand was identified as

important in two of the case studies. This is perhaps lower than would be expected,

but may be due to the level of originality of the innovations studied. These tend to be

driven by the internal insights of the innovator rather than market demand.

Chapter 8 of this thesis will discuss and attempt to find convergence in the findings

from the literature review, the AHP study and the case studies. Diverse factors have

been identified via these three methods and differing weightings have been noted as

resulting from the three methodologies used in this research. Some differences are

generated due to the anonymity of the AHP survey compared with the public nature

of the case studies. Nevertheless, significant agreement has been noted and some

speculative theory has been generated.

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CHAPTER 8 A MODEL OF SME TECHNICAL INNOVATION DELIVERY

Chapter 8 analyses the convergences and contradictions between the three mixed

method strands of inquiry into technical innovation by small and medium construction

enterprises. A diagrammatic model of successful technical innovation delivery is

presented.

8.1 Convergence of methodologies at factor level

The AHP study rated the five factors in the Value Tree in order of priority as:

1. Regulatory climate

2. Client and end-user influences

3. Industry networks

4. Project-based conditions

5. Company resources.

The factor priorities expressed in the AHP survey proved to be quite robust, even

allowing for a level of inconsistency in the survey answers. The anonymity of the

AHP survey meant that respondents were able to disregard any potential public

relations consequences if, for example, clients or public bodies were the object of

implied criticism. Many of the Value Tree factors were also raised in the case study

data, but the level of emphasis was different. In the case study interviews, the

successful innovators, knowing that what they said would be published, were careful

to present only positive accounts of their relationships with clients and funding

bodies.

8.1.1 Regulatory climate

Regulations were rarely mentioned specifically by the case study innovators, except

when they were speaking of past problems which they had overcome. The expense of

providing independent tests as verification of the performance of the innovation with

respect to the Building Code of Australia (BCA) and Australian Standards was

256

mentioned (three case studies). This was particularly important when an innovative

product or process was competing with a recognised prescriptive or ‘Deemed to

satisfy’ solution in the BCA. Sufficient capital to back the innovation through this

phase was, therefore, deemed to be an essential prerequisite for innovation delivery.

8.1.2 Client and end-user influences

The role of clients and end-users varied a great deal depending on the specific nature

of the case study innovation. In some cases, marketing techniques to raise consumer

awareness were critical. The use of internet websites to make the unique features of

an innovation known to the general public was practiced by all the case study

companies. In most cases, significant investment had been made in this area. Other

media such as television and radio were also used by the innovators to incite public

interest (five of seven case studies). Supportive clients were mentioned as important

in the early stages of innovation delivery by some case study innovators, particularly

those from small businesses (three of seven case studies). The use of open days to

demonstrate the innovation to industry decision makers was found to be a very

effective technique (single case study).

8.1.3 Industry networks

‘Industry networks’ were very important to some innovators, although this was not

universally so. Many innovators were heavily involved in a relevant professional

organisation or industry group (five of seven case studies). The value of industry

awards as a promotional tool was recognised by several case study innovators (five of

seven case studies). Some innovators had encountered difficulties with their

associations based on conservative attitudes to technical changes to established

practice. Malerba and Vonortas (2009) stress the importance of industry or sectoral

networks as part of the general strategy of a firm looking towards technological

advancement, increased market share and general competitiveness. Cohen and Prusak

(2001) describe how important networking is to the concept of social capital.

Progressive companies value knowledge exchange, collaboration and the reward of

being appreciated by those who understand their achievements. In general, industry

networks may have contradictory effects on innovation development and diffusion.

They can speed up the innovation delivery process for those inside the network, but

257

they can also have the effect of excluding those outside it (Malerba and Vonortas

2009).

8.1.4 Project-based conditions

Six of the seven case study innovations were driven by the need to deal with ‘project-

based conditions’ or difficulties. These ranged from lowering the likelihood of

accident and injury on site (four case studies) to introducing entirely new alternative

solutions to common construction operations (five case studies). All the case studies

were practical solutions to problems in construction management or to problems in

the wider environment.

8.1.5 Company resources

The lowest ranked factor in the AHP study was that of ‘company resources’ and the

case studies tended to confirm this rating. It may be that a prerequisite for successful

technical innovation, as described in the case studies, is the ability to draw together

sufficient economic and other resources to ensure that the business is not operating at

the edge of survival. It may also be that internal motivational factors are less

important than other innovation elements as found by Szulanski (1996). Many small

construction companies do operate under constant threat of bankruptcy, as evidenced

by business failure rates. Significant innovations do not, however, appear to be

delivered by such companies. The evidence from this study is that problems of

managing cash flow and maintaining liquidity need to be solved before an SME is

able to take on the task of developing a technically innovative product or process.

8.2 Convergence of methodologies at sub-factor level

The AHP study prioritised the fifteen sub-factors in the following order:

1. Client characteristics

2. Improving OH&S

3. Performance-based standards

4. Professional and industry associations

5. Research organisations and universities

6. Supply chain relationships

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7. Personal motivation

8. Procurement systems

9. Solving problems that occur on site

10. Available skill levels

11. Local government regulations

12. Industry standards

13. Available finance

14. Available time

15. Insurance and risk.

8.2.1 Client characteristics

The case study innovators did not mention ‘client characteristics’ as being of primary

importance in the way that the AHP study prioritised them. A possible explanation of

this may be that in the anonymous survey, it is possible to acknowledge the critical

nature of a client’s relative openness to new ideas, but in the case studies where the

innovators knew that their comments might be published, they preferred not to reflect

adversely in any way on the nature of their clients. It could also be that some of the

seven case studies represent a kind of elite among innovators and are no longer

dependent on patronage from foresighted clients. Some may have reached the state of

maturity in their innovation processes where specific patronage is no longer required.

Either way, the case study evidence is insufficient to lead the critical observer to

ignore the high rating for this factor in the survey.

8.2.2 Improving Occupational Health and Safety

‘Improving OH&S’ was given high importance in the case studies, as well as in the

AHP study. Five of the seven case studies involved a distinct focus on improving

health and safety on construction sites. Safety is likely to be a high priority for any

technical innovator as any serious safety incidents would set the process of innovation

delivery back by a large amount. In addition, the human costs of workplace industry

accidents have been widely canvassed in the construction industry in recent years

(Loosemore and Andonakis 2007). With a significant technical innovation, there is

no track record of safe practices to indicate how best to manage safety issues. As

Weick (2001 p.330) explains, accidents occur because the people who operate

259

complex systems may not be able to anticipate all the potential problems that can be

generated by those systems. Consequently, this issue must be thoroughly examined

and options tested before the new product or process is offered on the market. Even

so, safety can never be entirely assured; however the probability of misadventure may

be reduced to a level considered acceptable.

8.2.3 Performance-based standards

The third most important sub-factor ‘Performance-based standards’ was also not

mentioned directly in information collected about the case study innovations. Only

two of the seven case studies involved an innovation that competed directly with a

prescriptive or ‘deemed to satisfy’ solution in the BCA. It may be that this is another

item that is important in the establishment phase of a technical innovation, but

becomes less so over time if compliance has been well managed in the early stages.

The need for approval authorities to be up-to-date with technology development was

mentioned as an aside by two innovators. This is the issue that is specifically

addressed when new products or processes are presented via performance-based

solutions for particular projects.

8.2.4 Professional and industry associations

‘Professional and industry organisations’ were given a high priority in the AHP study

(ranked 4th). Six of seven case study businesses had significant involvement in a

relevant organisation. These included the Australian Institute of Building (AIB), the

Civil Contractors Federation (CCF), Housing Industry Association (HIA) and

Engineers Australia (EA). The innovators relied on contacts through their

membership of these organisations in order to raise awareness about their product or

process. They also relied on the kudos of industry awards distributed by these

organisations for general credibility as a successful contractor. The role of broader

industry organisations in lobbying governments was also recognised. In addition, the

innovators monitored their competition by means of contact through their professional

organisation.

8.2.5 Research organisations and universities

Four of the seven case studies had close associations with universities or other

research organisations. In some cases, this was mostly about independent testing and

260

verification, but in other cases there was ongoing collaboration with academic

researchers during the development and delivery process for the technical innovation.

Some innovators also perceived universities as possible sources of new ideas and

potential developments in their fields. There was, however, also some wariness about

the loss of confidentiality and ownership of intellectual property when external

research bodies became involved in SME product development.

8.2.6 Supply chain relationships

Case study innovators did not reveal a great deal about their ‘Supply chain

relationships’ (ranked 6th in importance by the AHP study). Like the previous

comment on ‘Client characteristics’, this may simply represent a reluctance to be open

about commercially sensitive relationships. Managing the supply chain for a

construction business involves balancing a large number of variables. Much of the

necessary information is regarded as commercially in confidence. In the anonymous

AHP survey, however, this was rated as a moderately important factor for technical

innovation delivery. It is also likely that supply chains are critical during the

establishment phase of an innovation, but become less so when things are progressing

well. Economic downturns and materials shortages may also have great impact in this

area, independent of the innovation cycle.

8.2.7 Personal motivation

‘Personal motivation’ was ranked 7th in the AHP study, although few of the case

study innovators sought to put themselves forward as the primary driver of their

innovation. Mostly they wanted to emphasise the performance of their product or

process, rather than their personal input as an innovator. None of the case study web

sites make a feature of the individual or individuals who developed the innovation to

any great extent. They emphasise the range and the advantages of the product or

process, not the person or the team. None presented themselves using words like

‘inventor’ or ‘originator’. Nor did they characterise their products as ‘revolutionary’,

although several did declare their products to be ‘ground-breaking’. Nevertheless,

some of the individual innovators did speak privately of financial security,

sustainability and social benefits as being matters which motivate their work and their

lives in general.

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8.2.8 Procurement systems and solving problems on site

‘Procurement systems’ and ‘Solving problems that occur on site’ were ranked 8th and

9th in the AHP study. Both these factors relate to the applied nature of construction

and the importance of management skills in quality project delivery. The case study

companies all present themselves in their publically available information as flexible,

responsive and reliable. Some particularly stress their abilities as problem solvers and

claim that they prefer the difficult projects, as these give them the opportunity to excel

and to surpass expectations. The detail of preferred procurement routes was not

discussed by the case study innovators. Once again, this probably relates to issues of

commercial sensitivity.

8.2.9 Available skill levels

To round out the top ten in the sub-factor rankings, ‘Available skill levels’ was a

factor for some of the case studies as well as for the survey respondents. In particular,

two of the case study businesses had programs in place to train workers in the specific

tasks involved in their technical innovation. In both these cases, the innovator

expressed the opinion that existing trade training courses through TAFE colleges, did

not produce workers with sufficient skills to deal with new products or processes, so

the innovators had chosen to deliver the training through their own business.

8.2.10 Remaining sub-factors

The remaining five sub-factors were given relatively low importance by the AHP

survey and this was largely confirmed by the case studies. ‘Industry standards’ and

‘Local government regulations’ were not mentioned in the case study information.

Local government matters are mainly of concern to those innovators dealing with

housing stock. Only one of the case studies dealt primarily in this area and that

business had very good local community involvement and therefore, good

relationships with the local Council and its building inspectors. Several of the

innovators indicated that they were the ones who set the industry standards for

performance, rather than being followers of those standards. They regarded

themselves as ‘trend-setters’. ‘Available finance’, ‘Available time’ and ‘Insurance

and risk’ all scored low ratings on the AHP survey and were not mentioned in the

case study information. Although SMEs and small businesses, in particular, are often

said to suffer badly from these constraints, the case study businesses did not exhibit

262

any such distress. As previously mentioned, this is probably due to their being elite

innovators, who have successfully managed these contingencies in order to set the

preconditions for their innovation delivery. As Drucker (2007 p.127) has pointed out,

successful innovators are not ‘risk-focused’; they are ‘opportunity-focused.’ This

may account for the successful innovators in the survey giving ‘Insurance and risk’

their lowest priority rating of any of the fifteen sub-factors.

8.3 Innovation delivery model

This research demonstrates that it is a suite of factors that enable a technical innovator

to deliver a new product or process. A new synthesis of factors can be derived from

the results of the mixed methods studies. Technical skill and a good idea do not

represent a sufficient precondition for successful innovation delivery. There must

first be a spark of a creative idea which may have any of several motives including

economic, environmental or social factors. That creative idea needs to be supported

by other skills in the areas of networking and business proficiency. This dependency

can be expressed graphically in the triangle of innovation delivery. In Figure 8.1, this

model is presented. The spark of contractor creativity is at the head of the triangle.

Stability is achieved if the creative idea is supported on a solid base of two

complementary skills. These are ‘Social networking’ and ‘Business competence’. In

the absence of either factor, or if one factor is weak, the triangle collapses. The

innovation effectively ‘goes nowhere’ and potential gains are not made. Drucker has

stressed that “Successful innovators use both the right and the left sides of their

brains” (Drucker 2007 p.123). It is contended that cases of successful innovation are

likely to fit this stable triangle format. Particularly for SMEs, the support factors of

social networks and business skills must be in place, as SMEs are unlikely to have the

resources to deliver significant innovations entirely ‘in-house’ and unaided. As

Bessant and Venables (2008) state “innovation is a process – an extended set of

activities that translate new knowledge into something of value” (Bessant and

Venables 2008 p.3). They go on to state that innovation involves the weaving

together of two different strands: the supply strand of knowledge about possible

means; and the demand strand of knowledge about needs. Successful innovators

know this and they avoid relying on narrow perceptions of acceptable practice, when

263

alternatives are available for those who want to take advantage of all available

opportunities. Successful innovators recognise the complexity of the change process.

A successful innovation, however, also needs to be simple and focussed. It should

produce a specific end-result. Drucker says that the best praise an innovation can

receive is the response of “Why didn’t I think of that?” (Drucker 2007 p.123).

Without this acknowledgement from both competitors and customers, a good idea is

likely to remain unrealised. For this reason, all the successful innovators in this study

actively courted wider industry recognition and acceptance of their products and

processes. They had to balance the need for product awareness with the imperative of

protecting their intellectual property. Innovations usually start out as relatively small

investments in changes to existing practice. This allows the time for adjustments and

reassessments to be made before large scale and radical innovation is attempted.

Finally, all the innovations studied for this thesis aimed at achieving a position of

leadership in their particular field. Whether this leadership aspiration extended to

achieving market domination, or simply to successfully occupying a particular niche

in the market, depended on the nature of the innovation. All the innovators studied

wanted to achieve successful innovation delivery themselves, rather than altruistically

creating opportunities for others to exploit. This was true of innovations that were

motivated by environmental and social issues, as well as those with a primary

economic focus.

As Rogers (2003) noted, getting a new idea adopted is difficult even when it has

obvious advantages. The time frame may be long and there may a need for multiple

re-innovations to adapt to changing demands.

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Figure 8.1 A model of technical innovation by construction SMEs

The particular virtue of SMEs is flexibility, due to their reliance on the leadership of

‘hands on’ individual enthusiasts rather than on the collective choices of Boards of

Directors and other corporate structures, which may be at some distance from the

company’s core business. In the wider international economy, it is reported that many

of the most successful businesses of today were created by individuals, who

tenaciously pursued ideas that had been rejected by the decision making bureaucracies

in large organisations (Acs et al. 2009). Examples cited include Apple Computer,

Xerox, Microsoft, Google and Genetech (Acs et al, 2009 p.8). The power to have a

real influence on the direction that a business takes is one of the factors that attract

creative individuals to the running of small and medium-sized businesses. They are

less likely to be restricted by the conservative attitudes of over-cautious and multi-

layered management systems which sometimes characterise large firms. Indeed,

noted innovation theorist Baumol (2004) found revolutionary technical breakthroughs

to be the specific province of small firms, while large firms specialise in systematic

and incremental innovation.

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The downside of this picture is that SME business owners may have trouble attracting

the investment and the skill base necessary to deliver their innovative ideas. If the

creative individual is not also an entrepreneur and an adept business manager, then it

is necessary acquire these skills, or to form alliances with individuals who already

have them. This may happen by self-education, or from the formation of strategic

alliances with people or organisations that possess the necessary expertise. This is the

core idea behind the model presented in Figure 8.1. The creative contractor must

acquire by one means or another, the necessary skills and supports at the base of the

triangle if any creative technical ideas are to be translated into successful marketplace

innovations.

This gives context to the model presented in Figure 8.1, which is based on the

Schumpeterian perspective of entrepreneurial leadership, albeit by small and medium,

as well as by large businesses (Schumpeter 1942). However, the model also

acknowledges the significance of problem solving pull factors, as well as the social

environment via networking. It is not possible from the study carried out for this

thesis to determine the relative impacts of the individual compared with the

supporting environment. It is possible, however, to say that there is some congruency

between the factors found to be significant and the larger economic theory about the

generation of technological change at the level of the individual enterprise.

It is for this reason that the proposed model of technical innovation (Figure 8.1)

acknowledges the importance of the individual, but also maintains the importance of

networks with other individuals to support creative problem solving. In seeking to

understand how organisations can be effective generators of ideas, Weick (2001)

stresses the need for an appreciation of “the social, interpersonal, multiple actor

quality of coordinated activity that characterises most task performance” (Weick 2001

p.x). This is certainly the case in the construction industry. Almost all construction

endeavours involve multiple actors. One person alone may be able to build a log

cabin, but almost anything larger than that requires several pairs of hands for a

successful outcome. In other words, while individuals can have enormous impact,

they mostly cannot do so unassisted. Consequently, the model of technical innovation

presented here incorporates the importance of social networks at a level equal to that

of economic and resource factors. Similarly, almost all construction endeavours

involve profit as a motivating factor and innovation is a well recognised source of

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competitive advantage in a market economy (Keen 1997). Consequently, the business

competency leg of the triangle also cannot be neglected.

It must be noted that the quantitative study for this thesis found relatively few

statistically significant differences among the identified high-level technical

innovators. Factors such as company size, innovation type and whether or not the

innovation was patented had less impact on the innovation delivery process than was

anticipated. Consequently, the process of successful delivery of a technical

innovation can be seen to have outweighed the individual characteristics of the SME

innovators, at least to some extent. The innovators studied had managed to balance

the three legs of the innovation triangle presented in Figure 8.1 and this, in itself,

makes their experience unusual for a construction SME where business failure is

commonplace. Nevertheless, the high-level innovator’s experience has potential

lessons for others in the industry who seek to improve innovation performance on

several levels.

Extrapolating from the model presented as well as the outcomes of the quantitative

and qualitative studies, the final chapter of this thesis will attempt to draw out the

research outcomes in terms of recommendations for the various interest groups

involved in the construction industry which have an interest in lifting the rate of

technical innovation.

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CHAPTER 9 CONCLUSIONS AND

RECOMMENDATIONS

Chapter 9 identifies the major outcomes of this research in terms of advice for

aspiring innovators, industry umbrella bodies, professional organisations, research

institutions and government regulators. Possible areas of future research in this field

are also identified.

9.1 A matter of pre-existing resources?

While the detailed storyline of the delivery of each successful innovation is likely to

be unique, nevertheless, the distilled collective experience of SME technical

innovators in the construction industry has many potential lessons for the industry as a

whole, as well as for companies specifically looking to improve their own innovation

performance. Large businesses may have a level of slack resources which they can

choose to deploy towards finding solutions for technical problems. Indeed, this is the

traditional economic theory view of the generation of invention and innovation, where

it is largely considered to be impractical for small businesses to generate innovations

of significant originality (Schumpeter 1942). It is true that SMEs are rarely in the

happy situation of having a pool of unused resources which may be allocated towards

innovation. Nevertheless, some SMEs do manage to go against the general trend and

are able to generate, develop and deliver significant technical innovations. Often,

they are able to do this because of the level of control that the chief decision maker

may have in such businesses. Unlike the practice in many large companies, it is

probably not necessary for the business owner or manager to seek several levels of

approval from within the organisation. The SME individual therefore, has greater

power to follow his or her own insights and set his or her own goals. Many of the

survey respondents commented that they value this sense of autonomy and feel that it

enables them to make significant changes to standard practice. Speaking of the wider

economy rather than specific industries, Acs and Audretsch (1990) demonstrated that

small firms were featuring more prominently in the delivery of technological change

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at the end of the twentieth century, although this was against the ‘common wisdom’

of prevailing economic theory. More recently, Dodgson et al. (2008) has reported

that SMEs often have an ‘external orientation’ that enables them to be receptive to

working with other firms, research organisations and universities. Flexibility and

adaptability can, in part, make up for a lack of initial resources. Connections with

external bodies can assist the SME through the difficult start-up phase of technical

innovation delivery. The focus needs to be on delivering value and building

competitive advantage. Under these circumstances, SMEs are fully capable of

generating and delivering significant technical innovations (Dodgson et al. 2008,

p.131).

Although improving the rate at which construction companies develop new solutions

is a useful industry goal, the diversity of the industry probably limits the effectiveness

of simple ‘one size fits all’ programs on construction innovation. An open-ended

structure in the regulation and approval system appears to be needed as a prerequisite

for successful innovation. Flexibility in procurement systems and discretionary

encouragement by repeat clients with their own innovative practices are likely to

prove useful aids to innovation performance. Industry networks have a clear role to

play in supporting the efforts of innovators. Real and effective change is, however,

largely driven by the enthusiasm of talented individuals, who simply refuse to accept

that there is only one solution to a given problem. These ‘out of the box’ thinkers

combine technical know-how with an understanding of what the market wants and

how best to deliver it. An industry climate that provides scope and opportunity for

such people to develop and prosper is the primary prerequisite for improved technical

innovation rates.

In spite of perceptions that the construction industry can be slow to innovate, this does

not alter the fact of the accelerating rate of technological change in our wider society.

While encouraging the embracing of new technology, Keen (1991, p.211) stresses

that this is not a matter for ‘change management’, because change cannot be managed

when, because of the accelerating rate of change, there is no longer a status quo. In

any case, such change management strategies are necessarily reactive rather than

proactive. The preferable situation is that managers should seek to align their

business strategies with the process of change occurring in the wider society. This

desired alignment is the basis of the advice to stakeholders given below.

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In keeping with the research intent outlined in Section 1.10 of this thesis, ‘to perform

a systematic study of successful construction SME innovations and the strategies

adopted for their delivery, with the intention of yielding useful lessons for other

businesses wishing to improve their own innovation performance’ (p.32) the

following sections will outline the thesis findings for such businesses, as well as, for

other interested parties.

9.2 Findings for aspiring innovators in SMEs

Technical innovation is not limited to radical, paradigm-altering inventions. It may

include small changes and modifications to existing practice which have the effect of

improving the efficiency of project delivery. Furthermore, technical innovation may

be driven by several different motives. These include economic prosperity,

environmental performance or social improvements, such as safety-driven

technologies. Developing a ‘Technology strategy’, as advised by Shane (2009), is

important for any business, as it is the major source of value creation, as well as a way

of satisfying needs not previously met, and thereby generating competitive advantage

(Shane 2009 p.7).

The evidence from this study is that aspiring innovators who are decision makers in

construction industry SMEs should be aware of the importance of the two supporting

factors at the base of the technical innovation delivery model in Figure 8.1; namely

social networks and business competency. Such managers should seek to establish

good, cooperative relationships with repeat clients, investors, end-user representatives

and supply chain associates. They should join and become active members of

appropriate industry or professional organisations. This serves multiple purposes. It

provides a possible sounding board for innovative ideas that are not fully developed.

It enables the publicising of technical innovations among those most likely to be

interested in adopting them. It also enables an SME to have contact with its

competitors. This is not about industrial espionage, but rather about the reflective

monitoring of competitors’ activities in order to understand and constantly measure

the impact of different strategies on the success of innovation delivery. Additionally,

SME managers need to make contact with research and testing organisations, because

even when an innovation is entirely generated in house, it will almost inevitably

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require verification by independent authorities in order to convince a sceptical

marketplace of the utility and safety of the innovation concerned.

The company manager with a great idea for a potential technical innovation or one

with a problem that needs to be solved (either a push or a pull issue), should not

concentrate exclusively on the idea or problem itself. It is important that sufficient

attention is also given to establishing a business plan for the management of the

company during the development and delivery process of the innovative solution.

Lack of adequate capital and poor cash flow management can ensure that there is no

successful outcome for even the brightest of bright ideas. This area must be

addressed early in the process by developing the appropriate expertise or by acquiring

it from elsewhere; otherwise the likelihood of success is poor.

Potential innovators should scan available market options with an eye to potential

innovation opportunities. They should ‘cast their nets widely’ and not confine their

searches according to too many preconceptions. There are lessons to be learned from

other industries and other spheres of activity.

SME managers who wish to improve their firm’s innovation performance should be

heartened by the histories of the innovations described in this thesis. It is clear that

SMEs are capable of delivering significant technical innovations. They should not

leave the field of research and development to the large companies. The enthusiasm

and insight of those in SMEs who are ‘close to the action’ in the building process can

certainly deliver new solutions to the industry’s problems, both now and in the future.

9.3 Findings for industry bodies and professional organisations

Both the AHP study and the case studies undertaken for this thesis signalled that

networking by means of professional organisations and industry bodies is particularly

useful for SMEs. There was also some indication that this is especially so for small

businesses. SME managers certainly used their association memberships for business

and social contacts, but their importance was much broader than this basic

networking. Innovators specifically mentioned in their open-ended comments, the

value of professional bodies as lobbyists who could influence legislation and

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Australian Standards. This role is one that the organisations may be well advised to

stress in their recruitment drives among SMEs.

Keeping the wider industry up-to-date with innovative developments in their field was

clearly seen as an expected role for professional associations. Local and national

awards were valued by innovators for these purposes. Peer recognition was

specifically sought and valued by all the participants in this study. Furthermore, peer

recognition was seen as a significant marketing advantage for a new product or

process. There is also a potential role for industry bodies in providing

‘entrepreneurial apprenticeships’, or other structured guidance, to potential innovators

who have an abundance of good ideas, but lack the business skills to deliver them in

the marketplace. This has been demonstrated to have worked in other industries (Acs

1999).

The attitude of the innovators in this study was, however, not entirely positive

towards professional and industry groups. Some expressed the belief that these

bodies were sometimes captured by particular groupings, who operated for their own

benefit rather than that of the larger industry. It may be useful for the bodies

themselves to consider ways of countering both the perception and the actual

possibility of their being captured by special interest groups within the organisation.

9.4 Findings for researchers

Several innovators in this study described the importance of relationships they had

developed with universities or other research bodies. In a few cases, this amounted to

a genuine research partnership. This was particularly true for the more ‘cutting edge’

innovations. Others, however, saw traditional academic research as something that

had no relevance for their organisations. Their inventions or innovations were largely

generated and developed in-house. The role of independent testing for the finished

product was acknowledged, but there was little regard for research partnerships. The

problems expressed about university researchers included: a lack of concern for the

economic imperatives for businesses; the issue of confidentiality; and the different

time frames imposed by academic publication rules.

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If university researchers are to play a more active role in assisting innovation by

construction SMEs, it will be necessary for the different priorities of applied and

academic research to be carefully negotiated. University researchers need to be aware

of the scruples some SMEs have about the possible loss of control and confidentiality

of their innovation, once research bodies become involved. A more engaged and

cooperative approach is needed when dealing with industries like construction as

opposed to research in the traditional sciences. Something along the lines of the

Constructing Excellence Clubs in the UK may be a useful strategy (Constructing

Excellence UK 2010).

The possible role of universities as ‘innovation brokers’ and as centres for intra-

industry collaboration by SMEs is something that has not been much addressed in the

Australian context. These strategies have the potential to assist overall industry

performance and provide mutual benefits for the participants from industry and

academia alike. If, as has been suggested, inventive solutions and eventually market

delivered innovations can arise when different individuals with separate bodies of

knowledge are brought together to address a problem, closer relationships between

industry and academic research are a potential source of new ideas which may be of

mutual benefit.

9.5 Findings for governments and regulators

Governments and regulators should not fall into the trap of believing that innovation

is the exclusive province of large firms. While small and medium construction

businesses in the aggregate do not appear to be particularly research intensive or

innovative, many exceptions to this rule exist. There is considerable benefit to be

gained for the wider economy, from encouraging SME innovators. Indeed, some

researchers have found that small firms have the advantage in generating innovation

in industries that utilise a high component of skilled labour (Acs and Audretsch

1990).

A variety of attitudes to the role of governments and regulators were expressed by the

innovators studied for this thesis. Some innovators praised government institutions

such as the Australian Trade Commission (AUSTRADE) and the Australian

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Technology Showcase. These were perceived to be helpful in disseminating the

message about a technical innovation to a wider audience than the innovator could

reach unaided. Support was quite widespread for an ongoing government role in this

area. There was also some support for tax concessions for research, but much

opposition to the ‘red tape’ and bureaucracy that controls such concessions.

Governments may need to prioritise this issue, as there is a perception that innovators

are not able to access some of the available government support because of the time

pressures involved in running an SME.

The question of patents and patent administration is of critical importance to high end

SME innovators. The cost of taking out and defending patents can, at times, be

prohibitive for small firms. The growth of litigation over patents is a factor which, if

left unchecked, may become a significant brake on SME innovation of the more

radical kinds. Government authorities need to monitor this situation carefully, as it

has the potential to have great impact on industry development.

A difference of opinion was found with regard to the role of building regulations.

The findings from the AHP survey are equivocal when it comes to the importance of

performance-based standards for construction innovators with high variance being

shown on the priority rating for this factor. In the sample surveyed, ‘product

innovators’ expressed support for the performance-based strand of the Building Code

of Australia, but ‘process innovators’ did not see this as relevant or significant to their

innovation delivery. It may be that this is simply a reflection of whether or not the

innovation had a direct competitor among ‘deemed to satisfy’ or traditional

prescriptive standards. This was unlikely to be the case for those innovators not

involved in residential construction. The cost burden of regulation compliance for

small business was mentioned as a barrier to innovation by SMEs generally. This

area deserves further attention.

The prevailing assumption among governments in market economies has long been

that technological change is generated primarily by large firms and by specialist

research institutions (Acs and Audretsch 1990; Acs 1999; Acs et al. 2009). For a long

time, the role of small firms and entrepreneurship has been regarded as fairly

insignificant in the innovation process (Acs et al. 2009, p.3). This study provides

some support for the contention that this is not necessarily so. With appropriate

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support, even SMEs in traditional industry sectors like construction, may prove able

to generate, develop and deliver significant changes in standard practice. Government

policies should, therefore, avoid excluding this option by the way they frame

incentives for research and development. Technical innovation remains a central

component in the generation of new economic value. As such, a certain level of

open-mindedness to new ideas independent of their source, should guide those who

set the parameters for research support (Shane 2008).

9.6 Contribution of this research

This thesis has attempted to address the research question of ‘What are the factors

which affect the successful delivery of technical innovations by construction industry

SMEs in Australia?’ The researcher has taken a mixed method approach, because the

research field is comparatively immature and an exploratory, rather than a definitive

process was considered to be more likely to yield useful conclusions. The

quantitative and qualitative strands of the research did, indeed, yield results that were

both complementary and divergent for different factors. The sample sizes are small,

but necessarily so, because of the strict eligibility criteria for the study. While caution

needs to be exercised in extrapolating the results from this study to SMEs generally,

the study does yield significant insights into the processes undertaken by successful

SME innovators. The results presented here can inform future studies in the area of

SME innovation delivery.

The research undertaken for this thesis has identified ten factors that resist change and

innovation in the construction industry. As listed in Chapter 1, these are:

1) The proliferation of many very small businesses who have difficulty

surviving let alone introducing innovations;

2) Insecurity of much employment in the industry;

3) The tacit and individualised nature of much of industry experience, skills

and knowledge;

4) Lack of expertise in, and value placed on, human resource management;

5) Contractual risk shifting towards those who can least afford to bear the

cost;

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6) Its temporary project-based nature;

7) Procurement systems which stress lowest price rather than best value;

8) The complexity and lack of integration in existing industry supply

chains;

9) Resistance to standardisation and modularisation because of the inherent

diversity of industry participants;

10) Self-perceptions of the industry’s nature which limit both top-down and

bottom-up innovation.

Despite the existence of these impediments, this thesis has reported on the activities

of successful SME innovators who have been able to overcome this cultural

background. While these successful technical innovators may be atypical with

respect to other construction SMEs, nevertheless, their experience can yield some

useful lessons for all construction companies. Five principal factors that enabled

these SMEs to deliver their technical innovations have been identified as:

1) Project-based conditions;

2) Client and end-user influences;

3) Regulatory climate;

4) Industry networks;

5) Company resources.

Contributing sub-factors have also been identified and prioritised. Exemplars of

successful technical innovation delivery by construction SMEs have been described

as an illustration of good practice.

The principal qualitative finding of this research is that specific areas of expertise

beyond that of construction technology are of critical importance to the successful

delivery of a technical innovation in construction. In other words, superior technical

skills are a necessary, but not a sufficient condition for the effective delivery of a

technical innovation. Soft skills relating to people management and networking are

significant to the delivery process, as are a high degree of economic understanding,

marketing and business planning skills. A great idea for a technical innovation is not

enough in itself to produce a delivered technical innovation. The great idea needs to

be supported by adequate investment, effective research development and testing,

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strong linkages with intra-industry groups and timely delivery into the market. The

successful innovators studied in this research have all managed, in one way or

another, to acquire this diversity of skill-sets. They may not have had the appropriate

skills or training at the commencement of the innovation process, but they either

formed connections with people who did or they expanded their own skill-set to meet

the need. The high-level innovators in the study appear to form a distinct group

among SME construction companies, as signified by the fact that they have largely

overcome the limitations caused by internal company resources.

A secondary finding is that industry bodies and government departments are able to

assist overall industry performance by providing access to advice on achieving

competence in business and human resource management to SME managers who may

not already be in possession of such skills. This research supports the idea that

investment in such services would have a positive effect on industry innovation and

may lead to a more efficient and forward looking construction sector. Given the

importance of the sector to the overall economy, as well as to the quality of life of the

human beings who live and work in the built environment, a better performing

construction sector would have benefit far beyond the limited bounds of the industry

itself.

The work undertaken in this thesis specifically develops the theory of innovation by

providing evidence that, contrary to classical Schumpeterian theory, construction

SMEs are capable of generating and successfully delivering significant technical

innovations. Furthermore, this research stresses the critical significance of non-

technical inputs in the delivery of technical innovation by SMEs. When large

companies generate and develop a technical innovation, it is likely that they will call

upon specific expertise in the fields of capital investment, market research,

intellectual property and product placement. The smaller the business, the less likely

it is that such expertise will be available ‘in house’ or via existing relationships.

Consequently, the vital importance of making these skills available to potential SME

innovators is the chief contribution this thesis has to make to the general academic

discourse on innovation in the construction sector.

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9.7 Summary of outcomes from the research objectives

The six research objectives identified in Section 1.2 of this thesis have been met in the

following ways:

• Identify a series of possible factors which impact on the successful delivery of

a technical innovation by a construction SME; The possible factors were

identified from a review of published literature and synthesised into the Value

Tree presented on p.102 in Chapter 5 of this thesis.

• Prioritise those factors via a structured survey of successful SME innovators;

An AHP survey of 21 established technical innovators was undertaken and the

priorities generated were presented in Table 6.1, p.132. The method is able

establish robust priorities, even in the face of some inconsistency in human

value judgements.

• Illustrate the survey outcome by descriptive case studies of successful

innovation delivery; Seven case studies have been presented in Chapter 7.

These represent a variety of different kinds of technical innovation. They

demonstrate that a relatively high level of originality as defined in the Oslo

Manual (2005) can be achieved by SME construction firms.

• Provide encouragement for interested parties such as other construction

SMEs who are considering introducing a technical innovation; The case

studies, in particular, provide this encouragement, as they illustrate some

occurrences of strategic decision making leading to successful innovation

delivery. The strategies employed, such as the use of industry open days, an

emphasis on appropriate in-house training and the use of the broader media to

publicise new ideas, are all possible options for aspiring innovators.

• Provide advice for government bodies, professional and industry associations

who wish to foster a culture of innovation in the construction industry;

Sections 9.3 and 9.5 of this chapter specifically address ways that innovation

performance can be assisted by interested parties in government and the wider

industry.

278

• Indicate possible strategies for universities and other research institutions on

how they can best contribute to SME innovation. Section 9.4 of this chapter

raises specific issues for academic researchers. In particular, university

researchers need to be aware of the different priorities and time frames under

which SMEs operate and be more cooperative in their dealings with small

business and potential innovators.

These objectives having been delivered, attention turns to areas of potential future

research.

9.8 Future research directions

Several avenues suitable for further inquiry are opened up by this research. Firstly,

the documentary data collected for this thesis is suitable for encoding with text-

matching software (NVIVO9). This further avenue of qualitative research may yield

new insights into the behaviour of technical innovators. It will be undertaken in the

light of the established patterns of innovation generation and diffusion as defined by

Rogers (2003).

Secondly, as this research only looked at successful innovators, there remains the

question of the factors affecting aspiring innovators. This includes those who may

have been less than successful in the past. These groups may, or may not, prove to

have similar motivations. Research on a larger scale, taking a representative sample

of SMEs and studying what they believe is necessary to lift their innovation

performance, has considerable potential for future economic value.

Thirdly, as some significant differences were found between small and medium-sized

innovating firms, albeit less than expected, these differences could be tested using a

larger Australia-wide sample. It may be that small businesses require a particular

level of support, beyond that necessary for medium-sized businesses in order to

deliver their innovative ideas to the market. Whether this support is best provided by

government departments themselves, or primarily by professional and industry bodies

with some government subsidy, is another question for further research.

279

The particular needs of micro-businesses have not been addressed in this thesis, but

potentially the gains to be made from researching this area are very large, due to the

numbers of businesses involved. During the search for non-micro SMEs who had

delivered technical innovations, some micro-businesses were identified. They could

form the core of future research into the grouping.

Data collection for this thesis was geographically restricted to Sydney and the

surrounding region. Future research along the same lines in other areas could

potentially examine the effect of innovation clusters, as well as whether interaction

between high-level innovators assists innovation delivery. Innovation has been

widely reported to occur in clusters both temporally and spatially (Feldman and

Kogler 2008). A broad scale study to observe these effects in the Australian context

is a potential future direction for innovation research. It may be that networking

between innovators can provide the spark for new and improved technical

innovations. This phenomenon has not yet been closely studied in the context of the

Australian construction industry.

Finally, the matter of the differing priorities of innovating firms at different stages of

innovation delivery, could be the subject of much further inquiry. This matter was

raised by the innovators themselves, during the open-ended survey comments. The

effectiveness of government assistance programs targeted at innovation could greatly

benefit from a rich-textured understanding of what the innovators need at different

points in the innovation cycle.

9.9 Conclusion

Like all entrepreneurial activity, innovation delivery focuses on the recognition and

pursuit of opportunity. Individuals with foresight can make significant contributions

towards the development of new and more efficient technical solutions to industry

problems. It is particularly true in the construction industry, that those who deal day-

to-day with construction project delivery, are likely to have ideas about how products

and processes could be improved. Provided that appropriate support is available, the

flexibility and responsiveness of SME structure, has the potential to allow such ideas

to blossom and develop into realistic solutions. The policy settings of governments

280

should make allowance for this possibility. Certainly, regulators and other

government bodies should avoid putting unnecessary obstacles in the path of potential

SME innovators.

Research into construction SME technical innovation has the potential to generate

spill-over innovations, which may significantly improve the performance of the

construction industry in economic terms, as well as, on environmental and social

parameters. Modern economic theory acknowledges the significance of motives other

than the simple ‘bottom line’ of economic benefit. While some economic theory has

suggested that research and innovation should remain the province of large businesses

with surplus resources to devote to speculative ventures, this is not always the case.

This research has shown that innovations motivated by pressing economic,

environmental and social issues, can sometimes be generated by SMEs, even in a

conservative industry like construction. As well as benefiting these likely future

priority areas, technical innovation in construction can indirectly make an important

contribution to the prosperity and the standard of living of Australians generally.

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314

APPENDICES

Appendix 1 – Survey Script

Question 1:

Thinking of your most successful technical innovation which was more important in assisting the delivery process company resources or client and end-user inputs?

Company resources Client end-user influences

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9

Much more important More important Equal value More important Much more important

Question 2:

Thinking of your most successful technical innovation which was more important in assisting the delivery process company resources or project-based conditions?

Company resources Project-based conditions

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 3:

Thinking of your most successful technical innovation which was more important in assisting the delivery process company resources or industry networks?

Company resources Industry networks

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


315

Question 4:

Thinking of your most successful technical innovation which was more important in assisting the delivery process company resources or the regulatory climate?

Company resources Regulatory climate

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 5:

Thinking of your most successful technical innovation which was more important in assisting the delivery process client and end-user inputs or project-based conditions?

Client end-user inputs Project-based conditions

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 6:

Thinking of your most successful technical innovation which was more important in assisting the delivery process client and end-user inputs or industry networks?

Client end-user inputs Industry networks

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 7:

Thinking of your most successful technical innovation which was more important in assisting the delivery process client and end-user inputs or the regulatory climate?

Client end-user inputs Regulatory climate

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


316

Question 8:

Thinking of your most successful technical innovation which was more important in assisting the delivery process project-based conditions or industry networks?

Project-based conditions Industry networks

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 9:

Thinking of your most successful technical innovation which was more important in assisting the delivery process project-based conditions or the regulatory climate?

Project-based conditions Regulatory climate

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 10:

Thinking of your most successful technical innovation which was more important in assisting the delivery process industry networks or the regulatory climate?

Industry networks Regulatory climate

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


317

Second level comparisons

Question 11:

Thinking of your most successful technical innovation which was more important personal motivation or available finance?

Personal motivation Available finance

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 12:

Thinking of your most successful technical innovation which was more important personal motivation or available time?

Personal motivation Available time

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 13:

Thinking of your most successful technical innovation which was more important personal motivation or available skill levels?

Personal motivation Available skill levels

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


318

Question 14:

Thinking of your most successful technical innovation which was more important personal motivation or insurance and risk?

Personal motivation Insurance and risk

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 15:

Thinking of your most successful technical innovation which was more important available finance or available time?

Available finance Available time

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 16:

Thinking of your most successful technical innovation which was more important available finance or available skill levels?

Available finance Available skill levels

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 17:

Thinking of your most successful technical innovation which was more important available finance or insurance and risk?

Available finance Insurance and risk

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


319

Question 18:

Thinking of your most successful technical innovation which was more important available time or available skill levels?

Available time Available skill levels

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 19:

Thinking of your most successful technical innovation which was more important available time or insurance and risk?

Available time Insurance and risk

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 20:

Thinking of your most successful technical innovation which was more important available skill levels or insurance and risk?

Available skill levels Insurance and risk

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 21:

Thinking of your most successful technical innovation which was more important procurement system or client characteristics?

Procurement system Client characteristics

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


320

Question 22:

Thinking of your most successful technical innovation which was more important supply chain relationships or solving problems that occur on site?

Supply chain relationships Solving problems that occur on site

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 23:

Thinking of your most successful technical innovation which was more important supply chain relationships or improving OH&S?

Supply chain relationships Improving OH&S

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 24:

Thinking of your most successful technical innovation which was more important solving problems that occur on site or improving OH&S?

Solving problems that occur on site Improving OH&S

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 25:

Thinking of your most successful technical innovation which was more important professional and industry associations or research organisations and universities?

Professional and Industry associations Research organisations and universities

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


321

Question 26:

Thinking of your most successful technical innovation which was more important performance-based standards or local government regulations?

Performance-based standards Industry standards

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 27:

Thinking of your most successful technical innovation which was more important performance-based standards or industry standards?

Performance-based standards Local government regulations

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


Question 28:

Thinking of your most successful technical innovation which was more important local government regulations or industry standards?

Industry standards Local government regulations

9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9


322

Appendix 2 - Participant Information Sheet

324

Appendix 3 – Participant Consent Form

325

Appendix 4 – International definitions of SMEs NOTE: The citations in this appendix are included in the main reference list.

Context

The Australian construction industry is characterised by having many small

businesses and sole operators (Australian Bureau of Statistics 2004). These

businesses account for the majority of industry employment and a significant, though

lesser, slice of industry contribution to Gross Domestic Product (de Valence 2010a).

The tendency for the construction industry to contain many small businesses is a

widely studied phenomenon in several different economies. Examples include Revell

and Blackburn (2007) in the United Kingdom; Hassanien and Adly (2008) in Egypt;

Tang et al. (2007) in China; Hua (2007) in Singapore; De Jong and Vermeulen (2006)

in the Netherlands; Navickas et al. (2006) in Lithuania; Acar et al. (2005) in Turkey;

Jaafar and Abdul-Aziz (2005) in Malaysia; Maes et al. (2005) in Belgium; Yavas et

al. (2004) in the United States; and Eyiah (2001) for several parts of Africa. The only

notable exceptions to this rule appear to be some of the transition economies of the

former USSR and Eastern Europe (Istomina 2005; Orlov 2003; Khodov 2003) where

SMEs still represent a relatively small proportion of employment and GDP as a result

of the predominance of government owned enterprises.

The widespread nature of construction SMEs may be due to the relatively low entry

barriers to establishing a construction business and to the traditional craft and trade

base of much construction industry activity, especially in the housing sector. While

the potential for economic growth at the very small or micro-business end of the

spectrum is by definition large, it can be contended that the limitations on what can

easily be achieved are equally large. As a result, this thesis has opted to exclude

micro-businesses employing less than five people from its study area. It has instead

focussed on the small to medium sector other than these micro-businesses.

Businesses employing five or more people (upper limit 200 to be discussed below)

represent a considerable percentage of the industry in gross turnover, contribution to

GDP and employment (ABS 2004) and their potential for efficiency growth is both

significant and achievable. Consequently, it is necessary to statistically define the

population of businesses in the classification area of the study.

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Definitions of SMEs

The definition of what constitutes a Small and Medium Enterprise varies a great deal

depending on the nature of the national economy and the industry sector concerned.

Most definitions are based on number of employees though annual turnover,

capitalisation and company structure are also included in some definitions (Loecher

2000). In general, larger economies such as the United States of America (USA) set

the maximum bar higher as regards inclusion in the category of small business. The

European Union has an agreed definition and the World Bank has attempted to define

the term in an international context, including both developed and developing nations.

In Australia, the Australian Bureau of Statistics has its own definition which varies in

the detail from the other definitions and is based on data collected through the system

of Australian Business Numbers (ABNs).

USA definition

The American Government’s Small Business Administration has existed since 1953

as an independent agency of the federal government. It has a general definition of a

small business for research purposes as “an independent business having fewer than

500 employees” (American Small Business Administration 2010). The qualifying

descriptor “independent” is included to ensure that wholly owned subsidiaries or

affiliates of larger companies are excluded whatever their company structure may be.

To be eligible for various assistance packages, the business must be independently

owned and operated and it must not be dominant in its field of operation. When

looking at a specific industry, factors such as the structure of the industry, the degree

of competition, average firm size, start-up costs and existing entry barriers are

considered (American SBA 2010). The primary qualifying factor may be either

employee numbers or gross annual receipts according to industry classification.

Employee numbers are defined as the average number employed over the preceding

12 months and part-time or temporary employees are counted as the same as full-

time. Gross annual receipts are defined as ‘total income’ plus ‘cost of goods sold’.

Net capital gains and taxes collected such as sales tax are not included in this

definition. For the construction industry, the current definition is one of gross receipts

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(though employee numbers have been used in the past). The qualifying total as at

October 2010 is $US33.5 million in gross receipts for the previous twelve months.

The terminology of SME is not used in the American regulatory context. Companies,

partnerships or other entities are defined as either ‘small’ or ‘not small’. The US

definition of a small business would include many businesses considered both large

and medium-sized in other jurisdictions, especially in developing countries. It

contains important caveats to exclude companies who might try to structure their

operations by separating them into a number of apparently independent companies,

but retaining control in the hands of the parent organisation. There are significant

penalties for attempting to gain benefit by misrepresentation of company size.

European definition

The European Union has had a standardised definition of an SME since 1996

(Loecher 2000). The quantified upper limits as reported in 2000 were:

• Less than 250 employees;

• Maximum 40 million Euro annual turnover;

• Maximum 27 million Euro annual balance sheet total (Loecher 2000).

The maximum monetary qualification limits are in both cases significantly more than

the American limits. This may be largely due to the inclusion of medium-sized

businesses which the American system excludes.

The European definition also distinguishes between different categories of SME. The

micro-business category is defined as having up to nine employees. The small

category is defined as having between 10 and 49 employees and the medium category

as having between 50 and 250 employees. However, as in the USA, it is

acknowledged that there needs to be consideration of factors other than the simple

quantitative factors. The issue of independence and ‘unity of leadership and capital’

also comes into the question. Consequently, a five point qualification list has been

recommended:

• Less than 250 employees;

• Maximum 40 million Euro annual turnover;

• Maximum 27 million Euro annual balance sheet total;

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• Minimum of 75% of company’s assets owned by company management;

• Owner managers or their families manage the company personally (Loecher

2000).

This last point brings up one of the factors which tend to distinguish SMEs from

larger companies. There is usually a nexus between ownership and management. It

is not within the scope of this thesis to test this proposition, but anecdotally it does

appear that most construction SMEs tend to be based on individual or family

ownership.

World Bank definition

A research report commissioned by the World Bank began looking into the nature of

SMEs across the globe in 2003 (Ayyagari et al. 2003 & 2007). The report collected

data from 76 countries using local definitions of SMEs. Both the formal and informal

sectors were included and this made a significant difference to the results in less

developed economies. The upper limit for an SME ranged between 100 and 500

employees, depending on the national definition, with the most common limit being

250 employees. The more developed countries tended to elect the higher range upper

limit although this was not exclusively so. The inclusion of the informal economy in

the figures allowed for a broader capture of the proportion of economic activity

generated by SMEs. It was determined that SMEs constitute most of the economy in

developing nations other than in the transition economies of the former communist

bloc where SMEs are still uncommon. Establishment costs, property rights

protections and efficient credit information sharing were the principal factors that

affected the relative size of the formal SME sector. High costs and inefficient

governance systems tended to contribute to a larger informal economy populated

principally by SMEs.

Australian definition

The Australian Bureau of Statistics has been collecting specific data on SMEs since

the early 1990s. The definition of an SME has varied in the time since statistics were

first separately kept. Initially 100 employees was the cut-off limit, but since 2003 this

has been raised to 200 employees. The SME sector is further sub-divided as between

20 and 200 in medium business and up to 19 employees in small business, with a

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further sub category of micro-businesses consisting of less than five employees (de

Valence 2010). It is this definition that is accepted for the purposes of this study.

While this means that comparisons to the collected data from other nations are limited

by the different cut-offs, this is more than compensated for by the consistency of the

government collected data. Year-to-year comparisons within Australia have a high-

level of validity due to the structural nature of how information is collected. The

comparison between the various international definitions is shown in Table A4.1

overleaf.

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Table A4.1 Comparison of international definitions

Definition Employee numbers Income limit Additional requirements

American Small Business Administration

< US$33,500,000 (A$36,046,000 as at 1st May 2010)

Must be independently owned and operated

Must not be dominant in its field of operation

European Union

< 250 employees

(Micro-business < 10 employees, Small business between 10 and 49 employees and Medium business between 50 and 250)

< 50 million Euro annual turnover (A$71,250,000 as at 1st May 2010)

< 43 million Euro annual balance sheet total

(A$61,275,000 as at 1st May 2010)

Lower limits apply for small and micro-businesses

Minimum of 75% of company’s assets owned by company management

Owner managers or their families manage the company personally

World Bank Between 100 and 500 upper limit depending on country

250 most common limit

Australian Bureau of Statistics

< 200 employees (Micro-business has < 5 employees, Small business between 5 and 19 and Medium business between 20 and 200)

technical innovation delivery in small and medium ...11… · hardie, m. (2009), ‘construction...

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