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Application of the analytic hierarchy process (AHP) in multi-criteriaanalysis of the selection of intelligent building systems

Johnny K.W. Wong�, Heng Li

Department of Building and Real Estate, The Hong Kong Polytechnic University, Hunghom, Kowloon, Hong Kong

Received 23 February 2006; received in revised form 14 June 2006; accepted 5 November 2006

Abstract

The availability of innumerable intelligent building (IB) products, and the current dearth of inclusive building component selection

methods suggest that decision makers might be confronted with the quandary of forming a particular combination of components to suit

the needs of a specific IB project. Despite this problem, few empirical studies have so far been undertaken to analyse the selection of the

IB systems, and to identify key selection criteria for major IB systems. This study is designed to fill these research gaps. Two surveys: a

general survey and the analytic hierarchy process (AHP) survey are proposed to achieve these objectives. The first general survey aims to

collect general views from IB experts and practitioners to identify the perceived critical selection criteria, while the AHP survey was

conducted to prioritize and assign the important weightings for the perceived criteria in the general survey. Results generally suggest that

each IB system was determined by a disparate set of selection criteria with different weightings. ‘Work efficiency’ is perceived to be most

important core selection criterion for various IB systems, while ‘user comfort’, ‘safety’ and ‘cost effectiveness’ are also considered to be

significant. Two sub-criteria, ‘reliability’ and ‘operating and maintenance costs’, are regarded as prime factors to be considered in

selecting IB systems. The current study contributes to the industry and IB research in at least two aspects. First, it widens the

understanding of the selection criteria, as well as their degree of importance, of the IB systems. It also adopts a multi-criteria AHP

approach which is a new method to analyse and select the building systems in IB. Further research would investigate the inter-

relationship amongst the selection criteria.

r 2007 Elsevier Ltd. All rights reserved.

Keywords: Intelligent building; Building systems; Selection criteria; AHP

1. Introduction

For many years, buildings that offer comfortable,flexible and energy efficient living environment at aminimal cost has been the expectation of building ownersand occupiers. To attain this aspiration, a variety ofadvanced building technologies have been developed in thepast two decades, aiming to improve the buildingperformance to satisfy a variety of human needs andenvironmental sustainability. While a plethora of advancedbuilding products have been accessible, it has becomeincreasingly evident that developers are confronted withthe quandary of choosing the apposite components orproducts to suit the needs and to accomplish the unique

e front matter r 2007 Elsevier Ltd. All rights reserved.

ildenv.2006.11.019

ing author. Tel.: +852 2766 5882; fax: +852 2764 3374.

ess: [email protected] (J.K.W. Wong).

s article as: Wong JK, Li H Application of the analytic hierarc

ms. Building and Environment (2007), doi:10.1016/j.buildenv.2

configuration of a particular intelligent building (IB)project. The problems inherent in justifying the optionsof IB systems and components can be attributed to twofactors.First, there is a dearth of systematic and rigorous

methods in existence for selecting new building technolo-gies. Many of the current approaches were criticized foroveremphasizing the quantitative and financial aspects [1].Models focused only on the cost performance (i.e. purchaseor maintenance costs), which was easily quantifiable, butoverlooked other benefits such as improved humancomfort, environmental sustainability, and building flex-ibility. Consequently, option of building systems with thepre-eminent cost saving are generally chosen by using thisevaluation approach. This probably led to selectionmyopia and a biased decision. As such, a model ormethodology which can incorporate qualitative factors

hy process (AHP) in multi-criteria analysis of the selection of intelligent

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(i.e. human judgments) in quantitative approach is helpfulin selecting the IB systems.

Second, many performance criteria that were not easilyexpressed or quantified failed to be captured in manyevaluation approaches. The negligible considerations of theperformance factors have serious long-term consequences.In an IB, each building system is designed to enable allindividual systems to interrelate with one another in anatured way, allowing for interaction between systems andthe control of that system, so that the systems wouldcollaborate to respond flexibly to changing conditions anduser requirement throughout the whole life of the building[2]. An IB that fails to recognize the significance ofperformance and systems interface may lead to systemincompatibility, malfunctioning, and risk of obsolescence.If the building systems malfunction, it affects the businessoperations of occupants. The maintenance cost and thecost associated with a potential plunge in revenue arisingfrom loss of tenants have an adverse effect on the financialviability of the building [2]. The failure to match occupants’and clients’ expectations may eventually lead to disen-chantment and a serious decline in interest and confidencein IB. Based on these problems, the analysis of IB optionsduring the design stage is considered important.

In pursuit of excellent performance of IB, the last decadehas seen an explosion of interest in the assessment andevaluation in IB literature and research. A rich body ofknowledge has been developed [3–8]. Studies haveattempted to identify the performance criteria and toestablish the appraisal methods for IB. These performancecriteria provide a guideline and enabled feed-forward intoimproved planning, design and construction of futurebuildings [9]. Although these studies provide effectivefoundation for the evaluation of IBs, many current IBappraisal methods lack the power of comparabilityregarding the features of IBs [10]. The existing literaturein justification and selection of IB systems consists ofarticles or case studies only either in the internal report orin practitioner-focused journals [5,11]. There is a lack of apractical guide helping to compare two options of buildingsystem for one IB project, and researchers [1,12,13] alsorepeatedly emphasize the need for a model which assists theevaluation of IB options during design stage. Based on thecurrent research deficiencies, this paper proposes a multi-criteria decision-making model using the analytic hierarchyprocess (AHP) approach to evaluate the selection of IBsystems. This paper aims to identify the crucial selectioncriteria for IB systems; to test the criticality and compar-ability of the selection criteria; and to develop a model tohighlight the selection of the appropriate IB components orsystems.

2. Review of research in IB appraisal and evaluation

As an exploratory study, a particular set of selectionattributes must be derived in this study prior to the testing.The search for criteria was conducted first by reviewing the

Please cite this article as: Wong JK, Li H Application of the analytic hierarc

building systems. Building and Environment (2007), doi:10.1016/j.buildenv.2

literature. Despite the dearth of studies on evaluating theselection criteria of IB components, there has been asubstantial amount of research into the method ofappraising the performance of IBs. Since the 1980s,scholars [3,14,15] and professional bodies [16–20] haveconducted a considerable amount of research effort inunderstanding and measuring the performance of IBs. Forexample, Arkin and Paciuk [3] devised a unified index,‘intelligent building score (IBS)’, to assess the systemintegration in IBs and enable a building performance to bequantified in terms of the building systems installed and thelevel of integrated that exists between them. Smith [14]developed the ‘reframing’ and ‘quality facilities strategicdesign (QFSD)’, the former method aims to evaluate the IBenabling ability of the building to meet organizationalobjectives through the examination of four different frames(i.e., organizational structure, politics, human resourcesand culture), while the latter analyses the design character-istics and aims at establishing an order of priorities for thestakeholder requirements. Smith [15] further developed a‘building intelligent assessment index (BIAI)’ which aims toassess building intelligent level through seven buildingcharacteristics (i.e., site specification, operational cost,intelligent architecture, identity, intelligent technology,system responsiveness, and access and security). However,most of the assessment approaches were criticized for theirrestricted scope on either tangible (i.e., IBS and IBIA) orintangible (i.e., reframing and QFSD) aspects of buildings,and failed to provide a complete performance assessmentof IBs [15].In addition to the research conducted by scholars, there

have been various rating methods initiated by IB institutesfrom North America, Europe, and Asia in recent years[16–20]. These rating methods rely on a series of factors orindicators related to the performance issues together withtheir defined scales to rate an IB [10]. For example, theAsian Institute of Intelligent Buildings (AIIB) developedan ‘intelligent building index (IBI)’[19,20] to assess theperformance and categorize the IB. The BRE [16] devised amatrix tool for assessing the performance of IBs. Cur-rently, the CABA [21] is developing a new assessment toolnamed ‘intelligent building ranking tool (IBRT)’ whichaims to assess the level of integrated systems within an IB.Chen et al. [10] reviewed various latest IB assessmentsystems and found that the IBI method [19,20] has thebroader coverage of assessment clusters of indictorscompared with other IB assessment methods. Other ratingmethods, for example, the IB rating by SCC, onlyconcentrates on the Engineering cluster, while bothMATOOL and ASCIB assessment approaches cover fewerclusters (i.e., management, engineering and environment)than IBI. Although the identified factors established byAIIB [19,20] were designated for post-occupancy evalua-tion of IB, it was argued that these factors could beexploited as feedforward into improved planning anddesign of future building [22]. Table 1 summarizes theproposed selection criteria with respect to each of the IB


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Table 1

Summary of proposed selection criteria suggested by literature

Proposed selection

criteria

Intelligent building systems

Integrated

building

management

system

Telecom

and data

system

Addressable

fire detection

and alarm

system

Security

monitoring

and access

control system

HVAC

system

Vertical

transportation

system

Digital

addressable

lighting

control system

Energy

mgt.

system

Hydraulic and

drainage

system

Internal

layout

system

Building

fac-ade

system

Work efficiency

Further upgrade � � � � � � � � � � �Grade of system �Reliability (i.e.

frequency of

breakdown)

� � � � �

Capability for

integrating systems

�

Protocol standard

compliance

�

Efficiency (i.e. rate

of transmission)

� � � �

Service life � � � � � � � � � � �Electromagnetic

compatibility

�

Intranet

management system

�

Provision of

broadband Internet

�

Provision of fibre

digital data interface

(FDDI)

�

Superhighway

satellite conferencing

�

Leakage detection �Access for erection

and maintenance

�

Compatibility (i.e.

with other building

systems)

� � � � � � � � �

Connection to BAS � � � � � � � � �Fire detection and

fighting code

compliance

�

Fire resistance code

compliance

�

Automatic and

remote control/

monitoring

� � � � � � �

Time for public

announcement

�

Time for informing

building management

�

Time for total

egress

�

Waiting time �Journey time �Maximum interval

time

�

Permanent artificial

lighting average

power density

�

Preventive

maintenance scheme

� � � � � �

Area under power

supply

�

Uniformity of lux

level

�

Area under

supervision and

monitoring

�

Earthquake

monitoring

�

Wind load

monitoring

�

J.K.W. Wong, H. Li / Building and Environment ] (]]]]) ]]]–]]] 3

Please cite this article as: Wong JK, Li H Application of the analytic hierarchy process (AHP) in multi-criteria analysis of the selection of intelligent

building systems. Building and Environment (2007), doi:10.1016/j.buildenv.2006.11.019


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Table 1 (continued )

Proposed selection

criteria


Integrated

building

management

system

Telecom

and data

system

Addressable

fire detection

and alarm

system

Security

monitoring

and access

control system

HVAC

system

Vertical

transportation

system

Digital

addressable

lighting

control system

Energy

mgt.

system

Hydraulic and

drainage

system

Internal

layout

system

Building

fac-ade

system

Structural

monitoring

�

Handling capacity �

Technological Issues

Use of high-tech

design

� � � � � � � � �

Use of advanced

artificial intelligence

(AI)

� � � � � � � � �

Cost effectiveness

Initial costs � � � � � � � � � � �Operating and

maintenance costs

� � � � � � � � � � �

Proposed selection

criteria


Building

automation

and energy

mgt. system

Information

and

communication

network system

Fire

protection

system

Safety and

security

system

HVAC

system

Vertical

transportation

system

Lighting

system

Electrical

installation

system

Hydraulic

and

drainage

system

Internal

layout

system

Building

fac-ade

system

Environmental Issues

Average efficacy �Total energy

consumption

� �

Energy conservation

and regeneration

� �

Noise pollution � � � �Method of cooling �Pollution related to fuel

consumption

�

Sunlight pollution (by

curtain wall)

�

Total harmonics

distortion (THD)

�

Allow for natural

ventilation

�

Electrical power quality �Permanent artificial

lighting average glare

index

�

Permanent artificial

lighting average lux level

�

Pollution-free product � �

Safety Issues

Safety regulations

compliance

� �

User comfort

Predict mean vote

(PMV)

�

Indoor air quality

(IAQ)

�

Spatial flexibility �Acoustic comfort � � �Overall thermal

transfer value (OTTO)

�

Special ventilation in

particular area

�

Appearance �Odour level �Daylight factors �Ventilation for

excessive heat

�

J.K.W. Wong, H. Li / Building and Environment ] (]]]]) ]]]–]]]4




ARTICLE IN PRESS


Proposed selection

criteria


Building

automation

and energy

mgt. system

Information

and

communication

network system

Fire

protection

system

Safety and

security

system

HVAC

system

Vertical

transportation

system

Lighting

system

Electrical

installation

system

Hydraulic

and

drainage

system

Internal

layout

system

Building

fac-ade

system

Cleanliness � � �Average colour

temperature

�

Colour rendering �Glare � �Amount of fresh air

(i.e. change of air)

� �

Ease of control �Response to change in

temperature

�

Response to change in

sunlight

�

Vibration level �Acceleration and

deceleration

�


systems. These proposed criteria were identified based onthe work of AIIB [19,20] as well as other empirical studiesand literature [2,15,23–25], as shown in Table 2.

3. Research methodology

This study consisted of two surveys: a general survey andthe AHP survey. The general survey is first undertaken inorder to identify the perceived critical selection criteria andto select those professionals with relevant qualification andexperience to enter into the AHP survey. A pilot study wasfirst conducted prior to the general survey to test thesuitability of proposed criteria summarized from theliterature, and to examine the comprehensibility of thequestionnaire prior to sending it out. In order to sharpenand refine the results of the general survey, the AHP surveywas conducted to prioritize and assign the importantweightings for the perceived criteria. The research metho-dology and layout of this study are depicted in Fig. 1.

4. General survey: Identification of critical selection criteria

4.1. Data collection

A pilot study was initially conducted with a number ofIB experts including E&M design consultants, architects,and property developers with extensive knowledge andexperience of IB projects. The experts were presented withthe proposed selection criteria of IB systems. They wereinvited to review the relevance, coherence and the clarity ofthe questionnaire. At the end of the pilot study, a numberof amendments were made. Due to the assortment of IBsystems, this study is limited to 11 key IB systems asrecommended by the experts. These building systemsinclude: (1) integrated building management system(IBMS) for overall monitoring and building management



function; (2) energy management system for electrical andpower quality monitoring and analysis; (3) HVAC systemfor heating, ventilation and air-conditioning system forcomfort control and IAQ; (4) addressable fire detectionand alarm system for fire prevention and annunciation; (5)telecom and data system for communication networkbackbone; (6) security monitoring and access system forsurveillance and access control; (7) smart/energy efficientvertical transportation system for multi-floors service; (8)digital addressable lighting control system for light designand control; (9) hydraulic and drainage system; (10)building fac-ade systems; and (11) building layout systems.A total of 136 local construction experts (i.e., academics,

developers, design consultants, quantity surveyors, andconstruction practitioners) were invited to complete thequestionnaire. With their varied background and knowl-edge in the field, their views provided an accurate reflectionof the selection attributes and their relative importance.Finally, a total of 71 valid usable replies were received. Inorder to elicit the crucial criteria, the respondent percep-tions were measured on the interval basis using a five-pointLikert scale (where 1 represented ‘not important at all’, and5 represented ‘extremely important’). Only those criteriawith mean ratings above or equal to ‘4’ (‘important’) wereincluded for consideration. In the questionnaire, they werealso invited to add new attributes or criteria if necessary.Furthermore, in order to check the mean for each proposedcriterion that whether the population would consider thecriterion to be significant or otherwise, a t-test analysis wasemployed to examine the proposed criterion. If the t-valueof the statistical test of the mean ratings was larger thancritical t-value (t (70, 0.05) ¼ 1.6669 at 95% confidenceinterval), it suggested that the proposed criterion wassignificant. In addition, the non-parametric Kruskal–Wal-lis one-way ANOVA test was undertaken in orderto ascertain whether there were statistically significant


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Table 2

References of proposed selection criteria for IB systems

Selection attributes References

Integrated building management system (IBMS)

Work efficiency

Further upgrade, reliability [23,26,27]

Grade of BAS [19]

Capability of integrating systems [8,19,23,28]

Protocol standard compliance, preventive

maintenance scheme

[23,27]

Efficiency [8,23]

Service life [23,27,29]

Automatic and remote control/monitoring [8,23,26,28,30]

Cost effectiveness

Initial costs, operating and maintenance costs [2,19,27,31]

Telecom and data system

Work efficiency

Further upgrade [15,26]

Efficiency (i.e. rate of transmission) [19,26]

Service life [29]

Intranet management system, provision of

broadband Internet

[15,19,26]

Reliability (i.e. frequency of breakdown), provision

of fibre digital data interface (FDDI), superhighway

satellite conferencing

[19]

Electromagnetic compatibility [19,23]

Technological issues

Use of high-tech system [15,19]

Use of advanced artificial intelligence (AI) [19]

Cost effectiveness

Initial costs, operating and maintenance costs [2,31,19]

Addressable fire detection and alarm system

Work efficiency

Further upgrade [26]

Service life [29]

Compatibility (i.e. with other building systems) [31]

Connection to BAS [19,31]

Preventive maintenance scheme, efficiency (i.e. rate

of transmission)

[19]

Fire detection and fighting code compliance, fire

resistance code compliance

[19,24,32]

Automatic and remote control/monitoring [15,33,34]


Use of high-tech system, use of advanced artificial

intelligence (AI)

[19]

Cost effectiveness


HVAC system

Work efficiency


Reliability (i.e. frequency of breakdown) [26]

Service life [29]

Leakage detection, access for erection and

maintenance

[19]

Compatibility (i.e. with other building systems) [31]

Connection to BAS [19,23,31,33]


Use of high-tech design, use of advanced artificial

intelligence (AI)

[19,35]



Cost effectiveness


Environmental issues

Total energy consumption [19,31,36]

Energy conservation and regeneration [4,19]

Pollution related to fuel consumption, noise

pollution, method of cooling

[19]

User comfort

Predict mean vote (PMV), Indoor air quality (IAQ) [19,37]]

Acoustic comfort [19,26]

Overall thermal transfer value (OTTO), special

ventilation in particular area, appearance, cleanliness

[19]

Odour level [19,38]

Amount of fresh air [19,26,38]

Security monitoring and access control system

Work efficiency


Service life [29]

Compatibility (i.e. with other building systems) [31,39]

Connection to BAS [19,23,40]

Automatic and remote control/monitoring, time for

public announcement, time for informing building

management, time for total egress, preventive

maintenance scheme, earthquake monitoring,

structural monitoring, wind load monitoring

[19]

Area under supervision and monitoring [19,26]

Technological Issues


intelligence (AI)

[19]

Cost effectiveness

Initial costs, operating and maintenance costs [2,19]

Vertical transportation system

Work efficiency

Reliability (i.e. frequency of breakdown) [19,26]

Service life [29,23]

Compatibility (i.e. with other building systems) [23,31]

Further upgrade, connection to BAS [19,31]

Efficiency, automatic and remote control/

monitoring, maintenance

[19]

Waiting time, journey time, maximum interval time [19,23]

Handling capacity [19]


Use of high-tech design [19]

Use of advanced artificial intelligence (AI) [19,23]

Cost effectiveness

Initial costs, operating and maintenance costs [2,19,23,31]


Total energy consumption, energy conservation

and regeneration

[19,23]

Noise pollution, total harmonics distortion (THD) [19]

Safety issues

Safety regulation compliance [19,23]

User comfort

Acoustic comfort, amount of fresh air (i.e. change

of air)

[19,23,26]

Average illumination [19]

Vibration level , acceleration and deceleration [19,23]





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Digital addressable lighting control system


Permanent artificial lighting average glare index [19]

Permanent artificial lighting average lux level [15,19]

Average efficacy of all lamps [19,38]

User comfort

Daylight factors [15,19,25,38],

Ventilation for excessive heat, cleanliness [19]

Average colour temperature, colour rendering,

glare

[19,38]

Acoustic comfort [19,26]

Ease of control [15,19,25,26]

Work efficiency


Service life [29]

Compatibility (i.e. with other building systems),

automatic and remote control/monitoring

[25]

Connection to BAS [19,23,25]

Permanent artificial lighting average power density,

preventive maintenance scheme, uniformity of lux

level

[19]



intelligence (AI)

[19]

Cost effectiveness


Energy management system

Work efficiency

Further upgrade, reliability (Frequency of

breakdown)

[26]

Service life [29]

Connection to BAS, compatibility (i.e. with other

building systems)

[19,23,25]

Preventive maintenance scheme [31]

Area under power supply [19]

Technological related

Use of advanced artificial intelligence (AI) [19]

Cost effectiveness


Safety issues

Safety regulation compliance [19]


Electrical power quality and demand provision [4,19]

Hydraulic and drainage system

User comfort

Cleanliness [19,20]

Work efficiency


Service life [19,29]

Compatibility, connection to BAS, automatic

control/monitoring

[19]



intelligence (AI)

[19]

Cost effectiveness




Building facade system


Noise pollution, sunlight pollution (by curtain

wall), pollution free product

[19]

Allow for natural ventilation [4,19]

User comfort

Response to change in temperature, response to

change in sunlight

[2,41]

Work efficiency


Service life [29]

Compatibility, connection to BAS [19,41]

Automatic and remote control/monitoring [41]



intelligence (AI)

[41]

Cost effectiveness


Building interior layout system

Environmental Issues

Pollution-free product, [19]

noise pollution (reverberation time/indoor ambient

noise level)

[19,38]

User comfort

Spatial flexibility [26]

Work efficiency


Service life [29]

Compatibility, connection to BAS [19]


Use of high-tech design [19]

Cost effectiveness





differences or divergences between each group of profes-sionals regarding the relative importance of the criteria.The matched parametric testing method was not employedin this study since the parametric assumptions were notfulfilled and the variables were measured by ordinal scaleof measurement [22,32]. The results of the Kruskal–Wallis test were interpreted by the w2 and degree offreedom (df), and if the p-value was less than 0.05 whichmeant there was a significant difference between thegroups. The analysis indicated that there was no significantbias found among various groups of respondents. Themean scores of the selection criteria were computed andranked in Table 3.

4.2. Findings and discussion

As can be seen in Table 3, ranks of selectioncriteria revealed that each building system containeddifferent sets of criteria with varied degrees ofinfluence. A summary of the survey findings are presented


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SURVEY ONE

General

Study

To develop a set ofintelligent buildingsystems, proposed

selection criteria, andsub-criteria from the

literature

To design the firstquestionnaire

Identification of agroup of important

selection criteria andsub-criteria

To determine theimportance

weightings for thebuilding systems,

selection criteria andsub-criteria

A refinedconceptual

model

Establishmentof

conceptualmodel

To confirm the firstquestionnaire

To refine theconceptual model

using the AHPmethod

To review relevanceand coherence of

proposed criteria, andto check clarity of

questionnaire

SURVEY TWO

AHP

Survey

Fig. 1. Proposed research methodologies and layout.


as follows. The detailed findings of this survey are reportedin Wong and Li [12].

�

P

b

‘Work efficiency’ was perceived as the most importantcore criterion for the selection of IB systems.
� ‘Service life’ and ‘operating and maintenance costs’ were
regarded as the two most crucial sub-criteria in variousIB systems. The high rank of ‘operating and main-tenance costs’ supports that the view of Sobchak [42]that long-term expenses are the major concern of manyowners and decision makers.
� Four building systems (including HVAC system; secur-
ity monitoring and access control system; verticaltransportation system; and digital addressable lightingcontrol system) comprised a number of crucial sub-criteria, which indicated that these IB systems could notbe merely justified by a few sub-criteria due to theircomplexity.
� The high rank of ‘user comfort’ sub-criteria (i.e., predict
mean vote, indoor air quality, acoustic comfort, andamount of fresh air) in HVAC system implied a strongneed for the provision of a comfortable and productiveworking environment to satisfy the physiological needsof the occupants in IB [37].
� Surprisingly, technological advancement was not con-
sidered as a key criterion in the system selection. Thisfinding reinforced the argument of Clements-Croome [2]and DEGW [5] that a true IB is not a building withpurely advanced technologies; instead it should be theone that can ensure efficiency, enhance user comfort andcost effectiveness. This may explain why technologicalissues have a low score.
� Unexpectedly, a number of selection sub-criteria that
quoted as important in the literature were not rated

lease cite this article as: Wong JK, Li H Application of the analytic hierarc

uilding systems. Building and Environment (2007), doi:10.1016/j.buildenv.2

highly in this survey. For example: ‘compliance ofprotocol standard’ for BAS systems [19,30,43,44];‘OTTV and odour level requirement’ for HVAC system[19,39]; ‘noise pollution’ for vertical transportationsystem [19], and building fac-ade systems [41]; and‘spatial flexibility’ for interior layout system [19,39].These sub-criteria were statistically considered as lessimportant, and therefore their importance were de-clined.

5. The AHP survey: Prioritizing and assigning important

weightings for the criteria

5.1. The AHP method

In order to prioritize the selection criteria, and todistinguish in general the more important criteria fromthe less important ones, further investigation was con-ducted by employing the AHP approach. The AHPmethod helped to specify numerical weights representingthe relative importance of each individual building systemas well as their associated selection criteria with respect tothe goal (‘to select the most appropriate IB systems’). AHPallows both qualitative and quantitative approaches tosolve complex decision problems [45]. In the qualitativeaspect, AHP structures the problems through decomposingthem into a hierarchy of elements influencing a system byincorporating levels: objectives, criteria, sub-criteria [46]. Inquantitative aspects, AHP can prioritize (or ‘pair-wise’compare) a set of attributes and distinguish in general themore important factors from the less important factors[45–49]. The pair-wise comparison judgments were madewith respect to the attributes of one level of hierarchy giventhe attribute of the next higher level of hierarchy (from the


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Table 3

Ranks of perceived selection criteria for IB systems

Selection criteria Mean t-valuea

Sub-criteria Main criteria group

(a) Integrated building management system (IBMS)

Reliability Work efficiency 4.32 3.384

Operating and maintenance costs Cost effectiveness 4.30 3.535

Capability for integrating systems Work efficiency 4.23 2.633

Efficiency Work efficiency 4.20 2.488

(b) Telecom and data system (TCP/IP)


Further upgrade Work efficiency 4.28 3.206


Service life Work efficiency 4.23 2.791


(c) Addressable fire detection and alarm system

Fire detection and fighting code compliance Work efficiency 4.25 2.846

Fire resistance code compliance Work efficiency 4.24 2.576




Automatic and remote control/monitoring Work efficiency 4.21 2.561


(d) HVAC system


Predict mean vote (PMV) User comfort 4.24 2.856


Indoor air quality User comfort 4.21 2.422

Total energy consumption Environmental 4.21 2.303

Connection to BAS Work efficiency 4.21 2.250


Acoustic comfort User comfort 4.20 2.219

Compatibility Work efficiency 4.20 2.114

Initial costs Cost effectiveness 4.18 2.260

Amount of fresh air changes User comfort 4.17 1.885

(e) Security monitoring and access control system

Time for public announcement Work efficiency 4.42 5.919


Time for informing building management Work efficiency 4.27 2.986






Time for total egress Work efficiency 4.18 1.932

(f) Vertical transportation system

Safety regulations compliance Safety 4.42 4.750


Waiting time Work efficiency 4.34 3.872

Maximum interval time Work efficiency 4.30 3.188

Total energy consumption Environmental 4.28 3.293

Acceleration and deceleration User comfort 4.27 3.064

Journey time Work efficiency 4.25 2.846




Acoustic comfort User comfort 4.23 2.791

Air change User comfort 4.23 2.440

Vibration level User comfort 4.23 2.440






ARTICLE IN PRESS


Selection criteria Mean t-valuea

Sub-criteria Main criteria group

(g) Energy management system



Safety regulation compliance Work efficiency 4.24 2.638


(h) Digital addressable lighting control system




Permanent artificial lighting average power density Work efficiency 4.20 2.342



Ease of control User comfort 4.17 2.044

Average efficacy of all lamps User comfort 4.17 1.987

Automatic control/adjustment of lux level Environmental 4.17 1.839

(i) Hydraulics and drainage system



(j) Internal layout system




(k) Building fac-ade system



Response to change in temperature User comfort 4.39 4.702


Response to change in sunlight User comfort 4.37 4.058



aRepresents the t-value that is larger than critical t-value (1.6669).


main criteria to the sub-criteria). AHP is also able to solicitconsistent subjective expert judgment via the consistencytest. The topic of AHP has attracted wide attention in theconstruction field. Earlier studies applied AHP in evaluat-ing the new construction technologies [50], other applica-tions reported include studies by Cheung et al. [47], Chengand Li [45], Cheung and Suen [51], Al-Harbi [52], and Fongand Choi [53]. Due to the complicated nature of IB systemselection, the AHP approach is applied in this paper toprioritize the crucial selection criteria of the IB systems.The five-stage AHP set out by Saaty [49] is summarized asfollows:

�

P

b

define the problem, and determine the objective;
� development of the hierarchy from the top (the objective
from a general viewpoint) through the intermediatelevels (attributes and sub-attributes on which subse-quent levels depends) to the lowest level (the list ofalternatives);
� employ a simple pair-wise comparison matrices for each
of the lower levels;



�

hy

006

undertake a consistency test; and
� estimate relative weights of the components of each
level.

For designing the paired comparison matrices, thedecision hierarchies were formed (Fig. 2). The hierarchiesreaffirmed the results of the general survey and depicted theattributes for selecting IB systems. The top level was theselection goal, and following this was the building systemsof IB. The third and fourth level comprised the selectioncriteria and sub-criteria expanding from the buildingsystems. The relative importance of the criteria and sub-criteria was rated by the nine-point scale proposed by Saaty[49], as shown in Table 4, which indicated that the level ofrelative importance from equal, moderate, strong, verystrong, to extreme level by 1, 3, 5, 7, and 9, respectively.The intermediate values between two adjacent argumentsare represented by 2, 4, 6, and 8.The consistency test is one of the essential features of the

AHP method which aims to eliminate the possibleinconsistency revealed in the criteria weights through the

process (AHP) in multi-criteria analysis of the selection of intelligent

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Fig.2.ThedecisionhierarchyforselectingIB

system

s.





ARTICLE IN PRESS

Table 4

The AHP pairwise comparison scale (Source: Saaty [49, p. 54])

Intensity of weight Definition Explanation

1 Equal importance Two activities contribute equally to the objectives

3 Weak/moderate importance of one

over another

Experience and judgment slightly favoured one activity over another

5 Essential or strong importance Experience and judgment strongly favour one activity over another

7 Very strong or demonstrated

importance

An activity is favoured very strongly over another; its dominance

demonstrated in practice

9 Absolute importance The evidence favouring one activity over another is of the highest possible

order of affirmation

2, 4, 6, 8 Intermediate values between the two

adjacent scale values

Used to represent compromise between the priorities listed above

Reciprocals of above

non-zero numbers

If activity i has one of the above non-zero numbers assigned to it when

compared to activity j, then j has the reciprocal value when compared with I


computation of consistency level of each matrix [45]. Theconsistency ratio (CR) was used to determine and justifythe inconsistency in the pair-wise comparison made by therespondents. Saaty [54], and Cheng and Li [45] have set theacceptable CR values for different matrix’s sizes: (1) theCR value is 0.05 for 3� 3 matrix; (2) 0.08 for a 4� 4matrix; and (3) 0.10 for larger matrices. If the CR value islower than the acceptable value, the weight results are validand consistent. In contrast, if the CR value is larger thanthe acceptable value, the matrix results are inconsistent andwere exempted for the further analysis.

5.2. Questionnaire design and data collection

The AHP survey aimed at evaluating the comparabilityof the perceived selection criteria. To help accomplish theseaims, a questionnaire was designed for data collection, andthe format was synthesized with reference to AHP matrixproposed by Saaty [49]. Since the assignment of the weightrequires logical and analytical thinking, only the relevantexperts or professionals providing penetrating insights werehighly valuable to an empirical inquiry. In order to selectthe suitable respondents, a question on the preceding(general) survey asked the respondents if they wereexperienced in IB design and development. A total of 16experienced respondents in the general survey replied andexpressed their interest in conducting the AHP question-naire. On the other hand, AHP is a subjective method thatis not necessary to involve a large sample, and it is usefulfor research focusing on a specific issue where a largesample is not mandatory [45,55]. Cheng and Li [45] pointedout that AHP method may be impractical for a survey witha large sample size as ‘cold-called’ respondents may have agreat tendency to provide arbitrary answers, resulting in avery high degree of inconsistency. AHP survey with a smallsample size has been conducted in previous research. Forexample, Cheng and Li [45] invited 9 construction expertsto undertake a survey to test comparability of criticalsuccess factors for construction partnering. Lam and Zhao[55] also invited 8 experts for a quality-of-teaching survey.



In our study, 10 returned questionnaires were received forthe AHP survey. By evaluating the consistency level of thecollected questionnaires, 9 questionnaires appeared to haveacceptable consistency (Table 5) and would enter intoanalysis. Demographic information revealed that allrespondents were highly experienced and in differentconstruction positions, such as E&M engineers and designconsultants, architects, property developers, and construc-tion managers. Eight of them have participated in not lessthan three IB projects, and all replied with more than 10years experience in construction field.

5.3. Findings and discussions

To analyse the survey findings, the judgment matriceswere pair-wise compared and computed via the use ofcommercial software packages (i.e., ExpertChoiceTM). Thelocal priority weights of all main criteria and sub-criteriawere first calculated, and then combined with all successivehierarchical levels in each matrix to obtain a global priorityvector. The higher the mean weight of global priorityvector, the greater the relative importance is. This helps todistinguish the more important elements from the lessimportant ones.The distributive summary in Table 6 suggests that each

group of building systems and criteria have differentprioritization according to the mean weight of therespondent in the final selection of the IB systems. Themean global priority weight differs for the building systems(from the lowest of 0.057 to the highest of 0.119); the maincriteria (from the lowest of 0.010 to the highest of 0.091);and the sub-criteria (from the lowest 0.002 to the highest of0.051). The findings suggested that the criteria are allcomparable, and none of them can be sacrificed. As can beseen in Table 6, some interesting findings on theimportance of IB systems were identified:

�

hy

006

Respondents reported that both IBMS (0.119) andaddressable fire detection and alarm system (0.119) wereprime building systems in their consideration during the


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ARTICLE IN PRESS

Table 5

Consistency ratio (CR) values for the judgment matrices

Matrix set Respondent

1 2 3 4 5 6 7 8 9 10

A1 (11� 11) 0.030 0 0.063 0.068 0 0.020 0.011 0.010 0.082 0.060

B1 (2� 2) 0 0 0 0 0 0 0 0 0 0

B2 (3� 3) 0 0.010 0.010 0.028 0 0 0 0 0 0

C1 (2� 2) 0 0 0 0 0 0 0 0 0 0

C2 (4� 4) 0.247 0 0 0 0 0 0.023 0 0 0

D1 (2� 2) 0 0 0 0 0 0 0 0 0 0

D2 (6� 6) 0.316 0 0.031 0.024 0 0 0 0 0.022 0.020

E1 (4� 4) 0.128 0.023 0.019 0.058 0 0 0 0 0.070 0

E2 (4� 4) 0.099 0.000 0 0.010 0 0 0 0 0 0.020

E3 (4� 4) 0.099 0.017 0.012 0.023 0 0 0 0 0.023 0

E4 (2� 2) 0 0 0 0 0 0 0 0 0 0

F1 (2� 2) 0 0 0 0 0 0 0 0 0 0

F2 (7� 7) 0.057 0.021 0.068 0.053 0 0.020 0.010 0 0.066 0.020

F3 (2� 2) 0 0 0 0 0 0 0 0 0 0

G1 (5� 5) 0.044 0 0.074 0.012 0 0 0 0 0.016 0.040

G2 (7� 7) 0.168 0.084 0.054 0.020 0 0 0 0.084 0.034 0.010

G3 (4� 4) 0.058 0.070 0 0 0 0 0 0.023 0.023 0

H1 (3� 3) 0 0 0 0.028 0 0 0 0 0 0

H2 (2� 2) 0 0 0 0 0 0 0 0 0 0

I1 (4� 4) 0 0.070 0.058 0.017 0 0 0 0 0.023 0

I2 (6� 6) 0.091 0.034 0.049 0.039 0 0 0 0 0.080 0.060

J1 (2� 2) 0 0 0 0 0 0 0 0 0 0

K1(2� 2) 0 0 0 0 0 0 0 0 0 0

K2 (2� 2) 0 0 0 0 0 0 0 0 0 0

L1(3� 3) 0 0 0 0 0 0 0 0 0 0

L2 (4� 4) 0.044 0.074 0.058 0 0 0 0 0 0 0

L3 (2� 2) 0 0 0 0 0 0 0 0 0 0

Note: (1) The 10 respondents are assigned with no. 1–10; (2) Acceptable CR values (Saaty [49]): 0.05 or below for a 3� 3 matrix, 0.08 or below for a 4� 4

matrix; 0.1 or below for matrices larger than 5� 5; (3) Bolded when a value is larger than the acceptable CR value. Respondent No. 1 has six CR values

above the marginal, and therefore it is not considered in this analysis.


P

b

selection, followed by the telecom and data system(0.103), HVAC system (0.102), and digital addresslighting control system (0.102). The importance ofIBMS was consistent with So and Chan [35], Gann[56], and Carlson and Di Giandomenico [57], whosuggested that the IBMS acts as the ‘heart’ of IB whichprovides more effective and efficient control over allbuilding systems. Similarly, the immediate reaction andthe reliability of fire detection and alarm system are veryimportant to maintain the safety of the occupants in theIB. The importance of the fire protection system in goodtime is critical as it can contribute significantly to thesuccess of rescue operations and to limiting the degree ofdamage [34]. This might support why the fire detectionand alarm system was one of the main considerations inconfiguring IB systems;
� Surprisingly, respondents considered that the building
fac-ade system (0.057) was the least important in systemselection. The fac-ade system is often regarded as asystem providing protection from the weather as well asclimate modifiers controlling the amount of noise,sunlight and air that enters the buildings and sustaininga healthy environment [2]. The low rank of fac-adesystem may stem from the fact that the respondents



considered the internal building systems were moresignificant and influential in affecting user comfort andperformance of the IB.

Comparing the results of two surveys in this studyrevealed that the importance of selection criteria inAHP survey is slightly different from those of the generalsurvey, but they have a common premise that criteriaare all crucial and comparable. This AHP surveyfurther confirms the significance of all crucial selectioncriteria by the experts who have a high level of exper-ience in IB projects. Findings relating to relative impor-tance of selection criteria and sub-criteria are summarizedbelow:

�

hy

006

‘Work efficiency’ was continuously perceived as themost important main criterion for a number of IBsystems: addressable fire detection and alarm system(0.091), IBMS (0.078), security monitoring and accesscontrol system (0.060), telecom and data system (0.059),hydraulic and drainage system (0.040), and internallayout system (0.030). In addition, ‘‘user comfort’ wasconsidered as slightly more important in HVAC system(0.034) and lighting system (0.032).


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Table 6

Relative priorities of the selection criteria of the IB systems

Intelligent building

systems

Local

priority

Global

priority

Main Criterion Local

priority

Global

priority

Sub-Criterion Local

priority

Global

priority

Integrated building

management

system (IBMS)

0.119 0.119 Work efficiency 0.655 0.078 Reliability 0.536 0.042

0.078 Capability of integrating

systems

0.205 0.016

0.078 Efficiency 0.258 0.020

Cost

effectiveness

0.345 0.041 Operating and maintenance

costs

1.000 0.041

Telecom and data

system

0.103 0.103 Work efficiency 0.576 0.059 Reliability 0.362 0.021

0.059 Further upgrade 0.220 0.013

0.059 Service life 0.214 0.013

0.059 Efficiency 0.203 0.012

Cost

effectiveness


costs

1.000 0.044

Addressable fire

detection and

alarm system

0.119 0.119 Work efficiency 0.762 0.091 Fire detection and fighting

code compliance

0.253 0.023

0.091 Fire resistance code

compliance

0.199 0.018

0.091 Efficiency 0.139 0.013


0.091 Automatic and remote

control/monitoring

0.178 0.016

0.091 Service life 0.138 0.013

Cost

effectiveness


costs

1.000 0.028

Security

monitoring and

access control

system

0.091 0.091 Work efficiency 0.664 0.060 Time for public

announcement

0.139 0.008

0.060 Time for informing building

management

0.170 0.010

0.060 Compatibility 0.137 0.008

0.060 Connection to BAS 0.146 0.009

0.060 Service life 0.129 0.008


0.060 Time for total egress 0.149 0.009

Cost

effectiveness

0.336 0.031 Initial costs 0.416 0.013

0.031 Operating and maintenance

costs

0.584 0.018

HVAC system 0.102 0.102 Work efficiency 0.278 0.028 Service life 0.194 0.006

0.028 Reliability 0.442 0.013



User comfort 0.337 0.034 Predict mean vote (PMV) 0.226 0.008

0.034 Indoor air quality (IAQ) 0.294 0.010

0.034 Acoustic comfort 0.254 0.009

0.034 Amount of fresh air 0.226 0.008

Environmental 0.198 0.020 Total energy consumption 1.000 0.020

Cost

effectiveness

0.187 0.019 Initial costs 0.399 0.008


costs

0.601 0.011

Vertical

transportation

system

0.083 0.083 Work efficiency 0.228 0.019 Service life 0.099 0.002

0.019 Waiting time 0.234 0.004

0.019 Maximum interval time 0.200 0.004

0.019 Journey time 0.175 0.003



Automatic and remote

control/monitoring

0.122 0.002

User comfort 0.196 0.016 Acoustic comfort 0.248 0.004

0.016 Acceleration and deceleration 0.232 0.004

0.016 Air change 0.264 0.004

0.016 Vibration level 0.257 0.004





ARTICLE IN PRESS


Intelligent building

systems

Local

priority

Global

priority

Main Criterion Local

priority

Global

priority

Sub-Criterion Local

priority

Global

priority

Safety 0.302 0.025 Safety regulations compliance 1.000 0.025

Environmental 0.149 0.012 Total energy consumption 1.000 0.012

Cost

effectiveness


costs

1.000 0.010

Digital addressable

lighting control

system

0.102 0.102 Work efficiency 0.23 0.023 Compatibility 0.131 0.003


0.023 Permanent artificial lighting

aver. power density

0.180 0.004


0.023 Service life 0.203 0.005


control/monitoring

0.182 0.004

User comfort 0.312 0.032 Ease of control 1.000 0.032

Environmental 0.191 0.019 Average efficacy of all lamps 1.000 0.019

Cost

effectiveness


costs

1.000 0.027

Energy

management

system

0.095 0.095 Work efficiency 0.249 0.024 Connection to BAS 0.566 0.013


Safety 0.539 0.051 Safety regulations compliance 1.000 0.051

Cost

effectiveness


costs

1.000 0.020

Hydraulic and

drainage system


Cost

effectiveness


costs

1.000 0.029

Internal layout

system


Cost

effectiveness

0.497 0.030 Initial costs 0.525 0.016


costs

0.475 0.014

Building fac-ade

system

0.057 0.057 Work efficiency 0.317 0.018 Connection to BAS 0.238 0.004

0.018 Service life 0.341 0.006



control/monitoring

0.273 0.005

User comfort 0.325 0.019 Response change in

temperature

0.538 0.010

0.019 Response change in sunlight 0.462 0.009

Cost

effectiveness


costs

1.000 0.020


�

P

b

Consistent with the results of the general survey,reliability (0.042) and operating and maintenance costs(0.041) were further regarded as important sub-criteriain choosing the IBMS in this AHP survey. This isconsistent with the suggestions of So and Chan [33] inwhich the system reliability was reported as a keycriteria of choosing the right IBMS. Achieving expectedIBMS operational performance and reliability requiresattention to the selection and specification of thecomponents [33].
� The sub-criterion, operating and maintenance costs
(under main criteria ‘Cost effectiveness’), was perceivedas the most important selection sub-criteria in four IB

lease cite this article as: Wong JK, Li H Application of the analytic hierarchy


systems: telecom and data system (0.044), fire detectionand alarm system (0.028), building fac-ade system(0.020), and, security monitoring and access controlsystem (0.018).
� The findings further revealed that in various IB systems,
none of sub-criteria was dominant. For example, varioussub-criteria under ‘work efficiency’ were equally impor-tant in the vertical transportation system (from 0.002 to0.005); security monitoring and access control system(from 0.008 to 0.010); lighting system (from 0.003 to0.005); building fac-ade system (from 0.003 to 0.006).
� As shown in Table 6, ease of control (0.032) was justified
as the most important subcriteria for the selection of


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ARTICLE IN PRESS

Fig.3.A

refined

conceptualmodel

fortheselectionofIB

system

s.





ARTICLE IN PRESSJ.K.W. Wong, H. Li / Building and Environment ] (]]]]) ]]]–]]] 17

digital addressable lighting control system. This findingis consistent with the suggestions of Atif and Galasiu[58] that a careful control is an important factor inlighting systems justification as it helps reduce theelectric energy consumption as operation irregularities(i.e., reduced dimming linearity, incorrect adjustment ofthe phases of the dimming control system) can reducethe energy efficiency of the lighting control system.

Fig. 3 depicts a modified conceptual model of IB systemselection which is developed from the findings of thesurveys in this study. This modified conceptual modelillustrates the importance of the selection sub-criteria ofeach IB systems. It also suggests the accomplishment of theIB through the interaction and collaboration among the IBsystems.

6. Conclusions

This exploratory study evaluated and identified thecrucial selection criteria for the IB systems. A model forthe IB systems selection was established. The findings fillthe gaps that exist in the current body of research in thisarea. Our findings suggested that each IB system wasdetermined by a disparate set of selection criteria withdifferent weightings. Amongst all main selection criteria,‘work efficiency’ was perceived as the most important,while ‘user comfort’, ‘safety’ and ‘cost effectiveness’ werealso considered to be significant. Two sub-criteria, ‘relia-bility’ and ‘operating and maintenance costs’, were rankedhighly important by respondents. This implied that long-term expenses were the major concern of many owners anddecision makers. Also, reliability of systems can minimizethe risk of disillusionment as well as decline in interest andconfidence in IB systems by the occupants. It is expectedthe key criteria identified in this study improve theunderstandings of industry practitioners in IB systemsselection.

However, the examination of relationships was limited tothose between the building systems and selection criteriawith the use of the AHP method in this study. The inter-relationships amongst the selection criteria remainedunexplored. Future research would examine the underlyinginter-relationship amongst the criteria, i.e. by using theanalytical network process (ANP). For example, the inter-relationship between the ‘operating and maintenance cost’and ‘service life’ as well as their effects to the selection of IBsystems can be tested. Their interrelationship may affectthe extent to how to create the successful and well-performed IB systems.

References

[1] Wong JKW, Li H, Wang SW. Intelligent building research: a review.

Automation in Construction 2005;14:143–59.

[2] Clements-Croome DJ. Intelligent building, EssentialFM report No.

12, UK: The Eclipse Group; 2001.



[3] Arkin H, Paciuk M. Evaluating intelligent building according to level

of service system integration. Automation in Construction

1997;6:471–9.

[4] Cho MCT, Fellows R. Intelligent building systems in Hong Kong.

Facilities 2000;18(5/6):225–34.

[5] DEGW, Teknibank, the European Intelligent Building Group. The

intelligent building in Europe—executive summary. 1990, p. 1–23.

[6] Harrison A, Loe E, Read J. Intelligent buildings in South East Asia.

London: E&FN SPON; 1998.

[7] Preiser WFE, Schramm U. Intelligent office building performance

evaluation. Facilities 2002;20(7/8):279–87.

[8] So ATP, Chan WL, Tse WL. Building automation systems on the

Internet. Facilities 1997;15(5/6):125–33.

[9] Preiser WFE. Towards a performance-based conceptual framework

for systematic POEs. In: Preiser WFE, editor. Building Evaluation.

New York: Plenum Press; 1989. p. 9–18.

[10] Chen Z, Clements-Croome D, Hong J, Li H, Xu Q. A multicriteria

lifespan energy efficiency approach to intelligent building assessment.

Energy and Building 2006;38(5):393–409.

[11] ABSIC, ABSIC Project #00-2 Final Report: Building Investment

Decision Support (BIDS). 2001, /http://gaudi.arc.cmu.edu/bidsS.

[12] Wong J, Li H. Development of a conceptual model for the selection

of intelligent building systems. Building and Environment

2006;41(8):1106–23.

[13] Yang J, Peng H. Decision support to the application of intelligent

building technologies. Renewable Energy 2001;22:67–77.

[14] Smith S. The use of quality functional deployment in the design

of the office of the future. In: Proceedings of the second inter-

national conference on construction management, Sydney; 1999.

p. 146–55.

[15] Smith S. Intelligent buildings. In: Best R, de Valence G, editors.

Design and construction: building in value. UK: Butterworth

Heinemann; 2002. p. 36–58.

[16] Bassi R. MATOOL: a matrix tool for assessing the performance of

intelligent buildings. In: Proceeding of the BRE seminar on intelligent

buildings. UK: Building Research Establishment Ltd.; 2005.

[17] IBSK. Assessment Standards for Certifying Intelligent Buildings

2002. Intelligent Building Society of Korea (IBSK), Seoul, 2002.

[18] SCC. Shanghai intelligent building appraisal specification. China:

Shanghai Construction Council; 2002.

[19] The Asian Institute of Intelligent Buildings. The Intelligent Building

Index 10: Health and Sanitation, Manual Version 2.0. AIIB, 2001.

[20] The Asian Institute of Intelligent Buildings. The Intelligent Building

Index 10: Health and Sanitation, Manual Version 3.0. AIIB, 2004.

[21] CABA. Building IQ rating criteria, task force 1—Intelligent building

ranking system. Canada: Continental Automated Building Associa-

tion (CABA); 2004.

[22] Love PED, Irani Z, Edwards DJ. Industry-centric benchmarking of

information technology benefits, costs, risks for small-to-medium

sized enterprises in construction. Automation in Construction

2004;13:507–24.

[23] Chartered Institution of Building Service Engineers. Transportation

System in Building, CIBSE Guide D. London: CIBSE; 2000.

[24] Chartered Institution of Building Service Engineers. Fire Engineer-

ing, CIBSE Guide E. 2nd ed. London: CIBSE; 2003.

[25] Chartered Institution of Building Service Engineers. Energy efficiency

in buildings. CIBSE Guide F. 2nd ed. London: CIBSE; 2004.

[26] Armstrong P, Brambley MR, Curtiss PS, Katipamula S. Controls. In:

Kreider JF, editor. Handbooks of heating, ventilation and air-

conditioning. CRC Press; 2001 [chapter 5].

[27] Piper J. Automation: selecting building automation systems? Step by

step. Building Operating Management, 2002.

[28] Dwyer T. Integration is the key. Building Services Journal 2003:64–5.

[29] Loe E. Proving the benefits—justifying the costs of intelligent

systems. Facilities 1996;14(1/2):17–25.

[30] Finch E. Remote building control using the internet. Facilities

1998;16(12/13):356–60.


006.11.019

http://gaudi.arc.cmu.edu/bids


ARTICLE IN PRESSJ.K.W. Wong, H. Li / Building and Environment ] (]]]]) ]]]–]]]18

[31] Myers C. Intelligent buildings: a guide for facility managers. New

York: UpWord Publishing; 1996.

[32] Chow WK, Chow CL. Evacuation with smoke control for atria in

green and sustainable buildings. Building and Environment

2005;40:195–200.

[33] Shanghai Construction and Management Committee. Standard for

estimation of intelligent building: DG/TJ08-602-2001, J10105-2001:

(2001) [in Chinese].

[34] Trankler HR, Kanoun O. Sensor systems in intelligent buildings. In:

Gassmann O, Meixner H, editors. Hesse J., Gardner JW, Gopel W,

series, editors. Sensor application, vol. 2: Sensors in Intelligent

Buildings; 2001.

[35] So ATP, Chan WL. Intelligent building systems. Hong Kong: Kluwer

Academic; 1999. p. 21.

[36] Pan Y, Zhou H, Huang Z, Zeng Y, Long W. Measurement and

simulation of indoor air quality and energy consumption in two

Shanghai office buildings with variable air volume systems. Energy

and Buildings 2003;35:877–91.

[37] Alcala R, Casillas J, Cordon O, Gonzalez A, Herrera F. A genetic

rule weighting and selection process for fuzzy control of heating,

ventilating and air conditioning systems. Engineering Applications of

Artificial Intelligence 2005;18(3):279–96.

[38] Reffat RM, Harkness EL. Environmental comfort criteria: weighting

and integration. Journal of Performance of Constructed Facilities

2001;15(3):109–14.

[39] Hetherington W. Intelligent building concept. Ontario: EMCS

Engineering Inc.; 1999.

[40] Chebrolu S, Abraham A, Thomas JP. Feature deduction and

ensemble design of intrusion detection systems. Computers and

Security 2005;24(4):295–307.

[41] Wigginton M, Harris J. Intelligent skin. Oxford: Architectural Press;

2002.

[42] Sobchak P. Upping a building’s IQ. Building 2003;53(5):52.

[43] Bushby ST. BACnet: a standard communication infrastructure

for intelligent buildings. Automation in Construction 1997;

6:529–40.

[44] Finch E. Is IP everywhere the way ahead for building automation.

Facilities 2001;19(11/12):396–403.



[45] Cheng EWL, Li H. Construction partnering process and associated

critical success factors: quantitative investigation. Journal of Man-

agement in Engineering 2002;October:194–202.

[46] Crowe TJ, Noble JS. Multi-attribute analysis of ISO 9000 registration

using AHP. International Journal of Quality and Reliability

Management 1998;15(2):205–22.

[47] Cheung SO, Lam TI, Leung MY, Wan YW. An analytical hierarchy

process based procurement selection method. Construction Manage-

ment and Economics 2001;19:427–37.

[48] Hastak M. Advanced automation or conventional construction

process. Automation in Construction 1998;7:299–314.

[49] Saaty TL. The analytic hierarchy process: planning, priority setting,

resource allocation. US: McGraw-Hill; 1980.

[50] Skibniewski MJ. Evaluation of advanced construction technology

with AHP method. Journal of Construction Engineering and

Management 1992;118(3):577–93.

[51] Cheung SA, Suen HCH. A multi-attribute utility model for dispute

resolution strategy selection. Construction Management and Eco-

nomics 2002;20:557–68.

[52] Al-Harbi K Al-S application of the AHP in project mana-

gement. International Journal of Project Management 2001;19:

19–27.

[53] Fong PSW, Choi SKY. Final contractor selection using the analytical

hierarchy process. Construction Management and Economics

2000;18:547–57.

[54] Saaty TL. Fundamentals of decision making and priority theory with

the analytic hierarchy process. Pittsburgh: RWS Publications; 1994.

[55] Lam K, Zhao X. An application of quality function deployment to

improve the quality of teaching. International Journal of Quality

Reliability Management 1998;15(4):389–413.

[56] Gann DM. High-technology buildings and the information economy.

Habitat International 1990;14(2/3):171–6.

[57] Carlson RA, Di Giandomenico RA. Understanding building auto-

mation systems. Kingston: Means Company; 1991.

[58] Atif MR, Galasiu AD. Energy performance of daylight-linked

automatic lighting control systems in large atrium spaces: report on

two field-monitored case studies. Energy and Buildings

2003;35:441–61.


006.11.019


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