comprehensive australian study of entrepreneurial ... › 49327 › 1209 › causee... ·...

Comprehensive Australian Study of

Entrepreneurial Emergence (CAUSEE)

Handbook & User Manual

Version 7

www.bus.qut.edu.au/research/ace/

CAUSEE Handbook | Australian Centre for Entrepreneurship Research | QUT Business School

2

Recommended Citations and Acknowledgements

This version of the CAUSEE Handbook & User Manual was thoroughly revised and amended

by Jan Gruenhagen under Per Davidsson’s supervision for the public release of the CAUSEE

data, based on previous versions to which multiple authors contributed significantly.

Suggested citation:

Gruenhagen, J., Davidsson, P., Gordon, S.R., Salunke, S., Senyard, J., Steffens, P., &

Stuetzer, M. (2016). Comprehensive Australian Study of Entrepreneurial Emergence

(CAUSEE). Handbook & User Manual, Version 7. Brisbane: Australian Centre for

Entrepreneurship Research (ACE) at QUT Business School.

Other useful citations for descriptions of the CAUSEE study and data set are:

Davidsson, P., & Steffens, P. (2011). Comprehensive Australian Study of Entrepreneurial

Emergence (CAUSEE): Project Presentation and Early Results. In P. D. Reynolds & R. T.

Curtin (Eds.), New Business Creation (pp. 27-51). New York: Springer.

Davidsson, P., Steffens, P. & Gordon, S.R. (2011) Comprehensive Australian Study of

Entrepreneurial Emergence (CAUSEE): Design, Data Collection and Sample Description.

In Hindle, K & Klyver, K., Handbook of New Venture Creation Research (pp. 216-250).

Cheltenham: Elgar.

Users who publish research based on the CAUSEE data set should acknowledge the funders

of the project. We suggest you incorporate the following information in your

acknowledgement:

“We gratefully acknowledge the significant financial support for the CAUSEE study that

made this research possible. The CAUSEE data collection, documentation, and release

were funded by The Australian Research Council (grants DP0666616 and LP0776845);

the QUT Business School; industry partners BDO Australia and National Australia Bank,

and the Australian Government Department of Industry, Innovation and Science.”


3

Table of contents

1. Introduction ............................................................................................................................. 5

2. Sampling frame: The construction of the initial sample ............................................................. 8

3. The data collection ................................................................................................................. 11

3.1 Survey instruments and methods ................................................................................... 14

3.1.1 Skip patterns and question wording variations ....................................................... 14

3.1.2 The instrument ...................................................................................................... 17

3.1.3 Pilot study ............................................................................................................. 24

3.1.4 Wave 1 .................................................................................................................. 25

3.1.5 Wave 2 .................................................................................................................. 26

3.1.6 Wave 3 .................................................................................................................. 26

3.1.7 Wave 4 .................................................................................................................. 26

3.1.8 Wave 5 .................................................................................................................. 27

3.2 Response rates and reasons for non-response ............................................................... 31

4. Screening ............................................................................................................................... 33

4.1 Identifying nascent firms................................................................................................ 33

4.2 Identifying young firms .................................................................................................. 35

4.3 Identifying the control group ......................................................................................... 35

4.4 Identifying HP firms ....................................................................................................... 36

4.5 Classifying venture and respondent status in follow-up interviews ................................. 36

4.5.1 Criteria to establish transition to operational status (NF) ....................................... 37

4.5.2 Criteria for termination of NF or disengagement of respondents............................ 37

4.5.3 Criteria for termination of YF cases or disengagement of respondents ................... 39

4.5.4 Criteria for termination of NF/YF or disengagement of respondents in Wave 5 ...... 40

4.5.5 Treatment of terminated cases .............................................................................. 40

4.6 Identifying respondents for Re-Entry interviews (W5) .................................................... 41

5. Information on variables ........................................................................................................ 42

5.1 Primary variables ........................................................................................................... 42

5.1.1 Naming of primary variables .................................................................................. 45

5.1.2 Labelling of primary variables ................................................................................ 47

5.2 Computed variables ....................................................................................................... 52

5.2.1 Computations accounting for data privacy requirements ....................................... 52

5.2.2 Identification and classification variables ............................................................... 54

5.2.3 Consolidation of variables from regular waves and catch-up rounds ...................... 57


4

5.2.4 Outcome variables ................................................................................................ 58

5.2.5 Pre-computed outcome variables .......................................................................... 60

5.3 Known issues and recommended fixes ........................................................................... 63

5.3.1 Sales, profits section .............................................................................................. 63

5.3.2 Business plan section............................................................................................. 65

5.3.3 Differences between the pilot questionnaire and regular W1 questionnaire .......... 66

5.3.4 Time invested for nascent entrepreneurs .............................................................. 66

5.3.5 Sources of funding and advice ............................................................................... 67

5.3.6 Commencement date for HP cases ........................................................................ 67

5.3.7 Financial losses ...................................................................................................... 67

5.3.8 Time stamped gestation activities .......................................................................... 67

List of tables

Table 1: Profile of sampled firms – industry/sector (W1 – 2007)........................................................ 9

Table 2: Characteristics of NF, YF and Control respondents ............................................................. 10

Table 3: Fielding periods ................................................................................................................. 12

Table 4: Attrition in the study ......................................................................................................... 13

Table 5: Sections in the CAUSEE interview schedules ...................................................................... 17

Table 6: Pilot study data collection details ...................................................................................... 25

Table 7: Wave 1 data collection details (random sample) ................................................................ 26

Table 8: Sample sizes and response rates W1-4 .............................................................................. 31

Table 9: Sample sizes and response rates W5.................................................................................. 32

Table 10: Nascent checkpoint ......................................................................................................... 39

Table 11: Young Firm Checkpoint .................................................................................................... 39

Table 12: Sections in the interview schedule (reproduced from Table 5 above) ............................... 42

Table 13: Section and Theme Identification Table (Group-wise) ...................................................... 49

Table 14: Consolidated variables..................................................................................................... 57

List of figures

Figure 1: Development of the sample ............................................................................................. 28

Figure 2: Development of the sample (NFs) .................................................................................... 29

Figure 3: Development of the sample (YFs) ..................................................................................... 30

Figure 4: Sampling and screening procedure ................................................................................... 34


5

1. Introduction

The CAUSEE user manual is designed to introduce new users to the CAUSEE research

project. It first provides an introduction to the study and then documents in detail

describing the logic, research design and procedures that were followed in sequence over

five waves of data collection. While this handbook provides comprehensive information, it

is advisable that the user consults the following additional documentation in conjunction

with this user manual:

Questionnaires including the CATI script

The CAUSEE Dataset

Appendices to this handbook (available in a separate document)

The open-access version of the CAUSEE dataset includes almost all information and

variables from the original dataset. However, there are some constraints: In order to

protect the privacy of the respondents and ensure confidentiality, some variables have

been removed from the publicly available dataset or alternative variables on an aggregate

level were computed. For more details on the de-identification of the dataset see section

5.2.1. Additionally, due to intellectual property agreements variables related to the

theoretical constructs of ‘effectuation’ and ‘bricolage’ are currently not available in the

open-access dataset.

For a general overview on the CAUSEE project two short videos are available online

which introduce key data and the objectives of the study1,2.

DISCLAIMER: The CAUSEE data set is comprehensive and complex. Whilst the greatest

care was exercised in developing the data set and this handbook, the research team cannot

completely rule out the possibility of potential errors. Should a user encounter potential

flaws when using the handbook and dataset, the research team would appreciate to be

notified3. Further, this handbook has evolved over the course of five waves of data

collection and with the help of several, consecutive research assistants. As a result,

although considerable editing was undertaken prior to public release of the data there may

1 http://bit.ly/1j1rW4I 2 http://bit.ly/1Giwpog 3 [email protected]

http://bit.ly/1j1rW4I

http://bit.ly/1Giwpog

mailto:[email protected]


6

be remaining issues. It is possible to start working with the data without reading the

document in great detail. However, we strongly recommend users to deeply familiarise

themselves with this main document prior to use, as this is likely to save users from

spending considerable time undertaking and interpreting erroneous analyses. Further, each

user is fully responsible for any reporting of results they undertake based on the analyses

of the public CAUSEE dataset.

About CAUSEE

The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) is the

largest study of new firm creation ever undertaken in Australia. The longitudinal project

follows Nascent Firms (NF) and Young Firms (YF) over a six year period. NFs are on-going

start-up efforts while YFs are already established but less than four years old. These firms

were identified and interviewed via random sampling of Australian households which

makes them largely representative of the population of Australian start-ups. The study also

includes a comparison group of non-founders and over-samples of just over 100 High

potential (HP) start-ups in each category. The first survey was conducted in 2007 using

computer aided telephone interviewing (CATI) with subsequent waves conducted at

approximately 12 month intervals. Additionally, a follow-up study was conducted in 2013

to collect updated outcome information and to screen discontinued respondents and

ventures for a potential re-entry into entrepreneurship.

This research is designed on the lines of the Panel Study of Entrepreneurial Dynamics

(PSED) conducted in the United States and is partially harmonized with the PSED II4 study.

CAUSEE employs and extends the research approach of PSED and to some extent the

Global Entrepreneurship Monitor5 (GEM). Initially, individuals who are actively involved

with nascent firms and young firms (fitting our definition) were identified from a screening

interview of a large sample of Australian households following which extensive interviews

were conducted about their venture over six years (2007/8-2013). While CAUSEE benefits

greatly from the progress that has been made in previous research (e.g. PSED) on emerging

entrepreneurship, it differs from and extends prior approaches as follows:

4 For more information on PSED II, refer to http://www.psed.isr.umich.edu/psed/home. 5 http://www.gemconsortium.org/

http://www.psed.isr.umich.edu/psed/home

http://www.gemconsortium.org/


7

1. A non-random over-sample of “high potential” firms is included as high growth

firms are relatively rare in any random sample of new firms

2. Additional theory-driven content including packages related to effectuation,

bricolage, the resource-based view, venture newness and venture relatedness is

incorporated

3. Policy-relevant content related to location choices, collaborations and government

support is incorporated in Wave 5

4. In addition to nascent firms, an equally-sized sample of young firms is included that

allows us to both compare progress of young firms with our nascent cohort over

the same period and identical factor conditions and also combine the two samples

to study some processes of entrepreneurial emergence over a longer time frame

5. Terminated ventures and discontinued respondents were surveyed in terms of a

potential re-entry into entrepreneurship

6. The venture is considered as the primary unit of analysis, whereas PSED uses a

mixture of new venture and individual

7. Entrepreneurial emergence is studied within an Australian context

While these differences signal important potential contributions to theoretical

advancements in the area of emerging entrepreneurship, the mature and well-conceived

researcher-defined criteria as outlined in prior PSED studies formed the basis in this

research to identify the status and category of the venture.

The next section first discusses the sampling procedures, followed by the data collection

and the fielding procedures. Information is also provided in relation to the response rates,

screening criteria, sample sizes and questionnaires that were administered to the

respondents in each wave.


8

2. Sampling frame: The construction of the initial sample

The CAUSEE sampling frame was drawn from the AMSRO (Association of Market and

Social Research Organizations) random digit dialling (RDD) telephone resource and the data

collection was carried out by TNS (Australia), on behalf of

Queensland University of Technology (QUT). The RDD

telephone sample provides randomly generated landline

phone numbers by postcode for residential sampling and is

an excellent representation of the Australian population by

each state. The sample was drawn from a list of known

active telephone numbers using prefixes linked to local

government areas and drawn randomly via RDD. Data

collection was conducted using interviews via Computer

Assisted Telephone Interviewing (CATI). A large number of screening interviews were

conducted to qualify respondents for full-length interviews. The study followed a PSED-

style ‘early catch and then follow up’ approach which is a sound process research approach

appropriate in entrepreneurship research.

The sample was framed and selected using a nationwide sample of over 30,000

Australian residential households. As indicated earlier, these households were contacted

randomly to identify: 1) Nascent Firms (NF) and 2) Young Firms (YF). An oversample of High

Potential (HP) start-ups comprising both NFs and YFs with higher levels of education,

experience, aspirations and technological sophistication was also identified through a

broad spectrum of organisations and individuals likely to be in contact with such start-ups

in early stages. It is important to note that NFs are difficult to identify as they are typically

not registered or listed in any database. The only way then to identify such early stage

venturing efforts is to screen the general population for nascent firm formation efforts.

In the first year (2007), 1,010 NFs & 1,058 YFs were identified randomly (625 and 559 of

which, respectively, completed the full Wave 1 interviews) along with 106 NF HPs and 120

YF HPs. A control group (n=508) was also identified comprising every 50th respondent that

did not qualify as a NF or YF to allow for basic socio-demographic comparisons. The profile

of the sampled firms is shown in Table 1 below. First the number of cases in each sector is

indicated separately for the random sample and HP sample followed by the respective

percentages. Thereafter, the combined frequencies and percentages for the sample firms

in Wave 1 are indicated.

Note: While recent developments have reduced landline phones coverage of the relevant population (Steffens, Tonelli & Davidsson, 2010), this had not yet become a significant problem in 2007, when the screening was undertaken. Continued interviewing with identified cases used multiple modes of contact.


9

As indicated in Table 1, the dominant industries in the random sample were retailing

(13.5%), consumer services (12.5%) and business consulting (11.2%). In the HP sample,

manufacturing was the most dominant sector (25%) followed by business consulting

(16.8%) and communications (7.5%).

Table 1: Profile of sampled firms – industry/sector (W1 – 2007)

Industry Frequency Percent Combined

Random

sample

HP

sample

Random

sample

HP

sample

Frequency Percent

Retailing 160 5 13.5 2.2 166 11.8

Hospitality 49 3 4.1 1.3 52 3.7

Consumer services 148 11 12.5 4.9 159 11.3

Health, education or

social services

141 13 11.9 5.8 154 10.9

Manufacturing 70 56 6.0 24.8 127 9.0

Construction 113 14 9.5 6.2 127 9.0

Agriculture 63 12 5.3 5.3 75 5.3

Mining 8 3 0.7 1.3 11 0.8

Wholesale 33 11 2.8 4.9 44 3.1

Transportation 30 2 2.5 0.9 32 2.3

Utilities 7 -- 0.6 -- 7 0.5

Communications 47 17 4.0 7.5 64 4.5

Finance 28 3 2.4 1.3 31 2.2

Insurance 2 -- 0.2 -- 2 0.1

Real Estate 16 2 1.3 0.9 18 1.3

Business consulting or

services

133 38 11.2 16.8 171 12.1

Other 136 36 11.5 15.9 172 12.2

Total 1184 226 100 100 1410 100

Some demographic characteristics of the respondents and the comparisons across the

NF, YF and the Control group (2% of the non-qualified respondents) are illustrated in Table

2 below. As indicated, NF respondents are likely to be younger on average; they are


10

somewhat more likely to be male; they are more highly educated, and they are more likely

to have a parent who owned a business or was self-employed.

Table 2: Characteristics of NF, YF and Control respondents

Variable Nascent Firm

Respondent

Young Firm Respondent

Control Group Respondent

Stat. sig. across the 3 groups

Age (years) 44.0 43.8 49.5 p<.001

Male (%) 55.8 57.2 47.4 p<.001

University education (%)

37.8 37.6 23.9 p<.001

Home owner (%) 69.7 76.6 75.2 p<.05

Parental role model (%) 58.7 55.0 48.2 p<.005

Users should always bear in mind that a random sample of start-ups - like any random

sample of firms - will be dominated by a “modest majority” that is not particularly

ambitious or innovative, and therefore unlikely to grow large. This is one of the reasons

why judgment-based over-samples of HP firms were added. However, random samples

represent the phenomenon as it actually presents itself in the economy, and due to its

large numbers, the “modest majority” can collectively produce large economic effects.


11

3. The data collection

The CAUSEE data was collected over six years. The first round of data collection, Wave

1, collected through random sampling yielded N=625 (NF) and N=559 (YF) who were fully

interviewed; including cases identified during the pilot study6 (see note on additional data

available in Section 3.1.2: Wave 1). This was obtained by screening 30,105 adults, the

details of which are as follows:

- Total completed screener: 30,105; Ineligible cases screened out: N=27,909

- Eligible cases not interviewed: 464 cases qualified but declined; 349 refused part

way through full interview

- NF cases identified (N=1,010) / interviewed (N=625); YF cases identified (N=1,058) /

interviewed (N=559)

- Confirmed non-eligible cases (Control Group) identified and selected for the

control group interview (N=508)

Smaller supplementary, non-random samples of HP ventures of both nascent firms (N =

106) and young firms (N = 120) were also generated by judgment sampling (refer to Section

4.4). The second round of data collection, Wave 2, was conducted after 12 months and

comprised random samples of N=493 (NF) and N=472 (YF); and HP samples of N=91 (NF)

and N = 98 (YF). Similarly, the third round of data collection yielded N=281 (NF) and N=353

(YF); and HP samples of N=71 (NF) and N = 81 (YF). A fourth of round of data collection

yielded N=185 (NF) and N=262 (YF); and HP samples of N=58 (NF) and N = 64 (YF).

In addition, a fifth round of data collection was conducted in 2013 as a follow-up to

collect updated outcome information on the firms. This Wave 5 was split into two separate

sections. In the first section contact was sought with all prior cases which were not known

to be disengaged. This yielded N=197 (NF) and N=252 (YF); and HP samples of N=65 (NF)

and N=67 (YF). The separate second section targeted disengaged respondents to screen for

a potential re-entry into entrepreneurship. This re-entry section yielded a sample of N=412

respondents of whom N=120 indicating to be involved in starting a new business.

6 Any reference to included “pilot study” cases refers to the first set of cases obtained through the random sampling mechanism employed for the main study, and not to the convenience samples used for earlier pre-tests. See further 3.1.3.


12

Table 3: Fielding periods

Stages of data

collection

Fielding period Approx. duration

Interviews conducted

From To

Pilot study 22-03-2007 07-05-2007 50 minutes 78 (31 NF; 47 YF) 27 (CG)

Wave 1 NF&YF

HP

Control

27-06-20077 01-12-2007

13-04-2008 13-04-2008

50 minutes

5 minutes

1184 (625 NF; 559 YF) 226 (106 NF; 120 YF) 508 (CG) Please note: cases from the pilot study are included in Wave 1 numbers

Wave 2 NF&YF

HP

24-07-2008 05-12-2008

16-06-2009 16-06-2009

50 minutes

965 (493 NF; 472 YF) 189 (91 NF; 98 YF)

Wave 3 NF&YF

HP

01-10-2009 01-02-2010

09-06-2010 09-04-2010

40 minutes

634 (281 NF; 353 YF) 152 (71 NF; 81 YF)

Wave 4 NF&YF

HP

18-08-2010 25-01-2011

02-09-2011 01-09-2011

20 minutes

447 (185 NF; 262 YF) 122 (58 NF; 64 YF)

Wave 5 NF&YF

HP

20-06-2013 20-06-2013

03-10-2013 03-10-2013

10 minutes

449 (197 NF; 252 YF) 132 (65 NF; 67 YF)

Wave 5 Re-Entry Section

21-06-2013 23-09-2013 10 minutes 412

The attrition between waves was on account of:

- Cases excluded because terminated venture and/or terminated respondent

(terminated in the last wave). These cases were treated as being not eligible for

next wave interviews. An exception is Wave 5 during which all prior cases were

contacted regardless of their previous outcome.

- Cases eligible, but not successfully interviewed. (see table 4)

7 Data derived from the time stamps on the SPSS files/ TNS field reports

Note: In April 2012, 8 interviews were conducted for cases which were regularly interviewed in W3

but whose data for W3 were not delivered by the survey vendor.


13

Table 4: Attrition in the study

Identified Eligible Sample

Eligible but not

interviewed

Interviewed sample

Interviewed but discontinued

Eligible for the next

wave

Wave 1 Regular firms

NFs YFs

HP firms

NFs YFs

1010 1058

-- --

385 499

-- --

625 559

106 120

-- --

-- --

625 559

106 120


NFs YFs

HP firms

NFs YFs

625 559

106 120

132 87

15 22

493 472

91 98

152 77

6 3

341 395

85 95


NFs YFs

HP firms

NFs YFs

341 395

85 95

60 42

14 14

281 353

71 81

65 44

9 9

216 309

62 72


NFs YFs

HP firms

NFs YFs

216 309

62 72

31 47

4 8

185 262

58 64

30 31

5 3

155 231

53 61


NFs YFs

HP firms

NFs YFs

Re-Entry Section

380 412

86 106

545

183 160

21 39

133

197 252

65 67

412

53 43

14 9

--

N/A

*This table is based on information in variables Q803#I and Q803#J for Wave 1, A38 and A41 for waves 2-4 and Q1, Q4 and TERMIN00 for Wave 5. For cases with no data available in A38/A41 in waves 2-4 information from A0 is included. Actual sample size for variables may be lower due to skip patterns and item non-response. Furthermore, some of the interviews in waves 2-5 are only partially complete as the respondent refused to continue. Rudimentary respondent data is available for additional cases in W1, see variable Q76# to Q84#.


14

3.1 Survey instruments and methods

The survey instruments that were used to collect information from respondents in the

five waves are accessible online for download8. As indicated earlier, data collection was

conducted using interviews of 40-50 minutes duration (approximately 10 minutes duration

for the follow-up interviews in Wave 5) via Computer Assisted Telephone Interviewing

(CATI), the programming for which was comprehensively aided by the aforesaid

questionnaires. The programming comprised several skip patterns and question wording

variations which are illustrated next.

3.1.1 Skip patterns and question wording variations

The CAUSEE undertakes very comprehensive interviews within a very heterogeneous

sample of new and emerging ventures. This means that not all questions apply to all cases.

The interview schedules include literally hundreds of skip patterns where the venture’s

sampling category (NF vs. YF); its status (e.g., operational, ‘still trying’ or terminated) or

responses to preceding questions dictate whether a question is asked or not. Skip patterns

may apply to entire questionnaire sections; a sequence of questions, or an individual

question. This implies the following:

1. Users of the data should always check the number of valid cases for a question before

including it in any more complex analysis.

2. When the number of cases is substantially lower than expected, a) check the general

number of valid cases for the analysed category of ventures in the data wave analysed

and b) consult the questionnaires in order to understand what respondents have

received the question.

3. It may be possible to compute a new variable and assign a valid ‘zero’ to cases that

have system missing value for the question (for example, a computed variable of the

type ‘has this case ever reported this behaviour/event, etc.?)

4. On the other hand, users should be careful not to compute new variables and

mistakenly assign a value (e.g., zero) to cases where this amounts to suggesting that

something is known about a case when in actual fact it is unknown.

8 http://eprints.qut.edu.au/49327/

http://eprints.qut.edu.au/49327/


15

In addition, among those getting a question the variation in the nature of the venture

(selling products or services; being run by a team or a solo entrepreneur; stage of

development, etc.) required variations in the wording of questions in order for the

interviews to progress as natural, case-adapted conversations. These wording variations

have no effects on the analysis; however, for key variables users may want to consider

whether there is enough ‘instrument equivalence’; i.e., that they are confident that the

question assesses the ‘same phenomenon’ across all respondents who have answered it.

The following three examples (B1, C21 & D2) illustrate various combinations of skip

patterns:

SECTION APPLIES TO ALL YOUNG FIRMS (INCL. ‘reduced’). Nascents skip to section C.

ASK IF W2-B1 NE 1 (NO EVIDENCE OF BUSINESS PLAN IN W2)

B1 OPERATIONAL (A41 = 1 OR 2) TEXT: Last time you said a business plan had never been

prepared for this business. During the last 12 months, have you prepared a business plan,

will you do so in the future, or is this not relevant to this business?

TERMINATED (A41 = 3) TEXT: Did this business ever prepare a business plan? [IF ‘NO’

record ‘3’]

1 Yes

2 No, not yet – will in future

3 No, Not relevant

--------

ASK IF C20 = 2

C21 (W1-Sect1[GA1]-Q5a) ENGAGED (A40 = 1 OR 2) / PRODUCT TEXT: Is the product that this new

business will sell completely developed and ready for sale or delivery, has it been tested

with customers as a prototype, is it being developed as a model, or is the product still in the

idea stage?

ENGAGED (A40 = 1 OR 2) / SERVICE TEXT: Is the service that this new business will sell

completely developed and ready for sale or delivery, has it been tested with customers as a

procedure, is it being developed as a procedure, or is the service still in the idea stage?

REDUCED (A40 = 3) / PRODUCT TEXT: To the best of your knowledge, before or after your

involvement ended, was the product that this new business would sell completely

developed and ready for sale or delivery, had it been tested with customers as a prototype,

was it being developed as a model, or was the product still in the idea stage?

REDUCED (A40 = 3) / SERVICE TEXT: To the best of your knowledge, before or after your

involvement ended, was the service that this new business would sell completely

developed and ready for sale or delivery, had it been tested with customers as a procedure,


16

was it being developed as a procedure, or was the service still in the idea stage?

1 Completed and ready for sale

2 Prototype/procedure tested with customers

3 Model/procedure is being developed

4 Still in the idea stage; no work done yet

--------

D2. (W1 Q22a)

ACTIVE START-UP NASCENT (A38=2) TEXT - SOLO TEXT: Can you say roughly how much

money or financial resources of any kind you have invested in this business in the last 12

months – including any loans, equity and expenditures made to help the business get

started?

ACTIVE START-UP NASCENT (A38=2) TEXT - PARTNER TEXT: Can you say roughly how much

money or financial resources of any kind you and your partner have invested in this

business in the last 12 months – including any loans, equity and expenditures made to help

the business get started?

ACTIVE START-UP NASCENT (A38=2) TEXT - TEAM TEXT: Can you say roughly how much

money or financial resources of any kind you and all other owners combined have invested

in this business in the last 12 months – including any loans, equity and expenditures made

to help the business get started?

YOUNG FIRMS (A43=1) AND OPERATIONAL NASCENT (A38=1)- SOLO TEXT: Can you say

roughly how much money or financial resources of any kind you have invested in this

business in the last 12 months – including any loans, equity and expenditures made to help

the development of this business?

YOUNG FIRMS (A43=1) AND OPERATIONAL NASCENT (A38=1)- PARTNER TEXT: Can you

say roughly how much money or financial resources of any kind you and your partner have

invested in this business in the last 12 months – including any loans, equity and

expenditures made to help the development of this business?

YOUNG FIRMS (A43=1) AND OPERATIONAL NASCENT (A38=1) - TEAM TEXT: Can you say

roughly how much money or financial resources of any kind you and all other owners

combined have invested in this business in the last 12 months – including any loans, equity

and expenditures made to help the development of this business?

INTERVIEWER NOTE: ESTIMATE IS BETTER THAN DON’T KNOW. ENTER FULL AMOUNT

(DO NOT SHORTEN TO THOUSANDS OR MILLIONS).

ENTER FULL $ AMOUNT:

Don’t Know - 888888888

Refused - 999999999

******


17

3.1.2 The instrument

The instrument comprised of over 500 variables including screening questions and

several sections comprising variables relating to theoretical constructs of interest (shown in

Table 5). Additionally, the follow-up in Wave 5 includes a separate re-entry section for

previously disengaged founders assessing whether they start or intend to start a new

venture.

Table 5: Sections in the CAUSEE interview schedules

Section Purpose Applies to Harmonized with US-PSED II

Waves

Screening Assesses the suitability of the respondent

All respondents including control

group respondents

Yes W1

Basic respondent demographics

Captures demographic information

All ventures and control group respondents

Yes W1

Classifying the venture

Categorizing the venture on a number of dimensions

All ventures Mostly W1-W5

Gestation activities Initiation and completion of certain activities typical for start-ups, inclusive of time stamps for these events

Nascent ventures Yes W1-W5

Activities Similar to above but adapted to young firms and without time stamps

Young Firms N/A W1-W5

Venture idea newness

Degree of 4 types of newness (product, marketing, process/sourcing, target market)

All ventures Unique to CAUSEE W1-W3

Venture idea relatedness

Degree of relatedness to prior knowledge; available resources; market opportunities

Nascent ventures Unique to CAUSEE W1

Venture idea change Different types of changes of the idea and reasons for these changes

Nascent ventures Unique to CAUSEE W1-W4

Venture idea source Insights gained through different sources (e.g. previous jobs, education, hobby etc.)

All ventures Unique to CAUSEE W5

Effectuation Behaviours reflecting theoretical effectuation



18

principles

Team Resources The investment of Human, Social, Financial and other resources

All ventures Partly W1-W4

Resource advantages

Identification of particular resource strengths and weaknesses (RBV)


Bricolage Use of frugal tactics for obtaining and combining resources


Sources of funding and advice

Use and relative importance of different sources

All ventures Unique to CAUSEE/funding info simplified in

CAUSEE

W1-W3

Internationalization International experiences, perceptions and ambitions


Future expectations Assessing the founders/ views on the firm’s future development


Location Different types of location (e.g. business incubator), reasons for changing the venture’s location, and customers’ location


Collaboration Identifies different collaboration partners and reasons for these collaborations


Government support

Use of different types of government support


Exit interview Reflections upon their involvement and experience with the start-up

Terminated ventures;

discontinued founders of

ongoing ventures

N/A W2-W5

Screening Re-Entry Interview

Assess the suitability of the respondent for the re-entry interview



ongoing ventures

Unique to CAUSEE W5

Re-Entry interview Surveys disengaged founders of terminated and ongoing ventures who start or try to start a new venture; classifies the venture; addresses selected questions from previous waves

Re-entering respondents

Unique to CAUSEE W5


19

In the first four waves of data collection, the same questionnaire was used with minor

modifications or addition of a few questions. Essentially, this was done so as to allow a true

longitudinal analysis of the data. The follow-up data collection in Wave 5 comprised a

shortened questionnaire based on the previous four waves with some additional questions

and a section for re-entry interviews of disengaged founders. Although consistent

procedures were followed to ensure that the same questions were asked of the

respondents across all the five waves, there were some notable differences as listed below:

1) The variable naming convention followed in Wave 1 was markedly different in

comparison with the subsequent waves in the TNS generated SPSS file. On account of a

technical error, the variable names in Wave 1 were incorrectly represented by the

question numbers (e.g., Q53#) instead of section numbers (which are much clearer to

understand). In the following waves, this error was rectified by using section numbers as

the variable names (e.g., A1). For waves 2, 3 and 4 a consistent standardized approach

was followed which originated from Wave 1. However, accounting for a significantly

changed and altered questionnaire for the follow-up

interviews in Wave 5, section numbers could not be

applied to all survey questions in this wave. It is for this

reason that an emphasis is placed in this document to

provide relevant variable comparison information

between data from all 5 waves.

2) Building on the experience of the pilot study test, some minor changes were made in

the W1 questionnaire. Users should be aware of these differences when including pilot

study cases in the analysis. Please see section 5.3.3 for a detailed description of the

differences.

3) There was catch-up data associated with Wave 1 on account of a question that was

erroneously omitted from CAUSEE W1 CATI Survey. That is, respondents were

recontacted by email for a brief interview to gain additional information regarding to

the following 6 new variables in relation to “efforts invested”.

a) ECW1_Q1H. Total Effort Devoted to Business (in Hours)

b) ECW1_Q1W. Total Effort Devoted to Business (in Weeks)

c) ECW1_Q1M. Total Effort Devoted to Business (in Months)

d) ECW1_Q2H. Effort Devoted to Business Since W1Date (in Hours)

Note: Comparison of

variables between all 5 waves

can be done using table 13

(Section 5) which provides a

quick cross-comparison of wave

1/2/3/4/5 variables.


20

e) ECW1_Q2W. Effort Devoted to Business Since W1Date (in Weeks)

f) ECW1_Q2M. Effort Devoted to Business Since W1Date (in Months)

Computed variables are available in the dataset which consolidate information from the

regular wave and the catch-up round. Please see section 5.2.3.

4) The following additions were made in W2 and/or W3

- In Section A & B: A22A (income from sales); A24A (has monthly revenue ever

exceeded monthly expenses); A30b (owners active in business); B13p (patents

granted); B13t (trademarks granted) {asked in W3-W4}

- In Section A: A48 & A49 (questions about success and failure with prior ventures) and

A50 (questions relating to active business ownership) {asked in W2 & W3 only}

- In Section C in Wave 3: C85_W2, C86_W2 & C87_W2 are catch-up questions for level

of sales, profits and losses in W2 {asked in W3 only} as some nascent firms skipped

these questions due to a programming error.

- In Section C: C107 & C108M & C108Y (related to filing of income tax) {asked in W3 &

W4 only}

- In Section D: D94-D97; areas in which non-owners made important contributions

were expanded in comparison to W1. The additional questions are related to

experience from industry, start-up experience, management of larger firms, and

international experience of non-owners {asked in W2-W4}

- In Section F: F16 (question about the reason for business idea change because of lack

of access to required staff or skills) {asked in W2 & W3 only}; F17 (question about the

reason for business idea change because of deep recession (GFC)) {asked in W3 only}

- In Section L: L17 & L18 (costs of business development covered); L44-L63 (questions

about the global financial crisis) {asked in W3 only}; L19-L43 (questions related to

market value, assets, liabilities) {asked in W3-W4}

- In Section L: L44-L63 (question about the impact of the GFC on future expectations of

the firms) {asked in W3 only}


21

- In Section X: X28 & X29 (questions relating to recovering costs/remuneration; cf. L17-

18) {asked in W3-W4}

5) There was a catch-up associated with Wave 3 on account of questions that were

erroneously omitted in the first version of W3 questionnaire. This error was recognized

midway in Wave 3. Respondents missing questions on sales and profits were

recontacted by email for a brief interview to gain additional information in relation to

the following 9 new variables:

a) ECW3_A22A. Sales, revenues or fees received at any time

b) ECW3_A23M. Timing of first sales, revenues or fees

c) ECW3_A23Y. Timing of first sales, revenues or fees

d) ECW3_A24A. Revenues exceeding expenses at a monthly base at any time

e) ECW3_A25M. Timing of revenues exceeding expenses at a monthly base

f) ECW3_A25Y. Timing of revenues exceeding expenses at a monthly base

g) ECW3_A26. Salary of owners included in the computation of monthly expenses

h) ECW3_A27M. Timing of revenues exceeding monthly expenses (including owner

salaries)

i) ECW3_A27Y. Timing of revenues exceeding monthly expenses (including owner

salaries)



6) Wave 4 was considerably reduced in comparison with the earlier waves. The

interviewing was much shorter (20 minutes) in comparison with previous waves (50

minutes). This was done taking into account the cost and benefit considerations as

applicable to this research. The changes in Wave 4 were as follows:

a) The following sections were excluded: E. Business Idea Newness (32 items), H.

Resource advantages (106 items), I. Sources of funding & advice (32 items) and K.

Bricolage (9 items).

b) The following sections were reduced: F. Business idea change (12 items), J.

Internationalization (4 questions), L. Outcomes and future expectations (20

questions) and Wrap-up (1 question).


22

c) 6 new questions were added in Section L – Outcomes and future expectations.

d) HPSC9a, HSPC9b, HSPC9c. All HP firms did not go through the screener questions in

the regular W1 questionnaire. Thus 3 catch-up questions were included in W4 in

order to gather some information about the founding year of the HP firms.

7) There was a catch-up associated with Wave 4 on account of questions that were

erroneously skipped in the CAUSEE W4 CATI Survey. That is, respondents were

recontacted by telephone for a brief interview to gain additional information regarding

to the following new variables in relation to sales, profits and salaries:

a) TCW4_ANYSALES: Sales, revenues or fees received between W3 and W4 interview

b) TCW4_C85: Sales in $ (total), between W3 and W4 interview

c) TCW4_C85ALT: Sales in $ (total), past 12 months

d) TCW4_ANYPROFITS: Revenue exceeding expenses at a monthly base, between W3

and W4 interview

e) TCW4_A26: Salary of owners included in calculation of monthly expenses, between

W3 and W4 interview

f) TCW4_A24ALT: Revenue exceeding expenses at a monthly base, past 6 of 12 months

g) TCW4_A26ALT: Salary of owners included in calculation of monthly expenses

h) TCW4_A27M: Timing of revenue greater than monthly expenses including owners

salary

i) TCW4_A27Y: Timing of revenue greater than monthly expenses including owners

salary

j) TCW4_C86: Profits in $, between W3 and W4 interview

k) TCW4_C87: Losses in $, between W3 and W4 interview

l) TCW4_C86ALT: Profits in $, last 12 months

m) TCW4_C87ALT: Losses in $, last 12 months

n) TCW4_L17-TCW4_L19 and TCW4_X28-TCW4_X29: Venture success

o) TCW4_L20-TCW4_L23: Market value of business




23

8) Wave 5 was a follow-up last interview to get updated outcome information on all

ventures which were not previously known to be terminated. The questionnaire was

considerably reduced taking into account cost and benefit considerations. Furthermore,

the objective of this wave was to focus on the outcome of the venturing process rather

than covering again all classifying and theoretical sections as applicable to earlier waves.

Interviews took approximately 10 minutes. As in earlier waves exit interviews were

conducted with disengaged ventures. A few new questions were included in this wave,

such as asking for government support or location changes. In addition, Wave 5

included a separate section (R-Section: Re-Entry Interview) for interviewing respondents

who disengaged from a new venture but indicated to be actively involved in currently

starting another new business. Notable changes and additions in Wave 5 are as follows:

a) Due to the considerably reduced questionnaire and the differing objective of this

wave, the survey instrument did not follow the subdivision into sections as done in

waves 2, 3 and 4. Instead, particular questions from selected sections were asked to

the respondents. However, the exit interview for disengaged respondents remained

unchanged from earlier waves.

b) Selected questions were asked from the following sections: A. Classifying the venture

(20 items), B. Activities young firms (6 items), C. Gestation activities (8 items), L.

Outcomes and future expectations (22 items).

c) 4 follow-up questions were asked in terms of internationalisation activities

(W5_Q28-Q31). The questioning in Wave 5 captures more detailed time frames (e.g.

‘any time ever’; ‘last 12 months’). Therefore, the questioning is slightly different to

previous waves; however, data might be compared with previous waves.

d) Corresponding to section A, 2 questions were added in Wave 5:

i. W5_Q6: Work done on start-up this year

ii. W5_Q10B: First extended revenue received from sales any 6 of 12 months

e) Corresponding to section A, 2 questions on revenues were asked with slight

differences regarding the time frame: W5_Q13 and W5_Q16.

f) 2 new questions were added in terms of venture harvest:

i. W5_Q45: Ever sell the business, or parts of the business, to new owners?

ii. W5_Q46: Did this sale mean a profit for the seller?

g) Corresponding to section L, question W5_Q48 (Cost of business development

covered if sold ever at any time) was asked with slight differences to previous waves.


24

h) 7 new questions were added in Wave 5 to ask for the source of the venture idea

(W5_Q57-Q64).

i) W5_Q64 (Business location change) was asked in Wave 5 with a slight difference to

previous waves in order to capture a more detailed time frame.

j) A new question was added to capture the location of the most important customer

(W5_Q86).

k) 8 new questions were added in Wave 5 to ask for the reasons of a business location

change and whether the venture has been located within a business incubator

(W5_Q65-Q71)

l) 14 new questions were added in Wave 5 to ask for a potential collaboration including

its purpose, partners, form and reasons (W5_Q72-Q85).

m) 9 new questions were added in Wave 5 to ask for potential government support and

its form (W5_Q87-Q95Y).

n) The exit interview for disengaged respondents (Section X) remained unchanged from

earlier waves (W5_X1-X27).

o) Re-Entry interviews (Section R) with 37 items were conducted within Wave 5 to

survey respondents who disengaged from a previous new venture but have started

or try to start another new business. Previously known disengaged respondents or

respondents how indicated termination/discontinuation in Wave 5 were screened

whether they are currently trying to start a new business or whether they are

currently the owner of a new business. Identified start-ups were asked questions

primarily in terms of classifying the venture, (gestation) activities and future

expectations. For a detailed elaboration of the questions please see section R of the

Wave 5 questionnaire, Appendix 1 (available in a separate document) and the

CAUSEE dataset.

3.1.3 Pilot study

Prior to fieldwork cognitive interviewing was undertaken to test respondent

understanding of the questionnaire. In 2006 pre-testing was undertaken using a

convenience sample of 71 firms. This was followed by a full scale pilot test conducted by

TNS in 2007 using CATI-RDD techniques. This pilot yielded 78 randomly sampled NF and YF

firms (see table 6 for more details). Whenever the “pilot study” or “pilot cases” are

mentioned in this handbook, it refers to these randomly sampled cases. Since very few

design changes were undertaken after this pilot test, these cases have been retained in the

data set and can safely be included in most analyses. See further 5.3.3.


25

Table 6: Pilot study data collection details

Numbers dialed 17179

Engaged/No answer/Unobtainable 3942

Dead numbers 2970

Business Number 1503

Killed 2892

Contact with 5872 NF YF

Completed Screeners 1719

Screened out (Did not qualify) 1512

Screened in (qualified) 207 76 131

Qualified & did not agree / dropped out 129 45 84

Complete full interview 78 31 47

Time taken Average total screener Demo section only Appointment section only

1 min 40 secs (N=438) 1 min 20 secs (N=233) 2 min 15 secs (N=102)

3.1.4 Wave 1

W1 commenced in early July 2007 and continued into April 2008 using CATI-RDD

techniques. Detailed briefing notes were prepared and full briefing of the interviewers was

undertaken prior to the main survey fieldwork. This stage involved large scale screening for

eligible cases (the screening procedures are described in detail in the latter sections)

followed by comprehensive interviewing (Table 7 below and Appendix 2 in the separate

appendices document provide a sample of the data collection details). A total of 30,105

adults (with equal male/female representation) from randomly selected households went

through a screening interview (including the full scale pilot test cases since the redesign

was minor). As the length of the interview was fairly long (approx. 50 minutes), an incentive

(i.e. a chance to win a prize to the value of $5,000) was offered to Wave 1 respondents to

minimize the potential negative impact of interview length on respondent participation.

The initial phase yielded a random sample of 1,184 firms comprising 625 NF (61.9% of

eligible cases) and 559 YF (52.9% of eligible cases). Cases from the pilot study are included

in this sample since there was only a minor redesign of the questionnaire (for details please

see section 5.3.3). A pre-computed variable is available to identify pilot study cases among

the Wave 1 sample (see section 5.2.2). The HP sample comprised 226 firms, out of which

106 were NFs and 120 were YFs.


26

Table 7: Wave 1 data collection details (random sample)

Numbers dialed 158708

Engaged/No answer/Unobtainable 18493

Dead numbers 49771

Business Number 6951

Killed 18236

Contact with 65257 NF YF

Completed Screeners 30105

Screened out (Did not qualify) 27909

Screened in (qualified) 2068 1010 1058

Complete full interview 1184 625 559

3.1.5 Wave 2

W2 commenced in early July 2008 and continued till June 2009. Out of 1,184 firms

(random sample) and 226 firms (HP sample) that were eligible from W1, we were able to at

least partially interview 965 random sample cases and 189 HP cases. This comprised 493

NFs (88.2% of eligible cases) & 472 YFs (75.5% of eligible cases) and a HP sample of 91 NFs

(75.8% of eligible cases) & 98 YFs (92.5% of eligible cases).

3.1.6 Wave 3

W3 commenced in early Oct 2009 and continued till June 2010. Out of 736 firms





3.1.7 Wave 4

W4 commenced in early Aug 2010 and continued till Sep 2011. 8 additional interviews

were conducted in April 2012 as these cases were erroneously dropped from the W3

delivery by TNS and rediscovered later in the process of data cleaning. Out of 525 firms

Note on additional data: In wave 1, 1,010 NFs and 1,058 YFs were identified in the random

sample of which 625 NFs and 559 YFs were fully interviewed. The remaining firms, those that were

not fully interviewed, answered the demographic background questions in Section B (12 items), the

data for which is available in the SPSS data file.


27





3.1.8 Wave 5

W5 commenced in late June 2013 and continued till early October 2013. It was

conducted as a follow-up with two objectives reflected by two separate questionnaire

sections.

The first section followed the objective to obtain updated outcome information on all

prior cases which were not previously known to be disengaged. That is, not only ongoing

cases which completed Wave 4 were contacted, but also cases for which the outcome was

unknown (for example, for which contact attempts failed in earlier waves or which dropped

out during interviews). Accordingly, contact was sought with 792 firms (random sample)

and 192 firms (HP sample). Out of those we were able to at least partially interview 449

random sample cases and 132 HP cases. This comprised 197 NFs (51.8% of eligible cases) &

252 YFs (61.2% of eligible cases) and a HP sample of 65 NFs (75.6% of eligible cases) & 67

YFs (62.2% of eligible cases). Please note that the response rates are lower since not only

eligible on-going cases from Wave 4 were contacted but also all prior cases for which the

outcome was unknown.

In the separate second section of Wave 5, re-entry interviews were conducted with

respondents who currently start or just have started a new business after they had

disengaged from the previous start-up effort. Respondents were screened for the re-entry

interview if (1) it was known from previous waves that they disengaged or if (2) they

indicated in Wave 5 that the venture has been terminated or that they have disengaged

from the business. In total, 412 disengaged respondents (75.6% of eligible cases) were

interviewed for the screener. Of those, 120 respondents indicated to be the (partial) owner

of a new start-up effort.

The overall development of the sample is summarized in figure 1. Additionally, figures 2

and 3 show venture status information for NFs and YFs throughout the 5 waves.


28

Initial pretesting Convenience sample

71 NF and YF Nov-Dec 2006

Full-scale pilot test - CATI (computer aided telephone interviewing) using RDD (random digital dialling) - Conducted by TNS in April-May 2007 - Contact with 1,810 households - Yield of 78 NF and YF who completed the full interviews (included in the main data set)

Analysis, Redesign,

Programming, Internal testing

Analysis, Minor Redesign, Programming, Internal testing

Wave 1 data collection (random sample) - Large scale screening for eligible cases using CATI - RDD techniques - Conducted by TNS from July 2007-April 2008 - Contact with 30,105 households - Yield of 625 NF and 559 YF who complete the full interviews; including pilot study cases. Total: 1184 firms

Wave 2 data collection (random sample) - Conducted by TNS from July 2008-April 2008 - Yield of 493 NF and 472 YF who (partially) completed the interviews; Total: 965

Wave 4 data collection (random sample) - Conducted by TNS from Aug 2010-Sept 2011 (additional interviews in Apr 2012) - Yield of 185 NF and 262 YF who (partially) completed the interviews; Total: 447

Wave 1: HP sample - CATI interviews (Following manual HP Screener) - Judgment sample - Contact with 260 firms - Fielded: Dec’07- Apr’08. - Yield: 106 NF & 120 YF

Wave 2: HP sample - Fielded: Dec’08 – Jun’09 - Yield: 91 NF & 98 YF (Total: 189 HP firms)

Wave 4: HP sample - Fielded: Jan’11 – Sep’11 (add. Interviews in Apr’12) - Yield: 58 NF & 64 YF (Total: 122 HP firms)

Wave 3 data collection (random sample) - Conducted by TNS from Oct 2009-Jun 2010 - Yield of 281 NF and 353 YF who (partially) completed the interviews; Total: 634

Wave 3: HP sample - Fielded: Feb’10 – Apr’10 - Yield: 71 NF & 81 YF (Total: 152 HP firms)

Wave 5 data collection (random sample) - Conducted by TNS from Jun 2013-Oct 2013 - Contact attempted with all cases from W1/2/3/4 not known to be discontinued - Yield of 197 NF and 252 YF who (partially) completed the interviews; Total 449

Wave 5: HP sample - Fielded: Jun’13 – Oct’13 - Yield: 65 NF & 67 YF (Total: 132 HP firms)

Wave 5 Re-Entry Interviews (random & HP sample) - Conducted by TNS from Jun 2013-Oct 2013 - Contact attempted with 545 prior respondents known to be disengaged - Yield of 412 screener interviews among which 120 respondents qualified as new business owners

Figure 1: Development of the sample


29

Figure 2: Development of the sample (NFs)

Wave 1

Wave 2

Wave 3

Wave 4

Operational

Still trying

Terminated

N=625 (Ran) N=106 (HP)

N=196 (Ran) N=45 (HP)

N=145 (Ran) N= 50 (HP)

N=152 (Ran) N= 6 (HP)

N=162 (Ran) N=41 (HP)

N=54 (Ran) N=21 (HP)

N=65 (Ran) N=9 (HP)

W3 eligible cases {N=341 (Ran); N=85 (HP)}

Eligible but not interviewed

N=132 (Ran) N= 15 (HP)


N=60 (Ran) N=14 (HP)

N=125 (Ran) N=34 (HP)

N=30 (Ran) N=19 (HP)

N=30 (Ran) N=5 (HP)

N=31 (Ran) N=4 (HP)

Wave 5

W5 eligible cases {N=380 (Ran); N=86 (HP)} (excluding the separate Re-Entry section)

N=142 (Ran) N=53 (HP)

N=53 (Ran) N=14 (HP)

N=185 (Ran) N=19 (HP)


30

Figure 3: Development of the sample (YFs)

*Note that the numbers for the development of the sample in Figures 1-3 are based on the

interview scheme variable (NF: A40; YF: A43) for waves 2,3,4. For a few cases with missing

data on A40/A43 similar (albeit self-perceived) status information from variable A0 is used

for waves 2,3,4. For Wave 5 the numbers are based on variables W5_Q1, W5_Q4 and

TERMIN00. Please note that higher numbers in Wave 5 are a result of attempting to

contact all cases from previous waves which were not known to be discontinued.

Wave 1

Wave 2

Wave 3

Wave 4

Continuing

Terminated

N=559 (Ran) N=120 (HP)

N=395 (Ran) N=95 (HP)

N=77 (Ran) N= 3 (HP)

N=309 (Ran) N=72 (HP)

N=44 (Ran) N=9 (HP)


Eligible but not interviewed

N=87 (Ran) N= 22 (HP)


N=42 (Ran) N=14 (HP)

N=231 (Ran) N=61 (HP)

N=31 (Ran) N=3 (HP)

N=47 (Ran) N=8 (HP)

Wave 5

W5 eligible cases {N=412 (Ran); N=106 (HP)} (excluding the separate Re-Entry section)

N=210 (Ran) N=60 (HP)

N=43 (Ran) N=9 (HP)

N=159 (Ran) N=37 (HP)


31

3.2 Response rates and reasons for non-response

As indicated in the foregoing sections (also see Table 8 below), the response rate in

Wave 1 was about 57.4%, 81.8% in Wave 2, 85.8% in Wave 3, and 86.3% in Wave 4. The

response rates were calculated as follows:

- The response rates for W1 were calculated by dividing cases that completed the

full interview by the cases that were eligible to participate.

- Response rates for W2-4 were calculated by dividing cases that had at least

partially completed the interview in the respective wave by the number of eligible

cases from the previous. Eligible cases were those who had at least partially

completed the previous interview and were neither terminated nor had the

respondent abandoned a still ongoing firm. In other words if either the firm was

terminated or the respondent left the firm, the case was treated as non-eligible for

the next wave.

Table 8: Sample sizes and response rates W1-4

Wave 1

N Eligible cases

Participants screened

30105

Qualified to participate

2068 6.9%

NF 1010 3.4% YF 1058 3.5%

Control Group 508 1.9% Wave 2 Wave 3 Wave 4 Completions N Response

rates N Response

rates N Response

rates N Response

rates

Regular NF 625 61.9% 493 88.2% 281 82.4% 185 85.6%

Regular YF 559 53.0% 472 75.5% 353 89.4% 262 84.8%

HP NF 106 91 75.8% 71 83.5% 58 93.5%

HP YF 120 98 92.5% 81 85.3% 64 88.9%

Overall completions

1410 (Regular S.

1184)

57.4%

1154 81.8% 786 85.8% 569 86.3%

In Wave 5 contact was attempted with all prior cases not previously known to be

disengaged. In other words, contact was sought with all cases which did not indicate

termination in waves 2, 3 or 4. The objective was to obtain updated outcome information

by also contacting those cases which did not complete the interviews in previous waves.

Therefore, sample sizes cannot be directly compared to the development between

previous waves. Additionally, a separate Re-Entry section was included in Wave 5. For this


32

section all respondents were contacted who were previously known to be disengaged or

indicated disengagement during Wave 5. Sample sizes and response rates for the two

separate sections in Wave 5 are summarised in table 9 below.

Table 9: Sample sizes and response rates W5

Wave 5 Catch-up sample

Wave 5 Re-entry interviews

Completions N Response rates related to eligible sample (=all cases not previously known to be disengaged)

N Response rates related to eligible sample (=all cases

known to be disengaged prior or in Wave 5)

Regular NF 197 51.8%

412 75.6%

Regular YF 252 61.2%

HP NF 65 75.6%

HP YF 67 63.2%

Overall completions 581 59.0%

Clearly, these high response rates in all waves indicate that extensive and appropriate

sampling procedures were followed to yield positive results. These results are notable

given that the interviews were fairly lengthy at an average of 50 minutes duration

(approximately 10 minutes in W5). It is also important to note that these high response

rates compare favourably to mail and online surveys, many of which have reported

response rates of less than 20%.

The reasons for non-response have been recorded in Wave 1. The most cited reason for

not participating in the CAUSEE study was that the respondents were generally busy at the

time of the call (n=154). Further non-response reasons were recorded as: refused (n=89),

busy with family commitments (n=34), concerned about confidentiality (n=12), and other

(n=175).


33

4. Screening

A comprehensive screening procedure was followed to identify firms of interest. Figure

4 illustrates the screening process and screening criteria that were followed. The screening

for the sample of NFs began with the broadest self-perceived definition of NF and was

narrowed down from there to the sample finally judged eligible.

The following focal screening questions were asked to a very large sample of adult

individuals (N= 30,105):

1) Potential NFs were screened using the following two questions:

a) Are you, alone or with others, currently trying to start a new business, including

any self-employment or selling any goods or services to others?

b) Are you, alone or with others, currently trying to start a new business or a new

venture for your employer, an effort that is part of your normal work?

2) Potential YFs were identified using the following question:

a) Are you, alone or with others currently the owner of a business you help

manage, including self-employment or selling any goods or services to others?

Those who positively responded to the aforementioned questions were identified either

as potential NFs or YFs. In most cases the response to all of these is ‘no’, in which case they

are excluded as non-eligible for the study other than for the Control Group of non-

entrepreneurs. As illustrated in Figure 4, their eligibility was further confirmed using a set

of qualifying questions, the most important being (part) ownership of the emerging

business in question (Q5a).

4.1 Identifying nascent firms

The target respondent for ‘nascent firms’ was the principal/owner of an on-going

business start-up. As indicated in Figure 4, in order to be included as NF the case had to:

- affirm at least one of the first two screening items (1-2)

- confirm that concrete actions toward starting a business have been undertaken

within the last 12 months

- confirm that the respondent will be a part owner of the venture (4a; 5a)

- disconfirm having regular revenue that covers all costs (6a)


34

In other words, if 4a (confirming active activity to start a business over last 12 months)

was answered ‘no’ the case was not eligible in this category and instead transferred to

‘suspected young firms’ to check if they were eligible under this category. Otherwise they

continued to 5a, where they affirm intended (part) ownership to stay eligible. If 6a (actually

two items) identified the firm as already substantially trading, the case was over qualified

and instead transferred to the ‘suspected young firm’ sequence. Otherwise, the case was

tentatively qualified as a nascent firm.

Figure 4: Sampling and screening procedure


35

4.2 Identifying young firms

Operational businesses that were less than four years old were classified as young firms.

In addition to the filters above to prevent overlapping, checks were introduced to ensure

that the firms were operational but not in a mature stage. As indicated in Figure 4, to be

included as YF, the case had to:

- confirm the third screening item (3, which already requires ownership)

- confirm having at least one 12-month episode where revenue covered all costs half

of the time

- date the first such episode as occurring within the last three years

In other words, if minimum trading requirement was confirmed (4b: a twelve month

period where revenues > costs half the time) and the business started in 2004 or later (5b),

the case was treated as tentatively confirmed young firm. If 4b was not confirmed, the case

was transferred to 4a and tested for eligibility as a nascent firm. Under certain

circumstances cases could get into a loop and arrive at 4b for the second time. This

question was then skipped and they go directly to 5b. If that question was not affirmed the

case was deemed ineligible.

Furthermore, in rare cases where ambiguities would arise, additional questions and criteria

were asked in the following situations to ascertain whether the firm was a NF or a YF:

a) when a respondent was involved in both a valid NF and a valid YF, preference was

given to the former

b) and when a respondent was involved in more than one valid NF, preference was given

to the most recently initiated effort

In all, this exercise resulted in the identification of 1,010 NFs and 1,058 YFs in the first

wave of data collection (2007/2008). Of these, 625 NFs and 559 YFs completed the full

interview and were then followed longitudinally.

4.3 Identifying the control group

As noted earlier, a ‘control group interview’ was performed on a random sub-sample of

cases that did not qualify as NF or YF. Among the non-eligible cases every 50th respondent


36

(non-respondent) was selected for inclusion in a Control Group (CG) (n=508) to allow for

basic socio-demographic comparisons. This group was interviewed in Wave 1 only.

4.4 Identifying HP firms

Start-ups with ‘high potential’ (above average characteristics) were classified as High

Potential (HP) firms and were identified using judgment sampling. 100+ ‘high potential’

cases in each of the NF and YF categories were added and examined as part of the study.

These were sourced from a wide range of organizations that had potential networks and

dealings with this type of start-ups. The use of many different sources served to minimize

any particular bias in the sample.

The ‘suspected’ HP cases were subjected to an expanded, customized screening using a

combination of criteria relating to human capital (education, management experience, and

start-up experience); aspirations (growth orientation); technological sophistication and

newness (innovation; IP protection); and being in a ‘growth friendly’ industry. A

compensatory scoring system was developed such that no particular characteristic was

necessary for HP status whereas a predefined total score had to be reached across the

dimensions. Cases that reached this pre-defined total score were included in the study and

subjected to the full length interview. 226 HP cases completed the W1 interview (106 NF

and 120 YF). The criteria for distinguishing between high potential NFs and YFs were the

same as in the random sample.

4.5 Classifying venture and respondent status in follow-up interviews

In subsequent follow-up interviews (conducted at 12 month intervals for waves 2, 3, 4),

first the eligibility and categorization of the venture were confirmed. Subsequently, its

transition to operational status or termination was determined using a series of questions.

During the follow-up Wave 5 after a 36 month interval only selected questions for

classifying the venture and respondent status were asked. The following criteria therefore

apply to waves 2 to 4. Questions were harmonized with the PSED-II by applying the

following strict criteria:


37

4.5.1 Criteria to establish transition to operational status (NF)

Becoming an operational firm is an important outcome for nascent firms. Operational

status can be determined based on the following criteria:

Q1) Has this business received any sales revenue, income, or fees for more than six

of the past twelve months? [Variable name: Wx_A22]

Q2) Was the monthly revenue more than monthly expenses for more than six of the

past twelve months? [Variable name: Wx_A24]

Q3) Are salaries for the owners who were active in managing the business included

in the computation of monthly expenses? [Variable name: Wx_A26]

(See Table 10 below: Operational/ Active start-up)

Unlike PSED II which used the criterion of Q1+Q2+Q3 for a venture to be classified as

operational, CAUSEE adopted a slightly different approach. For interview question wording

purposes, the venture was considered to be operational if the respondent answered in the

affirmative to Q1 above. Users of the data can use Q1 or Q1+Q2 or Q1+Q2+Q3 as their

outcome criterion. Timestamps obtained in relation to the first occurrences of these events

were also used in conjunction with these benchmarks to allow harmonization with PSED-II.

Cases that are not classified as ‘terminated’ or ‘operational’ are classified as ‘still trying’.

Variable W2_A38 (and corresponding in latter waves) is a status variable computed from

the criteria described above. These variables are available in Wave 2-4. For a few cases

where this information is missing, similar status information (albeit self-perceived) can be

obtained from variable W2_A0 (and corresponding) which was asked as part of the

introduction to the interview.

4.5.2 Criteria for termination of NF or disengagement of respondents

1) NF cases were not eligible for inclusion in future waves if:

a) They failed to answer ‘yes’ to either of the following questions: “In the past

twelve months, since the first interview, did you devote more than one

hundred and sixty hours – four weeks of full time work – to this business start-

up?” [Variable name: Wx_A9] or “Over the next six months, do you expect to


38

spend more than eighty hours – two weeks of full time work – on this business

start-up?” [Variable name: Wx_A13] and

b) If they answered ‘no’ to “Over the next six months, will somebody else spend

more than eighty hours – two weeks of full time work – one this business start-

up?” [Variable name: Wx_A14] and

c) They answer ‘disengaged’ to the question “Do you consider yourself to be

actively involved with the new business start-up you were working on 12

months ago, or disengaged from it?” [Variable name: Wx_A17] and/or

d) They answer ‘yes’ to “It appears that neither you nor anyone else is currently

working on the start-up you were working on 12 months ago. Is that correct?”

[Variable name: Wx_A20]

2) NF cases were also not eligible for inclusion in future waves if there were major or

unrelated deviations from earlier stated product or service offering(s). That is,

where the respondent claims that what they now (intend to) offer the market is a

“completely different product or service” [Variable name: Wx_A5] and that this is a

new effort that did not grow organically out of the original one [Variable name:

Wx_A6], are regarded as terminated. (Note: no cases were excluded on this basis

after the first follow-up interview, i.e. in Wave 2)

Based on the aforementioned questions in Section A, it was determined a) whether the

NF venture was terminated or b) whether the NF respondent discontinued (although the

venture might still be in operation). If either or both applied, the case was terminated and

taken through Section C (Gestation Activities) and the exit interview (see Section 4.5.5 -

Treatment of Terminated Cases below). Technically, the latter are still ‘eligible’, i.e., from a

venture level perspective, data is missing from the data set rather than being non-

existent/irrelevant. From an interviewing point of view terminated ventures and continuing

cases with a disengaged respondent are treated equally (other than in the exit interview).

Correspondingly, the NF venture status (W2_A38), the respondent status (W2_A39) and

the interview scheme (W2_A40) together established the nascent checkpoint (see table

below).


39

Table 10: Nascent checkpoint

A38. Venture Status A39. Respondent status A40. Interview Scheme

1. Operational 1.Objectively involved 1. Operational

1. Operational 2. Subjectively involved 1. Operational

1. Operational 3. Subj. inv.; poss. by others only 1. Operational

2. Active start-up 1. Objectively involved 2. Active start-up

2. Active start-up 2. Subjectively involved 2. Active start-up

2. Active start-up 3. Subj. inv.; poss. by others only 2. Active start-up

1. Operational 4. Disengaged 3. Reduced

2. Active start-up 4. Disengaged 3. Reduced

3. Terminated after operational 4. Disengaged 3. Reduced

4. Terminated before operational 4. Disengaged 3. Reduced

4.5.3 Criteria for termination of YF cases or disengagement of respondents

1) YF cases were terminated if the respondent fails to affirm “Is this business still

active? Is it still trading regularly and are you or others working with it at this point

in time?” [Variable name: Wx_A15] and

2) The respondent answers ‘Bankrupt’ or ‘Closed without bankruptcy’ to “Can you

explain a little more what happened? Did the firm go bankrupt; did you close down

voluntarily; is it a seasonal business that is currently off season, or is the business

dormant but you intend to re-activate it?” [Variable name: Wx_A16]

Akin to NFs, based on the aforementioned questions in Section A, it was determined a)

whether the YF venture was terminated or b) whether the YF respondent discontinued. If

either applied, the case was terminated (or reduced) and taken through the exit and wrap-

up interview (see Section 4.5.5 - Treatment of Terminated Cases below). Similar to NFs, the

latter YF cases are still ‘eligible’, but from an interviewing point of view they are treated

equally (other than in the exit interview). Correspondingly, the YF venture status (Wx_A41),

the respondent status (Wx_A42) and the interview scheme (Wx_A43) together established

the young firm checkpoint (see table below).

Table 11: Young Firm Checkpoint

A41. Venture Status A42. Respondent status A43. Interview Scheme

1. Operational 1. Engaged 1. Full YF

1 Operational 2. Uncertain 1. Full YF

1. Operational 3.Disengaged 2. Reduced

2. Uncertain 1. Engaged 1. Full YF

2. Uncertain 2. Uncertain 1. Full YF 2. Uncertain 3. Disengaged 2. Reduced

3 Terminated 3. Disengaged 2. Reduced


40

4.5.4 Criteria for termination of NF/YF or disengagement of respondents in Wave 5

Cases were terminated if:

a) The respondent answers ‘no’ to the question “Is this business still active? Are you

or others working with it at this point in time? [Variable name: W5_Q3] or

b) The respondent answers ‘disengaged’ to the question “Do you consider yourself to

be actively involved with this new business or disengaged from it? [Variable name:

W5_Q4]

Additionally, respondents were asked whether it is more or less than 12 months since

anyone was doing any work on this business. Depending on the answer two different

termination checkpoints were computed during the interview:

- Terminated any time [Variable name: Termin00]

- Terminated last 12 months [Variable name: Termin12]

4.5.5 Treatment of terminated cases

NF terminated cases were flagged as REDUCED and were first taken through Section C

(Gestation Activities) and then through the Section X and Z (Exit interview & Wrap up).

Similarly, YF terminated cases were flagged as REDUCED and were first taken through

Section B (Activities – Young Firms) and then through Section X and Z (Exit interview &

Wrap up). In Wave 5, selected questions in terms of gestation activities were asked and

then respondents were taken through Section X (Exit interview). In addition, during Wave 5

respondents from terminated cases and respondents who disengaged from a business

start-up were taken through a re-entry interview (Section R) if they indicated that they are

starting or trying to start another new business. Criteria for inclusion in the re-entry

interviews are described in the following section 4.6.


41

4.6 Identifying respondents for Re-Entry interviews (W5)

Wave 5 included a separate section (Section R) to survey respondents who re-enter

entrepreneurship after previous disengagement or termination. Criteria for inclusion in the

re-entry interviews were:

1) The business was classified in Wave 5 as being terminated at any time [Variable

name: Termin00] or

2) The respondent answered in Wave 5 to be disengaged from the venture [Variable

name: W5_Q4] or

3) The respondent was previously classified as being disengaged [Variable name: Pre-

Disengaged]

Consistent with the screening in Wave 1 (cf. Section 4.1 et seqq.), aforementioned

respondents were asked the following questions to assess whether they re-entered or try

to re-enter entrepreneurial activities:

1) Potential re-entry NFs were screened using the following two questions:

a) Are you, alone or with others, currently trying to start a new business, including

any self-employment or selling any goods or services to others? (W5_R1)

b) Are you, alone or with others, currently trying to start a new business or a new

venture for your employer, an effort that is part of your normal work? (W5_R2)

2) Potential re-entry YFs were identified using the following question:

a) Are you, alone or with others currently the owner of a business you help

manage, including self-employment or selling any goods or services to others?

(W5_R3)

Those who positively responded to the questions above were identified either as potential

re-entry NFs or re-entry YFs. If the answer to all questions was ‘no’ the interview was

ended. Eligibility was further confirmed by question W5_R8:

- Will you personally own all, part, or none of this business?

If the respondent answered either ‘all’ or ‘part’ the interview was continued, otherwise

respondents were not classified as re-entry entrepreneurs and surveying was ended. The

screening identified a sample of 120 re-entry entrepreneurs who completed the interview.


42

5. Information on variables

This section provides information on the variables used in CAUSEE. The variables are mainly

of two types:

a) Primary variables – derived from the direct responses via the survey instrument

that was administered

b) Computed variables – derived using the primary variables and based on responses

to more than one data item. E.g. indices based on multiple item scales. This section

also includes an overview of possible outcome variables

5.1 Primary variables

In the first year of data collection (W1), the CAUSEE dataset had approximately 600

primary variables. These variables were organized to gather information according to the

venture type and corresponding to different sections of theoretical interest (See table 12).

There were some changes to the primary variables in subsequent waves; however, in

essence the changes were of a minor nature.

Table 12: Sections in the interview schedule (reproduced from Table 5 above)

Section Purpose Applies to Harmonized with US-PSED II

Waves

Screening Assesses the suitability of the respondent

All respondents including

control group respondents

Yes W1

Basic respondent demographics

Captures demographic information

All ventures and control group respondents

Yes W1


Categorizing the venture on a number of dimensions

All ventures Mostly W1-W5

Gestation activities Initiation and completion of certain activities typical for start-ups, inclusive of time stamps for these events

Nascent ventures

Yes W1-W5

Activities Similar to above but adapted to young firms and without time stamps

Young Firms N/A W1-W5


43

Venture idea newness

Degree of 4 types of newness (product, marketing, process/sourcing, target market)

All ventures Unique to CAUSEE

W1-W3

Venture idea relatedness

Degree of relatedness to prior knowledge; available resources; market opportunities

Nascent ventures

Unique to CAUSEE

W1

Venture idea change

Different types of changes of the idea and reasons for these changes

Nascent ventures

Unique to CAUSEE

W1-W4

Venture idea source

Insights gained through different sources (e.g. previous jobs, education, hobby etc.)


W5

Effectuation Behaviours reflecting theoretical effectuation principles


W1-W4

Team Resources The investment of Human, Social, Financial and other resources


Resource advantages

Identification of particular resource strengths and weaknesses (RBV)


W1-W3

Bricolage Use of frugal tactics for obtaining and combining resources


W1-W3

Sources of funding and advice

Use and relative importance of different sources

All ventures Unique to CAUSEE/funding info simplified in

CAUSEE

W1-W3

Internationalization International experiences, perceptions and ambitions


W1-W5

Future expectations

Assessing the founders/ views on the firm’s future development


Location Different types of location (e.g. business incubator), reasons for changing the venture’s location, and customers’ location


W5

Collaboration Identifies different collaboration partners and reasons for these collaborations


W5

Government support

Use of different types of government support


W5


44

Exit interview Reflections upon their involvement and experience with the start-up



ongoing ventures

N/A W2-W5


Assess the suitability of the respondent for the re-entry interview



ongoing ventures

Unique to CAUSEE

W5

Re-Entry interview Surveys disengaged founders of terminated and ongoing ventures who start or try to start a new venture; classifies the venture; addresses selected questions from previous waves

Re-entering respondents

Unique to CAUSEE

W5

Over 100 variables were screening and demographic questions which comprise the first

two sections in Table 13. The remaining variables were grouped into different sections.

Each section comprised items representing a construct of theoretical interest. For example,

Section 2 (Newness) had 12 questions related to business idea newness in nascent and

young ventures. Terminated cases answered an exit interview section (W2-W5). A re-entry

section (W5) was administered to respondents who start or try to start a new venture after

previous termination or disengagement.

Note: The primary variables also include:

- Time stamp variables for the gestation activities in NF which recorded the time stamps for the initiation and completion of business activities relating to the start-up process.

E.g., If a respondent has answered ‘yes’ to the development of proprietary technology, processes or procedures [Variable name: W2/3/4_C27], a following question was asked in relation to the timing of the business activity: In what month [W2/3/4_C28M] and year [W2/3/4_C28Y] was the proprietary technology or process developed for this new business?

- Elapsed time variables for ancillary data that recorded the time taken by the respondent to answer the questions between two time points. E.g., ET2, the second time elapsed variable records the time taken by respondents to answer questions up to variable A10.

- Case information variables that contain classification information about the cases (e.g., ID variable contains identifying information about each case; W2_A43 variable contains information about whether the YF is operational or terminated).


45

5.1.1 Naming of primary variables

The CAUSEE longitudinal data was collected over a six-year period. Five different sets of

survey instruments9 were used in the collection of the CATI-RDD interview data. The

primary variables and the response categories used across the five waves were largely

consistent with a few exceptions: The variable naming conventions in Wave 1 and Wave 5

were different in comparison with Wave 2/3/4. As indicated earlier, on account of a

technical error, the variable names in Wave 1 were incorrectly represented by the question

numbers (e.g., Q53#) instead of section numbers which are much clearer to understand. In

the subsequent waves 2,3 & 4 this error was rectified by using section numbers as the

variable names (e.g., A1). For waves 2, 3 & 4 a consistent standardized approach was

followed which originated from Wave 2. In the follow-up Wave 5, due to the considerably

reduced questionnaire and the differing objective of this wave, the survey instrument did

not follow the subdivision into sections as done in waves 2,3 & 4. See table 13 in the next

section for a comparison between W1 and W2/W3/W4 and W5 variables.

Below, the variable naming conventions followed in Wave 1, in Wave 2,3 & 4 and in

Wave 5 are explained.

- Wave 1: The variable name consists of either a three-element code (e.g., Q53#) or

a four-element code (e.g., Q59#A) as illustrated below:

a) In the three-element code variable (Q53#), the prefix “Q” represents the

symbol for the question; the two digit number “53” represents the unique

question number associated with the particular variable; and the suffix “#”

signifies the variable stands on its own and is not arranged within a set of

closely associated variables;

b) In the four-element code variable (Q59#A), the prefix “Q” represents the

symbol for the question; the two digit number “59” represents the unique

question number associated with the particular variable; and the suffix “#”

followed by “A” signifies that the variable is the first in a set of other closely

associated variables. For instance, Q59#A is followed by Q59#B, Q59#C, Q59#D,

Q59#E and Q59#F – all relating to “Helped to start up a new business”.

9 Survey instruments available online: http://eprints.qut.edu.au/49327/

http://eprints.qut.edu.au/49327/


46

Please note that in addition to the two-digit numbers shown above (i.e., 53 & 59), the

variables are also represented by three-digit numbers (e.g., Q347#) as well as four-digit

numbers (e.g., Q2022#A).

- Wave 2,3 & 4: In general, the variable name consists of a four-element code (e.g.,

W2_A1) using letters and numbers and separated by underscore ( _ ). The prefix

indicating that the variable belongs to Wave 2 and the suffix indicating the section

(A) and question (1). Other notable points were:

a) Each section was assigned a new letter and number which proceeded in

ascending order. For example, Section A commenced with “A010” and ended

with “A51”; similarly Section B commenced with “B1” and ended with “B24”.

b) Elapsed time variables interspersed with the other variables were named using

a combination of letters and ascending numbers. E.g., “ET8” shows us that this

variable measures the elapsed time after seven (7) time intervals.

c) Some variables were named showing periods of activity or points in time.

Example: “A11H” showed ‘hours’ devoted; “A11W” showed ‘weeks’ devoted;

“A11M” showed ‘months’ devoted; “A19Y” showed ‘year’ active role ended.

d) 10 variables in Section L were named using a three-element code {i.e., L15A-

L15D (four variables) & L16A-L16D (four variables)}.

- Wave 5: In general, similar to waves 2,3 & 4 the variable name consists of a four-

element code (e.g., W5_Q1) using letters and numbers and separated by

underscore ( _ ). However, since Wave 5 was not entirely separated into sections

(as waves 2,3 & 4) the logic of the naming convention is slightly different and can

be divided into two groups:

a) For the Wave 5 condensed follow-up interviews, questions were not separated

into sections and therefore variables are continuously named in the format

10 Question number ‘0’ (zero) is a special case that applies only to Section A of Waves 2,3,4 and Section R of Wave 5. Normally, the sequence starts with question number 1. Question A0 and R0 were asked while introducing the interview, before the interview had formally commenced.

Handy hint: A11H/ A11W/A11M are alternative response formats. For this type, the information from the three formats should be combined into one variable using the same unit across all cases with valid data in (H)ours, (W)weeks, or (M)onths. A pre-computed variable Wx_time_invested is available in the dataset for waves 2,3 & 4 providing information about the amount of time in hours invested into the firm.


47

W5_Q1 to W5_Q95. The prefix indicating that the variable belongs to Wave 5

and the suffix indicating the question number (e.g. Q1).

b) For Exit (X) and Re-Entry (R) interviews variables are named according to the

section applicable. That is, e.g. W5_X1 and W5_R1. The prefix indicating that

the variable belongs to Wave 5 and the suffix indicating the section (either X or

R) and the question (1).

Other notable points are:

a) Some variables were named showing points in time. Example: W5_Q12M

captures the month and W5_Q12Y captures the year when revenue first

exceeded monthly expenses.

b) Some variables were named using a three-element suffix code. Example: Q32A-

Q32D capturing the percentages of customers located within different

distances from the business (from A=local to D=abroad).

5.1.2 Labelling of primary variables

Other than the variable name, the variable label can also be used to identify primary

variables in waves 1-5. Unlike the variable name, the labelling of the primary variables is

consistent across the five waves. The variable labels generally consist of six elements:

- The first part comprises the thematic topic the respective variable belongs to (if

applicable)

- The second part contains the information about the variable (if applicable)

- The third part comprises the variable name

- The fourth part presents information on data availability across waves

- The fifth part identifies the questionnaire section to which the variable belongs in

Wave 1 (if applicable; that is if the variable is available in Wave 1).

- The sixth part identifies the questionnaire section to which the variable belongs in

Wave 2-4 (if applicable).

- The seventh part identifies the questionnaire section to which the variable belongs

in Wave 5 (if applicable).

- If applicable, an eighth part identifies a comparable variable in other waves if not

the exact same question has been used across the waves.


48

Example 1: The label of variable W3_F1

BUSINESS IDEA CHANGES - the products or services that you sell or intend to sell, W3_F1

(W1234, W1: Q238#A S4-Q1, W234: F1)

- The main thematic topic of this question is business idea changes

- The question asks for the products or services that you sell or intend to sell

- The variable name is W3_F1

- This question was asked in Waves 1,2,3,4; but not in Wave 5

- In Wave 1 the variable name is Q238#A and the respective section in the

questionnaire is S4 (question Q1). In Waves 2, 3 & 4 the variable refers to question

1 in Section F.

Example 2: The label of variable W5_Q26

INTERNATIONAL ACTIVITIES - Imports of goods or services from abroad ANY TIME EVER

W5_Q28 (W5, W1234: na, W5: Q28) [cf W1: Q360#D S10-Q1D, W234: J6]

- The main thematic topic of this question is international activities

- The question asks for imports of goods or service from abroad any time ever

- The variable name is W5_Q28

- This question was only asked in Wave 5, but not in Waves 1,2,3,4

- In Wave 5 the variable refers to Question 28 of the questionnaire

- The last part [cf W1: Q360#D S10-Q1D, W234: J6] tells that a comparable variable is

available in Waves 1,2,3,4. The variable name for Wave 1 is Q360#D and the

respective section in the questionnaire is S10 (question Q1D). In Waves 2,3 & 4 the

variable refers to question 6 in section J.

In particular the bracketed last part of the variable label contains all necessary

information to identify and find the matching variables across all five waves; if applicable.

Table 13 below summarises the labelling of variables and shows how variable labels

throughout the five waves can be matched with corresponding sections and themes.


49

Table 13: Section and Theme Identification Table (Group-wise)

Variable label

starting with

No of variables

Range Variable label

includes the

sections

No of variables

Range Variable label

includes the

sections

No of variables

Range

Screener

Wave 1 Section W1-A

Wave 2/3/4: --

Wave 5: General questionnaire

SA, SB, SC 46 SA…SC12 A7 (SC5); A22 (SC6); A24 (SC7); A51 (SC2)

4 -- Q 2 Q10A; Q17

Demographic

Wave 1: Section W1-B

Wave 2/3/4: --

Wave 5: --

ID 11 ID1…ID12 -- -- -- -- -- --

Interview participation

Wave 1: Section W1-C

Wave 2/3/4: --

Wave 5: --

T 7 T1…T4 -- -- -- -- -- --

Appointment follow-up

Wave 1: Section W1-D

Wave 2/3/4: --

Wave 5: --

QA0 (a,b,c) 2 QA0B…QA0C -- -- -- -- -- --


Wave 1: Section W1-E

Wave 2/3/4: Section A


QB 33 QB1A…QB21 A 59 A0…A51 Q 24 Q1…Q17

Activities (YF) & Gestation activities (NF)

Wave 1: Section 1: Activities (YF)

Wave 2/3/4: Section B


S1-YF 21 S1-YF-Q1… S1-YF-Q4E

S1-YF-Q37… S1-YF-Q45

B 24 B1…B24

Q 10 Q18…Q26

Wave 1: Section 1: Gestation activities I (NF)

Wave 2/3/4: Section C

S1-NE 46 S1-NE-Q5A… S1-NE-Q36

C 153 C1…C106

Wave 1: Section 1: Activities (YF) & Gestation activities I (NF)

Wave 2/3/4: Section B & Section C

S1-NE/YF 4 S1-NE/YF-Q5B…

S1-NE/YF-Q25

see Section B & Section C above


50

Business Idea Newness (NF/YF)

Wave 1: Section 2

Wave 2/3/4: Section E

Wave 5: --

S2-Q 12 S2-Q1… S1-Q12

E 32 E1…E32 -- -- --

Business Idea Relatedness (NF)

Wave 1: Section 3

Wave 2/3/4: --

Wave 5: --

S3-NE-Q 12 S3-NE-Q1… S3-NE-Q1

-- -- -- -- -- --

Business Idea Change (NF/YF)

Wave 1: Section 4:

Wave 2/3/4: Section F

Wave 5: --

S4-Q 15 S4-Q1… S4-Q5

F 15 F1…F15 -- -- --

Business Idea Source (NF/YF)

Wave 1: --

Wave 2/3/4: --


-- -- -- -- -- -- Q 7 Q57…Q63

Gestation activities II (NF)

Wave 1: Section 5

Wave 2/3/4: Included in Section C


S5-NE-Q 74 S5-NE-Q1… S5-NE-Q37

see Section C above see above

Effectuation (NF/YF)

Wave 1: Section 6

Wave 2/3/4: Section G

Wave 5: --

S6-Q 10 S6-Q1… S6-Q8

G 10 G1…G10 -- -- --

Team resources (NF/YF)

Wave 1: Section 7

Wave 2/3/4: Section D

Wave 5: --

S7-Q 81 S7-Q1… S7-Q27

D 109 D1…D107 -- -- --

Resource advantages (NF/YF)

Wave 1: Section 8

Wave 2/3/4: Section H

Wave 5: --

S8-Q 33 S8-Q1(a)… S8-Q5(d)

H 99 H1…H106 -- -- --

Sources of funding (NF/YF)

Wave 1: Section 9

Wave 2/3/4: Section I

Wave 5: --

S9-NE/YF-Q 64 (32NF+32YF)

S9-NE/YF-Q1A…

S9-NE/YF-Q2N

I 35 I1…I35 -- -- --

Internationalisation (NF/YF)

Wave 1: Section 10

Wave 2/3/4: Section J


S10-Q 21 S10-Q1(a-k)… S10-Q8

J 18 J1…J18 Q 4 Q28…Q31

Bricolage (NF/YF)


51

Wave 1: Section 11

Wave 2/3/4: Section K

Wave 5: --

S11-Q 9 S11-Q1… S11-A1

K 9 K1…K9 -- -- --

Future expectations (NF/YF)

Wave 1: Section 12

Wave 2/3/4: Section L


S12-Q 22 S12-Q0A… S12-Q9D

L 16 L1…L16 Q 25 Q32A-Q56

Wrap Up (NF/YF)

Wave 1: Section 13

Wave 2/3/4: Section Z

Wave 5: --

S13-Q + misc 2 S13-Q4… S13-Q5

Z 5 Z1…Z5 -- -- --

Location (NF/YF)

Wave 1: --

Wave 2/3/4: --


-- -- -- -- -- -- Q 9 Q64…Q71; Q86

Collaboration (NF/YF)

Wave 1: --

Wave 2/3/4: --


-- -- -- -- -- -- Q 14 Q72…Q85

Government support (NF/YF)

Wave 1: --

Wave 2/3/4: --


-- -- -- -- -- -- Q 10 Q87…Q95Y

Exit interview

Wave 1: --

Wave 2/3/4: Section X

Wave 5: Section X

-- -- -- X 29 X1…X29 X 27 X1…X27


Wave 1: --

Wave 2/3/4: ---

Wave 5: Section R

-- -- -- -- -- -- R 8 R1…R8

Re-Entry Interview

Wave 1: --

Wave 2/3/4: ---

Wave 5: Section R

-- -- -- -- -- -- R 36 R9…R37

Note: There may be slight variations in the number and organisation of variables throughout waves due to adaptions and updates in the questionnaire. Therefore, number of variables and ranges should be understood as indicative but do not replace an inspection of the dataset and the variable overview in this document. Example: ‘Exit interview’ Section X comprises 27 questions in Waves 2 and 5, but 29 questions in Waves 3 and 4. Example: ‘Future Expectations’ Section L includes additional questions in Wave 3 to account for potential effects of the Global Financial Crisis (GFC). Example: The section on ‘Bricolage’ was included in waves 1,2,3 but not in waves 4,5.


52

5.2 Computed variables

Computed variables are derived using the primary variables and are mostly based on

responses to more than one data item. The research team computed a range of variables in

order to facilitate use and analysis of the data. For example, several potential outcome

variables were computed reflecting information on sales, profits or venture status. While

these variables may be very useful for a broad range of analyses it is strongly

recommended that users inspect (1) the syntax of the computed variable, (2) the primary

source variables and (3) the corresponding sections in the questionnaires to retrace scope

and limitations of the computed variables prior to any use.

Other variables were computed for identification and classification purposes or to

consolidate information from regular surveys and catch-up surveys. Additionally, some

variables were computed in compliance with data privacy requirements. The following

pages list and describe the computed variables.

5.2.1 Computations accounting for data privacy requirements

Accounting for data privacy requirements and to ensure non-identifiability of

respondents, some variables needed to be removed from the publicly available CAUSEE

dataset. However, for most of these cases alternative variables were computed which

ensure privacy for the respondents and their ventures, and at the same time allow users of

the dataset to conduct meaningful analyses. As a general rule, these computed variables

aggregate or categorise information originally contained in the primary variables. Following

variables were computed and are included in the dataset.

Venture location: Remoteness area [Variable name: REMOTENESS]: Detailed venture

location variables such as postcode or city are not included in the publicly accessible

dataset. However, a variable denoting the geographic environment of the venture was

computed, following the classifications of the Australian Bureau of Statistics (ABS). This

allows users to differentiate between ventures which are based in (1) Major Cities of

Australia, (2) Inner Regional Australia, (3), Outer Regional Australia, (4) Remote Australia,

and (5) Very Remote Australia. For a detailed description about background and


53

interpretation of the classification please refer to the Australian Bureau of Statistics’

website11.

Industry: Sector aggregation for HP firms [Variable name: Wx_Sector_HP_firms]: The

industry variable for the smaller sample of HP firms was aggregated into broader sectors

(e.g. Retail-Wholesale; Manufacturing, Mining & Utilities etc.). The variable is placed after

the corresponding industry variable in each wave. Please note that the primary industry

variables (i.e. Q127 and Wx_A8) do not contain information for HP firms.

Industry: Sector aggregation for W5 re-entry section [Variable name: W5_Sector_RE]:

Similarly, the industry variable for respondents surveyed in the Wave 5 re-entry section

was aggregated into sectors.

Number of current owners [Variable name: Wx_Owners]: The number of current

owners was re-computed into categories; i.e. 1, 2, 3, 4 and 5 or more owners. Please note

that further variables are available which, for example, specifically contain information on

whether the venture is being started by a solo-entrepreneur or together with a spouse/de-

facto partner; e.g. Q135#.

Number of female owners [Variable name: W1_female_owners]: The number of female

owners was re-computed into categories; i.e. 1, 2, 3, 4 and 5 or more female owners.

Number of male owners [Variable name: W1_male_owners]: The number of male

owners was re-computed into categories; i.e. 1, 2, 3, 4 and 5 or more male owners.

Age difference between youngest and oldest owner [Variable name: Age_difference]:

This variable reflects the age difference between the youngest and the oldest owner of a

business.

Number of active businesses owned [Variable name: W1_businesses_owned]: The

number of active businesses owned was categorized; i.e. 1, 2, 3, 4 and 5 or more.

11 http://www.abs.gov.au/websitedbs/D3310114.nsf/home/remoteness+structure

http://www.abs.gov.au/websitedbs/D3310114.nsf/home/remoteness+structure


54

5.2.2 Identification and classification variables

Variables in this section were computed to ease identification and classification of cases.

Several variables are available to assist during potential analyses. Syntax for the following

variables in this sub-section is noted in Appendix 3 (available in a separate appendices

document).

Random sample firm filter [Variable name: Filter_RSFirm]: This variable can be used to

identify the 1,184 random sample firms in the dataset. This variable accounts for both

nascent and young firms.

High potential firm filter [Variable name: Filter_HPFirm]: This variable can be used to

identify the 226 HP firms in the dataset. This variable accounts for both nascent and young

firms.

Pilot study filter [Variable name: Filter_PS]: This variable can be used to identify the 106

cases which are included from the pilot study (see 3.1.3). This variable includes randomly

sampled nascent firms, young firms and a non-entrepreneur control group. In combination

with the other identification variables, these sub-groups can be filtered.

Non-Entrepreneur control group [Variable name: Filter_CG]: A control group of 508

cases not involved in starting up a new business is included in the dataset with basic

demographic information. This variable can be used to identify the non-entrepreneur

control group.

Nascent firm with complete W1 interview [Variable name: Filter_NFW1]: This variable

can be used to identify the 731 (625+106) nascent firms in the dataset with Wave 1

interviews. This variable includes both the random and the high potential sample.

Nascent firm (random sample) with W1 interview [Variable name: Filter_NFRSW1]:

This variable identifies the 625 nascent firms from the random sample with Wave 1

interviews.


55

Nascent firm (high potential sample) with W1 interview [Variable name:

Filter_NFHPW1]: This variable identifies the 106 nascent firms from the high potential

sample with Wave 1 interviews.

Young firm with complete W1 interview [Variable name: Filter_YFW1]: This variable

can be used to identify the 679 (559+120) young firms in the dataset with Wave 1

interviews. This variable includes both the random and the high potential sample.

Young firm (random sample) with W1 interview [Variable name: Filter_YFRSW1]: This

variable identifies the 559 young firms from the random sample with Wave 1 interviews.

Young firm (high potential sample) with W1 interview [Variable name: Filter_YFHPW1]:

This variable identifies the 120 young firms from the high potential sample with Wave 1

interviews.

Longitudinal nascent firm [Variable name: Filter_NF_longitudinal]: This variable can be

used to identify nascent firms with known “final” outcome; i.e., outcome information is

available from Wave 5 or the case is known to be previously terminated. Both random and

high potential sample firms are included.

Longitudinal young firm [Variable name: Filter_YF_longitudinal]: This variable can be

used to identify young firms with known “final” outcome; i.e., outcome information is

available from Wave 5 or the case is known to be previously terminated. Both random and

high potential sample firms are included.

Product-Service classification [Variable name: Wx_PS_classify]: Based on Q128# in W1

respectively A44 in W2-4, this variable indicates whether the firm (intends to) mainly offer

products (Wx_PS_classify=0) or services (Wx_PS_classify=1). This variable is placed directly

after Q128# or A44.

Time invested by nascent entrepreneurs [Variable name: Wx_time_invested]: This

variable combines the three variables A11H, A11W and A11M in W2-4 – containing

information about the hours, weeks or months of time invested by the nascent

entrepreneurs – into a single variable. Due to the different questionnaire this information is


56

not available for Wave 5. Wx_time_invested is in total hours invested into the start-up in

the 12 month period prior to the W2-4 interviews. Thereby we assume that a week is

equivalent to 40h of work and a month is equivalent to 168h of work. Due to an error of

the survey vendor, the time invested question was not part of the W1 questionnaire.

However, catch-up questions were asked in an email-catchup after W1 (ECW1_Q1_hours,

xxx_weeks, xxx_months, ECW1_Q2_hours, xxx_weeks, xxx_months) and in W2 (W2_A12H,

W2_A12W, W2_A12M). From these information a W1_time_invest variable was computed

applying the following procedure:

a. If available, we used data from the W2 catch-up question (W2_A12) for computation

of the time invest variable following the steps as described above for W2-4.

b. Some did not respond to W2 catch-up question (W2_A12) but to the email-catch up

after W1. Here, the starting point of the computation is the email-catchup data on

“total time invested since inception” (ECW1_Q1xxx). As the time lag between the

original W1 interview and the email-catch-up differs among the nascent firms, we

proportionally reduced this time investment to the time since project initiation

(timing of the second earliest gestation activity) and time between the W1 interview

and the email catch-up. The computation is as follows: Time invested from start until

W1 = total time invested since start*time from start until W1/time from start until

W1 + time from W1 to email catch-up. This builds on the assumption that working

time is roughly equally invested since project start.

c. For the remaining missing cases we imputed time invested with an auxiliary

regression. Thereby we used predicted values from a negative binomial model

regressing the time invested from steps b and c on timing of the second earliest

gestation activity, number of completed gestation activities, team size and hours

worked per week (Q332#). For two cases with missing info for Q332# we replicated

this procedure excluding this variable from the auxiliary regression.

d. W1_time_invested comes in two different versions. W1_time_invested1 comprises

steps a) and b). W1_time_invested2 comprises steps a), b), and c).


57

5.2.3 Consolidation of variables from regular waves and catch-up rounds

As noted earlier in this handbook, during some waves there were issues with single

survey items which led to partially incomplete data gathered during regular waves. Catch-

up questions were administered via email or telephone to collect missing information. The

following variables are consolidations from regular waves and catch-up rounds. In general,

if both regular and catch-up variables had data for the same case, the value from the

regular wave was used.

Please note that users should exercise some caution when using the consolidated

variables. Due to the time lag between regular wave and catch-up round answers may be

subject to a recall bias. Additionally, for a few variables the time period captured is not

entirely equivalent for the regular wave variable and the catch-up variable. Users are

encouraged to inspect the original source variables in combination with the questionnaire

before using the consolidated variables. In the CAUSEE dataset file, consolidated variables

are placed under the corresponding regular wave variable.

Table 14: Consolidated variables

Regular wave variable Catch-up variable Consolidated variable

W2_C85 W3_C85_w2 W2_C85_consolidated



W3_A22A TCW3_A22A W3_A22A_consolidated

W3_A23M TCW3_A23M W3_A23M_consolidated

W3_A23Y TCW3_A23Y W3_A23Y_consolidated

W3_A24A TCW3_A24A W3_A24A_consolidated



W3_A26 TCW3_A26 W3_A26_consolidated



W4_A22A TCW4_ANYSALES W4_A22A_consolidated

W4_C85 TCW4_C85 W4_C85_consolidated

W4_A24A TCW4_ANYPROFITS W4_A24A_consolidated

W4_A26 TCW4_A26 W4_A26_consolidated


58





W4_L17 TCW4_L17 W4_L17_consolidated







W4_X28 TCW4_X28 W4_X28_consolidated

W4_X29 TCW4_X29 W4_X29_consolidated

Q2017#Q W2_I33 Q2017#Q_consolidated

Q2017#R W2_I34 Q2017#R_consolidated

Q2019#C W2_I35 Q2019#C_consolidated

5.2.4 Outcome variables

Depending on the user’s particular interest and research question, almost anything in

(at least later waves) in the CAUSEE data set could conceivably be used as ‘dependent

variable’ in relational analyses. Not least does the longitudinal nature of the data, where

the same question is asked at 12-month intervals (and partially in the follow-up survey in

Wave 5), allow that many types of change can be used as DV in analyses of surviving cases.

As regards dependent variables reflecting ‘business performance’ the alternatives listed

below – at least – are available. References to variable names use the stem of the variable

name from W2 and onwards, for ‘translation’ to W1 and W5 variables see Section 5.5.2

below.

1) Especially for NF – and for early stages – some of the Gestation Activities (See 5.5.3

below) can be used either for computation of achieving individual milestones

(completion of product development; first external finance), or as a cumulative

variable (e.g. number of gestation activities completed between two waves of data

collection). This type of outcome variable arguably reflects ‘making progress’

(rather than being a direct measure of ‘success’). Gestation Activities are collected


59

from all cases that are interviewed in a wave, including those that report having

terminated since the last interview. However, for many of the activities the

question is re-asked only when the activity has not been confirmed

initiated/completed in a previous wave. Therefore, computing variables across

waves may be necessary in order to correctly represent the status of the venture.

For some examples of computed variables see the next section 5.2.5.

2) The status of the venture as operational vs. terminated can be derived from

variable A38 (NF) or A41 (YF) in Wave 2,3 & 4. For NF there is a third category: ‘Still

Trying’ to establish the venture. These variables were dynamically computed during

the interview based on a combination of answers to previous questions (see

Section 4.5). Continuation vs. termination arguably assesses ‘persistence’ (rather

than success). Conversely, ‘termination’ is not necessarily the same as ‘failure’ or a

‘worse’ outcome than is continuation (e.g., of a loss-generating business). Users

may want to consult the variables in section X to better understand the reason and

cost of termination in individual cases. For a few cases with missing data on

A38/A41 similar status information is given by variable A0.

3) Having established regular sales (A22) that cover all costs (A24; A26). These

variables apply to NF only.

4) Existence and levels of sales and profits. For YF this information is given by

variables B18-B20; for NF the corresponding information is found in variables C85-

C87. Computed variables are available; see section 5.2.5.

5) Self-assessed performance in relation to expectations. This information is collected

from all participating respondents except for those who have

terminated/discontinued their engagement in the present wave. The question has

four items that can be used individually or as a computed index: profit, sales, cash

flow, and company value. This information is given by variables L1-L4.

6) Self-assessed performance in relation to competitors. This information is collected

from YFs and NFs with regular sales. The question has the same four items as just

described, which can be used individually or as a computed index: profit, sales,

cash flow, and company value. This information is given by variables L5-L8.

7) Existence and numbers of employees. For YF, this information is reflected in

variables B15-B17 whereas for NF the corresponding variables are C77 and C79-80.

Comparison across waves allows the computation of ‘employment growth’.


60

8) Whether or not the venture has recouped all its start-up costs. This information is

reflected in variables L17-L19 for surviving cases (Note: L18 is not available in Wave

5) and X28-X29 for terminated cases. The question was only asked from

respondents reporting positive cash flow at any time, so eligible cases with system

missing value can safely be assumed NOT to fulfil this criterion. Unfortunately, the

variables are only available from W3 and W4, so the information is missing for

cases terminating in W2 or not participating (although eligible) in W2-W3; similarly

it is missing for W5. Please also note that due to an error in the CATI script of the

Wave 4 questionnaire, some ventures skipped these questions. Catch-up

interviews were conducted in order to minimize missings. The corresponding

variables have the variable names TCW4_L17-L19, X28-S29. Also see section 5.2.3

for computed variables which consolidate information from regular and catch-up

waves.

9) Self-assessed value of the business is available for W3, W4 and W5. This

information is given by variables L20-L23. Please note that due to an error in the

CATI script of the Wave 4 questionnaire, some ventures skipped these questions.

Catch-up interviews were conducted in order to minimize missings. The

corresponding variables have the variable names TCW4_L20-L23. Also see section

5.2.3 for computed variables which consolidate information from regular and

catch-up waves.

10) Existence and proportion of international sales. This information is contained in

variables J8-J15. In combination with level of sales (see 4 above) this also allows

computation of absolute international sales. In Wave 5 questions were slightly

changed and information is available in variables W5_Q30 and W5_Q31.

5.2.5 Pre-computed outcome variables

Several variables were computed which, depending on the research objective, may be

used as outcome variables. The computed variables in this section are based on primary or

computed variables throughout the five waves. Prior to using the variables it is strongly

recommended to consult the respective questionnaires and original variables in the

dataset. This section provides a brief description of each computed outcome variable. The

detailed syntax is included in Appendix 3 (available in a separate appendices document)

and allows inference on scope and limitations of each of the variables.


61

Nascent firms’ highest outcome achieved [Variable name: NF_highestoutcome]: This

variable is based on venture status information from waves 2 to 5 and provides information

on the highest outcome a nascent firm has ever achieved throughout all waves. That is,

whether revenues cover expenses (including or excluding owner’s salary), the venture is

operational with sales, it is still trying or it has been terminated. A second variable [Variable

name: NF_highestoutcome_wave] records the time (i.e. the wave) this highest outcome

was achieved.

Nascent firms’ latest known outcome [Variable name: NF_latestoutcome]: This variable

provides information on the latest known outcome a nascent venture has achieved; in

terms of whether revenues cover expenses (including or excluding owner’s salary), the

venture is operational with sales, it is still trying or it has been terminated. Values are

based on venture status information from waves 2 to 5. A second variable [Variable name:

NF_latestoutcome_wave] records the time (i.e. the wave) this latest known outcome was

achieved.

Start-up costs covered [Variable name: startup_costs_covered]: This variable is

dichotomous and indicates whether a venture has ever covered its start-up costs.

Information in this variable is based on outcome sections and venture status information

from waves 2 to 5.

Highest sales achieved: Data in this variable records the highest amount of sales a firm

has ever achieved throughout the five waves. The variable is available for young firms

[Variable name: YF_highest_sales] and nascent firms [Variable name: NF_highest_sales].

Information in these variables is based on primary variables from all waves (B-Section:

Activities Young Firms; C-Section: Gestation Activities Nascent Firms). Additionally, the

corresponding variables [Variable name: YF_highest_sales_wave] and [Variable name:

NF_highest_sales_wave] record the time (i.e. the wave) when the highest amount of sales

was achieved.

Latest known sales: This variable includes the latest known amount of sales for a

venture. For example, latest known sales might have been reported during Wave 5. If not,

information from Wave 4 is included etc. The variable is available for young firms [Variable


62

name: YF_latest_sales] and nascent firms [Variable name: NF_latest_sales]. Information in

these variables is based on primary variables from all waves (B-Section: Activities Young

Firms; C-Section: Gestation Activities Nascent Firms). Additionally, the corresponding

variables [Variable name: YF_latest_sales_wave] and [Variable name:

NF_latest_sales_wave] record the time (i.e. the wave) when the latest known amount of

sales was achieved.

Highest profits/Smallest losses: This variable captures the highest profit (or smallest

loss) a business has ever achieved. The variable is available for young firms [Variable name:

YF_highest_profits] and nascent firms [Variable name: NF_highest_profits]. Values in this

variable are based on respondents’ answers to questions in sections B and C. Additionally,

the corresponding variables [Variable name: YF_highest_profits_wave] and [Variable name:

NF_highest_profits_wave] denote the time (i.e. the wave) the highest profit was achieved.

Latest known profits/losses: Information in this variable allows tracing back when there

is the most recent data available in terms of profits or losses. If latest known profits/losses

have not been reported during Wave 5, data from Wave 4 is included etc. The variable is

available for young firms [Variable name: YF_latest_profits] and nascent firms [Variable

name: NF_latest_profits]. Values in this variable are based on respondents’ answers to

questions in sections B and C. Additionally, the corresponding variables [Variable name:

YF_latest_profits_wave] and [Variable name: NF_latest_profits_wave] denote the time (i.e.

the wave) for which latest profit/losses data is available.

Highest number of employees: This variable captures the highest number of employees

a business has ever employed. In accordance with the information available throughout the

waves, separate variables are available for (1) employees working 35 or more hours and for

(2) employees working less than 35 hours. These variables are available for young firms

[Variable name: YF_employees_max_ft] / [Variable name: YF_employees_max_pt] and

nascent firms [Variable name: NF_employees_max_ft] / [Variable name:

NF_employees_max_pt]. Additionally, the corresponding variables [Variable name:

YF_employees_max_ft_wave] / [Variable name: YF_employees_max_pt_wave] and

[Variable name: NF_employees_max_ft_wave] / [Variable name:

NF_employees_max_pt_wave] record the time (i.e. the wave) the highest number of

employees was employed by a business.


63

Latest known number of employees: This variable incorporates information on when

there is the most recent data available in terms of staff employed. Similarly to the previous

set of variables, separate variables are available for (1) employees working 35 or more

hours and for (2) employees working less than 35 hours. These variables are available for

young firms [Variable name: YF_employees_latest_ft] / [Variable name:

YF_employees_latest_pt] and nascent firms [Variable name: NF_employees_latest_ft] /

[Variable name: NF_employees_latest_pt]. Additionally, the corresponding variables

[Variable name: YF_employees_latest_ft_wave] / [Variable name:

YF_employees_latest_pt_wave] and [Variable name: NF_employees_latest_ft_wave] /

[Variable name: NF_employees_latest_pt_wave] record the time (i.e. the wave) for which

latest employment data is available.

5.3 Known issues and recommended fixes

The CAUSEE data collection was a very complex undertaking involving many different types

of start-ups; themes, and development trajectories. Inevitably, some design omissions and

programming errors affect parts of the data. Although most analyses undertaken by most

users would likely not be affected by these errors it is important to be aware of the issues

that have been identified as well as of possible remedies. These are discussed below.

5.3.1 Sales, profits section

Unfortunately, this important section for nascent firms suffers from multiple issues listed

below:

- W1: Not all HP nascent firms completed the screener survey. This is because they were

not identified via random sampling but were sourced from a wide range of organizations

that had potential networks and dealings with this type of start-ups. However, the

survey vendor erroneously assumed they had completed the screener questions within

this identification process. As a result, some cases have missing information for Q61#

(any sales), Q62# (regular sales) and Q63# (regular profits).


64

- W2: There are no questions in the W2 questionnaire regarding achieving “any” sales

(A22A) and “any” profits (A24A). For those who don’t have regular sales or profits, we

thus do miss this important outcome information. This error is inherited from PSED II

and was fixed midway through the W3 data collection.

- W3:

Midway through W3, the research team recognized the missing of the questions

regarding “any” sales (A22A) and profits (A24A). For the remainder of the wave these

questions were incorporated into the CATI questionnaire. The other cases were

recontacted by phone. The respective catch-up questions ECW3_A22a, ECW3_A23M,

ECW3_A23Y, ECW3_A24a, ECW3_A25M, ECW3_A25Y, ECW3_A26, ECW3_A27M, and

ECW3_A27Y are included in the dataset. However, due to the complexity of the

issue, the programming of this catch-up questionnaire was not completely correct.

The respective questions were thus not asked all relevant cases.

The skip pattern prior to W3_A23, W3_A25 and W3_A27 was wrongly programmed

in the CATI questionnaire and thus the respective question was either skipped or

often erroneously asked.

The skip pattern prior to W3_A26 building on data from previous waves was not

programmed correctly (connects to W1 having profits instead of whether salaries

were included in the computation of expenses).

There is no uniform design of the inter-wave skip patterns in Wave 3. Sometimes one

skips the qualifying question (such as A26), but sometimes one skips the timing of an

activity (A23 and A25). This hampers the comparison of these variables with its

counterparts in other waves.

- W4:

The inter-wave skip pattern for questions W4_A23 and W4_A25 did not work as

intended. Thus, these questions were erroneously asked from too many

respondents.

The design of the inter-wave skip patterns in Wave 4 differs from Wave 3 and Wave

2. This hampers the comparison of these variables with its counterparts in other

waves.


65

W4_C85 (level of sales), W4_C86 (level of profits), W4_C87 (level of losses) and

connected questions in Section L (W4_L17 etc.) were erroneously skipped for those

who do not have regular sales (A22) but might have some sales in Wave 4. This is

because the respective skip pattern for A24A relies on prior wave information and

leads to skip if the firm had some sales in W1-3.

After extensive analysis of the problems, the research team has several recommendations:

- Regular sales (A22) and regular profits (A24): These primary variables can be used

throughout the waves as they are not affected by the issues.

- Having profits while owner-manager salaries are included in the computation of

expenses (A26): Can be used in W2 without issues, but approximately 10%-20% eligible

cases have missing values in W3 and W4.

- Any sales (A22A) and any profits (A24A): These variables should not be used. They

contain valuable but sometimes misleading information.

- Timing of first sales (A23), first profits (A25) and profits including salaries for owner-

managers (A27): These variables can be used without issues in W1 and W2, but they

often contain repeated information as respondents were sometimes asked the same

question in both waves. If so, use the timing information in the earlier wave. In Wave 3

it is safe to use A23 and A25 but not A27. In Wave 4 it is safe to use A27 but not A23 and

A25.

- Where a question has been asked from too many respondents the user can use the skip

pattern suggested in the questionnaire to filter out cases that should not have been

asked the question.

5.3.2 Business plan section

In Wave 3 and Wave 4 some pilot nascent firms skipped the questions C55-C63. This is

due to a data re-export error. The survey vendor treated the pilot cases and the remaining

regular W1 cases as two different “jobs” which led to errors when combining both data

sets. It is recommended to drop the pilot cases when analysing the business plan section.


66

5.3.3 Differences between the pilot questionnaire and regular W1 questionnaire

A small number of design changes between pilot and main studies affect data pertaining to

the pilot cases (cf. section 3.1.3):

- Q77#. Respondents’ highest level of education. The pilot questionnaire offers the

response categories 1=High School while this was split up in the W1 questionnaire in

5=High School Yr 10 and 6=High School Yr 12. An SPSS syntax is available to compute a

harmonized education variable (cf. Appendix 3 in the separate appendices document).

- Internationalization section. Nascent firms were not asked the majority of the

internationalization section in the pilot questionnaire. This section was asked nascent

firms in the regular W1 interviews. The recommendation is to drop the pilot cases (using

computed variable Filter_PS) when analysing the internationalization questions.

- Q518# and Q520#. These outcome questions were asked young firms in the pilot

questionnaire but not in the regular W1 questionnaire.

- Q2005#. Screener question for year of business founding of young firms. The cut-off

points for qualifying as young firm was changed from 2002 or later in the pilot

questionnaire to 2004 and later in the regular W1 questionnaire. Because the pilot

study commenced 6 months prior to the regular W1 interviews, young firms identified

in the pilot study (founded 2002 and 2003) are of somewhat similar age as the young

firms in the main study and thus do not need to be dropped from the analysis.

5.3.4 Time invested for nascent entrepreneurs

The W1 questionnaire did not include questions on the time invested by the nascent

entrepreneurs. In order to gain this information retrospectively, the research team

conducted a catch-up survey (questions ECW1_Q1xxx, Q2xxx) and included catch-up

questions in Wave 2 (W2_A12H, A12W, A12M). Note that pilot nascents were skipped from

the catch-up survey after W1. As the handling of these different time invested questions

can be complicated, the researchers pre-computed the respective variables

Wx_time_invested which contain information about the absolute number of hours

invested by the entrepreneurs into the start-up. More information on these pre-computed

variables can be found in Section 5.2.


67

5.3.5 Sources of funding and advice

Due to a programming error in W1 data on sources of funding were not collected for the

questions Q2017#Q (Equity from venture capital firms), and Q2017#R (Equity from any

other organization). Likewise there were no data collected for question Q2019#C (Advice

from external investors). Catch-up questions in Wave 2 (I33-I35) can be used to fill these

gaps. Also see section 5.2.3 for computed variables which consolidate information from

regular and catch-up waves.

5.3.6 Commencement date for HP cases

Due to a miscommunication with the survey vendor, HP cases were not asked the

screener questions. The missing variable includes the commencement date for young firms

(Q2005#). Catch-up questions in Wave 4 (HPSC9A, HPSC9B, HPSC9C) can be used to

compute the age of the respective firms. In the dataset the variables are placed in the

screener section after Q2005#.

5.3.7 Financial losses

Due to a CATI programming error, data are missing for question W2_X24 for most cases

which qualify for this question (X18=1). Unfortunately, there is no fix for this issue.

5.3.8 Time stamped gestation activities

Due to unusual inter-wave skip patterns, some timing information for gestation activities is

missing in W2-4:

- Registering legal form of business: Those answering “No” to formally registering the

business in Wx (Q133#=2 / Wx_C8=2) skip correctly the timing question in Wx.

However, they also skip the timing question (C9) in Wx+1 if they confirm that the form

of the legal business remains the same as in the in Wx. This error sums up to the

following numbers of missing timing data in Wx+1 given the firm still participated in the

survey: W2=134, W3=5, W4=3 cases. There is no fix available for this issue.


68

- IP protection: Those answering “Yes” to submitting IP protection in Wx (Q176#=1 /

Wx_C29=1) but had not granted a patent yet in Wx (Q437#=9997 / C30Y=8888) skip the

respective block of questions in Wx+1. Consequently, the time stamp is missing in

subsequent waves when submitted patents were granted. This affects W2-4. However,

for unknown reasons CATI scripts of W2-4 do not offer the response category “Still in

progress” to the IP granting time stamp question. It is very likely that “Still in progress”

answers are mixed with the “Don’t know” response category. This error sums up to the


survey: W2=33, W3=9, W4=0 cases. The research team recommends imputing the time

stamp as “middle of the wave” if the respondent mentions IP protection as competitive

advantage in question Wx+1_H85i.

- Funding: Those answering “Yes” to seeking funding in Wx (Q515#=1 / Wx_C68=1) but

had not received funding yet in Wx (Q244#=2 / C70=2) skip the respective block of

questions in Wx+1. Consequently, the time stamp is missing in subsequent waves Wx+1

when funding from outside sources was first received. This affects W2-4. This error

sums up to the following numbers of missing timing data in Wx+1 given the firm still

participated in the survey: W2=56, W3=18, W4=4 cases. The research team

recommends imputing the time stamp as “middle of the wave” if the respondent

acknowledges to use external funding sources in Wx+1 (I4, I11, I12, I13, I16, I17, I18).

Those who state that those sources played no role in funding in Wx+1 should be treated

as having received no outside funding in Wx+1.

- Business plan revision: Those answering “Yes” to having some form of a written

business plan in W1 (Q499#=2 or 3) which however was not yet finished in W1

(Q505#=9997) skip the respective time stamp question (C57) in W2. This only affects W2

as the response category “still in progress” for the business plan timing question was

dropped in W3 and 4. The number of missing timing data in W2 given the firm still

participated in the survey is 47 cases. The research team recommends imputing the

time stamp as 6 months prior to the time stamp of the potential revision of the business

plan in W2 (C58).

- Development of proprietary technologies: Those answering “Yes” to developing

proprietary technologies in Wx (Q174#=1 / Wx_C27=1) but did not finish this activity in

Wx (Q433#=9997 / C28=9997) skip the respective block of questions in Wx+1.

Consequently, the time stamp is missing in subsequent waves Wx+1 when the


69

proprietary technology was developed. This affects W2-4. This error sums up to the


survey: W2=8, W3=1, W4=4 cases. The research team recommends imputing the time

stamp as “middle of the wave” if the respondent mentions “technology development”

as competitive advantage in question Wx+1_H85i.

- Regulatory requirements: Those answering “Yes” to determining regulatory

requirements in Wx (Q193#=1 / Wx_C44=1) but did not finish this activity in Wx

(Q451#=9997 / C45=9997) skip the respective block of questions in Wx+1.

Consequently, the time stamp is missing in subsequent waves Wx+1 when the

regulatory requirements were determined. This affects W2-4. This error sums up to the


survey: W2=11, W3=6, W4=3 cases. There is no fix available for this issue.

- Internal non-response in W2: 7 cases (ID: 21562, 21689, 25070, 25910, 27561, 28308,

40114) have internal non-response for a sizeable part of the questionnaire (sections E-

K). The reason for this is unknown and there is no fix available.

- International activities in W1-3: For unknown reasons, the questions Q360#I / J12 and

Q360#J / J13 have rather non-matching wording variations for product and service

firms. In detail, the exact wording of these questions is:

Q360#I / J12 IF PRODUCT: Export of products through your own foreign office?

Q360#I / J12 IF SERVICE: Export by selling services produced in Australia directly

to customers located abroad?

Q360#J / J13 IF PRODUCT: Export of products directly to customers abroad?

Q360#J / J13 IF SERVICE: Selling directly to customers abroad by producing and

selling services in their countries

It is suggested to bundle Q360#I / J12 and Q360#J / J13 for products into one variable

and Q360#I / J12 and Q360#J / J13 for services into a new variable. As bundling mechanism

the research team suggests OR bundling, giving the value “1=Yes” if e.g. the firm has had

exports of products through your own foreign office OR sold products directly to customers

abroad. In combination these two variables could basically be interpreted as selling

products/services abroad at the firm’s own account using own firm resources.


70

comprehensive australian study of entrepreneurial ... › 49327 › 1209 › causee... ·...

Documents