Comprehensive Australian Study of
Entrepreneurial Emergence (CAUSEE)
Handbook & User Manual
Version 7
www.bus.qut.edu.au/research/ace/
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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.”
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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
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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
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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]
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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/
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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.
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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.
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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
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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.
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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.
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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.
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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
Wave 2 Regular firms
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
Wave 3 Regular firms
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
Wave 4 Regular firms
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
Wave 5 Regular firms
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#.
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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/
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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,
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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
******
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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
All ventures Unique to CAUSEE W1-W4
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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)
All ventures Unique to CAUSEE W1-W3
Bricolage Use of frugal tactics for obtaining and combining resources
All ventures Unique to CAUSEE 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
All ventures Unique to CAUSEE W1-W5
Future expectations Assessing the founders/ views on the firm’s future development
All ventures Partly W1-W5
Location Different types of location (e.g. business incubator), reasons for changing the venture’s location, and customers’ location
All ventures Unique to CAUSEE W5
Collaboration Identifies different collaboration partners and reasons for these collaborations
All ventures Unique to CAUSEE W5
Government support
Use of different types of government support
All ventures Unique to CAUSEE W5
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
Terminated ventures;
discontinued founders of
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
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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.
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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}
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- 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)
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.
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).
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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
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.
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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.
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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.
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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.
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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
(random sample) and 180 firms (HP sample) that were eligible from W2, we were able to at
least partially interview 634 random sample cases and 152 HP cases. This comprised 281
NFs (82.4% of eligible cases) & 353 YFs (89.4% of eligible cases) and a HP sample of 71 NFs
(83.5% of eligible cases) & 81 YFs (85.3% of eligible cases).
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.
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(random sample) and 134 firms (HP sample) that were eligible from W3, we were able to at
least partially interview 447 random sample cases and 122 HP cases. This comprised 185
NFs (85.6% of eligible cases) & 262 YFs (84.8% of eligible cases) and a HP sample of 58 NFs
(93.5% of eligible cases) & 64 YFs (88.9% of eligible cases).
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.
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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
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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)
W4 eligible cases {N=216 (Ran); N=62 (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)
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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)
W3 eligible cases {N=395 (Ran); N=95 (HP)}
Eligible but not interviewed
N=87 (Ran) N= 22 (HP)
W4 eligible cases {N=309 (Ran); N=72 (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)
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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
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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).
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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)
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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
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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
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(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:
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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
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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).
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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
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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.
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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.
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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
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
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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 principles
All ventures Unique to CAUSEE
W1-W4
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)
All ventures Unique to CAUSEE
W1-W3
Bricolage Use of frugal tactics for obtaining and combining resources
All ventures Unique to CAUSEE
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
All ventures Unique to CAUSEE
W1-W5
Future expectations
Assessing the founders/ views on the firm’s future development
All ventures Partly W1-W5
Location Different types of location (e.g. business incubator), reasons for changing the venture’s location, and customers’ location
All ventures Unique to CAUSEE
W5
Collaboration Identifies different collaboration partners and reasons for these collaborations
All ventures Unique to CAUSEE
W5
Government support
Use of different types of government support
All ventures Unique to CAUSEE
W5
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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
Terminated ventures;
discontinued founders of
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).
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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/
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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.
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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.
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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.
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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 -- -- -- -- -- --
Classifying the venture
Wave 1: Section W1-E
Wave 2/3/4: Section A
Wave 5: General questionnaire
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
Wave 5: General questionnaire
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
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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: --
Wave 5: General questionnaire
-- -- -- -- -- -- Q 7 Q57…Q63
Gestation activities II (NF)
Wave 1: Section 5
Wave 2/3/4: Included in Section C
Wave 5: General questionnaire
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
Wave 5: General questionnaire
S10-Q 21 S10-Q1(a-k)… S10-Q8
J 18 J1…J18 Q 4 Q28…Q31
Bricolage (NF/YF)
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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
Wave 5: General questionnaire
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: --
Wave 5: General questionnaire
-- -- -- -- -- -- Q 9 Q64…Q71; Q86
Collaboration (NF/YF)
Wave 1: --
Wave 2/3/4: --
Wave 5: General questionnaire
-- -- -- -- -- -- Q 14 Q72…Q85
Government support (NF/YF)
Wave 1: --
Wave 2/3/4: --
Wave 5: General questionnaire
-- -- -- -- -- -- 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
Screening Re-Entry Interview
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.
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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
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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
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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.
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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
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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).
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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
W2_C86 W3_C86_w2 W2_C86_consolidated
W2_C87 W3_C87_w2 W2_C87_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_A25M TCW3_A25M W3_A25M_consolidated
W3_A25Y TCW3_A25Y W3_A25Y_consolidated
W3_A26 TCW3_A26 W3_A26_consolidated
W3_A27M TCW3_A27M W3_A27M_consolidated
W3_A27Y TCW3_A27Y W3_A27Y_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
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W4_A27M TCW4_A27M W4_A27M_consolidated
W4_A27Y TCW4_A27Y W4_A27Y_consolidated
W4_C86 TCW4_C86 W4_C86_consolidated
W4_C87 TCW4_C87 W4_C87_consolidated
W4_L17 TCW4_L17 W4_L17_consolidated
W4_L18 TCW4_L18 W4_L18_consolidated
W4_L19 TCW4_L19 W4_L19_consolidated
W4_L20 TCW4_L20 W4_L20_consolidated
W4_L21 TCW4_L21 W4_L21_consolidated
W4_L22 TCW4_L22 W4_L22_consolidated
W4_L23 TCW4_L23 W4_L23_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
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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’.
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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.
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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
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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.
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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).
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- 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.
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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.
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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.
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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.
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- 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
following numbers of missing timing data in Wx+1 given the firm still participated in 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
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proprietary technology was developed. 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=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
following numbers of missing timing data in Wx+1 given the firm still participated in 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.
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