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1 Queensland University of Technology Panel Studies of New Venture Creation: a Review and Suggestions for Future Research Per Davidsson & Scott R. Gordon

2 Queensland University of Technology Paul D. Reynolds Recipient of the 2004 “Global Award for Entrepreneurship Research”

3 Queensland University of Technology Panel Studies of Nascent Entrepreneurs/ Venture Creation: Historical roots Pre- PSED Pilots PSED SwPSED; Other country sudies e.g. Gartner (1988); Katz & Gartner, 1988; Bhave, 1994 CAUSEEPSED 2 e.g. Sarasvathy, 2001; Shane, 2000; Baker & Nelson, 2005; Dahlqvist, 2007 e.g. China; Switzerland … GEM

4 Queensland University of Technology PSED-type Research: Basic Procedure Approach a very large, random sample of households or individuals Screen this sample for ‘nascent entrepreneurs’ = individuals currently involved in an active business start-up that is not yet an up-and-running firm Conduct a longer interview with those qualified as well as a randomly selected comparison group An important part of the contents concerns the initiation/completion and timing of a range of ‘gestation activities’ Follow up over time (every 6-12 months over months)

5 Queensland University of Technology Basic Rationales Overcome under coverage of smallest/newest entities Achieve international comparability Overcome selection bias Overcome hindsight bias/memory decay Allow the study of process issues Get temporal order of measurement right for causal analysis

6 Queensland University of Technology Studies of Nascent Entrepreneurs(hip) = the study of individuals who are currently involved in a business start-up. They may or may not have started other firms before (‘nascent’ is not equal to ‘novice’) = the study of on-going start-up efforts during their creation. They may or may not become up and running firms. Level of analysis issue Representativeness of sample issue

7 Queensland University of Technology Reviewed Works All 78 PSED-type manuscript that have been published or accepted into peer reviewed, scholarly journals Based on data sets from US, Canada, Netherlands, Norway and Sweden Plus a peep into other types of publications (not ignoring, but not striving for completeness outside of the journals)

8 Queensland University of Technology

9 Queensland University of Technology ArticleSaSa GbGb NcNc WdWd Theory e ComparisonFindings Carter et al. (2003) USA5581MotivationNEs vs. GP f NEs no different than GP in seeking independence, but less motivated by roles and recognition. Male NEs likely cite innovation and financial success as career reasons. Cassar & Craig (2009) USA1984Cognitive biasesNE subgroups NEs exhibit hindsight bias. Unsuccessful NEs correct their previous overestimation of their chances of success. More highly educated exhibit less overconfidence. Cassar (2006)USA5001Human capitalNE subgroups Individuals with higher levels of financial and human capital harbor greater growth intentions. Cassar (2007)USE1704MotivationNEs vs. GP Independence and self-realization are important motivations for entry. Financial motivations determine growth preferences, most strongly so for women. Chandler et al. (2005) SEE4085Social capital Team composition over time Large NE teams are more likely than small NE teams to take on additional members, but not more likely to drop members. Davidsson & Honig (2003) SEE3804 Social and human capital NEs vs. GP Bridging and bonding social capital are robust predictors for engagement in NE-ship; as is general human capital and prior start-up experience. Delmar et al. (2000) SEA11131AtheoreticalNEs vs. GP Higher levels of HC are associated with NE status. Males, recent immigrants, and those between years, and those with role models are more likely to engage. Diochon et al. (2005a) CAE1193EclecticGender No gender or general human capital differences in likelihood that NEs would abandon their venture. Diochon et al. (2007) CAE915 Attribution theory NE subgroupsNEs predominantly offer internal-stable attributions in describing positive situations. Diochon et al. (2008) CAE915Human capitalNE subgroups Neither NEs with prior start-up experience, nor those with business education had discernibly more financial management capability than novices/no business education. Gatewood et al. (1995) US*E852 Attribution theory Gender Male-female differences in how NEs attribute entry. Males are more likely cite external factors; females tend to be driven by internal factors, while both have stable cognitions. Johnson et al. (2008) USE11142Cognitive styleNEs vs. GP NEs are more likely to have an ‘innovator’ cognitive style than the GP. This cognitive style is also associated with optimism as regards to sales. Kim et al. (2006) USA10501Forms of capitalNEs vs. GP Neither financial nor cultural capital discriminates NEs from the GP on entry. Human capital is a significant advantage, especially education or managerial experience. Liao & Welsch (2003) USA4621Social capital High tech NEs vs. others Structural, relational and cognitive social capital leads to growth intentions. Structural social capitals' effect on aspiration is less for technology based NEs. Liao & Welsch (2005) USA5441Social capital NEs vs. GP, high tech NEs vs. others No quantitative differences in various dimensions of SC between NE and the GP. However patterns of association between social, relational and cognitive SC do differentiate NEs. Technology based NEs have higher relational capital. Summary of findings on the characteristics of nascent entrepreneurs.

10 Queensland University of Technology

11 Queensland University of Technology

12 Queensland University of Technology FINDINGS REGARDING CHARACTERISTICS OF NASCENT ENTREPRENEURS (I) As regards resource endowments, results largely confirm prior research: –NEs have more Human Capital (S-E exp; Education) –Social capital more varied results. Close role model no longer important in the US? –Household wealth; income has no or little effect (but NEs with more money have higher aspirations) –Methods issue lurking!

13 Queensland University of Technology FINDINGS REGARDING CHARACTERISTICS OF NASCENT ENTREPRENEURS (II) As regards motivation and cognition, the research stream has produced novel and surprising findings: –Little or unexpected difference from others in “career motivation” –Strong evidence against push motivation (‘revenge’) –NEs are more risk averse than others!? –NEs have higher ‘Need for Closure’ – preference for order and predictability! –Theory/representativeness issue lurking!

14 Queensland University of Technology FINDINGS REGARDING CHARACTERISTICS OF NASCENT ENTREPRENEURS (III) The majority works in partnerships or teams The majority of ‘teams’ is ‘romantic’ The majority of the remaining teams aren’t exactly ‘textbook’ teams, either The functionally well-balanced team that was assembled purely for business purposes is a rare occurrence Theory/representativeness issues lurking!

15 Queensland University of Technology Population prop. = 2/7 ventures Sampling prop = 2/3 ventures (because 10/15 individuals belong to teams)

16 Queensland University of Technology Fundamental issue with investigating ‘Characteristics of Nascent Entrepreneurs’ It’s a bit like comparing ‘holiday makers’ to other people… Some of whom will, of course, go on vacation next week… So perhaps we should be looking at ‘what does the NE experience do to the person’ rather than ‘what person characteristics make you become NE’?

17 Queensland University of Technology Findings regarding new venture creation process (I): Discovery Relatively non-systematic search for opportunity, and processes triggered by a particular idea rather than by a wish to become a founder-manager seem to be relatively more common than systematic, textbook- like processes Importantly, however, this descriptive result does not necessarily have any prescriptive implications. Even if less common those ventures resulting from systematic search may achieve better outcomes

18 Queensland University of Technology Findings regarding new venture creation process (I): Exploitation Enormous variation in duration Enormous variation in sequence –Liao, Welsh and Tan (2005): “firm gestation is a complex process that includes more than simple, unitary progressive paths” (2005: 15) and “a process where developmental stages are hardly identifiable” (2005: 13). However, there are systematic sub-group differences Additional method challenges Theoretical boundary challenges

19 Queensland University of Technology Jan 1.Sep. 1May 1Dec. 31 Sampling day Annual prop. = 25/75 Sampling prop = 50/50

20 Queensland University of Technology Jan 1.Sep. 1May 1Dec. 31 Sampling day

21 Queensland University of Technology Methods Insights Level of analysis issues: The sampling procedure yields a representative sample of current nascent entrepreneurs, but a biased sample of emerging ventures or of entrepreneurial teams There is a problem with a substantial group of ‘dilettante dreamers’ who never put their effort to an ‘acid test’ Another group start more ambitious ventures but take longer to get up and running – and may mistakenly appear less ‘successful’ –CAUSEE: Higher tech; higher ambition take longer; retailing and brick-and-mortar-only get up quicker (but retail have lower survival once they are up and running)

22 Queensland University of Technology Outcome Contrast Outcome Driver Operational vs. Terminated Operational vs. Still Trying vs. Terminated Characteristic Characteristic 2 none – ++++ Characteristic 3 none+ – – – Characteristic none Characteristic 5 none ++++ Characteristic 6 none CAUSEE Digression: Analysis Example

23 Queensland University of Technology Methods insight: In this type of research it is important to –Control for type of venture –Analyse different types of outcomes at different points in time Otherwise all sorts of confounding effects will blur our understanding

24 Queensland University of Technology FINDINGS REGARDING DRIVERS OF OUTCOMES(I) Some 33-50% of nascent ventures ever reach an operational stage (self-perceived / regular sales) HC influences appear weak or inconsistent Effects of financial endowment variables and social capital indicators are also unimpressive… And a cursory look at the results for motivation and expectation isn’t very enlightening, either …but there’s more to be said… …and measures of actual investment of capital (HC,FC,SC) tend to come out with positive effects

25 Queensland University of Technology Why the weak overall results? It may be overly simplistic to assume that effects on outcomes are direct, linear and generalizable across all types of ventures, founders, and environments The venture and the individual are distinct levels of analysis. The respondents may not invest all their capital in the focal venture, and the venture may draw on capital from multiple individuals The opportunity cost structure needs to be considered when assessing the effects of human capital on outcomes Outcomes for independent ventures are hard to assess, predict and interpret – especially when the respondents try to start very different ventures

26 Queensland University of Technology Human capital indicator Study and effect a Total US b Canada c Netherlands d Norway d Sweden e General human capital f Education Work experience n/a Team vs. Solo/Team size 0170n/a (Age)6230n/a (Gender - female) (Ethnicity or minority status) 052n/a Specific human capital Management experience 1123n/a Industry experience n/a Start-up experience Business or start-up classes n/a Othern/a Summary of findings on outcome effects of human capital by country a) + denotes a sig. positive effect; 0 denotes no significant effect; - denotes a sig. negative effect (p<.05); b) based on Brush et al. (2008a); Dimov (2009); Edelman et al. (2008); Liao and Gartner (2006); Liao et al. (forthcoming); Lichtenstein et al. (2007); Newbert (2005); Parker (forthcoming); Parker & Belghitar (2006); Tornikoski and Newbert (2007); Townsend et al. (in press); c) based on Diochon et al. (2005a); Menzies et al. (2006); d) based on van Gelderen et al. (2005); e) based on Alsos and Kolvereid (1998); Alsos and Ljunggren (1998); Rotefoss and Kolvereid (2005); e) based on Davidsson and Honig (2003); Delmar and Shane (2003); Delmar and Shane (2004); Honig and Karlsson (2004); Eckhardt et al. (2006); Samuelsson and Davidsson (2009); Shane and Delmar (2004); f) We have reluctantly (hence the parentheses) followed the practice of including age, gender and ethnicity among the indicators of general HC. Effect of Human Capital on Outcomes (operational-still trying-terminated)

27 Queensland University of Technology Methods Insight We should stop looking for direct, linear and very broadly generalizable effects with respect to a single outcome variable We need to model contingent relationships and assess multiple outcome variables over time in order to disentangle the intricacies and arrive at sounder interpretations

28 Queensland University of Technology

29 Queensland University of Technology

30 Queensland University of Technology Outcome measure and effect a Total Making Progress Continuation vs. non- continuation Reaching first sales Operational vs. terminated Operational vs. any other status Reaching profitability Completed business plan of any form Composite measure of extent of planning n/a Sequence measure of early planning n/a RESULTS ON BUSINESS PLANNING AND OUTCOMES

31 Queensland University of Technology FUTURE RESEARCH… Issue / Category Users of existing data sets may want to consider… Designers of new data sets may in addition want to consider… Statistically representative and/or theoretically relevant sampling  Excluding ‘dilettante dreamers’  Ways to deal with ‘modest venture’ dominance  Testing for non-response and attrition biases  Correcting through weighting the cases (individual and team levels)  Correcting through weighting down or eliminating cases (already) of long duration (venture level)  Applying methods for obtaining high initial and continued response rates  Dealing with decline of landline phones  Obtaining a larger sample to allow more sub-sample analysis  Obtaining a narrower, more homogenous and/or higher- potential sample for stronger theory testing  Including additional categories (e.g., social enterprise)

32 Queensland University of Technology FUTURE RESEARCH… Issue / Category Users of existing data sets may want to consider… Designers of new data sets may in addition want to consider… Level of analysis issues  Consistently applying an explicit level of analysis from sample restriction through use of explanatory, control and outcome variables  Applying the hitherto under-utilized team level  Explicitly modeling influences or effects on different levels  Designing the entire project with (a) specific level(s) in mind  Basing the design on the realization that the venture may draw on resources from more than one individual and, conversely, that the founder(s) may invest their resources in endeavors other than the focal venture  Including more other-than- venture level outcome indicators

33 Queensland University of Technology FUTURE RESEARCH… Issue / Category Users of existing data sets may want to consider… Designers of new data sets may in addition want to consider… Dealing with process heterogeneity  Controlling for initial stage of development  Re-organize the data set based on project time line  Checking that assumed outcome ‘milestones’ really can be regarded process outcomes (i.e., occur late)  Applying higher level of abstraction to gestation activity patterns  Double-checking data on activities pre-dating the first interview  Further refining conceptualization and operationalization of gestation activities

34 Queensland University of Technology FUTURE RESEARCH… Issue / Category Users of existing data sets may want to consider… Designers of new data sets may in addition want to consider… Dealing with other heterogeneity issues  Using well thought through control variables  Applying sub-sample analysis  Modeling contingent effects (e.g., moderation; mediation)  Obtaining a larger sample to allow more sub-sample analysis (cf. above)  Obtaining a narrower, more homogenous and/or higher- potential sample for stronger theory testing (cf. above)  Including controls/moderators/mediators not available in existing data sets

35 Queensland University of Technology FUTURE RESEARCH… Issue / Category Users of existing data sets may want to consider… Designers of new data sets may in addition want to consider… Choice and interpretation of dependent variables  Using several, carefully selected outcome indicators  Refraining from unwarranted ‘success’ or ‘failure’ labeling of outcome indicators  Distinguishing among indicators of engagement, persistence, and success, respectively  Paying attention to heterogeneity in process duration  Including improved measures of engagement, persistence, and success (and duration)  Including more other-than-venture level outcome indicators (cf. above)  Probing further into reasons for and losses associated with termination (individual and venture level)

36 Queensland University of Technology Panel Studies of New Venture Creation Are a Great Innovation! Are Practically Feasible! Entail Quite a Number of Conceptual and Methods Related Challenges! Thank You!


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