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The impact of human capital on the early success of necessity versus opportunity-based entrepreneurs

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Abstract

This paper examines whether founders’ backgrounds influence new firm survival in the early years after startup, focusing, in particular, on the impact of unemployment-driven entrepreneurship. For entrepreneurs who left their previous employment to found a new firm, both general and specific human capital play a key role in enhancing early survival chances. However, various forms of human capital have little effect on early survival of unemployment-driven entrepreneurs, who rely mostly on previous entrepreneurial experience to persevere. Results suggest that pre-entry capabilities play an important role in the early success of opportunity-based entrepreneurs, but have little influence on the early success of necessity-based ones.

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Notes

  1. We distinguish between a variety of sources of founder human capital: formal education; work experience; industry-specific experience; managerial experience; and business ownership experience.

  2. Busenitz et al. (2003, p. 298) point out that “opportunities do not come to fruition without unique insights, perspectives, and interpretations by the founders, and are not transformed into wealth generation without organizing actions”.

  3. According to the GEM definition, an enterprise is classified as a young business if it has paid salaries and wages for more than three months but for less than 42 months, and as an established business if it has paid salaries and wages for more than 42 months (Acs et al. 2005).

  4. This definition of spinout is used by, among others, Agarwal et al (2004) and Klepper (2001, 2007)—who uses the term “spinoff.” While it may be deemed too inclusive (not all founders incorporated into this concept are necessarily exploiting opportunities discovered while working for their previous employer), any bias that may be introduced would counteract the effects supporting the hypotheses being tested.

  5. The present study is restricted to business owners who have started their businesses, therefore excluding those who have acquired or inherited ownership. We believe that, in considering only starters and not acquirers and inheritors, we may better approach the concept of entrepreneurship as understood by the management literature (Busenitz et al. 2003).

  6. The data have information about each individual’s occupational position and status within the firm coded using the International Standard Classification of Occupations (ISCO) and the International Classification by Status in Employment (ICSE).

  7. Year-level dummy variables are included in these estimations.

  8. Although the data allow for lower levels of industry aggregation, a change in ISIC definitions in 1994 prevents us from making correspondences between sectors before and after that alteration. Such correspondences are indispensable to track founders’ pre-entry experiences.

  9. About 51 % of startups are founded by entrepreneurial teams.

  10. Entrepreneur age is measured in the year of founding. Using dummy variables for age classes considerably reduces the inevitable high correlation between age and work experience.

  11. The average length of an unemployment spell in our data is 1.3 years. Although the vast majority of individuals who appear “unemployed” in the Quadros de Pessoal database in fact correspond to the share of the workforce who is without occupation and actively searching for employment, a small minority may be composed of inactive individuals (e.g. people who were once employed but went back to being ful-time students), or individuals who are employed in industries not covered by the database (e.g. agriculture).

  12. During the period under analysis, there was no government support specifically directed at start-ups by the unemployed in Portugal. Support was available equally, irrespective of employment status.

  13. An alternative procedure would be to estimate single models including interaction (moderator) variables corresponding to the product between the employment (opportunity-based) dummy and each of the entrepreneur human capital variables. However, estimation by use of separate models for each type of entrepreneur avoids using interaction effects whose interpretation, especially in a Logit framework, is always problematic.

  14. A model pooling all entrepreneurs and adding interaction effects between the Employment variable and the human capital variables was estimated, showing significantly positive interaction effects favoring previously employed founders, thus supporting the results of the separate estimations presented here. Results are available from the authors upon request.

  15. Tests comparing the Wald statistics for models with and without the variables accounting for entrepreneurial characteristics show that the inclusion of this set of variables significantly improves explanatory power at the 1 % significance level for all cohorts individually and the sample as a whole.

  16. Results are omitted because of lack of space and are available from the authors upon request.

  17. Also, recent research finds evidence of a match between founders’ and early employees’ characteristics and human capital (Baptista et al. 2013).

  18. The completion of a high school degree seems to have a bigger impact when compared with primary education than a university degree, but both are significantly positive across all cohorts and for the complete sample.

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Acknowledgments

The authors wish to thank participants in the Interdisciplinary European Conference on Entrepreneurship Research and at the Academy of Management Annual Conference for useful discussion. We are also grateful for comments by two anonymous reviewers. We are indebted to the “Ministério do Trabalho e da Solidariedade Social” (Portuguese Ministry of Labor and Social Solidarity) for allowing us access to the data used in this paper. Support from “Fundação para a Ciência e Tecnologia” (Portuguese Foundation for Science and Technology in the form of funding for research projects PTDC/GES/71174/2006 and CMU-PT/Etech/0036/2008 is also gratefully acknowledged.

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Authors and Affiliations

  1. Brunel Business School, Brunel University, Kingston Lane, Uxbridge, Middlesex, UB8 3PH, UK

    Rui Baptista

  2. CEG-IST, Universidade de Lisboa, Lisbon, Portugal

    Rui Baptista

  3. Department of Econometrics, Faculty of Economics and Administrative Sciences, Akdeniz University, Antalya, Turkey

    Murat Karaöz

  4. IN+ Center for Innovation, Technology and Policy Research, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    Joana Mendonça

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  1. Rui Baptista
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Correspondence to Rui Baptista.

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Baptista, R., Karaöz, M. & Mendonça, J. The impact of human capital on the early success of necessity versus opportunity-based entrepreneurs. Small Bus Econ 42, 831–847 (2014). https://doi.org/10.1007/s11187-013-9502-z

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