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Is the impact of incubator’s ability on incubation performance contingent on technologies and life cycle stages of startups?: evidence from Japan

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Abstract

Supporting entrepreneurship has become an important policy target in Japan since 1990s and many incubators have been established as a part of regional innovation policy. Incubation strategy conducive to the improvement in incubation performance can be contingent on external factors, which makes it necessary to incorporate moderators, such as technology and growth phase, into the evaluation of incubators. This study examines how incubator’s ability affects incubation performance under different environments. Estimation results of a technology transfer function reveal that human resources (diversity of incubation managers’ professional experiences), physical resources (geographical proximity to universities), and organizational resources (alliance with universities) have different impacts on the creation and growth of startups according to technological fields (e.g., electronics and biotechnology) and life cycle stages (i.e., the nascent and early growth stage) of startups. Furthermore, the impact of selection strategy on incubation performance also varies according to technological fields and life cycle stages of startups. Policy implications of the key findings are discussed.

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Notes

  1. According to job description by the Japan Business Incubation Association (http://jbia.jp/biim.html accessed 12 February 2017), incubation managers nurture nascent entrepreneurs from a long-term perspective so that they can successfully create business, which is achieved through incubation managers’ tactics for business growth and strategy for new industry creation in the region.

  2. Social capital is defined as the ability of economic agents to extract benefits from their social structures, networks, and relationships (Davidsson and Honig 2003: 307).

  3. See Lewin (1947) and Allen and Cohen (1969) for knowledge gatekeepers, Burt (2003) for network entrepreneurs, Harada (2003) for knowledge transformers, and Aldrich and Herker (1977), Adams (1980), and Tushman and Scanlan (1981) for boundary spanners.

  4. Cohen and Levinthal (1990) describe this type of human capital as a gatekeeper who possesses the “knowledge of who knows what, who can help with what problem, or who can exploit new information” Cohen and Levinthal 1990: 133).

  5. Innovations in biotechnology tend to be standalone as opposed to systemic in that a final product can be clearly defined by specific information in patent documents (e.g., chemical equations), which makes it very difficult for followers to invent around, and makes patents particularly effective as appropriation mechanisms for innovators. In other technological fields, lead time and the first mover advantage are more important than legal protection. In fact, the quality of patents has a positive effect on growth of biotechnology startups (Fukugawa 2012).

  6. Previous literature shows that the flow of scientific knowledge is localized (Fukugawa 2013; Ghio et al. 2016), implying the significance of spillover channels other than publications. One of the reasons for localized flows of university knowledge lies in the characteristics of knowledge to be transferred from universities to firms. Academic inventions that are potentially valuable for industrial innovations tend to be embryonic and contain tacit knowledge of academic inventors (Agrawal 2006). Therefore, entrepreneurial firms attempting to industrialize academic inventions need to interact closely with university scientists in order to identify practical applications of the invention.

  7. For the number of graduates in the electronics industry, mean is 1.2 while variance is 11.1 for incubators aiming to support nascent entrepreneurs. Mean is 2.1 and variance is 62.1 for incubators aiming to support startups in the early growth stage.

  8. Previous entrepreneurs’ success and failure could act as regional knowledge pool from which potential entrepreneurs in the region could learn, thereby facilitating demonstration effect (Acs and Virgill 2010).

  9. It should be noted that the individual level information needed to be aggregated at the incubator level for the purpose of regression analysis.

  10. More than 80% of entrepreneurs have previous professional experience as regular employees mainly in small- and medium-sized enterprises (JFC 2010).

  11. It should be noted that it is empirically difficult to clearly distinguish the impacts of social capital and technological assistance resulting from the incubator's focus on technological skills of incubation managers.

References

  • Acs, Z., & Virgill, N. (2010). Entrepreneurship in developing countries. In Handbook of entrepreneurship research, volume 5 of the series international handbook series on entrepreneurship (pp. 485–515). New York: Springer.

    Google Scholar 

  • Acs, Z., Audretsch, D., & Lehmann, E. (2013). The knowledge spillover theory of entrepreneurship. Small Business Economics, 41, 757–774.

    Article  Google Scholar 

  • Adams, S. (1980). Interorganizational processes and organization boundary activities. In B. Staw & L. Cummings (Eds.), Research in organizational behavior (Vol. 2, pp. 321–355). Greenwich: JAI Press.

    Google Scholar 

  • Agrawal, A. (2006). Engaging the inventor: Exploring licensing strategies for university inventions and the role of latent knowledge. Strategic Management Journal, 27(1), 63–79.

    Article  Google Scholar 

  • Aldrich, H., & Herker, D. (1977). Boundary spanning roles and organization structure. Academy of Management Review, 2(2), 217–230.

    Article  Google Scholar 

  • Allen, J., & Cohen, I. (1969). Information flow in Research and Development Laboratories. Administrative Science Quarterly, 14, 12–19.

    Article  Google Scholar 

  • Amico Roxas, S., Piroli, G., & Sorrentino, M. (2011). Efficiency and evaluation analysis of a network of technology transfer brokers. Technology Analysis & Strategic Management, 23(1), 7–24.

    Article  Google Scholar 

  • Anderson, T., Daim, T., & Lavoie, F. (2007). Measuring the efficiency of university technology transfer. Technovation, 27(5), 306–318.

    Article  Google Scholar 

  • Asheim, B., Coenen, L., & Vang, J. (2007). Face-to-face, buzz, and knowledge bases: Sociospatial implications for learning, innovation, and innovation policy. Environment and Planning. C, Government & Policy, 25, 655–670.

    Article  Google Scholar 

  • Baum, J., Calabrese, T., & Silverman, B. (2000). Don’t go it alone: Alliance network composition and startups’ performance in Canadian biotechnology. Strategic Management Journal, 21(3), 267–294.

    Article  Google Scholar 

  • Bhide, V. (2000). The origin and evolution of new businesses. Oxford: Oxford University Press.

    Google Scholar 

  • Burt, R. (2003). The social capital of structural holes. In F. Guillen, R. Collins, P. England, & M. Meyer (Eds.), The new economic sociology: Developments in an emerging field (pp. 148–189). New York: Russell Sage Foundation.

    Google Scholar 

  • Cabinet Secretariat. (2016). FY2015 Report on Priority Policy Measures for Industrial Competitiveness Enhancement. http://www.kantei.go.jp/jp/singi/keizaisaisei/pdf/houkoku_honbun_160205_en.pdf. Accessed 27 Sep 2016.

  • Chapple, W., Lockett, A., Siegel, D., & Wright, M. (2005). Assessing the relative performance of university technology transfer offices in the UK: Parametric and non-parametric evidence. Research Policy, 34(3), 369–384.

    Article  Google Scholar 

  • Chukumba, C., & Jensen, R. (2005). University invention, entrepreneurship, and startups. NBER working paper #11475.

  • Cohen, W., & Levinthal, D. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.

    Article  Google Scholar 

  • Comacchio, A., Bonesso, S., & Pizzi, C. (2012). Boundary spanning between industry and university: The role of technology transfer Centres. Journal of Technology Transfer, 37, 943–966.

    Article  Google Scholar 

  • Davidsson, P., & Honig, B. (2003). The role of social and human capital among nascent entrepreneurs. Journal of Business Venturing, 18, 301–333.

    Article  Google Scholar 

  • Ebbers, J. (2014). Networking behavior and contracting relationships among entrepreneurs in business incubators. Entrepreneurship Theory and Practice, 38(5), 1159–1181.

    Article  Google Scholar 

  • Foster, L., Haltiwanger, J., & Krizan, C. (2001). Aggregate productivity growth: Lessons from microeconomic evidence. In C. Hulten, E. Dean, & M. Harper (Eds.), New contributions to productivity analysis (pp. 303–372). Chicago: The University of Chicago Press.

    Google Scholar 

  • Fukao, K., & Kwon, H. (2006). Why did Japan’s TFP growth slow down in the lost decade? An empirical analysis based on firm-level data of manufacturing firms. The Japanese Economic Review, 57(2), 195–227.

    Article  Google Scholar 

  • Fukugawa, N. (2009). Determinants of licensing activities of local public technology centers in Japan. Technovation, 29(12), 885–892.

    Article  Google Scholar 

  • Fukugawa, N. (2012). Impacts of intangible assets on the initial public offering of biotechnology startups. Economics Letters, 116(1), 83–85.

    Article  Google Scholar 

  • Fukugawa, N. (2013). University spillovers into small technology-based firms: Channel, mechanism, and geography. Journal of Technology Transfer, 38(4), 415–431.

    Article  Google Scholar 

  • Furman, J., & Stern, S. (2011). Climbing atop the shoulders of giants: The impact of institutions on cumulative research. American Economic Review, 101(5), 1933–1963.

    Article  Google Scholar 

  • Ghio, N., Guerini, M., & Rossi-Lamastra, C. (2016). University knowledge and the creation of innovative start-ups: An analysis of the Italian case. Small Business Economics, 47(2), 293–311.

    Article  Google Scholar 

  • Hackett, S., & Dilts, M. (2004). A real options-driven theory of business incubation. Journal of Technology Transfer, 29, 41–54.

    Article  Google Scholar 

  • Harada, T. (2003). Three steps in knowledge communication: The emergence of knowledge transformers. Research Policy, 32, 1737–1751.

    Article  Google Scholar 

  • Hellmann, T. (2007). When do employees become entrepreneurs? Management Science, 53(6), 919–933.

    Article  Google Scholar 

  • Howells, J. (2006). Intermediation and the role of intermediaries in innovation. Research Policy, 35(5), 715–728.

    Article  Google Scholar 

  • Hsu, D., Shen, Y., Yuan, B., & Chou, C. (2015). Toward successful commercialization of university technology: Performance drivers of university technology transfer in Taiwan. Technological Forecasting and Social Change, 92, 25–39.

    Article  Google Scholar 

  • Huang, K., & Murray, F. (2009). Does patent strategy shape the long-run supply of public knowledge? Evidence from human genetics. Academy of Management Journal, 52(6), 1193–1221.

    Article  Google Scholar 

  • Japan Finance Corporation. (2010). Entrepreneurship survey. Tokyo: Japan Finance Corporation.

    Google Scholar 

  • Jovanovic, B. (1982). Selection and the evolution of industry. Econometrica, 50(3), 649–670.

    Article  Google Scholar 

  • Lach, S., & Schankerman, M. (2008). Incentives and invention in universities. RAND Journal of Economics, 39(2), 403–433.

    Article  Google Scholar 

  • Lazear, E. (2005). Entrepreneurship. Journal of Labor Economics, 23(4), 649–680.

    Article  Google Scholar 

  • Leibenstein, H. (1968). Entrepreneurship and development. American Economic Review, 58(2), 72–83.

    Google Scholar 

  • Lewin, K. (1947). Frontiers in group dynamics: II. Channels of group life; social planning and action research. Human Relations; Studies Towards the Integration of the Social Sciences, 1, 143–153.

    Google Scholar 

  • Malerba, F. (2002). Sectoral systems of innovation and production. Research Policy, 31(2), 247–264.

  • Markman, G., Phan, P., Balkin, D., & Gianiodis, P. (2005). Entrepreneurship and university-based technology transfer. Journal of Business Venturing, 20(2), 241–263.

    Article  Google Scholar 

  • Martin, R., & Moodysson, J. (2011). Comparing knowledge bases: On the geography and organization of knowledge sourcing in the regional innovation system of Scania. Sweden European Urban and Regional Studies, 20(2), 170–187.

    Article  Google Scholar 

  • Mas-Verdú, F., Ribeiro-Soriano, D., & Roig-Tierno, N. (2015). Firm survival: The role of incubators and business characteristics. Journal of Business Research, 68, 793–796.

    Article  Google Scholar 

  • Molina-Morales, F., & Martinez-Fernandez, M. (2010). Social networks: Effects of social capital on firm innovation. Journal of Small Business Management, 48(2), 258–279.

    Article  Google Scholar 

  • Nelson, R., & Winter, S. (1982). An evolutionary theory of economic change. Cambridge: Belknap Press of Harvard University Press.

    Google Scholar 

  • Shane, S., & Cable, D. (2002). Network ties, reputation, and the financing of new ventures. Management Science, 48(3), 364–381.

    Article  Google Scholar 

  • Siegel, D., Wright, M., Chapple, W., & Lockett, A. (2008). Assessing the relative performance of university technology transfer in the US and UK: A stochastic distance function approach. Economics of Innovation and New Technology, 17(7–8), 717–729.

    Article  Google Scholar 

  • Somsuk, N., & Laosirihongthong, T. (2014). A fuzzy AHP to prioritize enabling factors for strategic management of university business incubators: Resource-based view. Technological Forecasting and Social Change, 85, 198–210.

    Article  Google Scholar 

  • Stankiewicz, R. (1995). The role of the science and technology infrastructure in the development and diffusion of industrial automation in Sweden. In B. Carlsson (Ed.), Technological systems and economic performance: The case of factory automation (pp. 165–210). Dordrecht: Kluwer.

    Chapter  Google Scholar 

  • Stinchcombe, A. (1965). Social structure and organizations. In J. March (Ed.), Handbook of organizations (pp. 142–193). Chicago: Rand McNally & Company.

    Google Scholar 

  • Tushman, M., & Scanlan, J. (1981). Boundary spanning individuals: Their role in information transfer and their antecedents. Academy of Management Journal, 24(2), 289–305.

    Google Scholar 

  • Vanderstraeten, J., Matthyssens, P., & van Witteloostuijn, A. (2012) Measuring the performance of business incubators, research paper 2012–012, University of Antwerp, Faculty of Applied Economics. entrepreneurial mentoring.

  • Xiao, L., & North, D. (2016) The graduation performance of technology business incubators in China’s three tier cities: The role of incubator funding, technical support, and entrepreneurial mentoring. Journal of Technology Transfer :1–20.

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Acknowledgments

This research was funded by the Japan Society for the Promotion of Science [15K03411], the Murata Science Foundation, and the Nomura Foundation.

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Correspondence to Nobuya Fukugawa.

Appendix

Appendix

Table 3 Factor analysis based on polychoric correlation matrix
Table 4 Rotated factor loadings
Table 5 Descriptive statistics

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Fukugawa, N. Is the impact of incubator’s ability on incubation performance contingent on technologies and life cycle stages of startups?: evidence from Japan. Int Entrep Manag J 14, 457–478 (2018). https://doi.org/10.1007/s11365-017-0468-1

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