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The rise and fall of startups: Creation and destruction of revenue and jobs by young companies

Author

Listed:
  • Antonio Davila

    (Department of Entrepreneurship and Accounting & Control, IESE Business School, University of Navara, Barcelona, Spain)

  • George Foster

    (Graduate School of Business, Stanford University, Stanford, CA, USA)

  • Xiaobin He

    (School of Management, Fudan University, Shanghai, China)

  • Carlos Shimizu

    (Graduate School of Business, Stanford University, Stanford, CA, USA)

Abstract

Using a large multi-country multi-industry sample of over 158,000 companies, the early-stage company sector is documented to have sizable destruction of revenues and jobs and as well as sizable gross creation of revenues and jobs. The creation aspect has captured the dominant attention of researchers, commentators, and policy makers. Destruction, despite its large magnitude, has long been a backwater of research and most commentary on this sector. Destruction is not simply non-growth but rather prior growth that is subsequently reversed. This paper analyzes creation and destruction evidence across 10 different countries and across eight different major industry groups. Yearly growth/decline rates using revenues and headcount for Years 2 to 5 are analyzed. In each of the three growth years examined there are large amounts of destruction as well as creation simultaneously occurring. For example, in Year 5 gross revenue destruction is 34% of gross revenue creation whilst gross job destruction is 65% of gross job creation. A small percentage of companies accounts for a large percentage of the total job and revenue destruction each year. This small percentage of large destroyers is especially interesting because they had to have had, by necessity, prior sizable creation. This rapid rise and subsequent rapid fall has been very much ignored in the research literature. Regression analysis highlights this aspect for the sample of destroyers. The diverse sources of revenue and job destruction are discussed and potential fruitful research directions highlighted.

Suggested Citation

  • Antonio Davila & George Foster & Xiaobin He & Carlos Shimizu, 2015. "The rise and fall of startups: Creation and destruction of revenue and jobs by young companies," Australian Journal of Management, Australian School of Business, vol. 40(1), pages 6-35, February.
  • Handle: RePEc:sae:ausman:v:40:y:2015:i:1:p:6-35
    DOI: 10.1177/0312896214525793
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    References listed on IDEAS

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    1. Alex Coad, 2009. "The Growth of Firms," Books, Edward Elgar Publishing, number 13424.
    2. Elizabeth Garnsey & Erik Stam & Paul Heffernan, 2006. "New Firm Growth: Exploring Processes and Paths," Industry and Innovation, Taylor & Francis Journals, vol. 13(1), pages 1-20.
    3. Ball, R & Foster, G, 1982. "Corporate Financial-Reporting - A Methodological Review Of Empirical-Research," Journal of Accounting Research, Wiley Blackwell, vol. 20, pages 161-234.
    4. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    5. Alexander McKelvie & Johan Wiklund, 2010. "Advancing Firm Growth Research: A Focus on Growth Mode Instead of Growth Rate," Entrepreneurship Theory and Practice, , vol. 34(2), pages 261-288, March.
    6. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    7. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    8. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 123-127.
    9. Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), 2013. "Handbook of Research Methods and Applications in Empirical Finance," Books, Edward Elgar Publishing, number 14545.
    10. Ball, R & Foster, G, 1982. "Corporate Financial-Reporting - A Methodological Review Of Empirical-Research - Reply," Journal of Accounting Research, Wiley Blackwell, vol. 20, pages 245-248.
    11. Simon Parker & David Storey & Arjen Witteloostuijn, 2010. "What happens to gazelles? The importance of dynamic management strategy," Small Business Economics, Springer, vol. 35(2), pages 203-226, September.
    12. Chandler, Gaylen N. & McKelvie, Alexander & Davidsson, Per, 2009. "Asset specificity and behavioral uncertainty as moderators of the sales growth -- Employment growth relationship in emerging ventures," Journal of Business Venturing, Elsevier, vol. 24(4), pages 373-387, July.
    13. Beaver, Wh, 1966. "Financial Ratios As Predictors Of Failure," Journal of Accounting Research, Wiley Blackwell, vol. 4, pages 71-111.
    14. Jonathan Levie & Benyamin B. Lichtenstein, 2010. "A Terminal Assessment of Stages Theory: Introducing a Dynamic States Approach to Entrepreneurship," Entrepreneurship Theory and Practice, , vol. 34(2), pages 317-350, March.
    15. Barringer, Bruce R. & Jones, Foard F. & Neubaum, Donald O., 2005. "A quantitative content analysis of the characteristics of rapid-growth firms and their founders," Journal of Business Venturing, Elsevier, vol. 20(5), pages 663-687, September.
    16. Dean Shepherd & Johan Wiklund, 2009. "Are we Comparing Apples with Apples or Apples with Oranges? Appropriateness of Knowledge Accumulation across Growth Studies," Entrepreneurship Theory and Practice, , vol. 33(1), pages 105-123, January.
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    Cited by:

    1. Benson, Karen & Faff, Robert & Smith, Tom, 2015. "Injecting liquidity into liquidity research," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 533-540.
    2. Alex Coad & Julian S. Frankish & Richard G. Roberts & David J. Storey, 2016. "Predicting new venture survival and growth: Does the fog lift?," Small Business Economics, Springer, vol. 47(1), pages 217-241, June.

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