IDEAS home Printed from https://ideas.repec.org/a/sae/ausman/v40y2015i1p6-35.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0312896214525793
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0312896214525793?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Benson, Karen & Faff, Robert & Smith, Tom, 2015. "Injecting liquidity into liquidity research," Pacific-Basin Finance Journal, Elsevier, vol. 35(PB), pages 533-540.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," JRFM, MDPI, vol. 13(10), pages 1-14, September.
    2. Marta Gancarczyk, 2015. "Proces wzrostu przedsiębiorstwa w świetle podejścia zasobowego i teorii kosztów transakcyjnych," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 5, pages 5-31.
    3. Erik Stam, 2010. "Growth beyond Gibrat: firm growth processes and strategies," Small Business Economics, Springer, vol. 35(2), pages 129-135, September.
    4. Geng, Ruibin & Bose, Indranil & Chen, Xi, 2015. "Prediction of financial distress: An empirical study of listed Chinese companies using data mining," European Journal of Operational Research, Elsevier, vol. 241(1), pages 236-247.
    5. Marta Gancarczyk & Jon Mikel Zabala Iturriagagoitia, 2015. "The Process of the Growth of Small and Medium-Sized Enterprises (SMEs)," Journal of Entrepreneurship, Management and Innovation, Fundacja Upowszechniająca Wiedzę i Naukę "Cognitione", vol. 11(4), pages 3-24.
    6. Kim, Soo Y. & Upneja, Arun, 2014. "Predicting restaurant financial distress using decision tree and AdaBoosted decision tree models," Economic Modelling, Elsevier, vol. 36(C), pages 354-362.
    7. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
    8. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
    9. Guido Max Mantovani & Gregory Gadzinski, 2022. "How to Rate the Financial Performance of Private Companies? A Tailored Integrated Rating Methodology Applied to North-Eastern Italian Districts," JRFM, MDPI, vol. 15(11), pages 1-18, October.
    10. Enrico Supino & Nicola Piras, 2022. "Le performance dei modelli di credit scoring in contesti di forte instabilit? macroeconomica: il ruolo delle Reti Neurali Artificiali," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2), pages 41-61.
    11. Haoming Wang & Xiangdong Liu, 2021. "Undersampling bankruptcy prediction: Taiwan bankruptcy data," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-17, July.
    12. Trueck, Stefan & Rachev, Svetlozar T., 2008. "Rating Based Modeling of Credit Risk," Elsevier Monographs, Elsevier, edition 1, number 9780123736833.
    13. Le, Hong Hanh & Viviani, Jean-Laurent, 2018. "Predicting bank failure: An improvement by implementing a machine-learning approach to classical financial ratios," Research in International Business and Finance, Elsevier, vol. 44(C), pages 16-25.
    14. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    15. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
    16. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    17. Shoukat Ali & Ramiz ur Rehman & Wang Yuan & Muhammad Ishfaq Ahmad & Rizwan Ali, 2022. "Does foreign institutional ownership mediate the nexus between board diversity and the risk of financial distress? A case of an emerging economy of China," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 12(3), pages 553-581, September.
    18. Juraini Zainol Abidin & Nur Adiana Hiau Abdullah & Karren Lee-Hwei Khaw, 2020. "Predicting SMEs Failure: Logistic Regression vs Artificial Neural Network Models," Capital Markets Review, Malaysian Finance Association, vol. 28(2), pages 29-41.
    19. Hamid Waqas & Rohani Md-Rus, 2018. "Predicting financial distress: Applicability of O-score model for Pakistani firms," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(2), pages 389-401, April.
    20. David Veganzones, 2022. "Corporate failure prediction using threshold‐based models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 956-979, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:ausman:v:40:y:2015:i:1:p:6-35. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: http://www.agsm.edu.au .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.