IDEAS home Printed from https://ideas.repec.org/a/taf/ujbmxx/v57y2019i2p640-657.html
   My bibliography  Save this article

Survival and Growth Patterns among New Technology‐Based Firms: Empirical Study of Cohort 2006 in Sweden

Author

Listed:
  • Heikki Rannikko
  • Erno T. Tornikoski
  • Anders Isaksson
  • Hans Löfsten

Abstract

This study investigates the survival and growth trends in a cohort of new technology‐based firms (NTBFs) established in Sweden in 2006. This cohort has faced both an economic upswing and a severe downturn, which started in 2008, and by 2014 provides 8 years of historical records. Our study makes several contributions to the current understanding of NTBF survival and growth. First, our empirical observations show that many NTBFs (72 percent) from the 2006 cohort were still operating at the end of 2014, indicating a much higher survival rate than those found in previous studies. Second, surviving firms from the 2006 cohort positively affected employment, as their annual job creation was higher than the reduction in employment caused by exiting firms. Third, very few companies experienced high‐growth during their first 7 years, and employment growth and sales growth were highly correlated among high‐growth firms.

Suggested Citation

  • Heikki Rannikko & Erno T. Tornikoski & Anders Isaksson & Hans Löfsten, 2019. "Survival and Growth Patterns among New Technology‐Based Firms: Empirical Study of Cohort 2006 in Sweden," Journal of Small Business Management, Taylor & Francis Journals, vol. 57(2), pages 640-657, April.
    • Handle: RePEc:taf:ujbmxx:v:57:y:2019:i:2:p:640-657
    DOI: 10.1111/jsbm.12428
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/jsbm.12428
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1111/jsbm.12428?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Ariel Alexi & Teddy Lazebnik & Labib Shami, 2024. "Microfounded Tax Revenue Forecast Model with Heterogeneous Population and Genetic Algorithm Approach," Computational Economics, Springer;Society for Computational Economics, vol. 63(5), pages 1705-1734, May.

    More about this item

    Statistics

    Access and download statistics

    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:taf:ujbmxx:v:57:y:2019:i:2:p:640-657. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/ujbm .

    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.