IDEAS home Printed from https://ideas.repec.org/a/sae/entthe/v46y2022i6p1500-1533.html
   My bibliography  Save this article

Entrepreneurial Disappointment: Let Down and Breaking Down, a Machine-Learning Study

Author

Listed:
  • Amanda Jasmine Williamson
  • Andreana Drencheva
  • Martina Battisti

Abstract

Despite its importance, our understanding of what entrepreneurial disappointment is, its attributions, and how it relates to depression is limited. Drawing on a corpus of 27,906 semi-anonymous online posts, we identified entrepreneurial disappointment, inductively uncovered its attributions and examined how depression differs between attributions. We found that posts with internal, stable, and global disappointment attributions (e.g., not fitting entrepreneurial norms) are, on average, higher in depression symptoms than posts with external, unstable, and specific disappointment attributions (e.g., firm performance). Our findings offer novel theoretical and methodological avenues for future research on entrepreneurs’ affective experiences and mental health.

Suggested Citation

  • Amanda Jasmine Williamson & Andreana Drencheva & Martina Battisti, 2022. "Entrepreneurial Disappointment: Let Down and Breaking Down, a Machine-Learning Study," Entrepreneurship Theory and Practice, , vol. 46(6), pages 1500-1533, November.
    • Handle: RePEc:sae:entthe:v:46:y:2022:i:6:p:1500-1533
    DOI: 10.1177/1042258720964447
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1042258720964447
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1042258720964447?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
    ---><---

    More about this item

    Keywords

    emotions; psychology; depression; machine learning; artificial intelligence; uncertainty; entrepreneur;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

    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:sae:entthe:v:46:y:2022:i:6:p:1500-1533. 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: SAGE Publications (email available below). General contact details of provider: .

    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.