IDEAS home Printed from https://ideas.repec.org/a/pep/journl/v13y2009i2p56-75.html
   My bibliography  Save this article

Decision Making in Entrepreneurial Finance: A Behavioral Perspective

Author

Listed:
  • Rassoul Yazdipour

    (California State University, Fresno)

Abstract

Central questions in entrepreneurship and entrepreneurial finance are briefly discussed and case is made for the need for applying the behavioral finance theories and models to better understand the decision making dynamics that is involved at each stage of the entrepreneurial process. By dissecting a venture's total risk into a "Resident Risk" component and a "Behavioral Risk" component, attempt is made in this writing to introduce a preliminary risk model for evaluating key retrepreneurial decisions like the decision to launch and fund a new venture. Although the focus here is on individual decision making under highly uncertain entrepreneurial environments, but the suggested risk framework and the related discussions can be extended to decision making processes in all other uncertain environment.

Suggested Citation

  • Rassoul Yazdipour, 2009. "Decision Making in Entrepreneurial Finance: A Behavioral Perspective," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 13(2), pages 56-75, Fall.
  • Handle: RePEc:pep:journl:v:13:y:2009:i:2:p:56-75
    as

    Download full text from publisher

    File URL: http://jefsite.org/RePEc/pep/journl/jef-2009-13-2-c-yazdipour.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Slovic, Paul, 1972. "Psychological Study of Human Judgment: Implications for Investment Decision-Making," Journal of Finance, American Finance Association, vol. 27(4), pages 779-799, September.
    2. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    3. Slovic, Paul & Finucane, Melissa L. & Peters, Ellen & MacGregor, Donald G., 2007. "The affect heuristic," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1333-1352, March.
    4. Dan Lovallo & Colin Camerer, 1999. "Overconfidence and Excess Entry: An Experimental Approach," American Economic Review, American Economic Association, vol. 89(1), pages 306-318, March.
    5. Michael Spence, 1973. "Job Market Signaling," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(3), pages 355-374.
    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. Linda Bergset, 2015. "The Rationality and Irrationality of Financing Green Start-Ups," Administrative Sciences, MDPI, vol. 5(4), pages 1-26, November.

    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. Elke Lüdemann, 2011. "Schooling and the Formation of Cognitive and Non-cognitive Outcomes," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 39.
    2. Hönl, Andreas & Meissner, Philip & Wulf, Torsten, 2017. "Risk attribution theory: An exploratory conceptualization of individual choice under uncertainty," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 67(C), pages 20-27.
    3. Dunne, Timothy C. & Clark, Brent B. & Berns, John P. & McDowell, William C., 2019. "The technology bias in entrepreneur-investor negotiations," Journal of Business Research, Elsevier, vol. 105(C), pages 258-269.
    4. Sandroni, Alvaro & Squintani, Francesco, 2013. "Overconfidence and asymmetric information: The case of insurance," Journal of Economic Behavior & Organization, Elsevier, vol. 93(C), pages 149-165.
    5. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    6. Lovric, M. & Kaymak, U. & Spronk, J., 2008. "A Conceptual Model of Investor Behavior," ERIM Report Series Research in Management ERS-2008-030-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    7. Tomas Bonavia & Josué Brox-Ponce, 2018. "Shame in decision making under risk conditions: Understanding the effect of transparency," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-16, February.
    8. Stefano DellaVigna, 2009. "Psychology and Economics: Evidence from the Field," Journal of Economic Literature, American Economic Association, vol. 47(2), pages 315-372, June.
    9. Benito Umana Hermosilla & Juan Cabas Monje & Juan Rodríguez Navarrete & Miguel Villablanca Fuentes, 2015. "Variables explicativas del comportamiento del inversor de multifondos. Un análisis desde la perspectiva de los inversores en el sistema de pensiones chileno," Estudios Gerenciales, Universidad Icesi, April.
    10. Zeckhauser, Richard, 2021. "Strategic sorting: the role of ordeals in health care," Economics and Philosophy, Cambridge University Press, vol. 37(1), pages 64-81, March.
    11. Leković Milјan, 2020. "Cognitive Biases as an Integral Part of Behavioral Finance," Economic Themes, Sciendo, vol. 58(1), pages 75-96, March.
    12. Jacquemet, Nicolas & Rullière, Jean-Louis & Vialle, Isabelle, 2008. "Monitoring optimistic agents," Journal of Economic Psychology, Elsevier, vol. 29(5), pages 698-714, November.
    13. Damon Clark & David Gill & Victoria Prowse & Mark Rush, 2020. "Using Goals to Motivate College Students: Theory and Evidence From Field Experiments," The Review of Economics and Statistics, MIT Press, vol. 102(4), pages 648-663, October.
    14. Christopher Dawson & David de Meza & Andrew Henley & G. Reza Arabsheibani, 2014. "Entrepreneurship: Cause and Consequence of Financial Optimism," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 23(4), pages 717-742, December.
    15. Ray Saadaoui Mallek & Mohamed Albaity, 2019. "Individual differences and cognitive reflection across gender and nationality the case of the United Arab Emirates," Cogent Economics & Finance, Taylor & Francis Journals, vol. 7(1), pages 1567965-156, January.
    16. Piotr Bialowolski & Dorota Weziak‐Bialowolska, 2021. "Good credit, bad credit: The differential role of the sources of debt in life satisfaction," Journal of Consumer Affairs, Wiley Blackwell, vol. 55(3), pages 967-994, September.
    17. A. Peter McGraw & Eldar Shafir & Alexander Todorov, 2010. "Valuing Money and Things: Why a $20 Item Can Be Worth More and Less Than $20," Management Science, INFORMS, vol. 56(5), pages 816-830, May.
    18. Magdalena Mikolajek-Gocejna, 2017. "From Homo Oeconomicus To Homo Altiore (Holistic). In The Search Of A New Paradigm," Eurasian Journal of Social Sciences, Eurasian Publications, vol. 5(3), pages 24-37.
    19. Argentiero, Amedeo & Bovi, Maurizio & Cerqueti, Roy, 2016. "Bayesian estimation and entropy for economic dynamic stochastic models: An exploration of overconsumption," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 143-157.
    20. Joseph E. Stiglitz, 2017. "The Revolution of Information Economics: The Past and the Future," NBER Working Papers 23780, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    Decision-making; entrepreneurship; entrepreneurial finance; behavioral finance; resident risk; behavioral risk;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D92 - Microeconomics - - Micro-Based Behavioral Economics - - - Intertemporal Firm Choice, Investment, Capacity, and Financing
    • M13 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - New Firms; Startups
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

    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:pep:journl:v:13:y:2009:i:2:p:56-75. 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: Craig Everett (email available below). General contact details of provider: https://edirc.repec.org/data/bapepus.html .

    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.