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Feeling Right: Regulatory Fit Theory and Early-Stage Entrepreneurial Investment Decisions

Author

Listed:
  • Shiyao Jiang

    (Lanzhou University)

  • Guiquan Li

    (Peking University [Beijing])

  • Haixin Liu

    (Department of Information Management - Peking University [Beijing])

  • Jie Xiong

    (ESSCA - ESSCA – École supérieure des sciences commerciales d'Angers = ESSCA Business School)

  • Shubho Chakraborty

    (ESC [Rennes] - ESC Rennes School of Business)

Abstract

Recent advances in entrepreneurial investment decisions research implied that early-stage investment decisions, given their extreme uncertainty and unpredictability, were results of investors' intuition processes. In other words, investors manage the high risks of early-stage investment decisions by finding justifications of future value against risk in the invested entrepreneurial projects. Although some studies have discussed the decision-making process of mid- and late-stage venture capital, there is still a lack of discussion on the early-stage investment decision-making mechanism. In this paper, we draw on regulatory fit theory to theorize how the fit of regulatory focus between investor and entrepreneur could lead to the investor's early-stage investment decisions in terms of investment amount and speed. Across three experimental studies, we found empirical support for our proposed model. Specifically, investors who have similar regulatory focus with the entrepreneurs are more likely to invest a larger amount of funds at a faster speed. We further found that investor's sense of rightness mediates the relationship between regulatory fit and investment decision, and investor's previous investment experience plays a moderating role.

Suggested Citation

  • Shiyao Jiang & Guiquan Li & Haixin Liu & Jie Xiong & Shubho Chakraborty, 2024. "Feeling Right: Regulatory Fit Theory and Early-Stage Entrepreneurial Investment Decisions," Post-Print hal-04817960, HAL.
  • Handle: RePEc:hal:journl:hal-04817960
    DOI: 10.1515/erj-2020-0408
    as

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