The DOI matches its Crossref record; 132 of the 132 references it cites were found in a registry or an index.
Managing the Unknowable: The Effectiveness of Early-stage Investor Gut Feel in Entrepreneurial Investment Decisions
Abstract
Using an inductive theory-development study, a field experiment, and a longitudinal field test, we examine early-stage entrepreneurial investment decision making under conditions of extreme uncertainty. Building on existing literature on decision making and risk in organizations, intuition, and theories of entrepreneurial financing, we test the effectiveness of angel investors’ criteria for making investment decisions. We found that angel investors’ decisions have several characteristics that have not been adequately captured in existing theory: angel investors have clear objectives—risking small stakes to find extraordinarily profitable investments, fully expecting to lose their entire investment in most cases—and they rely on a combination of expertise-based intuition and formal analysis in which intuition trumps analysis, contrary to reports in other investment contexts. We also found that their reported emphasis on assessments of the entrepreneur accurately predicts extraordinarily profitable venture success four years later. We develop this theory by examining situations in which uncertainty is so extreme that it qualifies as unknowable, using the term “gut feel” to describe their dynamic emotion-cognitions in which they blend analysis and intuition in ways that do not impair intuitive processes and that effectively predict extraordinarily profitable investments.
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Qualitative Data Analysis: An Expanded Sourcebook
(1994) · Journal of Environmental Psychology · doi:10.1016/s0272-4944(05)80231-2 · Cited by 48,420
The Discovery of Grounded Theory: Strategies for Qualitative Research.
Wagner, H. R., Glaser, B. G., & Strauss, A. L. (1968) · Social Forces · doi:10.2307/2575405 · Cited by 46,361
(1998) · Sage eBooks · Cited by 38,631
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241
(1993) · Journal of the American Dietetic Association · doi:10.1016/0002-8223(93)91697-o · Cited by 18,154
A Theory of Cognitive Dissonance
(2017) · Macat Library eBooks · doi:10.4324/9781912282432 · Cited by 18,122
Armstrong, J. S., & Georgoff, D. M. (1988) · International Journal of Forecasting · doi:10.1016/0169-2070(88)90019-2 · Cited by 17,894
(2011) · Cited by 14,317
The Handbook of Social Psychology
Gravatt, A. E., Lindzey, G., & Aronson, F. (1969) · The Family Coordinator · doi:10.2307/582242 · Cited by 12,517
Basics of Qualitative Research (3rd ed.): Techniques and Procedures for Developing Grounded Theory
Corbin, J., & Strauss, A. (2008) · SAGE · doi:10.4135/9781452230153 · Cited by 12,136
Cited by
Artificial intelligence and the changing sources of competitive advantage
Krakowski, S., Luger, J., & Raisch, S. (2023) · Strategic Management Journal · doi:10.1002/smj.3387 · Cited by 594
Huang, L., Joshi, P., Wakslak, C., & Wu, A. (2021) · Academy of Management Journal · doi:10.5465/amj.2018.1417 · Cited by 116
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Metadata
- Authors
- Huang, L., & Pearce, J. L.
- Venue
- Administrative Science Quarterly
- Publisher
- SAGE Publications
- Published
- 2015-07-16
- Volume
- 60
- Issue
- 4
- Pages
- 634-670
- ISSN
- 0001-8392 (ISSN-L)
- 1930-3815
- OpenAlex
- W1869260116
- Cited by
- 465
- References
- 132
- FWCI
- 97.26
- Type
- journal article
- Language
- en
- Open access
- closed
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