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CEO Overconfidence and Innovation
Open accessAbstract
Are the attitudes and beliefs of chief executive officers (CEOs) linked to their firms' innovative performance? This paper uses a measure of overconfidence, based on CEO stock-option exercise, to study the relationship between a CEO's “revealed beliefs” about future performance and standard measures of corporate innovation. We begin by developing a career concern model where CEOs innovate to provide evidence of their ability. The model predicts that overconfident CEOs, who underestimate the probability of failure, are more likely to pursue innovation, and that this effect is larger in more competitive industries. We test these predictions on a panel of large publicly traded firms for the years from 1980 to 1994. We find a robust positive association between overconfidence and citation-weighted patent counts in both cross-sectional and fixed-effect models. This effect is larger in more competitive industries. Our results suggest that overconfident CEOs are more likely to take their firms in a new technological direction. This paper was accepted by Kamalini Ramdas, entrepreneurship and innovation.
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Cites
Managerial Incentive Problems: A Dynamic Perspective
Holmstrom, B. (1999) · Review of Economic Studies · doi:10.1111/1467-937x.00083 · Cited by 3,172
Cited by
Forming beliefs: Why valence matters
Sharot, T., & Garrett, N. (2016) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2015.11.002 · Cited by 345
Norouzinik, Y., Rahimnia, F., Maharati, Y., & Eslami, G. (2022) · Innovation · doi:10.1080/14479338.2021.1897467 · Cited by 48
CUMBERLAND, D. M., MEEK, W. R., & GERMAIN, R. (2015) · Journal of Developmental Entrepreneurship · doi:10.1142/s1084946715500041 · Cited by 42
Metadata
- Authors
- Galasso, A., & Simcoe, T. S.
- Venue
- Management Science
- Published
- 2011-08
- Volume
- 57
- Issue
- 8
- Pages
- 1469-1484
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2138389645
- Cited by
- 867
- References
- 1
- FWCI
- 61.78
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
