The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Do Innovations Really Pay Off? Total Stock Market Returns to Innovation
Open accessAbstract
Critics often decry an earnings-focused short-term orientation of management that eschews spending on risky, long-term projects such as innovation to boost a firm's stock price. Such critics assume that stock markets react positively to announcements of immediate earnings but negatively to announcements of investments in innovation that have an uncertain long-term pay off. Contrary to this position, we argue that the market's true appreciation of innovation can be estimated by assessing the total market returns to the entire innovation project. We demonstrate this approach via the Fama-French 3-factor model (including Carhart's momentum factor) on 5,481 announcements from 69 firms in five markets and 19 technologies between 1977 and 2006. The total market returns to an innovation project are $643 million, more than 13 times the $49 million from an average innovation event. Returns to negative events are higher in absolute value than those to positive events. Returns to initiation occur 4.7 years ahead of launch. Returns to development activities are the highest and those to commercialization the lowest of all activities. Returns to new product launch are the lowest among all eight events tracked. Returns are higher for smaller firms than larger firms. Returns to the announcing firm are substantially greater than those to competitors across all stages. We discuss the implications of these results.
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Cites
Prospect Theory: An Analysis of Decision under Risk
Kahneman, D., & Tversky, A. (1979) · Econometrica · doi:10.2307/1914185 · Cited by 48,524
Prospect theory: An analysis of decision under risk
Kahneman, D., & Tversky, A. (1988) · Decision, Probability and Utility · doi:10.1017/cbo9780511609220.014 · Cited by 32,474
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
CAPITAL ASSET PRICES: A THEORY OF MARKET EQUILIBRIUM UNDER CONDITIONS OF RISK*
Sharpe, W. F. (1964) · The Journal of Finance · doi:10.1111/j.1540-6261.1964.tb02865.x · Cited by 19,441
On Persistence in Mutual Fund Performance
Carhart, M. M. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03808.x · Cited by 17,283
Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency
JEGADEESH, N., & TITMAN, S. (1993) · The Journal of Finance · doi:10.1111/j.1540-6261.1993.tb04702.x · Cited by 11,584
Brown, S. J., & Warner, J. B. (1985) · Journal of Financial Economics · doi:10.1016/0304-405x(85)90042-x · Cited by 6,488
Strategic Factor Markets: Expectations, Luck, and Business Strategy
Barney, J. B. (1986) · Management Science · doi:10.1287/mnsc.32.10.1231 · Cited by 5,548
(1997) · RePEc: Research Papers in Economics · Cited by 4,621
The Role of Market Forces in Assuring Contractual Performance
Klein, B., & Leffler, K. B. (1981) · Journal of Political Economy · doi:10.1086/260996 · Cited by 3,653
Cited by
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Rubera, G., & Kirca, A. H. (2012) · Journal of Marketing · doi:10.1509/jm.10.0494 · Cited by 835
Does Chatter Really Matter? Dynamics of User-Generated Content and Stock Performance
Tirunillai, S., & Tellis, G. J. (2012) · Marketing Science · doi:10.1287/mksc.1110.0682 · Cited by 623
Self-citationAlliance Portfolio Resource Diversity and Firm Innovation
Cui, A. S., & O'Connor, G. (2012) · Journal of Marketing · doi:10.1509/jm.11.0130 · Cited by 262
Metadata
- Authors
- Sood, A., & Tellis, G. J.
- Venue
- Marketing Science
- Published
- 2009-05
- Volume
- 28
- Issue
- 3
- Pages
- 442-456
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W2136044665
- Cited by
- 294
- References
- 60
- FWCI
- 17.37
- 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).
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