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Choosing the devil you don’t know : evidence for limited sensitivity to sample-size based uncertainty when it offers an advantage
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Kutzner, F. L., Read, Daniel, Stewart, Neil and Brown, G. D. A. (2017) Choosing the devil you don’t know : evidence for limited sensitivity to sample-size based uncertainty when it offers an advantage. Management Science, 63 (5). pp. 1519-1528. doi:10.1287/mnsc.2015.2394 ISSN 0025-1909.
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Official URL: http://dx.doi.org/10.1287/mnsc.2015.2394
Abstract
Many decision makers seek to optimize choices between uncertain options such as strategies, employees, or products. When performance targets must be met, attending to observed past performance is not enough to optimize choices—option uncertainty must also be considered. For example, for stretch targets that exceed observed performance, more uncertain options are often better bets. A significant determinant of option uncertainty is sample size: for a given option, the smaller the sample of information we have about it, the greater the uncertainty. In two studies, choices were made between pairs of uncertain options with the goal of exceeding a specified performance target. Information about the options differed in the size of the sample drawn from them, sample size, and the observed performance of those samples, the proportion of successes or “hits” in the sample. We found people to be sensitive to sample size–based uncertainty only when differences in observed performance were negligible. We conclude that in the presence of performance targets, people largely fail to capitalize on the value advantages of small samples in the presence of stretch targets.
Item Type: | Journal Article | ||||||||||
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Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > QA Mathematics Q Science > QC Physics |
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Divisions: | Faculty of Social Sciences > Warwick Business School > Behavioural Science Faculty of Science, Engineering and Medicine > Science > Psychology Faculty of Social Sciences > Warwick Business School |
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Library of Congress Subject Headings (LCSH): | Rationalization (Psychology), Convex domains , Bayesian statistical decision theory | ||||||||||
Journal or Publication Title: | Management Science | ||||||||||
Publisher: | Institute for Operations Research and the Management Sciences (I N F O R M S) | ||||||||||
ISSN: | 0025-1909 | ||||||||||
Official Date: | May 2017 | ||||||||||
Dates: |
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Volume: | 63 | ||||||||||
Number: | 5 | ||||||||||
Page Range: | pp. 1519-1528 | ||||||||||
DOI: | 10.1287/mnsc.2015.2394 | ||||||||||
Status: | Peer Reviewed | ||||||||||
Publication Status: | Published | ||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||
Date of first compliant deposit: | 15 December 2015 | ||||||||||
Date of first compliant Open Access: | 4 May 2016 | ||||||||||
Funder: | Deutsche Forschungsgemeinschaft (DFG), Economic and Social Research Council (Great Britain) (ESRC), Leverhulme Trust (LT) | ||||||||||
Grant number: | KU3059/1 and 2 (DFG), ES/K002201/1 and ES/K004948/1] (ESRC), RP2012-V-022 (LT) | ||||||||||
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Is Part Of: | Economic and Social Research Council [Grants ES/K002201/1 and ES/K004948/1], and the Leverhulme Trust [Grant RP2012-V-022] |
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