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Patience Versus Decisiveness in Decision-Making

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Author Info
W. Bentley MacLeod (Columbia University)
Mark Pingle () (Department of Economics, University of Nevada, Reno)

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Abstract

When rationality is bounded, a variety of factors may influence how far a choice is from optimal. We examine the willingness to search among alternatives. We find fixed individual differences in this temperament measure. People may be usefully typed according to how they obtain improved choices. More patient subjects obtain improvement by effectively using decision resources, performing better when the decision is more complex. More decisive subjects obtain improvement by conserving valuable decision resources, performing better when the decision problem is simple. We find that a bonus incentive frame encourages patience, while a penalty frame encourages decisiveness. These results suggest an organization can enhance its performance by matching individual temperaments and incentive frames to decision tasks at hand.

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File URL: http://www.business.unr.edu/econ/wp/papers/UNRECONWP07004.pdf
File Format: application/pdf
File Function: First version, 2007
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Publisher Info
Paper provided by University of Nevada, Reno, Department of Economics & University of Nevada, Reno , Department of Resource Economics in its series Working Papers with number 07-004.

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Length: 25 pages
Date of creation: Aug 2007
Date of revision:
Handle: RePEc:unr:wpaper:07-004

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Related research
Keywords: framing; deliberation cost; bounded rationality; heuristics; incentives;

Find related papers by JEL classification:
D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information

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References listed on IDEAS
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  1. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December. [Downloadable!] (restricted)
  2. MacLeod, W. Bentley & Pingle, Mark, 2005. "Aspiration uncertainty: its impact on decision performance and process," Journal of Economic Behavior & Organization, Elsevier, vol. 56(4), pages 617-629, April. [Downloadable!] (restricted)
  3. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366 Elsevier. [Downloadable!] (restricted)
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  4. Conlisk, John, 1988. "Optimization cost," Journal of Economic Behavior & Organization, Elsevier, vol. 9(3), pages 213-228, April. [Downloadable!] (restricted)
  5. Falk, Armin & Fehr, Ernst, 2003. "Why labour market experiments?," Labour Economics, Elsevier, vol. 10(4), pages 399-406, August. [Downloadable!] (restricted)
  6. W. Bentley MacLeod, 2002. "Complexity, Bounded Rationality and Heuristic Search," The B.E. Journal of Economic Analysis & Policy, Berkeley Electronic Press, vol. 0(1). [Downloadable!]
  7. Harrison, Glenn W & Morgan, Peter, 1990. "Search Intensity in Experiments," Economic Journal, Royal Economic Society, vol. 100(401), pages 478-86, June. [Downloadable!] (restricted)
  8. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-91, March. [Downloadable!] (restricted)
  9. Tversky, Amos & Kahneman, Daniel, 1991. "Loss Aversion in Riskless Choice: A Reference-Dependent Model," The Quarterly Journal of Economics, MIT Press, vol. 106(4), pages 1039-61, November. [Downloadable!] (restricted)
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