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Buyers' Pricing Behavior for Risky Alternatives: Encoding Processes and Preference Reversals

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  • Jeff T. Casey

    (W. Averell Harriman School for Management and Policy, State University of New York at Stony Brook, Stony Brook, New York 11794-3775)

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    Abstract

    Numerous studies have examined individuals' minimum selling prices or certainty equivalents for lotteries as measures of preference, but few have examined maximum buying prices. Because every transaction involves a buyer as well as a seller, buyers' pricing behavior is of interest in its own right. Two prospect theory based descriptive models of maximum buying prices---the integration and segregation models---are developed from different assumptions about cognitive encoding processes. The models were tested experimentally using an incentive-compatible cash payoff scheme in which maximum buying prices for bets and choices between bets were elicited from subjects. Surprisingly, observed maximum buying prices were far below expected values even for bets with probabilities of winning near 1.0. This suggests buyers are strongly influenced by loss aversion and that the conventional assumption that the buying price for a risky alternative is a reduction in the alternative's payoffs fails to describe behavior. Instead, it appears subjects predominately employed a segregation encoding process in which the buying price was encoded separately from the bet's payoffs and treated as a sure loss. However, an additional result was not explained adequately by either encoding model: Buying prices were less risk averse than choices for $3 expected value bets---creating preference reversals of the standard kind (Lichtenstein and Slovic 1971)---but more risk averse for $100 expected value bets---creating reverse preference reversals (Casey 1991). Implications for the scale compatibility principle (Tversky et al. 1988) are discussed. Two theoretical approaches are outlined which offer promise in the development of a unified model of price judgments and choice preferences under risk.

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    File URL: http://dx.doi.org/10.1287/mnsc.40.6.730
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 40 (1994)
    Issue (Month): 6 (June)
    Pages: 730-749

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    Handle: RePEc:inm:ormnsc:v:40:y:1994:i:6:p:730-749

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    Related research

    Keywords: judgment; decision making; risk; preference reversal;

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    Cited by:
    1. Levy, Haim & Levy, Moshe, 2002. "Experimental test of the prospect theory value function: A stochastic dominance approach," Organizational Behavior and Human Decision Processes, Elsevier, vol. 89(2), pages 1058-1081, November.
    2. Haim Levy, 2004. "Prospect Theory and Mean-Variance Analysis," Review of Financial Studies, Society for Financial Studies, vol. 17(4), pages 1015-1041.
    3. Malul, Miki & Rosenboim, Mosi & Shavit, Tal, 2013. "So when are you loss averse? Testing the S-shaped function in pricing and allocation tasks," Journal of Economic Psychology, Elsevier, vol. 39(C), pages 101-112.
    4. Berg, Joyce E. & Dickhaut, John W. & Rietz, Thomas A., 2010. "Preference reversals: The impact of truth-revealing monetary incentives," Games and Economic Behavior, Elsevier, vol. 68(2), pages 443-468, March.
    5. Edwards, Kimberley D., 1996. "Prospect theory: A literature review," International Review of Financial Analysis, Elsevier, vol. 5(1), pages 19-38.
    6. Weber, Bethany J. & Chapman, Gretchen B., 2005. "Playing for peanuts: Why is risk seeking more common for low-stakes gambles?," Organizational Behavior and Human Decision Processes, Elsevier, vol. 97(1), pages 31-46, May.

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