Nonlinear Utility Models Arising from Unmodelled Small World Intercorrelations

Nonlinear Utility Models Arising from Unmodelled Small World Intercorrelations

Savage's axioms show the rationality of maximizing expected utility when all uncertainties are explicitly modelled. But individuals actually make decisions in bounded contexts called small worlds. Savage's axioms do not imply the optimality of maximizing expected utility in small worlds un...

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Bibliographische Detailangaben
Veröffentlicht in:Management Science. - Institute for Operations Research and the Management Sciences, 1954. - 38(1992), 7, Seite 1010-1017
1. Verfasser: Bordley, Robert F. (VerfasserIn)
Weitere Verfasser: Hazen, Gordon
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1992
Zugriff auf das übergeordnete Werk:Management Science
Schlagworte:Decision Theory Small Worlds Probability/Utility Interactions Nonlinear Utility Theory Economics Law Philosophy Behavioral sciences Information science Mathematics
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520 |a Savage's axioms show the rationality of maximizing expected utility when all uncertainties are explicitly modelled. But individuals actually make decisions in bounded contexts called small worlds. Savage's axioms do not imply the optimality of maximizing expected utility in small worlds unless lotteries in different small worlds are probabilistically independent. Relaxing this independence assumption causes Savage's axioms to imply the optimality of maximizing a nonlinear utility model which includes, as special cases, the Chew weighted linear utility model, the Bell elation/disappointment model and the Allais mean/variance model in utility-independent small worlds. 
540 |a Copyright 1992 The Institute of Management Sciences 
650 4 |a Decision Theory 
650 4 |a Small Worlds 
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650 4 |a Nonlinear Utility Theory 
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650 4 |a Mathematics  |x Applied mathematics  |x Statistics  |x Applied statistics  |x Descriptive statistics  |x Statistical distributions  |x Normal distribution curve  |x Standard deviation 
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952 |d 38  |j 1992  |e 7  |h 1010-1017