Generalized expected utility, heteroscedastic error, and path dependence in risky choice

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Mixture models of choice under risk (2011, background): “Some of the empirical literature adopted the strategy of trying to find the best preference functional individual by individual; see, for example, Hey and Orme (1994) and Gonzales and Wu (1999).”
Stochastic models for binary discrete choice under risk: a critical primer and econometric comparison (2008, background): “Buschena and Zilberman (2000) and Loomes et al.”
Models of Stochastic Choice and Decision Theories: Why Both are Important for Analyzing Decisions (2010, unknown): “Hey (1995) and Buschena and Zilberman (2000) extend a Fechner model of random errors by assuming that the error term is heteroscedastic; i.e., the standard deviation of errors is higher in Copyright 2009 John Wiley & Sons, Ltd. J. Appl.”
Stochastically more risk averse: A contextual theory of stochastic discrete choice under risk (2011, background): “Buschena and Zilberman (2000) and Loomes, Moffatt and Sugden (2002) point out that the best-fitting stochastic model may depend on the structure estimated and offer empirical illustrations of this sensible econometric point.”
Stochastic Utility Theorem (2008, background): “For example, Camerer (1989) reports that 31.6% of subjects reversed their choices when presented with the same binary choice problem for the second time. Starmer and Sugden (1989) find that 26.5% of all choices are reversed on the second repetition of a decision problem. Hey and Orme (1994) report a”