We develop a continuum of stochastic dominance rules for expected utility maximizers. The new rules encompass the traditional integer-degree stochastic dominance; between adjacent integer degrees, they formulate the consensus of individuals whose absolute risk aversion at the corresponding integer degree has a negative lower bound. By extending the concept of “uniform risk aversion” previously proposed in the literature to high-order risk preferences, we interpret the fractionalized degree parameter as a benchmark individual relative to whom all considered individuals are uniformly no less risk averse in the lottery choices. The equivalent distribution conditions for the new rules are provided, and the fractional degree “increase in risk” is defined. We generalize the previously defined notion of “risk apportionment” and demonstrate its usefulness in characterizing comparative statics of risk changes in fractional degrees. This paper was accepted by David Simchi-Levi, decision analysis.

We introduce the fatigue disutility model. Set in continuous time, the model formalizes the notion that fatigue accumulates with effort, decays with rest, and produces an increase in marginal instant disutility. The model is meant to be prescriptive, although it rationalizes several anomalies observed in time preference. Under very general conditions, the most efficient temporal profile of effort exhibits a high-low-high pattern. We consider a variant whereby marginal productivity decreases with fatigue, and we examine the optimal management of fatigue and productivity under various scenarios. We also reexamine the beneficial role of breaks in reducing fatigue. We bring the model to the data and provide a calibration that favorably predicts the speed profiles observed in swimming competitions. Data are available at https://doi.org/10.1287/mnsc.2017.3018. This paper was accepted by Han Bleichrodt, decision analysis.

Models in which current utility depends solely on current consumption (a.k.a. time-separable preferences) are widely acknowledged to be unrealistic, especially when attempting to describe preferences over consumption rates. Alternatively, one may stipulate that instant utility also depends on a state, for example, some stock of past consumption. Escaping the gravitational pull of time separability, however, is difficult because (1) the behavioral axioms that characterize the state and the instant utility are not known, (2) how to elicit the preference parameters—most notably the initial level of the state and the decay rate—is not known, and (3) managerial applications where state-dependent preferences produce interesting insights and solutions are scarce. This paper makes advances on these three fronts by proposing a novel set of axioms that characterize the satiation model, a proof of concept on how to elicit all preference parameters using consumption rates, and a mixed-integer linear formulation to solve the optimal design of experiential services under satiation. Our preferences introduce a de-satiation motive, absent in separable preferences, and we explore how to optimally manage this motive. This paper was accepted by David Simchi-Levi, decision analysis.

Levy [Levy H (2016) Aging population, retirement, and risk taking. Management Sci. 62(5):1415–1430.] proposes asymptotic first-degree stochastic dominance (AFSD) as a distribution-ranking criterion for all nonsatiable decision makers with infinite investment horizons. By assuming that the terminal wealth follows a log-normal distribution and that the marginal utility is bounded, he offers the necessary and sufficient distributional condition for AFSD. Given Levy’s setting, we provide a counterexample to show that his condition is not necessary and offer the correct equivalent distributional condition for AFSD. This paper was accepted by Karl Diether, finance.