Everything in Moderation: Foundations and Applications of the Satiation Model

Manel Baucells and Lin Zhao ()
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Lin Zhao: Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

Management Science, 2020, vol. 66, issue 12, 5701-5719

Abstract: 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.

Date: 2020
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