An Experience-Based Choice Model (EBCM): Formulation, identification, behavioural insights and well-being assessment

Abstract

The Experience-Based Choice Model (EBCM) accounts for the underlying learning process within choices, where the main learning unit is the instant utility: a representation of the hedonic momentary feelings. It merges Kahneman’s (Kahneman et al., 1997) notions of experienced utility with the Integrated Choice and Latent Variables (ICLV) framework, drawing on the current knowledge about the use of physiological signals to measure psychological states. EBCM allows us to model choices as a function of the learnt descriptive information of attributes and the hedonic experiences from past choices and to obtain a measure of the experience which can be used to analyse Subjective Well-Being (SWB). In this article, we first implement the model as a Markovian learning process in which the individual uses the remembered utility to update the decision utility at a certain learning rate while aggregating the instant utilities using an Instance-Based Learning (IBL) approach. We discuss specification and identification issues with Monte Carlo simulations . Besides, we use numerical experiments to show how this framework allows us to capture challenging behavioural phenomena such as the duality of habitual and goal-directed behaviour, the hot stove effect, the status quo bias, and the recency effect. Then, we discuss how this formulation contributes to the analysis of SWB. EBCM can help to assess SWB, particularly in situations where traditional assumptions of consumer rationality may not hold and when consumers are captive. Finally, new lines of research are discussed. • EBCM bridges the theories of Experienced Utility and Random Utility. • It models the impact of experience on future decisions. • Simultaneously, it models experience emotions using physiological data. • Behavioural insights are discussed in numerical experiments. • Potential applications for well-being analysis are discussed.