Abstract
Existing dynamic pricing models which take consumers’ learning behavior into account generally assume that consumers learn on the basis of reinforcement learning and belief-based learning. Nevertheless, abundant empirical evidence of behavior game indicates that consumers’ learning is normally described as a process of mixed learning. Particularly, for experience goods, a consumer’s purchase decision is not only based on his previous purchase behavior (adaptive learning), but also affected by that of other consumers (sophisticated learning). With the assumption that consumers are both adaptive and sophisticated learners, we study a dynamic pricing model dealing with repeated decision problems in a duopoly market. Specifically, we build a dynamic game model based on sophisticated experience-weighted attraction learning model (SEWA) and analyze the existence of the equilibrium. Finally, we show the characteristics and differences of the steady-state solutions between models considering adaptive consumers and models considering sophistical consumers by numerical results.
Highlights
For experience goods, consumers are only able to learn about their own preferences for a certain product after experiencing it
Compared with the steady states of dynamic pricing model which only considers adaptive consumers in the last section, the relative market share of two firms is less in the steady states obtained from this section
This paper considers the dynamic pricing problems of experience goods in a duopoly market
Summary
Consumers are only able to learn about their own preferences for a certain product after experiencing it. Hopkins [17] compares and analyzes the steady state of reinforcement learning model and brief learning model in dynamic pricing All these literatures assume that consumers’ purchase behavior is a process of adaptive learning, but Camerer et al [2] suggest sophisticated learning of consumers are more realistic in real world. Because of the particularity of experience goods, consumers cannot perceive the utility of products before purchasing; there definitely exist limitations when describing the learning process of adaptive and sophisticated consumers with EWA model and SEWA model, respectively To address these problems, we simplify the EWA model and SEWA model on the basis of belief learning proposed by Sarin and Vahid [8] and enforcement learning proposed by Borgers and Sarin [9].
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