by : Ed Hopkins - 2006
Published : Journal of Economic Literature classification numbers: C73, D11, D83, L13, M31.
Abstract
In a model of dynamic duopoly, optimal price policies are characterized assuming consumers learn adaptively about the relative quality of the two products. A contrast is made between belief-based and reinforcement learning. Under reinforcement learning, consumers can become locked into the habit of purchasing inferior goods. Such lock-in permits the existence of multiple history-dependent asymmetric steady states in which one firm dominates. In contrast, belief-based learning rules must lead asymptotically to correct beliefs about the relative quality of the two brands and so in this case there is a unique steady state.
Keywords: learning, consumer behavior, dynamic pricing, behavioral economics, reinforcement learning, market structure.
Introduction
Keywords: learning, consumer behavior, dynamic pricing, behavioral economics, reinforcement learning, market structure.
Introduction
Adaptive learning models attempt to describe the behavior of agents faced with repeated decision problems by assuming they use simple learning rules. These models are used in a number of apparently disparate environments. Economic theorists have analyzed them in abstract settings.1 They have been fitted to actual choice data both in economic experiments and the quite different context of the empirical analysis of consumer behavior.2 Despite differences in aims and terminology, some models of dynamic choice found in empirical marketing analysis are essentially the same as those used in economic theory. This research in marketing supports the experimental evidence that even simple adaptive learning models can help to explain human behavior. In the context of econometric work on experimental data, there has been an . . . . . (Read more)
Artikel lengkap dikompilasi oleh/hubungi :
Kanaidi, SE., M.Si (Penulis, Peneliti, PeBisnis, Trainer dan Dosen Marketing Management). e-mail ke : kana_ati@yahoo.com atau kanaidi@poltekpos.ac.id
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