奖励计划动态模型的识别

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2018-07-08 DOI:10.1111/jere.12188

Andrew T. Ching, Masakazu Ishihara

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引用次数: 7

摘要

“常客”奖励计划通常被公司用作争夺市场份额的营销工具。它们为研究消费者的前瞻性行为提供了一个独特的环境。消费者的奖励积分积累问题可以表述为一个平稳无限视界离散选择动态规划模型。我们表明，该模型的参数，包括折扣因子，是很好的识别。特别是，它可以识别与状态相关的折扣因素(即折扣因素可以随着奖励点数的数量而变化)。我们讨论了这种识别结果与消费心理学文献中研究的目标梯度假设的关系。

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Identification of Dynamic Models of Rewards Programme

“Frequent-buyer” rewards programmes are commonly used by companies as a marketing tool to compete for market share. They provide a unique environment for studying consumers’ forward-looking behaviour. The consumer's problem on accumulating reward points can be formulated as a stationary infinite horizon discrete choice dynamic programming model. We show that the parameters of this model, including the discount factor, are well-identified. In particular, it is possible to identify state-dependent discount factors (i.e. discount factors can vary with the number of reward points). We discuss how this identification result is related to the goal-gradient hypothesis studied in the consumer psychology literature.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.