• Medientyp: E-Book
  • Titel: Identification of Dynamic Models of Rewards Programme
  • Beteiligte: Ching, Andrew T. [Verfasser:in]; Ishihara, Masakazu [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2019]
  • Erschienen in: Published in Japanese Economic Review, vol.69(3): 306-323, 2018
  • Umfang: 1 Online-Ressource (29 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.2616110
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 29, 2017 erstellt
  • Beschreibung: 'Frequent-buyer' type of rewards program is a commonly used marketing tool for companies to compete for market shares. It also provides an unique environment for studying consumer's forward-looking behavior. The consumer's problem on accumulating reward points can be formulated as a stationary infinite horizon discrete choice dynamic programming (DDP) 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 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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