• Medientyp: E-Book
  • Titel: Stochastic Dynamic Product Search
  • Beteiligte: Bo, Lijun [Verfasser:in]; Li, Meng [Sonstige Person, Familie und Körperschaft]; Zhang, Tingting [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2020]
  • Umfang: 1 Online-Ressource (32 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.3511098
  • Identifikator:
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 26, 2019 erstellt
  • Beschreibung: Before making purchase decisions, consumers often search for information on product attributes.In this paper, we incorporate a key feature of consumer search behavior---namely, search intensity---into a stochastic dynamic model. Specifically, motivated by industry evidence, we model search intensity as a mean-reverting square root process which is fed back to consumers' valuation. Due to this stochastic dynamic search intensity, the consumers' decision-making subjects to a two-dimensional (consumers' product valuation and search intensity) optimal stopping problem. We develop an asymptotic expansion technique to facilitate the solution procedure. We also prove that the value of consumers continuing a search is smaller, as (i) the search intensity becomes smaller, (ii) the search intensity decreases faster, (iii) the mean-reverting value of the search intensity becomes smaller, and (iv) the market is more volatile. Given this, we also evaluate the firm's pricing strategy of the product
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