Why and how do branders sell new products on flash sale platforms?

Mingyang Zhang, Juliang Zhang, T. C.E. Cheng, Guowei Hua

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

Flash sale (FS) is a popular e-commerce marketing mode through which branders sell a limited number of new products at discounted prices within a specified time ahead of the normal sale period. Studying why and how branders use FS, we construct a model in which a brander sells a new product in two periods: first on an FS platform with a given number of members and then in normal sale period to the public. In the first period, the brander decides whether to sell the product using FS and, if so, the quantity and price of the product, which will affect the demand in the second period because of the word-of-mouth (WOM) and price discrimination effects. Then the brander decides the inventory in the second period. The demand in the second period is realized and satisfied by the available inventory. We characterize the brander's optimal policy under the fixed-fee and two-part tariff charging mechanisms for using the FS platform. We show that the main aim of using FS is for product promotion. In some special cases, the brander uses the FS platform as a profit source. Which function of FS is used depends on the brand's popularity, purchasers’ WOM effect, potential purchasers’ WOM effect, and customers’ sensitivity to price discrimination. We conduct numerical studies to assess the impacts of the model parameters on the brander's optimal policy and to derive managerial insights from the analytical findings.

Original languageEnglish
Pages (from-to)337-351
Number of pages15
JournalEuropean Journal of Operational Research
Volume270
Issue number1
DOIs
Publication statusPublished - 1 Oct 2018

Keywords

  • Flash sale
  • New product
  • OR in marketing
  • Pricing
  • Retail operations

ASJC Scopus subject areas

  • Computer Science(all)
  • Modelling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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