New retail versus traditional retail in e-commerce: channel establishment, price competition, and consumer recognition

Xuan Wang, Chi To Ng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

34 Citations (Scopus)


The concept “new retail” in e-commerce is to establish an offline channel and integrate it with the online retail channel. The development of new retail encounters three main problems: locations of the offline stores, the price competition with the traditional online retail, and the difficulty in consumer recognition in the two channels. In this paper, we present a duopoly model consisting of a new retail firm and an online firm, which sell the same product in two periods. The two firms compete for the market share using the behavior-based pricing (BBP), which means that in the second period each firm offers different prices to consumers with different purchasing histories/behaviors in the first period. We also solve the benchmark pricing model, where the histories/behaviors are not considered. The results of this paper provide valuable insights to the development of new retail in e-commerce. In the Nash equilibrium, each price of the new retail firm is higher than the corresponding price of the online firm due to a higher channel cost for the offline stores and high-speed deliveries. Under certain condition, the new retail firm will establish an offline channel with a larger hassle cost, which is a measure of the easiness of reaching the offline stores by the consumers, in the BBP model than that in the benchmark model. Interestingly, the difficulty in consumer recognition results in that the new retail firm occupies more market share and may obtain higher profit.

Original languageEnglish
Pages (from-to)921-937
Number of pages17
JournalAnnals of Operations Research
Issue number1-2
Publication statusPublished - 1 Aug 2020


  • Behavior-based pricing
  • Consumer recognition
  • New retail
  • Price competition

ASJC Scopus subject areas

  • General Decision Sciences
  • Management Science and Operations Research


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