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A Two-Layer Location Choice Model Reveals What’s New in the “New Retail”

Author

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  • Liyan Xu
  • Fu Li
  • Keqing Huang
  • Jing Ning

Abstract

The New Retail is an emerging e-commerce model in recent years. It claims innovation in creating competitive advantages through intensive Internet-based data to promote online-to-offline interactions. Whether this self-claimed innovation would cause a different rationale in the choice of store locations is a subject worthy of investigation. In this article, taking Beijing’s Starbucks and Luckin coffee stores as cases, we build a two-layer business location choice model to examine the problem. The model consists of a macroscale (city-wide) submodel and a microscale (street block) submodel. Results show that the macroscale store location choice logics for the two are consistent, with differences predicted by economic geographical laws, thus rejecting the hypothesis of the big-data-driven location choice advantage for the New Retail. Results from the microscale model, however, suggest that the difference between the two brands is better explained with cognition and behavioral theories, where the delivery agents, rather than the customers’ environmental cognition characteristics, shape the New Retail’s peculiar store location preference over less “fancy” urban locales. We argue this unique location preference is indeed something new in the New Retail. We conclude the article with discussions on the relevance of the cognitive and behavioral perspectives in the business location choice problem, and suggest incorporating the microscale layer that explicitly considers these aspects in addressing the problem in real-world settings.

Suggested Citation

  • Liyan Xu & Fu Li & Keqing Huang & Jing Ning, 2023. "A Two-Layer Location Choice Model Reveals What’s New in the “New Retail”," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 113(3), pages 635-657, March.
  • Handle: RePEc:taf:raagxx:v:113:y:2023:i:3:p:635-657
    DOI: 10.1080/24694452.2022.2115972
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