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    Does Apple Anchor a Shopping Mall? The Effect of the Technology Stores on the Formation of Market Structure
    17 Dec 2019Working Paper Summaries

    Does Apple Anchor a Shopping Mall? The Effect of the Technology Stores on the Formation of Market Structure

    by Doug J. Chung, Kyoungwon Seo, and Reo Song
    How do technology stores, particularly those owned by Apple and Microsoft, affect retail sales and market dynamics at malls? Through modeling and simulation, the authors found that these stores helped malls draw more high-income consumers, supporting the entry of upscale stores and exit of midscale and discount stores.
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    Author Abstract

    This study examines the effect of technology stores—company-owned Apple and Microsoft retail stores—on mall configuration. We formulate a structural model that considers the endogenous location decisions of retail stores, taking into account both market characteristics and the spillover effects of co-location. As a byproduct, the study provides guidance on location choice to mall developers and retailers by examining the equilibrium outcome of mall configuration that affects retail sales. The results show that competitive effects dominate within and across store categories for traditional department stores, but agglomeration effects exist between technology stores and upscale department stores. The presence of an Apple store, for example, attracts high-income consumers, promoting the entry of upscale stores and the exit of midscale and discount stores. This study also introduces three key methodological innovations to the marketing literature. First, we address multiple equilibria by estimating equilibrium selection from the observed data. Second, we develop an efficient simulator that requires fewer random draws to evaluate the likelihood function for complete information games with multiple equilibria. Third, we overcome the remaining computational burden by utilizing the GPGPU technology, using multiple processing cores in a graphics-processing unit to increase computational speed.

    Paper Information

    • Full Working Paper Text
    • Working Paper Publication Date: December 2019
    • HBS Working Paper Number: 20-066
    • Faculty Unit(s): Marketing
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