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Where you live matters: The impact of offline retail density on mobile shopping app usage

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  • Cui, Xuebin
  • Zhu, Ting
  • Chen, Yubo

Abstract

Consumers residing in different areas have varying levels of access to local retail stores. In contrast, with the prevalence of mobile internet, consumers have gained widespread access to mobile shopping. This research examines the impact of local offline retail density on consumers’ mobile shopping app usage and heterogeneity across consumer segments and different types of shopping apps. We use a unique dataset of individual-level mobile app usage with real-time location information across 1622 counties in China and employ the control function approach to address the endogenous retail density. Overall, the findings show that local offline retail density has a negative effect on mobile shopping app usage frequency and duration, indicating that consumers in areas with lower offline retail density engage more in mobile shopping app usage. This negative effect is weaker for consumers with higher mobility. Also, we find that this negative effect is weaker for shopping apps selling more technically complex products such as electronics than for those selling less technically complex products such as clothing and cosmetics. These results offer managerial implications for online retailers to launch targeting strategies to enhance consumer engagement with their shopping apps.

Suggested Citation

  • Cui, Xuebin & Zhu, Ting & Chen, Yubo, 2024. "Where you live matters: The impact of offline retail density on mobile shopping app usage," Journal of Retailing, Elsevier, vol. 100(1), pages 41-55.
    • Handle: RePEc:eee:jouret:v:100:y:2024:i:1:p:41-55
    DOI: 10.1016/j.jretai.2023.10.001
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    1. Raj Echambadi & James D. Hess, 2007. "Mean-Centering Does Not Alleviate Collinearity Problems in Moderated Multiple Regression Models," Marketing Science, INFORMS, vol. 26(3), pages 438-445, 05-06.
    2. Rajiv Lal & Miklos Sarvary, 1999. "When and How Is the Internet Likely to Decrease Price Competition?," Marketing Science, INFORMS, vol. 18(4), pages 485-503.
    3. Ting Zhu & Vishal Singh, 2009. "Spatial competition with endogenous location choices: An application to discount retailing," Quantitative Marketing and Economics (QME), Springer, vol. 7(1), pages 1-35, March.
    4. Gensler, Sonja & Neslin, Scott A. & Verhoef, Peter C., 2017. "The Showrooming Phenomenon: It's More than Just About Price," Journal of Interactive Marketing, Elsevier, vol. 38(C), pages 29-43.
    5. Anindya Ghose & Avi Goldfarb & Sang Pil Han, 2013. "How Is the Mobile Internet Different? Search Costs and Local Activities," Information Systems Research, INFORMS, vol. 24(3), pages 613-631, September.
    6. Pradeep K. Chintagunta & Junhong Chu & Javier Cebollada, 2012. "Quantifying Transaction Costs in Online/Off-line Grocery Channel Choice," Marketing Science, INFORMS, vol. 31(1), pages 96-114, January.
    7. Erik Brynjolfsson & Yu (Jeffrey) Hu & Mohammad S. Rahman, 2009. "Battle of the Retail Channels: How Product Selection and Geography Drive Cross-Channel Competition," Management Science, INFORMS, vol. 55(11), pages 1755-1765, November.
    8. Shaohui Wu & Yong Tan & Yubo Chen & Yitian (Sky) Liang, 2022. "How Is Mobile User Behavior Different? A Hidden Markov Model of Cross-Mobile Application Usage Dynamics," Information Systems Research, INFORMS, vol. 33(3), pages 1002-1022, September.
    9. Laxman Narasimhan & Kannan Srinivasan & K. Sudhir, 2015. "Editorial —Marketing Science in Emerging Markets," Marketing Science, INFORMS, vol. 34(4), pages 473-479, July.
    10. Chris Forman & Anindya Ghose & Avi Goldfarb, 2009. "Competition Between Local and Electronic Markets: How the Benefit of Buying Online Depends on Where You Live," Management Science, INFORMS, vol. 55(1), pages 47-57, January.
    11. Jeffrey M. Wooldridge, 2015. "Control Function Methods in Applied Econometrics," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 420-445.
    12. Mohammed Alyakoob & Mohammad S. Rahman & Zaiyan Wei, 2021. "Where You Live Matters: Local Bank Competition, Online Marketplace Lending, and Disparity in Borrower Benefits," Information Systems Research, INFORMS, vol. 32(4), pages 1390-1411, December.
    13. David R. Bell & Santiago Gallino & Antonio Moreno, 2018. "Offline Showrooms in Omnichannel Retail: Demand and Operational Benefits," Management Science, INFORMS, vol. 64(4), pages 1629-1651, April.
    14. Pauwels, Koen & Neslin, Scott A., 2015. "Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment," Journal of Retailing, Elsevier, vol. 91(2), pages 182-197.
    15. Bing Jing, 2018. "Showrooming and Webrooming: Information Externalities Between Online and Offline Sellers," Marketing Science, INFORMS, vol. 37(3), pages 469-483, May.
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    1. Guyt, Jonne Y. & Datta, Hannes & Boegershausen, Johannes, 2024. "Unlocking the Potential of Web Data for Retailing Research," Journal of Retailing, Elsevier, vol. 100(1), pages 130-147.

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