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Which Retail Outlets Generate the Most Physical Interactions?

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  • Avi Goldfarb
  • Catherine Tucker

Abstract

This paper seeks to answer the simple question of what category of retail outlets generates the most physical interactions in the regular course of life. In this way, we aim to bring a marketing perspective to discussions about which businesses may be most risky from the standpoint of spreading contagious disease. We use detailed data from people's mobile devices prior to the implementation of social distancing measures in the United States. With this data, we examine a number of potential indicators of risk of contagion: The absolute number of visits and visitors, how many of the visits are generated by the same people, the median average distance traveled by the visitor to the retailer, and the number of customers from Canada and Mexico. We find that retailers with a single outlet tend to attract relatively few visitors, fewer one-off visitors, and have fewer international customers. For retailers that have multiple stores the patterns are non-linear. Retailers that have such a large number of stores that they are ubiquitous, tend to exhibit fewer visits and visitors and attract customers from a smaller distance. However, retailers that have a large enough footprint to be well known, but not large enough to be ubiquitous tend to attract a large number of visitors who make one-off visits, travel a long distance, and are disproportionately international.

Suggested Citation

  • Avi Goldfarb & Catherine Tucker, 2020. "Which Retail Outlets Generate the Most Physical Interactions?," NBER Working Papers 27042, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:27042
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    Cited by:

    1. Tyler Atkinson & Jim Dolmas & Christoffer Koch & Evan F. Koenig & Karel Mertens & Anthony Murphy & Kei-Mu Yi, 2020. "Mobility and Engagement Following the SARS-Cov-2 Outbreak," Working Papers 2014, Federal Reserve Bank of Dallas.
    2. Goolsbee, Austan & Syverson, Chad, 2021. "Fear, lockdown, and diversion: Comparing drivers of pandemic economic decline 2020," Journal of Public Economics, Elsevier, vol. 193(C).
    3. Cronin, Christopher J. & Evans, William N., 2021. "Total shutdowns, targeted restrictions, or individual responsibility: How to promote social distancing in the COVID-19 Era?," Journal of Health Economics, Elsevier, vol. 79(C).
    4. Anton Pichler & Marco Pangallo & R. Maria del Rio-Chanona & Franc{c}ois Lafond & J. Doyne Farmer, 2020. "Production networks and epidemic spreading: How to restart the UK economy?," Papers 2005.10585, arXiv.org.
    5. Raj Chetty & John N. Friedman & Michael Stepner & The Opportunity Insights Team, 2020. "The Economic Impacts of COVID-19: Evidence from a New Public Database Built Using Private Sector Data," NBER Working Papers 27431, National Bureau of Economic Research, Inc.
    6. Seth G. Benzell & Avinash Collis & Christos Nicolaides, 2020. "Rationing social contact during the COVID-19 pandemic: Transmission risk and social benefits of US locations," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(26), pages 14642-14644, June.
    7. Monte, Ferdinando, 2020. "Mobility Zones," Economics Letters, Elsevier, vol. 194(C).
    8. Christopher J. Cronin & William N. Evans, 2020. "Private Precaution and Public Restrictions: What Drives Social Distancing and Industry Foot Traffic in the COVID-19 Era?," NBER Working Papers 27531, National Bureau of Economic Research, Inc.

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    More about this item

    JEL classification:

    • M38 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Government Policy and Regulation

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