An empirical investigation of forward-looking retailer performance using parking lot traffic data derived from satellite imagery

Cong Feng, Scott Fay

Research output: Contribution to journalArticlepeer-review

Abstract

In this research note, we study the effectiveness of parking lot traffic in predicting forward-looking retailer performance (measured by Tobin's q). We obtain parking lot car count data derived from satellite images to construct a quarterly aggregate measure of parking lot traffic for 15 general merchandise retailers. To mitigate endogeneity concerns, we exploit the exogenous shocks of mass shootings that provide exogenous variations in parking lot traffic. Applying the control function approach and a panel firm fixed-effects estimator on 402 retailer-quarter observations, we find that quarterly aggregate parking lot traffic significantly predicts forward-looking retailer performance. Moreover, drawing on the perspectives of organizational competency, we find that the positive relationship between parking lot traffic and forward-looking retailer performance is moderated by factors that are related to a retailer's store management competency, namely, a retailer's existing store management competency (measured by comparable store sales), its proactivity to maintain the competency (reflected by store management intensity, i.e., the total number of store openings and closings relative to the total number of stores), and the external environment (measured by industry concentration) that affects its store management competency.

Original languageEnglish (US)
JournalJournal of Retailing
DOIs
StateAccepted/In press - 2022

Keywords

  • Alternative data
  • Contingency factors
  • Parking lot
  • Retailer performance
  • Satellite imagery

ASJC Scopus subject areas

  • Marketing

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