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Recharging Retail: Estimating Consumer Demand Spillovers from Electric Vehicle Charging Stations

Author

Listed:
  • Yash Babar

    (Operations and Information Management, University of Wisconsin-Madison, Madison, Wisconsin 53706)

  • Gordon Burtch

    (Information Systems, Boston University, Boston, Massachusetts 02215)

Abstract

Problem definition: We estimate the impact of electric vehicle (EV) charging stations on volumes of consumer foot traffic received by nearby retail establishments. We also explore the conditions under which any effects manifest. Methodology/results: We use a differences-in-differences design, exploiting the staggered introduction of Tesla Supercharger stations across the United States. We combine data on Supercharger installations with mobile phone–based estimates of retailer foot traffic. We explore heterogeneity in the treatment effect, in terms of EV charger characteristics, visitor characteristics, establishment type, and local physical context. We estimate that establishments experience an average 4% increase in monthly visits following the installation of a Tesla Supercharger. These effects arise primarily for retailers that offer relatively quick services (e.g., fast food) and for those located very near to the charger (within 150 meters). The effects are also more pronounced when the Supercharger is one of the first EV chargers introduced into the local area. Managerial implications: We document evidence of the positive retail demand spillovers arising from EV charging station infrastructure. We also document the conditions under which the benefits manifest. Insights for EV network operators, retailers, and policymakers are included.

Suggested Citation

  • Yash Babar & Gordon Burtch, 2024. "Recharging Retail: Estimating Consumer Demand Spillovers from Electric Vehicle Charging Stations," Manufacturing & Service Operations Management, INFORMS, vol. 26(3), pages 797-813, May.
  • Handle: RePEc:inm:ormsom:v:26:y:2024:i:3:p:797-813
    DOI: 10.1287/msom.2022.0519
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    References listed on IDEAS

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    Cited by:

    1. Yao, Zhaosheng & Ren, Xinyue & Chan, Wai Kin (Victor) & Jia, Fengwei & Zhu, Hongli & Xu, Yinliang & Wu, Qiuwei, 2026. "Innovative business model for private charging pile sharing operation and its vehicle-to-grid energy management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 206(C).
    2. Xi Chen & Xiulan Liu & Xijuan Yu & Yongda Li & Shanna Luo & Xuebin Li, 2025. "Bayesian-Spatial Optimization of Emergency EV Dispatch Under Multi-Hazard Disruptions: A Behaviorally Informed Framework for Resilient Energy Support in Critical Grid Nodes," Energies, MDPI, vol. 18(17), pages 1-23, August.

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