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Pricing shared vehicles

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  • Zakharenko, Roman

Abstract

This paper analyzes profit-maximizing pricing in a model of shared vehicle (SV) market, with particular emphasis on spatial inequality of demand. I show that the best policy assigns a score to every location, and rewards (penalizes) customers for relocating the vehicle to a place with higher (lower) score. Such spatially explicit pricing enables providers to expand the vehicle dropoff “home” area into otherwise unprofitable low-density suburban areas and into for-fee parking zones. A greater geographic coverage has positive spillovers on operations within the initial home area. The empirical part of the paper uses novel microdata on SV trips to develop a strategy to estimate demand parameters, extrapolate them into larger counterfactual home area, evaluate optimal location scores, and predict profit gains from the expansion.

Suggested Citation

  • Zakharenko, Roman, 2023. "Pricing shared vehicles," Economics of Transportation, Elsevier, vol. 33(C).
    • Handle: RePEc:eee:ecotra:v:33:y:2023:i:c:s2212012222000478
    DOI: 10.1016/j.ecotra.2022.100296
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    References listed on IDEAS

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    Cited by:

    1. Jun Tu & Juan Du & Min Huang, 2023. "Competition between Green and Non-Green Travel Companies: The Role of Governmental Subsidies in Green Travel," Sustainability, MDPI, vol. 15(9), pages 1-33, May.

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    More about this item

    Keywords

    Shared vehicle; Home area; Spatial pricing; Trip demand;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L91 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Transportation: General
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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