Estimating Sparse Spatial Demand to Manage Crowdsourced Supply in the Sharing Economy

58 Pages Posted: 18 Feb 2024

Date Written: February 5, 2024

Abstract

This paper develops a structural approach to guide decisions regarding the acquisition, retention, and development of individual providers by a sharing-economy platform that crowdsources supply, which we call Provider Relationship Management. Taking the context of a French car-sharing platform for which we have historical data, we lay out a random-coefficient logit (RCL) model of spatial demand, combined with a Bertrand model of price competition between providers. Sparsity brings challenges in demand estimation; we resolve them through an approximation that brings new insights on a recent model with Poisson consumer arrivals. We then perform counterfactuals to evaluate the incremental value brought by existing potential providers to the platform. The results show that ignoring externalities between providers leads to large biases: provider incremental values are over-estimated by 40% on average and customer scorings are substantially impacted, resulting in suboptimal reward allocation. We also evaluate the potential impact of an advertising campaign to illustrate how our approach can be used to target acquisitions in specific locations, and we study the impact of activities that may increase the value of existing providers through price and / or location changes.

Keywords: sharing economy, customer relationship management, structural models, spatial modeling, sparsity, granular data

Suggested Citation

Stourm, Ludovic and Stourm, Valeria and Submitter, HEC Paris, Estimating Sparse Spatial Demand to Manage Crowdsourced Supply in the Sharing Economy (February 5, 2024). Available at SSRN: https://ssrn.com/abstract=4716903 or http://dx.doi.org/10.2139/ssrn.4716903

Ludovic Stourm (Contact Author)

HEC Paris ( email )

1 rue de la Liberation
Jouy-en-Josas Cedex, 78351
France

Valeria Stourm

HEC Paris ( email )

1 rue de la Liberation
Jouy-en-Josas Cedex, 78351
France

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