Robin Hood to the Rescue: Sustainable Revenue-Allocation Schemes for Data Cooperatives

48 Pages Posted: 3 Feb 2022

See all articles by Milind Dawande

Milind Dawande

University of Texas at Dallas - Department of Information Systems & Operations Management

Sameer Mehta

Rotterdam School of Management, Erasmus University

Liying Mu

University of Delaware

Date Written: January 29, 2022

Abstract

The promise of consumer data along with advances in information technology has spurred innovation not only in the way firms conduct their business operations but also in the manner in which data is collected. A prominent institutional structure that has recently emerged is a data cooperative — an organization that collects data from its members, and processes and monetizes the pooled data. A characteristic of consumer data is the externality it generates: data shared by an individual reveals information about other similar individuals; thus, the marginal value of pooled data increases in both the quantity and quality of the data. A key challenge faced by a data cooperative is the design of a revenue-allocation scheme for sharing revenue with its members. An effective scheme generates a beneficial cycle: It incentivizes members to share high-quality data, which in turn results in high-quality pooled data — this increases the attractiveness of the data for buyers and hence the cooperative's revenue, ultimately resulting in improved compensation for the members. While the cooperative naturally wishes to maximize its total surplus, two other important desirable properties of an allocation scheme are individual rationality and coalitional stability. We first examine a natural proportional allocation scheme — which pays members based on their individual contribution — and show that it simultaneously achieves individual rationality, the first-best outcome, and coalitional stability, when members' privacy costs are homogeneous. Under heterogeneity in privacy costs, we analyze a novel hybrid allocation scheme and show that it achieves both individual rationality and the first-best outcome, but may not satisfy coalitional stability. Finally, our RobinHood allocation scheme — which uses a fraction of the revenue to ensure coalitional stability and allocates the remaining based on the hybrid scheme — achieves all the desirable properties.

Keywords: data cooperative, data sharing, data monetization, revenue-allocation scheme, cooperative game

JEL Classification: C71, D47, D70

Suggested Citation

Dawande, Milind and Mehta, Sameer and Mu, Liying, Robin Hood to the Rescue: Sustainable Revenue-Allocation Schemes for Data Cooperatives (January 29, 2022). Available at SSRN: https://ssrn.com/abstract=4020556 or http://dx.doi.org/10.2139/ssrn.4020556

Milind Dawande

University of Texas at Dallas - Department of Information Systems & Operations Management ( email )

P.O. Box 830688
Richardson, TX 75083-0688
United States

Sameer Mehta (Contact Author)

Rotterdam School of Management, Erasmus University ( email )

RSM Erasmus University
PO Box 1738
Rotterdam, 3062 PA
Netherlands

Liying Mu

University of Delaware ( email )

Newark, DE
United States

HOME PAGE: http://https://lerner.udel.edu/faculty-staff-directory/liying-mu/

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