Title: Price coordination in closed-loop data supply chain

Authors: Xinming Li; Huaqing Wang; Lei Wen; Yu Nie

Addresses: School of Management, Xi'an Jiaotong University, China ' School of Business, Emporia State University, USA ' School of Business, Emporia State University, USA ' College of Engineering and Information Technology, University of Arkansas at Little Rock, USA

Abstract: By focusing on new features of data products and, based on game theoretical models, we study three pricing mechanisms' performance and their effects on the participants in the data industry from the data supply chain perspective. A win-win pricing strategy for the players in the data supply chain is proposed. We obtain analytical solutions in each pricing mechanism, including the decentralised and centralised pricing, Nash bargaining pricing, and revenue sharing mechanism. Our findings show that: 1) the decentralised pricing has the lowest performance; 2) although Nash bargaining pricing can achieve the centralised channel performance, the upstream data provider and downstream application provider can only equally divide the total channel profit; 3) revenue sharing mechanism, in which the data provider subsidises the application provider, can achieve the first best performance and divide the maximum profit arbitrarily. Accordingly, end-users benefit mostly from the bargaining pricing and revenue sharing.

Keywords: price coordination; data pricing; Nash bargaining; revenue sharing; channel coordination.

DOI: 10.1504/IJADS.2019.096551

International Journal of Applied Decision Sciences, 2019 Vol.12 No.1, pp.20 - 36

Available online: 22 Oct 2018 *

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