Price coordination in closed-loop data supply chain Online publication date: Mon, 22-Oct-2018
by Xinming Li; Huaqing Wang; Lei Wen; Yu Nie
International Journal of Applied Decision Sciences (IJADS), Vol. 12, No. 1, 2019
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.
Online publication date: Mon, 22-Oct-2018
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Applied Decision Sciences (IJADS):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email firstname.lastname@example.org