User Privacy Awareness, Incentive and Data Supply Chain Pricing Strategy

Abstract

In recent years, the collection, mining, and utilization of data have become a new profit growth point for enterprises, and these events have also accelerated the pace of enterprises to collect users’ data. However, the relevance of personal data privacy and the frequent occurrence of data leakage events have increased users’ privacy awareness. The purpose of our study is to enhance the effective flow of data while protecting users’ data privacy. The data supply chain consists of the end user, data provider, and service provider, and involves the flow of the value-added process of data. Our study focuses on the pricing strategy of data products considering data incentive and data protection levels. We propose three models—centralized pricing, decentralized pricing, and revenue-sharing pricing—and solve them, and then we analyze the impact of users’ privacy awareness on data incentives, protection, and pricing of data products in the three models. We also analyze which pricing method works best for participants.