关键词: 数据应用产品, 私域数据, 隐私顾虑

Abstract: Data application products, which cater to the customized needs of client companies, hold great potential in the current era of digital industrialization. This study focuses on the pricing of data application products in the duopoly market, considering the differentiated degree of private data utilization by suppliers, data externalities, and customer privacy concerns. We develop a game model analogous to the classical Hotelling’s linear city. In this model, two suppliers of data application products are positioned at the two ends of a unit line, while their client companies are uniformly distributed along this line. Suppliers create their data application products based on a common public dataset and their private dataset, the size of which is proportional to the respective installed base of the data application product. Thanks to the data externalities, leveraging the private dataset helps suppliers enhance the quality of the data application product. Meanwhile, client companies express privacy concerns, assumed to be proportional to the customer’s distrust against each supplier. Client companies typically procure data application products from a single supplier for data security reasons; thus, we assume they are single-homing in this paper. Each client company decides which supplier to procure the data application products from based on its own utility, influenced by the size of the common public dataset, size of the suppliers’ private dataset, the suppliers’ utilization levels on the two types of datasets, the price of the data application products, and its own privacy concern.
We identify three different stages of market evolution. In the initial stage, characterized by relatively low data utilization, the market is partially covered. Suppliers consistently price their data application products based on the value provided by the public dataset, but they could gain a larger market share by leveraging private data. In the second stage, with moderate degrees of data utilization, the market is almost fully covered, leading to multiple equilibrium prices. The supplier with a higher level of private data utilization prices its product based on the mutual level of private data utilization, while the other supplier prices its product based on the value of the public dataset. The former consistently sets a higher price than the latter. In the third stage, with relatively high degrees of data utilization, the market is fully covered, and both suppliers price their data application products based on the mutual level of private data utilization.
Furthermore, suppliers may experience different outcomes in the competition to improve their degree of private data utilization, depending on whether their rival improves simultaneously. In asymmetric competitions, the supplier enhancing its degree of private data utilization gains more revenue in the first two stages but incurs a loss in the third stage. In contrast, its rival generally receives no positive outcome but remains immune from losses if they are in the first stage of market evolution. In symmetric competitions, the revenues of the two suppliers mutually increase in the first two stages but decrease in the last stage. The results suggest that improving the degree of private data utilization is not advantageous when the market has evolved to the third stage with relatively high degrees of data utilization. Additionally, we identify a Prisoner’s dilemma for the two suppliers in the competition to enhance their degree of private data utilization.
Our findings contribute to a comprehensive understanding of pricing policies for data application products and provide valuable managerial insights. We also suggest several directions for future research, such as exploring subscription-based business models, pricing based on data application product usage, and pricing for vertically differentiated data application products.

Key words: data application product, private data, privacy concerns