Abstract:

The rapid development of digital economy promotes the transformation of manufacturing enterprises into services and enriches the business content of manufacturing and sales enterprises in the products services supply chain. Manufacturing service provider not only produces products but also provides comprehensive service packages of products， whiles sales service integrator not only sells products but also provides specific and personalized on-site services. As the most important production factor in digital economy， data resources are becoming the key resources for enterprises to obtain sustainable competitive advantages. In 2018， the proportions of Chinese manufacturing enterprises chose data mining strategy and engaged in network collaboration， service-oriented manufacturing and personalized customization were 33.7%， 24.7% and 7.6%. Mining and sharing of data resources will have a new impact on product and service decisions in product service supply chain. Considering the potential value of data resources， a two-stage dynamic game model of product service supply chain is constructed based on data resource mining strategy and data resource sharing strategy. The optimal operation behavior of supply product service chain under data resource mining strategy and data resource sharing strategy is described. By comparing the decision-making results of product service supply chain under data resource mining strategy and data resource sharing strategy and non-data-resource-mining and sharing， the influence of data resource mining strategy and data resource sharing strategy on product service supply chain are analyzed. Finally，the numerical examples are simulated. The results show that data resource mining strategy and data resource sharing strategy can increase the profit of manufacturing service provider and sales service integrator. The potential value of data resources provides “external incentives” under data resource mining strategy. Manufacturing service providers and sales service integrators are willing to reduce the wholesale price and retail price of products to obtain a larger market. To compensate for the loss caused by product price reduction， the manufacturing service provider will increase the service fee charged to the sales service integrator， while the sales service integrator will reduce the service fee charged to the customer to obtain more data resources. Data resource mining strategy can bring about the growth effect of product and service market. The higher the degree of certainty of data resource value and the higher the conversion coefficient of data resource value， the more obvious the market growth effect is. The higher the degree of data resource sharing and absorption capacity of data resources， the more excess profits the data resource sharing strategy can bring， and the stronger the motivation of manufacturing service providers and sales service integrators to choose the data resource sharing strategy. When the degree of data resource sharing is less than the threshold， data resource sharing strategy can make consumers get the most consumer surplus， increase user stickiness， make the same kind of users gathering， and form the scale effect of data sharing. When the degree of data resource sharing is higher than the threshold， sales service integrator will have the advantage of data information， and increase the retail price of products and service fees charged to customers to obtain higher profit level， resulting in the "winner-takes-all" effect. This study has scientific guiding significance for enterprise to understand the new changes of product and service under data resource mining and sharing strategy and has important reference for further studying the operation behavior of product service supply chain.

Key words: digital economy, product service supply chain, data resource mining strategy, data resource sharing strategy