UNISON framework of data-driven tripartite evolutionary game-based knowledge sharing decision for digital servitization

Abstract

The paradigm of digital servitization emerges as a new transformation strategy for the manufacturing industry in the data-driven era, with the intertwined trends of digitization and servitization. Considering digital servitization as a value co-creation strategy, the interactions of heterogeneous knowledge among different stakeholders are necessary to drive the strategy implementation. From the knowledge perspective, knowledge-sharing activities are supported by the form of data and information flows to provide complementary data assets, especially in the context of digital servitization. However, most studies have stayed in the context of servitization while paying less attention to the emerging context of digital servitization. The knowledge sharing among multiple stakeholders in the context of digital servitization involves complex decision mechanism that requires a systematic framework to integrate various influence factors and uncertain conditions. Most studies discussed this issue by qualitative methods or considered only two participants while rarely considered investigating the dynamic game process among three participants. To fill the gaps, this study proposes the UNISON framework to systematically analyze the knowledge interaction process among multiple stakeholders in the context of digital servitization. Moreover, this study establishes a tripartite evolutionary game model of knowledge sharing among manufacturers, service providers and users within the value chain digital ecosystem. Then the knowledge sharing strategy and key influencing factors of each participant are explored in the dynamic game process by simulation analysis. The results could provide decision support and strategic planning for the system in a data-driven manner and promote the effective implementation of the digital servitization strategy.