A Rental Platform Service Supply Chain Network Equilibrium Model Considering Digital Detection Technology Investment and Big Data Marketing

Abstract

Digital transformation is reshaping the decision making management of the rental service mode in the manufacturing industry, and improving digital detection technology and big data marketing have become effective ways to create value. Based on the three-level rental platform service supply chain network structure composed of manufacturers, rental platform operators and the demand market, a supply chain network equilibrium model considering the digital detection technology input and big data marketing is constructed by using variational inequality and the Nash equilibrium theory, and the optimal decision making conditions of the manufacturers and rental platform operators are derived. Combined with the Euler algorithm design procedure and numerical examples, the influences of the digital detection technology level, big data marketing cost coefficient and cost sharing ratio on the equilibrium state are analyzed. The results show that the input of digital detection technology leads to the increase in profits of each participant in the rental platform service supply chain network and promotes a more coordinated development of the supply chain. When the rental platforms implement big data marketing, the manufacturers share the cost, which can continuously improve the profits of both partners and make the cooperation more stable and efficient.