Identifying firm-specific technology opportunities in a supply chain: Link prediction analysis in multilayer networks

Although technology opportunity discovery (TOD) for a target firm has considered the firm's internal characteristics such as technological capabilities and R&D directions, the firm's external environment, especially the supply chains it is in, is generally ignored. This paper proposes a novel approach to identifying firm-specific technology opportunities in each echelon of a multi-echelon supply chain, with the interactions among the technologies of different echelons considered. The proposed approach comprises four steps: 1) dividing the supply chain echelons and collecting patents for each echelon; 2) constructing a firm-centered International Patent Classification (IPC) multilayer network of the multi-echelon supply chain; 3) recommending IPC codes in each echelon of the supply chain for the target firm using a link prediction algorithm; and 4) evaluating technology opportunities to support the firm's R&D decisions with the indicators of technology importance, technology maturity, and technology impact. Using the General Motors Company (GM) in the fuel cell vehicle (FCV) supply chain as a case study, it is verified that the method can identify technology opportunities for GM efficiently and effectively. This work proposes an innovative method that identifies firm-specific technology opportunities from a supply chain perspective, and pioneers to apply multilayer networks to TOD.