A Global Temporal Networked Consensus Mining Method for Social Product Development

Social product development (SPD) extends open innovation beyond customer-involved models to socially engaged individuals involved in ideation and development of new products based on Web 2.0 technologies. SPD teams in the current market environment are increasingly dispersed around the globe. A global virtual team (GVT) is a team whose members are separated by space and time, which has been an increasingly popular organizational structure. The decision-making process of GVTs faces challenges because members usually find it hard to achieve synchronous communication and obtain a shared understanding. In this study, we construct a temporal network for GVTs and introduce a method to classify a GVT into temporal subgroups. A consensus mining method is proposed to reduce discrepancies in temporal subgroups considering knowledge distribution. Next, an alternative selection approach is put forward to select the optimal alternative for the GVT. An illustrative example regarding SPD tenant selection is provided to verify the applicability of our proposed model. This study contributes to global virtual teamwork, temporal network-based subgroup decision making and structural perspectives of group consensus.