Cross-functional group decision making with heterogeneous cooperation for digital transformation in supply chain resilience

Supply chain resilience plays a critical role in gaining competitive advantages for companies. The resilience of supply chains can be achieved by leveraging emerging digital technologies to realize digital transformation. It is necessary to select an appropriate digitalization technology under such background. The wide-spanning of digital transformation and technology selection needs cross-functional integration of various expertise. However, in the process of making decisions by leveraging expert wisdom, differences in experts' willingness to cooperate lead to difficulties in reaching a consensus. The existing literature fails to incorporate both non-cooperation and proactive-cooperation into the consensus reaching process. Thus, in this study, we introduce a cross-functional multi-attribute group decision making model for digitalization technology selection. To manage potential noncooperative behaviors in the group consensus reaching process, the proposed model allows experts to have proactive cooperation, i.e., making more contributions than recommended feedback suggestions provided by the moderator. Proactive cooperation can make up for the loss caused by the non-cooperative behaviors of experts. A knowledge mining method is proposed to mine academic and practical preferences for attributes. Two consensus mechanisms are put forward for the meso decision-making process in functional teams and the macro decisionmaking process in the whole group, respectively. An illustrative example regarding the technology selection in shipbuilding industry is provided to verify the applicability of our model. Numerical experiments suggest that our model will improve the efficiency of consensus reaching process.