An intuition-based evaluation framework for social credit applications

Social credit enhances countries’ economic and social development. Few studies, however, have addressed this issue or, more specifically, have focused on social credit risk assessment. This evaluation process is often influenced by various factors, and, in many contexts, it is poorly understood or analyzed in ways that fail to take reality into account. This study is based on the principles of multiple criteria decision analysis (MCDA), as well as on an integrated use of cognitive mapping and the interactive multiple criteria decision making approach (i.e., TODIM). The objective was to develop an idiosyncratic decision support mechanism for identifying underlying criteria and calculating their corresponding weights (i.e., trade-offs) in risk assessments of social credit applications. This socio-technical approach was grounded in face-to-face work sessions with a panel of experts in credit risk analysis. The results reveal that the proposed methodological combination provides value to the process of evaluating social credit applications because of the privileged contact established with specialized know-how. The study’s advantages, limitations, and practical implications are also discussed.