Sustainability risk management in a smart logistics ecological chain: An evaluation framework based on social network analysis

Abstract

Smart logistics ecological chain (SLEC) consists of a supply ecological group, a core ecological logistics platform, and a demand ecological group. As a diversified industrial cluster, SLEC faces a complex internal and external environment, which makes high sustainable risks threatens the survival of SLEC members. To reduce the risks of SLEC, we first identify three kinds of risk factors, namely, the risks of SLEC members, technology risks, and external environmental risks. Then we adopt social network analysis (SNA) to construct a research framework for analyzing the relationships among risk factors of SLEC. Based on the results of the SNA, we further build a risk evaluation system based on the improved technique for order performance by similarity to ideal solution (TOPSIS) method to evaluate the risks of different SLECs and achieve better global optimal risk control. Moreover, we use a case study of RRS logistics company to verify our research framework and evaluation system. The results show that, in the RRS home appliance SLEC, the risks of technological route change, government management risks, and industry management risks can easily lead to the generation of other risks, while external stakeholder risk, government management risk and internal stakeholder risk are easily induced by other risks. Besides, among the home appliance, fitness, and fast-moving consumer goods (FMCG) SLECs of RRS logistics company, when in-node degree and out-node degree risks have the same weight, the risks of the home appliance SLEC are the lowest, while that of the FMCG SLEC are the highest.