Risk Early Warning Indicator System Based On Supply Chain Management, Enterprise Logistics Research

For the past few years, the role of logistics in enterprise has increased in both scope and strategic importance. However, under the circumstance of supply chain management (SCM), some tendencies exposed enterprises to increasing logistics risk. The tendencies include: more complicate of logistics system, leaner of the supply chain, more complicate of the environment and fiercer of the competition. Therefore, it becomes urgent for enterprises to implement the logistics risk management, the focus of which is early warning. Furthermore, the key point of early warning management is the early warning indicator system (EWIS) of enterprise logistics. So it is necessary for enterprises to establish a reasonable and comprehensive EWIS of enterprise logistics. However, there is a shortage of research effort of enterprise logistics risk management to date. The research on EWIS is again very scarce in logistics area. Moreover, the questionnaire results we calculated also show that although enterprises'awareness of logistics risk is rather lack, their desire for the effective, specialized and systematic knowledge on enterprise logistics risk management is strong. The integrated nature of logistics processes necessitates that logistics risk be assessed from the SCM's perspective rather than the single company's perspective. Therefore, the research on the EWIS of enterprise logistics risk based on the SCM is of great theoretical and practical significance.This paper provides a literature review of related research area and makes a brief analysis of their problems, which will provide insights into the design of EWIS of enterprise logistics risk. Then the definition of enterprise logistics risk is proposed, the characteristics and causes of enterprise logistics risk is discussed, the relative theory of SCM is clarified. After the analysis of the design approaches and design principles of the EWIS, the preliminary EWIS of enterprise logistics risk based on the SCM is established. Then, the 168 valid questionnaires selected from the empirical survey are analyzed. Combined with the multivariate statistical analysis, we have screed out 28 indicators of enterprise logistics risk indicators and 4 risk consequence indicators. When the early warning indicators are finalized, the selected indicators are being analyzed thoroughly. In the next step, the integrated logistics risk level and the degree of the risk consequences of enterprises in China are evaluated based on the surveyed data by the exploring the method of Frequency & Duration Method and Fuzzy Integrative Evaluation Method. Therefore, enterprises have helpful references when implementing the early warning management of logistics risk.