Research Progress on Measurement Methods of Industrial Chain Resilience
Industrial chain resilience measurement serves as a crucial starting point for identifying risks associated with chain disruption and ensuring the safety and stability of industrial chains.This topic has gained prominence in light of the pressing need to address and navigate significant changes in the new era.However,current research on industrial chain resilience faces challenges.This paper takes an interdisciplinary approach to analyze the practical requirements of measuring industrial chain resilience.Drawing from classic and cutting-edge literature,it discusses this endeavor's theoretical foundations,methodological approaches,and application steps,and proposes future research directions.To begin with,this paper examines the theoretical underpinnings and evolutionary trajectory of both industrial chain and resilience theory,culminating in the concept of industrial chain resilience.Within the realm of social and economic activities,the interconnected structure of industrial sectors forms what we understand as the industrial chain,encompassing product production,commodity circulation,and value addition.As a dynamic process,industrial chain resilience encompasses four dimensions:resistance,recovery,adaptability,and transformative capabilities.Compared to economic resilience,its distinctiveness lies in its micro perspective,emphasis on"compensation",and network characteristics.Subsequently,this paper reviews cutting-edge advancements and critical challenges in methods for measuring industrial chain resilience,focusing on the core variable method,the comprehensive evaluation method,and the input-output method.The core variable method captures resilience's dynamic nature by selecting a representative variable,offering flexibility and operability.However,its limitation lies in its single-dimensional representation and the need for carefully considering counterfactual measurements.The comprehensive evaluation method employs multi-criteria decision analysis tools to assess complex decision-making issues,reflecting rich economic connotations.Nevertheless,challenges include insufficient authority in indicator selection,ambiguity in weighting algorithms and indicator systems,and the lack of impact connotation on the industrial chain.Based on the modeling analysis,the input-output method accurately quantifies chain correlations but falls short in describing the impact process of disequilibrium and lacks granularity in enterprise-level analyses.Further,from an interdisciplinary perspective,this paper comprehensively elucidates the application of resilience measurement theories and methods within the framework of"shock identification-structural analysis-resilience evaluation".Shock identification,as the first step,involves categorizing shock types and pinpointing their timing.Structural analysis,the subsequent step,encompasses network topology analysis and system dynamics analysis.Network topology analysis involves identifying network properties,establishing models,analyzing behavior,and designing performance.Resilience evaluation,the final step,addresses evaluation dimensions and methods.Finally,this paper outlines outstanding challenges in industrial chain resilience research and proposes future research directions.Challenges include the scarcity and quality of industrial chain data,the applicability of resilience scenarios,the identification of key industrial chains,and the timing and categorization of shocks.Future research should consolidate the academic foundation of industrial chain resilience while exploring interdisciplinary intersections with resilience theories,leveraging research methods from network science,machine learning,and complex systems science.
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