"A Good Ride Under a Big Tree?"——Perceived Risk Analysis of the Industrial Chain from the Perspective of Inter-organizational Dependency Structure
The global industrial chain is undergoing significant turbulence due to major shifts,posing substantial risks to Chinese enterprises.Compared to objective risks,the analysis of perceived industrial chain risks by enterprises offers more strategic foresight.A considerable portion of these perceived risks stems from Chinese enterprises'reliance on the"big tree"of multinational corporations.Does this reliance provide greater securi-ty,or does it harbor hidden dangers?This study leverages transaction data between upstream and downstream enterprises within the industrial chain,as well as textual data from management analyses in annual reports,employing a novel deep learning approach based on the BERT model.This method allows for feature extrac-tion,model pre-training,and measurement of perceived industrial chain risks,focusing on the theoretical di-mensions of relational risk and contextual risk.Furthermore,from the perspective of inter-organizational de-pendence,this research examines the mechanisms through which such dependence influences Chinese enter-prises'perceived industrial chain risks.The findings reveal two key insights:First,the greater the dependence of Chinese enterprises on multinational corporations,the higher the perceived relational risk,but the lower the contextual risk.Second,the innovation capacity of firms attenuates the significant relationship between inter-organizational dependence and these two types of risks.This study advances the methodology of deep learning for measuring perceived industrial chain risks,uncovers the impact mechanisms of inter-organizational de-pendence structures on firms'risk perceptions,and provides valuable insights for the theoretical exploration of industrial chain risk and the practice of enhancing industrial chain security.
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