Analysis of knowledge management process towards minimizing supply chain risks under the green technology: a direct and configurational approach.

Abstract

Adopting green technologies is crucial for a sustainable supply process and organization development. In this construct, the current study analyzes how green technology adoption (GTA) and knowledge management (KM) processes could minimize supply risk in large manufacturing companies. The current study utilizes research techniques based on the resource-based view and contingency theories to minimize supply chain risk. The present study selected green variables (learning, productivity, raw materials, and resource utilization) along with KM processes (acquisition, sharing, and utilization) to investigate these connections to achieve the research objective. The author collected the data (203) from manufacturing firms in Zhengzhou city and used PLS-SEM, fuzzy set qualitative comparative analysis (fsQCA) to examine the study aims. The relationship between the adoption of green technologies and the KM process, which may reduce supply risk, was verified via PLS-SEM. fsQCA is employed as a combined strategy with green technology and the KM dimension to examine supply risk. The study results showed a significant correlation between the KM process's ability to reduce supply risk under the GTA. The results of the fsQCA specify the numerous dimensions of green implementation enablers, and the KM process produced superior results in terms of supply risk minimization. This research contributes to bridging gaps and understanding the interrelationship between green measurement and the supply risk process minimization. The current study provides practical and social justification for enlightening the relationship between GTA and the KM process, aiming to minimize the supply risk. Based on the study outcome and ground information, this study reported limitations and future research direction.