Capturing Public Response on Social Media Regarding the Implementation of Sustainable Supply Chain Management using Natural Language Processing

Abstract

The concept of Sustainable Supply Chain Management (SSCM) attracts the attention of academics and practitioners with the triple bottom line concept (economic, social, environmental). In carrying out supply chain management, economic performance considers environmental and social factors through economic performance. Efforts to reduce negative impacts on social life and the environment are things that are considered in SSCM by applying this concept to the entire supply chain network. The application of SSCM becomes very complicated because it considers many things, and research that develops revolves around operational management. While the discussion from the consumer side is not much discussed. This study aims to discover the topics the public discusses regarding SSCM. Using the Natural Language Processing (NLP) method, public discussions on the Twitter platform were abstracted to obtain a list of topics and public sentiment towards SSCM. The results of extracting discussion topics on the Twitter platform show that economic and environmental discussions are more widely discussed than social factors. This can happen because there is a possibility that the concept of Green SCM has already been known. This concept discusses environmental factors that need to be considered in SCM. Meanwhile, public discussions were dominated by positive and neutral sentiments indicating optimism in the SSCM discussions.