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Please use this identifier to cite or link to this item: http://dspace.bu.ac.th/jspui/handle/123456789/5739

Title: Study of Factors Influencing Sustainable Supply Chain Management (SSCM) in China
Authors: Sifan Yan
Keywords: Sustainable Supply Chain Management (SSCM)
SEM
Environmental, Social, and Governance (ESG)
Blockchain
Internet of Things (IoT)
3D printing.
Issue Date: 10-Dec-2023
Publisher: Bangkok University
Abstract: Sustainability in the transportation and supply chain industry has been a concern for decades. Conversations have been ongoing about how to reduce the carbon footprint, incorporate electric vehicles into fleets, and adopt alternative fuels. Now, however, we’re at a crossroad. The global climate crisis has reached a tipping point, highlighting transportation’s contribution to the problem in the boardrooms of most corporations. And for good reason. According to the U.S. Environmental Protection Agency, transportation is responsible for nearly a third (29%) of all greenhouse gas emissions. While passenger vehicles make up a significant portion of that number, ships, trains, planes and freight trucks are also in the mix.
The purpose of this research is to study factors influencing Sustainable Supply Chain Management (SSCM) in China. These factors include seven first-order variables: independent variables: Carbon Footprint (CF), Organizational Practices (OP), Transportation Model (TM), Environmentally Responsible Packages (EP), Alternative Energy (AE), Partnership Initiative (PI), and Technology Development (TD); two second-order variables: Environmental, Social, and Governance (ESG) and Operating Model (OPER) and one dependent variable: Sustainable Supply Chain Management (SSCM). 400 sample were collected using electronic questionnaire through social media. We used Structural Equation Models (SEM) for data analysis. The result shows that since the RMSEA, which is an absolute fit index that assesses how far our hypothesized model is from a perfect model, for this model is .039 (<.05) which strongly indicates a “close fit” and the Goodness of Fit Index (GFI) value is .903 (>.90), the model seems to fit well according to the descriptive measures of fit. Moreover, CFI, which is incremental fit indices that compare the fit of our hypothesized model with that of a baseline model (i.e., a model with the worst fit), its value equals .956 indicating an acceptable fit.
More importantly, Environmental, Social, and Governance (ESG) and Operating Model (OPER), which are second-order factor of Carbon Footprint (CF), Environmentally Responsible Packages (EP), Alternative Energy (AE), and Organizational Practices (OP), Transportation Model (TM) respectively, seem to have significant effects on Sustainable Supply Chain Management (SSCM) in China due to their p-values are all less than .05. Also the first-order factors Partnership Initiative (PI) and Technology Development (TD) also significantly influence Sustainable Supply Chain Management (SSCM) in China for the same reason. That means if supply chain management companies in China can focus on ESG and their operating model by focusing on Organizational Practices (OP) e.g. using sophisticated business intelligence tools, economic and operational data can be integrated with supply chain goals to optimize day-to-day operations and long-range planning;) and Transportation Model (TM) e.g. consolidating loads and reducing truck idle time by being ready when goods are picked up or delivered, supply chain management companies in China will become more sustainable. This is also true for both Partnership Initiative (PI) e.g. collaboration among supply chain partners can improve supply chain performance, create new capabilities, and increase efficiencies; and Technology Development (TD) e.g. adopting and scaling innovative technologies such as machine learning, blockchain, internet of things (IoT), and 3D printing has potential to improve efficiency through improved visibility, flexibility and decision making across the supply chain.
Description: Independent Study (M.B.A.)--Graduate School,Bangkok University,2022
Advisor(s): Sumas Wongsunopparat
URI: http://dspace.bu.ac.th/jspui/handle/123456789/5739
Appears in Collections:Independent Studies - Master

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