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Growing Science » Authors » Thammasak Kuaites

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Guidelines for logistics system and supply chain management for environment in industrial business Pages 299-308 Right click to download the paper Download PDF

Authors: Thammasak Kuaites, Taweesak Roopsing, Thitirat Thawornsujaritkul

doi 10.5267/j.uscm.2024.8.003 Crossmark

🔑 Keywords: Logistics and Supply Chain, Environment, Sustainable, Green Industrial, Industrial Business, Structural Equation Model

Abstract:
Industry plays a vital role in developing Thailand and supporting and driving businesses. The increase in industry benefits the national income. However, it also affects the environment. Industrial companies must adapt to reduce problems by developing organizational infrastructure, such as logistics activities or operations, which are the major systems and causes of environmental issues. Therefore, this study aims to study guidelines for logistic system and supply chain management for the environment in industrial business and develop a structural equation model (SEM). The study used a mixed-method research design; the qualitative method, in-depth interviews with nine experts and a focus group with 11 experts were used. Concerning the quantitative method, a questionnaire survey was used with 500 green industries. Descriptive statistics, inference statistics, and multivariate analysis were also used to analyze the data. The study found four essential aspects: (1) Customer orientation, (2) Green network, (3) Logistic process, and (4) Organization management. Finally, the hypothesis testing results found that in medium- and large-sized industries, the importance of the variables of the logistic system and supply chain management for the environment had no statistically significant difference at 0.05. The results from the analysis of the structural equation model found that the study passed the evaluation and was relevant to empirical data with a chi-square probability level of 0.066, a relative chi-square of 1.133, a goodness of fit index of 0.954, and root mean square error of approximation equal to 0.016.
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Journal: USCM | Year: 2025 | Volume: 13 | Issue: 2 | Views: 455

 

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