LOGISTICS MANAGEMENT MODEL FOR SPORTS INDUSTRY IN THAILAND

บทคัดย่อ

This research addresses green reverse logistics model for Thailand's economically vital sports industry by developing a framework that integrates social, environmental, and economic pillars to enhance operational efficiency and overcome international trade barriers and aimed to develop a green reverse logistics management model for the sports industry in Thailand. The study employed mixed-methods research design, integrating both quantitative and qualitative approaches. The quantitative component was utilized to examine the causal relationships and outcomes among logistics management innovation factors, green reverse logistics management and information technology, in relation to the logistics operational performance of the sports industry. Data was collected from 295 businesses across three sectors: sporting goods retailers and wholesalers, sporting equipment manufacturers, and sports import and export operators. The qualitative component adopted a phenomenological approach, conducted through in-depth interviews, the findings of which were subsequently validated by means of focus group discussions. Participants comprised five individuals, including executive- and operational-level professionals from the sports industry sector as well as academics specializing in sports management. Data analysis was carried out using confirmatory factor analysis and structural equation modelling.

The hypothesis testing results revealed that: 1) logistics management innovation exerts a direct influence on green reverse logistics management within Thailand's sports industry; 2) information technology has a significant effect on green reverse logistics management in Thailand's sports industry; and 3) green reverse logistics management has a significant effect on the logistics operational performance of the sports industry. The analysis indicated that the hypothesized model demonstrated a satisfactory level of fit with the empirical data, meeting all prescribed criteria, as evidenced by the following fit indices: χ² = 13.78, p-value = 0.79, χ²/df = 0.72, GFI = 0.98, AGFI = 0.95, and RMSEA = 0.00.

The contributions of this research lie in its capacity to elucidate the causal relationships among logistics management innovation, green reverse logistics management, and information technology in relation to the logistics operational performance of the sports industry. The findings may be further applied to inform and enhance business management practices within the sports industry.