LOGISTICS MANAGEMENT STRATEGIES USING ELECTRIC VEHICLES (EVs) IN THAILAND'S MAJOR ECONOMIC CORRIDORS: A STRUCTURAL EQUATION MODELING ANALYSIS
Keywords:
Electric Vehicles, Logistics, Structural Equation ModelingAbstract
This research aimed to develop a structural equation model of the factors influencing the adoption of electric vehicles (EVs) and logistics management strategies using electric vehicles on Thailand’s major economic corridors, and to examine the model’s fit with the empirical data. The sample consisted of 305 executives, managers, and personnel involved in logistics management decision-making among road freight transport operators in Thailand, selected using convenience sampling. The research instrument was a five-point rating-scale questionnaire, with an overall reliability coefficient of .89. The data were analyzed using descriptive statistics and structural equation modeling.
The results revealed that the model demonstrated a good fit with the empirical data (χ²/df=0.96, GFI=0.95, AGFI=0.91, CFI=1.00, RMSEA=0.00, and SRMR=0.03). The cost and efficiency factor had a statistically significant positive effect on the adoption of electric vehicles (DE=0.83, p<.01), whereas the technology factor had a statistically significant negative effect on the adoption of electric vehicles (DE=−0.11, p<.01). The safety and environmental factor had a statistically significant positive effect on logistics management strategies using electric vehicles (DE=0.97, p<.01). In addition, the model explained 79% of the variance in electric vehicle adoption and 87% of the variance in logistics management strategies using electric vehicles.
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