Industrial areas are characterized by high trip generation and attraction due to the daily routine mobility of workers. This condition requires an efficient transportation system and an understanding of mode choice behavior. This study aims to understand workers’ travel characteristics, identify the factors influencing mode choice decisions, and estimate the probability of choosing motorcycles, online transportation, and employee shuttle services through the application of the Multinomial Logit (MNL) model. The research data were obtained by distributing questionnaires to 100 workers in the Pabedilan Industrial Area, Cirebon Regency, using a revealed preference approach. The analyzed variables included travel cost, distance, and travel time. The analysis was conducted using SPSS software, with model testing through multicollinearity tests, likelihood ratio tests, parameter estimation, pseudo R-square, and goodness-of-fit tests. The analysis findings show that travel cost and distance have a significant influence on mode choice, while travel time does not have a significant effect. Motorcycles have the highest choice probability at 84.2 percent, followed by employee shuttle services at 15.8 percent, while online transportation has a very small or nearly zero probability, at 0.0 percent. Practically, the results of this study can serve as a basis for policymakers to increase the attractiveness of employee shuttle services through cost efficiency and route adjustments that better align with workers’ travel patterns.
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