Shipment Size Analysis on Cross-Border Freight Transportation Using Stereotype Logistic Regression: Case Study Between West Kalimantan, Indonesia and Sarawak, Malaysia

Abstract

Cross-border freight transport is vital for regional logistics, facilitating trade between neighboring countries. However, inefficiencies in shipment size decisions, such as overloading or underutilizing vehicles, can lead to increased costs and logistical challenges. This study investigates the key factors influencing shipment size decisions in the West Kalimantan (Indonesia)–Sarawak (Malaysia) cross-border corridor. Data from 2,017 truck trips conducted between 2016 and 2018, provided by the Fish Quarantine and Inspection Agency, was used for the analysis. Ordinal logistic regression methods were employed to examine the relationship between shipment size and influencing variables, including company type, commodity value, transport distance, and vehicle type. Shipment sizes were categorized into five groups, ranging from less than 500 kg to more than 7,500 kg. The results indicate that the stereotype logistic regression model better fits the data than the generalized ordered logit model based on log-likelihood, R-squared, and information criteria values. Key findings highlight that firm classification and commodity value significantly impact shipment size decisions, while transport distance and vehicle type have a less pronounced effect. This study emphasizes optimizing shipment size decisions to enhance cross-border transport efficiency and reduce costs. The findings offer valuable insights for policymakers and logistics companies to develop targeted strategies, especially in the context of marine commodity exports. The study improves regional trade competitiveness and promotes sustainable logistics practices by addressing inefficiencies in shipment size decisions.