A key challenge in port–road logistics is the need to align operational priorities with efficient and sustainable freight transportation decisions. This study develops an Analytic Hierarchy Process (AHP)-based decision-support system for the Multi-Objective Electric Vehicle Routing Problem (MOEVRP) in port–road logistics. Initially, the AHP method is used to determine the relative importance of cost-efficient route planning, vehicle and port management, environmental impact management, energy efficiency, and operational efficiency and well-being based on expert judgment. Next, the resulting priority weights are then used to inform the decision-making framework for the MOEVRP, which determines routing decisions by minimizing total cost, carbon emissions, and maximum vehicle working time while accounting for electric vehicle constraints and charging behavior. This issue is critical in rapidly developing industrial corridors such as Thailand’s Eastern Economic Corridor, where growing freight demand, energy constraints, and environmental pressures must be managed simultaneously. By linking port–road operational priorities with the routing model, the proposed framework provides a structured approach for evaluating trade-offs between economic, environmental, and operational considerations during the transition toward low-carbon freight transportation. A case study in Chonburi–Rayong provinces demonstrates the applicability of the integrated system in a real-world maritime–land logistics corridor. The findings contribute to the design of more sustainable supply chain systems that support renewable and decarbonized logistics.

Background: The management of healthcare supply chains (HSCs) involves complex logistical challenges across storage, transportation, and distribution. Methods: This study proposes a mixed-methods research framework to assess healthcare logistics management and identify improvement priorities in Thailand’s HSC. A structured questionnaire survey is conducted among six stakeholder groups, yielding 358 valid responses. Six healthcare logistics management dimensions, comprising 29 assessment items, are evaluated: personnel, documentation systems, product distribution, storage facilities, inventory management, and complaints and returns. Quantitative data are examined using descriptive statistics and the Borda Count method to assess stakeholder agreement and prioritize logistics management dimensions. Qualitative responses are analyzed through content analysis to identify operational challenges, supplemented by stakeholder suggestions for improvement. Results: The findings indicate high stakeholder agreement regarding the importance of the evaluated dimensions, with transportation, storage and inventory management, personnel, and facilities emerging as key priorities. Qualitative findings highlight challenges involving temperature control, infrastructure constraints, workforce competency, and communication. Conclusions: Integrating these findings, five evidence-informed policy recommendations are developed to address operational procedures, traceability, transportation reliability, storage management, and emergency preparedness. The proposed framework provides a systematic approach to assessing healthcare logistics requirements and supporting policy development and refinement of healthcare logistics management standards.