A Hybrid MPSI-Extended AROMAN Decision-making Model for Assessing Green Logistics Performance: The Case of Asia-Pacific Countries

Background: This study examines the green logistics performance of Asia-Pacific countries (Australia, Bangladesh, Cambodia, China, India, Indonesia, Japan, Laos, Malaysia, New Zealand, Papua New Guinea, Philippines, Singapore, South Korea, Sri Lanka, Taiwan, Thailand and Vietnam) using nine criteria: climate change, environmental health, ecosystem vitality, customs, infrastructure, international shipments, logistics competences and quality, timeliness, and tracking and tracing. The criteria were determined based on a literature review. Data were obtained from Logistics Performance Index (LPI) and Environmental Performance Index (EPI) reports. Methods: This study combines the Modified Preference Selection Index (MPSI) and the Extended Alternative Ranking Order Method Accounting for the Two-Step Normalization (AROMAN) model to assess the green logistics performance of Asia-Pacific countries. The criteria weights were calculated using the MPSI method, while countries' green logistics performance was evaluated using the Extended AROMAN method. Results: The MPSI results show that environmental health, climate change, and infrastructure are the most important criteria, while tracking and tracing, international shipments, and timeliness are the least important. The Extended AROMAN results show that Japan, Australia, Singapore, New Zealand, and South Korea have the highest green logistics performance. In contrast, Indonesia, Vietnam, Bangladesh, Cambodia, and Laos have the lowest green logistics performance. Sensitivity and comparative analysis were conducted to assess the robustness of the results. Conclusion: This study presents a decision support system tailored to help the private sector, policymakers, and various stakeholders assess and improve nations' logistics performance, with a strong emphasis on green logistics. This model is a vital tool for analyzing key logistics metrics, promoting sustainable practices, and enabling informed decision-making to advance environmental responsibility and efficiency within logistics operations.