Optimal Selection and Ranking of Port Operation Contractors in a Selected Port Using the Best-Worst Method
Year: 2025
Type: article
Abstract: Selecting competent contractors for port operations is a critical yet complex multi-criteria decision-making challenge, significantly impacting operational efficiency and service quality. Despite its importance, many ports rely primarily on financial bids, overlooking qualitative and technical factors, leading to suboptimal contractor performance. This study develops a comprehensive and systematic evaluation framework based on the Best-Worst Method (BWM) to address these challenges by integrating expert judgments and prioritizing both quantitative and qualitative criteria. The method reduces the number of pairwise comparisons and enhances consistency, providing a transparent and reliable decision-making tool for port authorities. In this study, fourteen initial criteria were identified through extensive literature review and expert consultation, which were then refined to six key criteria for evaluation. The proposed model was implemented using GAMS software to rank three candidate contractors. Results highlight the paramount importance of relevant experience, equipment quality, and financial strength in contractor selection, with the framework successfully distinguishing the most suitable contractor. The findings offer strategic insights for port managers to improve contractor selection, mitigate risks, and enhance operational outcomes. This study fills a significant gap by applying BWM specifically in the context of port contractor evaluation, contributing a novel decision-support tool that can be adapted for broader maritime logistics applications. Future research is encouraged to incorporate emerging technological and sustainability factors and integrate real-time data analytics to further refine the evaluation process.
DOI: 10.63630/aiim.53.1
Authors: Masoud Khakbazan, Alireza Salmeh, Hamidreza Ahadi, Mahoor Rostamkhani, Mina Ahmadi
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4412527278