Evaluation and Ranking of Companies in the Transportation and Infrastructure Sector Using Data Envelopment Analysis (DEA)

Abstract

Transportation infrastructure plays a vital role in economic development, necessitating rigorous and reliable methods for evaluating contractor performance. Traditional administrative classification systems may not fully capture differences in the relative operational efficiency of firms. This study employs the output-oriented Andersen–Petersen (AP) super-efficiency model within the Data Envelopment Analysis (DEA) framework to evaluate and rank 30 road and transportation contractors using financial, operational, contract-related, and managerial indicators. To examine the consistency between DEA-based rankings and the established four-tier administrative classification system, Spearman’s rank correlation coefficient is calculated. The results indicate a strong and statistically significant positive correlation between the two ranking systems ( , ), suggesting substantial overall alignment between quantitative efficiency rankings and administrative classifications. Nevertheless, firm-level comparisons reveal notable differences between relative efficiency and administrative status. For instance, company B2 ranks first in DEA-based efficiency despite being assigned to Tier 2 in the administrative classification system. This discrepancy highlights the possibility that administrative classifications may fail to identify certain firms demonstrating comparatively high efficiency under the selected DEA framework. The findings suggest that DEA-based benchmarking could complement existing administrative classification systems by providing additional quantitative evidence for contractor evaluation, selection, and performance monitoring. By integrating relative efficiency assessment with established administrative criteria, the proposed approach offers a systematic basis for improving transparency and evidence-based contractor evaluation in transportation infrastructure projects.