Intercity Road Transportation Assessment: Double-Frontier Q-Cross-Efficiency Method

Abstract

Road transportation is a crucial component of the overall transportation system, providing public services for both passengers and freight. It is imperative for both government entities and transport operators to continuously assess and enhance the performance of road transportation to effectively meet the needs of passengers and freight stakeholders. This research aims to provide road transportation policymakers with a novel and effective hybrid method that incorporates Q-methodology to address the limitations of the conventional Cross-Efficiency (CE) method, particularly by utilizing both correlated and uncorrelated perspectives. The Q-methodology enables policymakers to identify and exclude Decision-Makers' (DMs') viewpoints, including sets of cross-efficiencies with low correlations, during the analysis process. It employs factor analysis to extract consensus perspectives, thereby providing a more realistic assessment of transportation unit efficiency and reducing the likelihood of biased results. The proposed technique incorporates the Q-methodology into the double-frontier CE method, referred to as DFQCE, to enhance its effectiveness by eliminating uncorrelated viewpoints from the efficiency evaluation process. The conventional CE method utilizes both correlated and uncorrelated viewpoints, which may introduce bias into the results. Furthermore, recent critiques have emerged regarding efficiency evaluations that rely solely on the efficient frontier, as these evaluations do not take into account the assessment results of transportation units from a pessimistic viewpoint, which may differ significantly from those based on the efficient frontier. By incorporating both pessimistic and optimistic perspectives, Double-Frontier Q-based Cross Efficiency (DFQCE) aims to produce more comprehensive outcomes compared to the conventional CE method. To validate the developed methodology, the road transportation operations of thirty-one Iranian provinces are evaluated using four input and three output indicators. Loading factors of 0.7 and 0.6 are selected for the optimistic and pessimistic views, respectively, to encompass the broadest range of cross-efficiencies, accounting for 93% and 96%. To enhance the performance of provinces facing subpar conditions, policy, and theoretical implications are suggested. The findings will be of considerable significance to provincial administrators and national policymakers in road transportation, as they provide insights that can facilitate more effective management of the sector by addressing inefficiencies within the provinces.