Road traffic accidents are critical public issue in developing countries, and they annually waste a significant amount of Gross Domestic Product (GDP). In order to urgently consider how this problem is related to the current policies, a proper safety evaluation of regional programmes in crash reduction is fundamental to the governments. The current research aims to employ a double-frontier Data Envelopment Analysis (DEA) model to assess the productivity of Iranian regional safety programmes in reducing the number of road fatalities. The safety efficiencies of Iranian provinces are simultaneously estimated using the double frontier DEA to reflect both the optimistic and pessimistic points of view. Then, the Evidential Reasoning (ER) approach is applied to aggregate the obtained efficiency values. These provinces are ranked based on the data panel for 2014–2016. Finally, a double-frontier Malmquist productivity index (MPI) is used to comprehensively measure the safety performance of Iranian roads over a period of time.

Many governments in the developing world face the social and economic consequences of road accidents and mortalities. Hence, more precise evaluation of regional programs to reduce road fatalities has been a concern for many safety professionals. Road safety performance is often measured using various extensions of Data Envelopment Analysis (DEA), in particular the model proposed by Charnes, Cooper and Rhodes (CCR), which deals only with the radial efficiency as the objective function neither taking into account input excesses nor output shortfalls. The Slacks-Based Measure (SBM) of efficiency overcomes this shortcoming by taking both measurements mentioned above simultaneously. In this regard, the current study aims to employ the SBM in analyzing road safety performance. It is noteworthy that the efficiency of each Decision Making Unit (DMU) can be pessimistically measured using the slacks-based measure of inefficiency such that the anti-efficient DMUs provide the anti-efficient frontier. The results obtained from the optimistic and pessimistic frontiers are nonlinearly aggregated by means of the Evidential Reasoning (ER) algorithm. Furthermore, a Double-Frontier SBM-based Malmquist Productivity Index (DF-SBM- MPI) is provided to analyze the efficiency and technological changes in safety performance from 2014 to 2016. For this purpose, the standard SBM and Super-SBM models are used to compute the optimistic Malmquist Productivity Index (MPI); similarly, the pessimistic MPI is determined by means of the inverted SBM and Super-SBM models. Finally, the obtained MPIs from the two different points of view are geometrically combined to obtain the overall MPI.

Vehicle related safety is the principal focus of many agencies and organizations targeting road safety issues. There are many conflicting factors contributing to safety in motor vehicle operations. Unfortunately, the lack of reliable crash data makes it extremely difficult to evaluate the crash causations associated with defective vehicles. Furthermore, clarifying the interrelationships among vehicle related factors causing accidents is very complicated when the conventional decision techniques are used. This study aims to employ a hybrid decision method based on DEMATEL (decision-making trial and evaluation laboratory) and ANP (Analytic Network Process) to construct an Influence Relations Map (IRM) as well as obtain the influential weight of vehicle-related criteria. An empirical case study is provided to demonstrate the implementation process. This paper also employs an Evidential Reasoning algorithm (so-called ER) for assessing the inter-city buses in terms of vehicle safety in order to deal with the uncertainties associated with incomplete input data. The ER improves decision making process by using a belief decision matrix and the Demspster-Shafer theory of evidence. The results and findings reveal that the braking system is the most important criterion impacting vehicle safety, followed by fuel supply and electrical systems.