All countries have suffered from the COVID-19 crisis; the pandemic has adversely impacted all sectors. In this study, we examine the transport sector with a specific focus on the problem of commuting mode choice and propose a new decision-making approach for the alternative modes after synthesizing expert opinions. As a methodology, a customized model of the recently developed best–worst method (BWM) is used to evaluate mobility choice alternatives. The survey reflects citizens’ opinions toward mobility choices in two Italian cities, Palermo and Catania, before and during the pandemic. BWM is a useful tool for examining mobility choice in big cities. The adopted model is easy to apply and capable of providing effective solutions for sustainable mode choice. The urban context is analyzed considering the importance of transport choices, evaluating the variation of resilience to the changing opinions of users.

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Sustainable urban transport requires smart and environmentally-friendly technical solutions. It also needs to meet the demands of different user groups, including current and potential future users, in order to avoid opposition of the citizens and to support sustainable development decisions. While these requirements are well-known, conducting full surveys of user needs and preferences are tedious and costly, and the interests of different user groups may be contradictory. We therefore developed a methodology based on the prevalent Analytic Hierarchy Process (AHP), which is capable of dealing with the inconsistencies and uncertainties of users’ responses by applying an Interval Analytic Hierarchy Process (IAHP) through comparing the results of passengers to reference stakeholder groups. For a case study in Mersin, a coastal city in southern Turkey with 1.7 Million inhabitants, three groups were surveyed with questionnaires: 40 users of the public transport system, 40 non-users, and 17 experts. Based on interval pairwise comparison matrices, consisting of whole judgments of all groups, the IAHP methodology could attain a consensual preference ranking for a future public transportation system between the three groups. A sensitivity analysis revealed that the factor ranking was very stable.

Nowadays, it is a really important issue to improve the supply quality of city public bus transportation in many cases. Meanwhile, the different participants of transport systems have different ideas on the ways of improvement, for this reason the taken measures can be inefficient and expensive. The operational costs are steadily increasing (e.g. price of fuel, wages, etc.) therefore the decision makers do not really have the opportunity to lower the price of tickets. For solving the above mentioned problems, before creating a plan of improving a certain public system, a clear image should have been gained on the preferences of passengers, company managers and governmental decision makers. In the current paper a general three-level-hierarchical model has been set up to analyze dynamically the public bus transport system of a city. The price is excluded, only the elements of supply quality are assessed in the hierarchy. Based on the model, questionnaires were created and for the analysis, Analytic Hierarchy Process (AHP) was used to determine preference weights of evaluators from different evaluator groups. Passengers, company managers and governmental officers evaluated exactly the same type of questionnaires so the results are comparable. Avoiding the difficulties of other AHP applications, we used a simplified Saaty-scale for scoring so that the missing data of the matrices could be calculated by an algorithm as well. This study revealed a priority ranking of the elements of supply quality within each level, and this ranking is comparable among the participants of public bus system. This may help the policy makers to synthesize various aspects of public transportation.

Driver behavior has been considered as the most influential factor in reducing fatal road accidents and the resulting injuries. Thus, it is important to focus on the significance of driver behavior criteria to solve road safety issues for a sustainable traffic system. The recent study aims to enumerate the most significant driver behavior factors which have a critical impact on road safety. The well-proven Analytic Hierarchy Process (AHP) has been applied for 20 examined driver behavior factors in a three-level hierarchical structure. Linguistic judgment data have been collected from three nominated evaluator groups in order to detect the difference of responses on perceived road safety issues. The comparison scales had been averaged prior to computing the weights of driver behavior factors. The AHP ranking results have revealed that most of the drivers are most concerned about the “Errors”, followed by the “Lapses” for the first level. The highest influential sub-criteria for the second level is the “Aggressive violations” and for the third level, the “Drive with alcohol use”. Kendall’s rank correlation has also been applied to detect the agreement degree among the evaluator groups for each level in the hierarchical structure. The estimated results indicate that road management authorities should focus on high-rank significant driver behavior criteria to solve road safety issues for sustainable traffic safety.