Big cities suffer from serious complex problems such as air pollution, congestion, and traffic accidents. Developing public transport quality in such cities is considered an efficient remedy to obviate these critical issues. This paper aims to determine the significant supply quality criteria of public transportation. As a methodology, a hybrid Analytic Hierarchy Process (AHP) combined with the Best Worst Method (BWM) is applied. The proposed model is basically a hierarchy structure with at least a 5 × 5 pairwise comparison matrix or larger. A real-world complex problem was examined to validate the created model (public transport quality improvement). An urban bus transport system in the Jordanian capital city, Amman, was used as a case study; three stakeholder groups (passengers, nonpassengers, and representatives of the local government) participated in the evaluation process. The conventional Analytic Hierarchy Process (AHP) leads to weak consistency in the case of existing 5 × 5 pairwise comparison matrices or larger, particularly in estimating complex problems. To avoid this critical issue in AHP, we used Best Worst Method (BWM) comparisons, which make the evaluation process easier for decision makers; moreover, it saves survey time and provides more consistency when compared to AHP pairwise comparisons. The model adopted highlighted the most significant service quality criteria that influence urban bus transport systems. Furthermore, the sensitivity analysis conducted detected the stability of the criteria ranking in the three levels of the hierarchical structure. Since the proposed AHP–BWM model (which is the sole example of this sort of combination) is independent from the decision attributes, it can be applied to arbitrary hierarchically structured decision problems with a relatively large number of pairwise comparisons.

Public transportation (PT) service quality is recognized as a cornerstone of infrastructure development in many countries. Understanding the satisfaction level of public transport users towards provided service quality is vital. However, there is still a lack of research to identify the specific relationship between the experience of service quality and private vehicle (PV) users’ satisfaction. Therefore, this paper aimed to examine the different satisfaction attributes of PV users due to the COVID-19 pandemic and to make possible suggestions to policymakers on how to adapt to these changed attitudes. The paper highlights that some satisfaction issues became more significant, while the importance of others was mitigated due to the unusual circumstances. In this study, variance-based Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to test the proposed hypotheses. Further, Partial Least Squares Multi-Group Analysis (PLS-MGA) was conducted for investigating the perception of age and gender groups on the basis of gap analysis. An online panel and printed questionnaire survey were used to collect data in Budapest, Hungary in October and November 2020 during COVID-19 from the perception of 100 PV users. The findings show that perceived service quality and accessibility are statistically significant in the formation of PV users’ satisfaction but safety and security were not significantly related to satisfaction. Additionally, results from PLS-MGA reveal that there was a significant difference among gender and age groups in achieving satisfaction associated with safety and security. The conclusions of this study are not only beneficial for the theory of this field but also contribute to practice for policymakers in terms of providing better service with specific identification of how to encourage more private vehicle users to use public transportation.

The current paper focuses on a comparative analysis of both public transport (PT) and private vehicle (PV) users’ perceptions on the quality of the service. To detect the key components of PT attributes a new hybrid methodology is applied, combining the importance-performance analysis and the importance-performance map analysis. The proposed hybrid approach is simpler and more integrated than the existing methods in the literature. The sample comprises an online panel and a total of 1028 questionnaires for PV and PT users surveyed during the pandemic period in Budapest. The results of the applied methods show that among the different groups, the service hour, the proximity, and the frequency attributes are important and performed well in the years of COVID-19. On the other hand, the temperature and the cleanliness factors are not significant predictors of the PV and PT users’ general satisfaction. The obtained results can be used by local governments and authorities, who seek to identify areas to enhance the service quality of PT during movement restrictions in a pandemic wave.

Road accidents becomes global health and safety issues because of the gradual increase in the number of injuries and fatalities. In the UK, road accidents due to weather conditions has been one of the traffic safety challenges for researchers as well as drivers particularly in Greater Manchester. This is because of its influence on driver behaviour approaching traffic lights on the road bends. Hence, to better understand driver behaviour, this paper presents various driving behaviour on wet and dry road conditions. Data were obtained from police reports of road accidents at hazardous locations in Greater Manchester between 2011 and 2015. The reported data covers information regarding: Accidents, Vehicle, and Casualties. The obtained data was used to examine how road surface is associated with road accidents by using Chi-Square statistical test. The analysis showed that road surface significantly contributed to accidents at bend roads. Moreover, drivers’ behaviour was investigated as they can be expected to have a significant impact on accident occurrence. Finally, the main goal is that these results might reflect the safety issue at bend roads.

Finding methods to develop transportation planning and accordingly attract more people to use sustainable transportation is one of the most important subjects for transportation planners and decision-makers in current studies. The Structural Equation Model (SEM) is a statistical approach to examining the relationship between observed variables and latent variables. SEM is not only a single process, but also a cluster of related statistical techniques. The potential of SEM techniques lies in the essence of several issues in transportation planning and in using it as a guide for authorities. The main aim of this study is to present a systematic review of the application of the SEM methods in the assessment of transportation planning in the past decades, consequently, encouraging researchers to further investigate.After conducting a review of 47 articles published in high-quality journals, from 2011–2020, the recorded articles are clustered into three main groups; perception, satisfaction and loyalty, and behavior related to mode choice. Further, these three groups are classified according to numerous key perspectives, containing published year, type of transportation mode, sample size, software and method.The result of this review article shows that since 2018 the usage of SEM approaches has significantly increased for the evaluation of public transportation service quality. Furthermore, recall findings in this article are recommended for researchers such as the improvement of the application and practice of SEM utilize methods in terms of transportation planning research to avoid imprecisions in a future study, particularly addressing the problems related to public transportation.