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Over the last decades, the analysis of mode choice preferences has become a vital aspect of enhancing the quality of public transport services. Most papers aim to derive conclusions from large-scale surveys. However, for specific homogenous patterns, such as university students, a smaller group of evaluators might also be sufficient. Such a survey can rather be considered as an expert survey, in which few representatives might express the preference of a larger community, thus, a different methodology can be more effective than the traditional statistical techniques. This paper aims to introduce a new approach that combines two multi-criteria decision-making methods, the analytic hierarchy process and the preference ranking organization method for enrichment evaluation, for a hybrid consensual model by aggregating the individual priorities defined by each decision-maker. The introduced model presents advantages in terms of reducing time, cost, and effort compared to statistical methods and requires solely necessary information from the users via objective and subjective evaluations. The model's effectiveness is tested with real-world data from the city of Budapest; highlighting the significant impact of the underground mode on users' behavior toward public transport. In addition, the outcomes are compared to other existing results of student preference surveys. [ABSTRACT FROM AUTHOR]

This paper explores a situation regulated by plural normative orders, which every-day public transport users and ticket inspectors experience and practice in the urban realm of the Hungarian capital city, Budapest. The paper analyses everyday interactions between members of the public and public transport staff (typically ticket inspectors) in ways which are not only regulated by formal rules, but which manifest in a non-state regulated normative order. By doing this, the paper theoretically engages with the interplay between multiple normative orders and the urban dynamics in which they operate. The norms which regulate these practices can exist because of how the public transport system operates in Budapest. The paper is based on twenty-five in-depth interviews conducted between February 2017 and March 2019 with long-term Hungarian residents and British migrants living in Budapest. A synthesis of Ehrlich's "living law" theory and Moore's concepts of "semi-autonomous social fields" provide the underlying theoretical framework to examine these informal interactions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

An effective way to optimize decision-making regarding the transport mode choice in the transportation system is improving or changing the travel cost, the travel time, or some other travel characteristics by using sensitivity analysis. This method encourages travelers to switch from private transportation to public transport, thus reducing pollution and emission. Furthermore, by searching for the most sensitive factors in travel behavior, the sensitivity analysis might highlight the directions of the improvement. However, according to previous studies, travelers will transfer from one transport mode to another only if the utility of the new choice is higher than the original transport mode. In the current paper, sensitivity analysis is applied to provide a comparison between the impacts of the physical and sensory parameters on the travel behavior and transport mode choice based on a utility function. The multinomial logit (MNL) model is used to estimate and perform the sensitivity analysis of the main variables. The sensitivity analysis demonstrates the degree of the travelers' sensitivity to changes in the travel characteristics including both physical and sensory parameters. The models are calibrated with the NLOGIT software and validated through statistical indicators; thus, the essential factors influencing the choices are obtained. The input variables selected for the models are based on the data collected in Budapest, Hungary. The sensitivity analysis is determined by the outputs of the variables based on the changes of the input variables. As the results show, the travelers have more sensitivity to the changes in the physical parameters. Furthermore, the outcomes indicate that the travel cost is an essential variable, which greatly affects the decisions related to the transport mode choice. From the sensory parameters, the comfort factor has more influence than other factors. The results of the analysis present that the travelers' sensitivity to changes in the travel utilities of the travel characteristics impacts the decisions regarding the mode choice behavior significantly. [ABSTRACT FROM AUTHOR]

Transport service provision in many urban areas is dominated by car users, resulting in several traffic externality issues (e.g., noise, pollution, accidents). This paper investigates the perception and satisfaction of private vehicle (PV) users, including micro-mobility users, during their commute by car in an Eastern European country context. The study used empirical data from a sample of 500 commuters in Budapest, Hungary, between October and November 2020. To achieve a deeper understanding of the motivation and explore the perception of PV users towards using sustainable transport services. For analysis in this study, descriptive statistics and segmentation techniques were applied. The key findings indicate that PV users can be attracted to using sustainable transport by designing the travel service quality to provide the level of service desired by customers. Moreover, the majority (73%) of PV commuters were satisfied or very satisfied with the quality attributes of the car service, assessed on a scale of 1 to 5; at the same time, PV users agreed that using public transport helps towards improving the environment and serves to reduce problems derived from traffic. In addition, various elements influence transport choice; for example, results from ordered logit models (OLMs) indicate that security, relaxation, flexibility and comfort are the main significant attributes influencing PV users' overall satisfaction with cars. The results suggest the necessity for a segmentation technique in the analysis of travel attitudes and satisfaction aimed at reducing the frequency of existing car use to enhance sustainable transportation. [ABSTRACT FROM AUTHOR]

Public transport service (PTS) analysis and provision is an important and challenging issue for public transport agencies. The results of the PTS analysis help transport planners to identify the areas in need of PTS improvement. Furthermore, relevant policy actions need to be determined for service provision to reach the desired level of PTS improvement in the identified areas. Without an appropriate decision support tool, planners need to apply several blind trials to find a policy action which improves the PTS in the examined areas. This paper introduces a data-driven decision support tool for PTS analysis and provision. The proposed framework combines a potentially large number of PTS measures while taking the correlation among the investigated measures into account and develops high-dimensional supervised classification models that predict the PTS levels for different policy actions. With this approach, planners can identify and prioritize the areas in need of PTS improvement, determine what policy actions should be targeted to improve the PTS in the identified areas, and predict the PTS impacts of these policy actions in the examined areas. The application of the proposed framework is demonstrated in detail through a case study of Budapest, Hungary, which is followed by a hypothetical policy implementation. The results show that mostly outskirts are in need of PTS improvement. Furthermore, the underlying reasons behind the areas with poor overall PTS are studied to target the relevant policy actions that improve the PTS in the identified areas. The PTS impacts of the targeted policy actions are studied by using the developed high-dimensional supervised classification models. • A data-driven decision support tool is proposed. • It combines a potentially large number of public transport service (PTS) measures. • It takes the correlation among PTS measures into account in its evaluation framework. • It identifies and prioritizes areas in need of PTS improvement. • It specifies relevant policy actions and predicts the PTS impacts of them. [ABSTRACT FROM AUTHOR]

This study explores the readiness of eight large Hungarian cities to adopt electric bike sharing systems as a sustainable transportation mode. By assessing 25 indicators related to infrastructure, safety, demographics, legislation, and transportation systems, we comprehensively understand each city's current situation and readiness level. By engaging experts, we derived weighted scores for key indicators to provide a comprehensive analysis of each city's potential. The results reveal varied readiness across cities, offering targeted insights for policymakers to enhance urban mobility sustainably. Our analysis reveals that certain cities, such as Budapest and Gyor, are better prepared for sustainable transportation than others. However, every city has positive and negative aspects that must be considered. Establishing infrastructure for cycling and connectivity to public transportation systems should be prioritized in Hungarian cities. Additionally, safety action plans should be implemented to address road safety concerns. Promoting cycling culture and electric vehicles is also essential to encourage the adoption of sustainable transportation modes. The findings of this research offer valuable insights to policymakers, urban planners, and researchers interested in promoting sustainable mobility. [ABSTRACT FROM AUTHOR]

Transport policymakers need to have an in-depth understanding of public transport (PT) customers in order to effectively manage transport systems and maintain the attractiveness of these systems to potential users. This research aims to compare the perceptions and satisfaction levels of two groups of PT users (habitual and occasional) among university staff and students regarding the quality of PT through a new integrated approach. A sample of 500 participants from Budapest, Hungary was used. Two stages of analysis were conducted: a descriptive analysis was conducted in the first stage, and Student's t-tests of two independent samples were applied to identify the varying perceptions and overall satisfaction. Second, a new integrated ordered probit model (OPM) and an importance–performance analysis (IPA) were used to envisage how best to prioritize actions for transport enhancement. The results show that in the circle of commuters, the habitual PT users were more satisfied with the existing PT service than the occasional PT users. According to the findings of the IPA, for habitual users, the attribute "information provided" has a high priority for improvement, whereas the cost for both user types was found to be significant for all models, contributing to overall satisfaction. This factor was included in the possible overkill quadrant, suggesting that there might be more cost resources than needed. The new model, along with the case study results, may help policymakers and transport operators to make better decisions regarding the identification of service priority areas. [ABSTRACT FROM AUTHOR]

The discovery of human mobility patterns of cities provides invaluable information for decision-makers who are responsible for redesign of community spaces, traffic, and public transportation systems and building more sustainable cities. The present article proposes a possibilistic fuzzy c-medoid clustering algorithm to study human mobility. The proposed medoid-based clustering approach groups the typical mobility patterns within walking distance to the stations of the public transportation system. The departure times of the clustered trips are also taken into account to obtain recommendations for the scheduling of the designed public transportation lines. The effectiveness of the proposed methodology is revealed in an illustrative case study based on the analysis of the GPS data of Taxicabs recorded during nights over a one-year-long period in Budapest. [ABSTRACT FROM AUTHOR]

In this article we use a natural experiment to assess the effects of a public transport disruption on the bicycle sharing system ridership. We exploit maintenance work on a major tram line in Budapest. Fixed effects panel regressions are applied in a difference-in-difference setting. Our results show that bicycle sharing usage significantly increased on weekdays during the disruption, however, this effect is not substantial relative to the baseline usage of the tram service. These findings raise interesting policy questions. [ABSTRACT FROM AUTHOR]