Improving the local urban transport system’s quality is often seen as one of the critical points for the government and the local operator. An amelioration of the system can improve users’ satisfaction and attract new users while simultaneously decreasing traffic congestion and pollution. Efficient methodologies are required to achieve sustainable development regarding complex issues associated with traffic congestion and pollution. In this study, we propose using the analytic hierarchy process (AHP) grey values to overcome the limitations of the uncertainty in the classical AHP approach. The presented grey-AHP model assumes an efficient contrivance to facilitate the public transport system’s supply quality evaluation, especially when respondents are non-experts. Finally, we estimate and rank the public transport system’s supply quality criteria by adopting the proposed model for a real-world case study (Amman city, Jordan). The study’s outcome shows the effectiveness and the applicability of the developed approach for enhancing the quality of the public transport system.

In recent decades, decision support system has been constantly growing in the field of transportation planning. PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation) method is an efficient decision-making support deployed in case of a finite number of criteria. It provides a partial ranking through PROMETHEE I and a complete ranking with PROMETHEE II. This outranking methodology is characterized by the elimination of scale effects between criteria and managing incomparability with the comprehensive ranking. However, PROMETHEE does not provide guidance to assign weights to criteria and assumes that decision makers are able to allocate weights. This review presents an overview of PROMETHEE models applied in transportation and points out the found gaps in literature.

The importance of public transportation service quality research is significantly increasing in recent years, it is the key to understanding and analyzing passengers’ preferences. Different approaches are utilized to explore users’ preferences however, dominantly these apply merely subjective scoring of the attributes and alternatives of the mobility. In this paper, we design a specific model for public transportation mode choice which is capable of integrating subjective scoring with scoring by objective measures such as distance or time. Owing to this purpose, we combine the outranking Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) as a method to evaluate passengers’ preferences for tangible and intangible criteria with the fuzzy theory, and the Graphical Analysis for Interactive Aid (GAIA) plane to visualize the interactions between attributes as well as to test the robustness of the results via sensitivity analysis. The contribution of this paper is the constructed integrative method that is less subjective than the well-known models but also keeps the freedom of individual evaluators in expressing their preferences. Moreover, another significant issue of mode choice analysis is the group consideration, which is also refined in the new methodology by taking into account not only the mean of group preferences but also their range. A common characteristic of public surveys, the possible vague responses of the layman pattern is solved with the fuzzy approach to reduce the risk of uncertain scoring. The proposed model acts as a great base for the fuzzy inference system that can facilitate mode choice for passengers within a changing environment. The efficiency of the new methodology is demonstrated through a real-world case study of Budapest city, the obtained results are supporting underground mode service quality and highlighting its impact on citizens’ behavior in favor of public transport.

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.

Preference surveys often strive to reveal the perceptions of respondents with different demographic and habitual characteristics to reflect the features of a local community or city. However, the target group can be considered a priori homogenous in some cases, which requires an adjusted survey methodology. Apart from the smaller sample size, the aggregation technique of the individual preferences into a global common priority is also different in these types of problems according to the decision science principles. Interestingly, this feature is often ignored in group multi-criteria decision-making problems, especially in PROMETHEE model applications. This paper aims to apply the Aggregation of Individual Judgement technique in PROMETEHEE AIJ-PROMETHEE via the introduction of a hybrid Group AIJ-AHP-PROMETHEE model, specifically designed for homogenous group preference problems, to be compared with the conventional Aggregation of Individual Priorities (AIP). The new AIJ-AHP-PROMETHEE model, which is more suitable for homogenous groups, is less costly and less time-consuming than the general aggregations. The effectiveness of this new model is emphasized with real data, surveying university students’ perceptions of different transport modes in the city of Budapest. Results show considerable findings of the introduced model and its general applicability to the evaluation of the public transport service quality system.