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.

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.

The demand for a service includes generally two major components; quality elements and the reasonable and affordable price. Public transport can be considered as a special service, there is no direct market competition for the provider, but the use of private transport modes substitutes the usage of public vehicles. The dominating competitor, the usage of private cars, causes higher CO2 emission and has a serious impact on the environment. Thus, it is important to analyze from market and sustainability point of view which are the preferences of the public for the improvement of the urban transport system. This paper aims to conduct this analysis by including quality criteria and transport fare criteria related to the current service of a city and by setting up and testing a generally applicable model for decision support. Since the acquisition of public preference was the primary objective, and the problem can be considered as decision making, the Analytic Hierarchy Process was selected as methodology. There are previous research results of applying this method on public transport, however, not in an integrated model, in which quality and cost considerations are pairwise compared. Thus, the conventional Analytic Hierarchy Process (AHP) technique was used and the well-proven requisites of consistency and sensitivity check were analyzed. The new model was tested in a case study: surveying the public transport demand in the capital of Jordan, Amman.

The COVID-19 pandemic has affected public transportation worldwide, and its implications need to be evaluated and study deeply on all public transportation aspects. Therefore, an analysis has been created to examine the effects of the pandemic on public transportation service quality decisions to have a better vision of the different stakeholders’ needs to keep the system functioning in a profitable way. Stakeholder participation in complex, multi-criteria decision-making often produces very different results in prioritizing the decision attributes. Rank correlation techniques generally measure the degree of agreement or non-agreement among the evaluator groups. However, the multi-criteria methodology can determine not only ordinal but also cardinal priorities. Consequently, except for the attributes’ positions, the weight values are also significant in the final decision. This paper aims to apply a more sophisticated measure of group agreement than rank correlation. First, the Fuzzy-hierarchical analytical process (FAHP) has been used to find out the aggregated weights, then the Kendall correlation values are computed to reveal stakeholder opinions. Finally, the agreement measure approach has been tested in a real-world case study: the public transport development decision of Amman, Jordan. The analysis shows that by applying the Kendall technique, Kendall could gain a more profound insight into the priority characteristics of different evaluator groups.

In the case of conflicting individuals or evaluator groups, finding the common preferences of the participants is a challenging task. This statement also refers to Intuitionistic Fuzzy Analytic Hierarchy Process models, in which uncertainty of the scoring of individuals is well-handled, however, the aggregation of the modified scores is generally conducted by the conventional way of multi-criteria decision-making. This paper offers two options for this aggregation: the relatively well-known entropy-based, and the lately emerged distance-based aggregations. The manuscript can be considered as a pioneer work by analyzing the nature of distance-based aggregation under a fuzzy environment. In the proposed model, three clearly separable conflicting groups are examined, and the objective is to find their common priority vector, which can be satisfactory to all participant clusters. We have tested the model results on a real-world case study, on a public transport development decision-making problem by conducting a large-scale survey involving three different stakeholder groups of transportation. The comparison of the different approaches has shown that both entropy-based and distance-based techniques can provide a feasible solution based on their high similarity in the final ordinal and cardinal outcomes.

Travel demand plays an essential role in strategic transport planning. Generally, experts use either discrete methods, e.g. discrete choice models or simulation, e.g. activity-based models to estimate demand in transportation. This paper offers a different solution; instead of using the traditional approach, the demand is considered as a Multi Criteria Decision Making (MCDM) problem and surveying the citizens’ preferences provides the results for decision support. Public transport demand depends on two main issues, quality and price of the transportation. In a hierarchical model, both issues have been integrated and the well-proven Analytic Hierarchical Process (AHP) method has been applied in the current research. Further, fuzzyfication of the scores have also been conducted because of the citizen evaluator pattern. The fuzzy-AHP (FAHP) model has been tested in a real-world situation with the case study of Amman (Jordan).

Transportation improvements affect technological and socio-economic development, and several scholars have researched various transportation problems. The current study aims to illustrate a thorough review of those transport problems, where the Analytic Hierarchic Process (AHP) is used for enumerating the related criteria and alternatives. A systematic review methodology, the PRISMA protocol, is applied in the review process. The contribution of this work is highlighted along with the extensions of the AHP improving decision-making support. To this end, current research demonstrates the relevant results of 58 papers published from 2003 to 2019. The results indicated that most researchers applied the conventional AHP method to deal with transportation issues, while the most critical issue was public transport, followed by logistics problems. On top of that, TOPSIS was integrated with AHP more than other MCDM methods when dealing with multi-criteria transportation problems. Moreover, the "Transportation Research Part A: Policy and Practice" journal achieved first place by publishing ten papers on the topic, and the highest number of articles was published in 2018. The results are discussed adequately, and in the conclusion policy implications are presented.