Public Transportation Service Quality Evaluation during the COVID-19 Pandemic in Amman City Using Integrated Approach Fuzzy AHP-Kendall Model

Fuzzy PROMETHEE model for public transport mode choice analysis

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.

A Comparative Analysis of Homogenous Groups’ Preferences by Using AIP and AIJ Group AHP-PROMETHEE Model

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.

The production and distribution of face masks to other countries: a strategic approach of Taiwan during COVID-19 outbreak

Purpose

COVID-19 pandemic has exposed that even the best of the developed nations have surrendered to the devastations imposed on the global supply chains. The purpose of this study is to explore how COVID-19 has exaggerated the supply chain of production and distribution of Taiwan-based face masks and also investigate the conscientious factors and subfactors for it.

Design/methodology/approach

In this study, an analytical hierarchy processes (AHP)-based approach has been used to assign the criterion weights and to prioritize the responsible factors. Initially, based on 26 decision-makers, successful factors were categorized into five main categories, and then main categories and their subcategories factors were prioritized through individual and group decision-maker’s contexts by using the AHP approach.

Findings

The results of this AHP model suggest that “Safety” is the most important and top-ranked factor, followed by production, price, work environment and distribution. The key informers in this study are stakeholders which consist of managers, volunteers, associations and non-governmental organizations. The results showed that good behavior of the employees under the “Safety” category is the top positioned responsible factor for successful production and distribution of face masks to the other countries with the highest global percentage of 15.7% and using sanitizers to protect health is the second most successful factor with the global percentage of 11.7%.

Research limitations/implications

The limitations faced in this study were limited to only Taiwan-based mask manufacturing companies, and it was dependent on the decisions of the limited company’s decision-makers.

Originality/value

The novelty of this study is that the empirical analysis of this study has been based on a successful Taiwan masks manufacturing company and evaluates the responsible factors for the production and distribution of Taiwan masks to other countries during COVID-19.

Understanding the Motivation and Satisfaction of Private Vehicle Users in an Eastern European Country Using Heterogeneity Analysis

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.

Assessment of Urban Mobility via a Pressure-State-Response (PSR) Model with the IVIF-AHP and FCE Methods: A Case Study of Beijing, China

Urban transportation issues continue to emerge and evolve as a result of rapid urbanization, and the systematic and scientific assessment of urban mobility is becoming increasingly essential. In this work, a Pressure-State-Response (PSR) model with 25 indicators was established to reflect the status of urban mobility. Then, the importance of indicators was determined with the interval-valued intuitionistic fuzzy analytic hierarchy process (IVIF-AHP) method, and the fuzzy comprehensive evaluation (FCE) method was applied to assess the overall status of urban mobility. The validity of the proposed model was demonstrated using the mobility system of Beijing as a case study, and the pressure, state, and response scores were calculated. The proposed assessment model can help to improve urban transportation monitoring and can also provide a scientific foundation for future urban transportation policymaking, planning, and traffic management, thereby further ensuring the sustainable development of urban transportation systems.