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

Abstract

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.

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