Integrated outranking techniques based on spherical fuzzy information for the digitalization of transportation system

The digitalization of the traditional technologies have facilitated humans globally as these technologies are not only time saving, modern, environment friendly but are economic as well. This study is concerned with the digitalization of the public transportation system in Istanbul to reduce the environmental pollution that is a big cause of different harmful diseases and climate changes. This article aims to manifest the decision-making aptitude of the elimination and choice translating reality methods working within the boundaries of modern, well structured and highly adaptable model of spherical fuzzy sets keenly focusing on group decision-making by presenting two significant tech-niques. Thus, the proposed methodologies operate by considering the dominance and subordination between alternatives relying on the prime concepts of concordance, discordance and indifferent sets. Further, these sets are exploited to determine the concordance and discordance indices in accordance with the weights of the decision criteria. Finally, the decision is made by observing the outranking relations among alternatives using the threshold values. The proposed strategies seek help from the technique of spherical fuzzy analytical hierarchy process for the evaluation of criteria weights. Noticing the widespread scope and appealing benefits of digital systems, this article targets the digitalization of the public transportation system in Istanbul. The potential of proposed approaches are highlighted via comparative studies. (C) 2023 Elsevier B.V. All rights reserved.

Automated summary

This study focuses on the digitalization of the public transportation system in Istanbul to reduce environmental pollution and address climate change. Two important techniques are proposed for decision-making by considering the dominance and subordination between alternatives. The decision is made based on concordance, discordance and indifferent sets, and the evaluation of criteria weights is conducted using the spherical fuzzy analytical hierarchy process.