Prioritization of zero-carbon measures for sustainable urban mobility using integrated double hierarchy decision framework and EDAS approach

Abstract

Zero-carbon is the current buzzword triggering the minds of every people in the world. The current pandemic situation has given the world an alarm to act towards the reduction/eradication of carbon footprint. Developing countries like India are striving hard to strike a balance between sustainability and global growth. To support the nation, certain measures and their prioritization would be helpful. Motivated by this notion, in this study, a new framework is proposed with double hierarchy fuzzy information, which not only gives experts a better style to articulate preferences linguistically but also makes a rational decision with methodical support. Mayor's transport strategy, 2018 is a popular document that provides valuable information towards sustainable transport practices, and the measures considered in this study are adapted from the same. In this framework, (i) a novel attitudinal evidence-based Bayesian approach is proposed for criteria weight estimation; (ii) experts' weights are determined by using variance approach, and (iii) Evaluation based on distance from average solution (EDAS) approach is extended for prioritizing zero-carbon measures. These approaches are integrated into a framework and its practicality is exemplified by considering a case example of prioritizing measures for a smart city in India. Finally, comparison with extant methods reveals the merits and shortcomings of the proposal.

Keywords: Bayesian approach; Double hierarchy information; Evaluation based on distance from average solution (EDAS); Hesitant fuzzy linguistic terms, multi-criteria decision making (MCDM).