Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/108477
| Title: | Adoption of energy consumption in urban mobility considering digital carbon footprint : a two-phase interval-valued Fermatean fuzzy dominance methodology | Authors: | Jeevaraj, S Gokasar, I Deveci, M Delen, D Zaidan, BB Wen, X Shang, WL Kou, G |
Issue Date: | Nov-2023 | Source: | Engineering applications of artificial intelligence, Nov. 2023, v. 126, 106836 | Abstract: | Interval-valued Fermatean fuzzy sets play a significant role in modelling decision-making problems with incomplete information more accurately than intuitionistic fuzzy sets. Various decision-making methods have been introduced for the different classes IFSs. In this study, we aim to introduce a novel two-phase interval-valued Fermatean fuzzy dominance method which suits the decision-making problems modelled under the IVFFS environment well and study its applications in the adoption of energy consumption in Urban mobility considering digital carbon footprint. The proposed method considers the importance and performance of one alternative with respect to all others, which is not the case with many available decision-making algorithms introduced in the literature. Transportation is one of the most significant sources of global greenhouse gas (GHG) emissions. Numerous potential remedies are proposed to reduce the quantity of GHG generated by transportation activities, including regulatory measures and public transit digitalization initiatives. Decision-makers, however, should consider the digital carbon footprint of such projects. This study proposes three alternatives for reducing GHG emissions from transportation activities: incremental adoption of digital technologies to reduce energy consumption and greenhouse gases, disruptive digitalization technologies in urban mobility, and redesign of urban mobility using regulatory approaches and economic instruments. The proposed novel two-phase interval-valued Fermatean fuzzy dominance method will be utilized to rank these alternative projects in order of advantage. First, the problem is converted into a multi-criterion group decision-making problem. Then a novel two-phase interval-valued Fermatean fuzzy dominance method is designed and developed to rank the alternatives. The importance and advantage of the proposed two-phase method over other existing methods are discussed by using sensitivity and comparative analysis. The results indicate that rethinking urban mobility through governmental policies and economic tools is the least advantageous choice, while incremental adoption of digital technologies is the most advantageous. | Keywords: | Decision support systems Dominance method GHGs Interval-valued fermatean fuzzy sets Multi-criteria decision-making Urban mobility |
Publisher: | Elsevier Ltd | Journal: | Engineering applications of artificial intelligence | ISSN: | 0952-1976 | EISSN: | 1873-6769 | DOI: | 10.1016/j.engappai.2023.106836 | Rights: | © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). The following publication S, J., Gokasar, I., Deveci, M., Delen, D., Zaidan, B. B., Wen, X., Shang, W.-L., & Kou, G. (2023). Adoption of energy consumption in urban mobility considering digital carbon footprint: A two-phase interval-valued Fermatean fuzzy dominance methodology. Engineering Applications of Artificial Intelligence, 126, 106836 is available at https://doi.org/10.1016/j.engappai.2023.106836. |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 1-s2.0-S0952197623010205-main.pdf | 778.43 kB | Adobe PDF | View/Open |
Page views
102
Citations as of Nov 10, 2025
Downloads
15
Citations as of Nov 10, 2025
SCOPUSTM
Citations
22
Citations as of Dec 19, 2025
WEB OF SCIENCETM
Citations
22
Citations as of Dec 18, 2025
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



