A multi-attribute group decision-making method for optimal selection of digital voting tools to ameliorate public participation in urban transport

A multi-attribute group decision-making method for optimal selection of digital voting tools to ameliorate public participation in urban transport

In urban transport decision-making, enhancing public participation is crucial for creating more inclusive and effective policies. The selection of digital voting tools is vital in facilitating this participation. This study aims to develop a decision-making model for evaluating and selecting digital...

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Bibliographic Details
Main Authors: Amir Hussain, Kifayat Ullah, Tapan Senapati, Domokos Esztergár-Kiss, Sarbast Moslem
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
Subjects:
Urban transport
Public participation
Rough set
Picture fuzzy set
Group decision-making
Online Access:http://www.sciencedirect.com/science/article/pii/S2590123024021108
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Summary:In urban transport decision-making, enhancing public participation is crucial for creating more inclusive and effective policies. The selection of digital voting tools is vital in facilitating this participation. This study aims to develop a decision-making model for evaluating and selecting digital voting tools based on uncertain factors. A multi-attribute group decision-making (MAGDM) approach is introduced for the evaluation and assessment of various digital voting tools, considering multiple aspects according to the needs of the policies and the stakeholders. A well-known framework called picture fuzzy rough est (PFRS) models the expert's opinion concerning the tools considered. This study proposes the MAGDM model integrating the Schweizer-Sklar t-norm (SSTNrM) and the Schweizer-Sklar t-conorm (SSTCNrM), i.e., picture fuzzy rough weighted averaging (PFRSSWA) and picture fuzzy rough weighted geometric (PFRSSWG), are introduced to aggregate the data in the form of the picture fuzzy rough values (PFRVs). The created AOs select the most appropriate digital voting tool based on the characteristics provided in a given list. The ranking of the tools is observed by altering the values of the involved parameters in SSTNrM and SSTCNrM. The findings obtained also contrast with those of other known AOs. Additionally, a graphic representation of each observation and result is provided.
ISSN:2590-1230

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