Manaswinee Kar , Shubhajit Sadhukhan , Manoranjan Parida
{"title":"User satisfaction-based prioritisation of attributes influencing walk accessibility to metro stations: A multi-attribute decision making approach","authors":"Manaswinee Kar , Shubhajit Sadhukhan , Manoranjan Parida","doi":"10.1016/j.cstp.2024.101255","DOIUrl":null,"url":null,"abstract":"<div><p>The current study suggests a user satisfaction-based approach to prioritise attributes influencing walk accessibility to metro stations in Delhi, India. The target user group of the present study includes metro users who access the metro stations by walking. Responses from 466 such users are collected using smart tablets through face-to-face interviews. User satisfaction ratings towards twelve walk accessibility influencing attributes identified in the study are recorded on a six-point Likert-type ordinal rating scale. The study engages a comparative Multi-Attribute Decision Making (MADM) approach comprising three prominent techniques, viz., Relative to an Identified Distribution Integral Transformation (RIDIT), Grey Relational Analysis (GRA) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for analysing the collected perception database and prioritising the attributes based on user satisfaction. The study outcomes identify ‘Extreme Weather Conditions’, ‘Illumination’, ‘Universal Design Considerations’ and ‘Safety and Security’ as the poorly performing attributes based on user perception and require immediate interventions. Spearman’s rank-order correlation analysis is performed to compare the attribute priority ranks derived from the three methods. The research findings can be useful to transportation planners, policymakers and enforcement officials in formulating and implementing strategies to allocate funds based on user-identified priorities for improving walk accessibility to metro stations.</p></div>","PeriodicalId":46989,"journal":{"name":"Case Studies on Transport Policy","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies on Transport Policy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213624X2400110X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
The current study suggests a user satisfaction-based approach to prioritise attributes influencing walk accessibility to metro stations in Delhi, India. The target user group of the present study includes metro users who access the metro stations by walking. Responses from 466 such users are collected using smart tablets through face-to-face interviews. User satisfaction ratings towards twelve walk accessibility influencing attributes identified in the study are recorded on a six-point Likert-type ordinal rating scale. The study engages a comparative Multi-Attribute Decision Making (MADM) approach comprising three prominent techniques, viz., Relative to an Identified Distribution Integral Transformation (RIDIT), Grey Relational Analysis (GRA) and Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for analysing the collected perception database and prioritising the attributes based on user satisfaction. The study outcomes identify ‘Extreme Weather Conditions’, ‘Illumination’, ‘Universal Design Considerations’ and ‘Safety and Security’ as the poorly performing attributes based on user perception and require immediate interventions. Spearman’s rank-order correlation analysis is performed to compare the attribute priority ranks derived from the three methods. The research findings can be useful to transportation planners, policymakers and enforcement officials in formulating and implementing strategies to allocate funds based on user-identified priorities for improving walk accessibility to metro stations.