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AuthorKeyvanfar A.
AuthorFerwati M.S.
AuthorShafaghat A.
AuthorLamit H.
Available date2019-11-04T05:19:29Z
Publication Date2018
Publication NameSustainability (Switzerland)
ResourceScopus
ISSN2071-1050
URIhttp://dx.doi.org/10.3390/su10041035
URIhttp://hdl.handle.net/10576/12280
AbstractTransportation is the major contributor of ever-increasing CO2 and Greenhouse Gas emissions in cities. The ever-increasing hazardous emissions of transportation and energy consumption have persuaded transportation and urban planners to motivate people to nonmotorized mode of travel, especially walking. Currently, there are several urban walkability assessment models; however, coping with a limited range of walkability assessment variables make these models not fully able to promote inclusive walkable urban neighborhoods. In this regard, this study develops the path walkability assessment (PWA) index model which evaluates and analyzes path walkability in association with the pedestrian's decision-tree-making (DTM). The model converts the pedestrian's DTM qualitative data to quantifiable values. This model involves ninetytwo (92) physical and environmental walkability assessment variables clustered into three layers of DTM (Layer 1: features; Layer 2: Criteria; and Layer 3: Sub-Criteria), and scoped to shopping and retail type of walking. The PWA model as a global decision support tool can be applied in any neighborhood in the world, and this study implements it at Taman Universiti neighborhood in Skudai, Malaysia. The PWA model has established the walkability score index which determines the grading rate of walkability accomplishment for each walkability variable of the under-survey neighborhood. Using the PWA grading index enables urban designers to manage properly the financial resource allocation for inspiring walkability in the targeted neighborhood.
Languageen
PublisherMDPI AG
SubjectDecision making
Green urban development
Pedestrian behavior
Urban assessment
Walkability
TitleA path walkability assessment index model for evaluating and facilitating retail walking using decision-tree-making (DTM) method
TypeArticle
Issue Number4
Volume Number10
dc.accessType Open Access


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