A decision support model to evaluate liveability in the context of urban vibrancy. (September 2022)

• Record Type: Journal Article
• Authors: Kirdar, Gulce; Cagdas, Gulen
• Other Names: Gómez Paula Z guest-editor.; Braida Frederico guest-editor.; Lima Fernando guest-editor.; Loyola Mauricio guest-editor.
• Is Part Of: International journal of architectural computing. Volume 20:Number 3(2022)
• Page Start: 528
• Page End: 552
• Publication Date: 2022-09
• Subjects: liveability -- vibrancy -- knowledge discovery process -- big data -- locative data -- Bayesian belief network; Architecture -- Data processing -- Periodicals; Architecture -- Informatique -- Périodiques; Virtual reality in architecture -- Periodicals; Computer-aided design -- Periodicals; Architecture -- Data processing; Periodicals; 720.2840285536
• DOI: 10.1177/14780771221121500
• Languages: English
• ISSNs: 1478-0771

Abstract

Liveability can be accepted as an umbrella term covering all the factors that make a place to live. We recognize the versatility of urban liveability and focus on the vibrancy aspect. Regarding the literature, we compile variables affecting urban liveability under the economic, image, and use value of place. This article aims to present a data-driven decision support system to evaluate different dimensions of vibrancy-focused liveability. We adopt a knowledge discovery process to handle the complexity of the liveability concept. This study develops a conditional-based relationship network of vibrancy parameters through the Bayesian Belief Network (BBN). Then, we assess the BBN's correlations with statistics and causal relations with the survey in this study.These results mostly agree with the findings of the relevant literature. The economic value results show that the high density, diversity and accessibility add a premium to the land value of properties. The use value results also demonstrate that the diversity and density of activities, cultural attributes, and high accessibility support place attractiveness. The selected streetscape variables improve image value, except for building enclosure and condition. The study has the potential for urban planners to vitalize neighborhoods by considering urban activities and urban physical attributes.