The attractiveness and vibrancy of an urban area are very complex aspects that both Public Administrations and real estate developers and construction companies have to carefully consider in order to correctly address their investments and sustainable urban development projects. 'e aim of this paper is to study urban vibrancy and its relationship with the neighbourhood services and the real estate market of new housing stock. Spatial analyses are performed to study the influence of the Neighbourhood Services Index (NeSI) and its Principal Components (PCs) on listing prices and the construction activity. Spatial autoregressive (SAR) models are applied both with lattice data and data points, in order to manage spatial dependence and to identify the variables that significantly influence housing prices and construction site density. Findings highlight that the NeSI significantly influences the real estate market of new housing stock and that above the analyzed neighborhood services and the retail activities have a great, significant, and positive influence on the density of housing construction sites. 'e results of this study represent a real support for both public and private bodies to identify the most and least attractive and vibrant urban areas and to deal with important aspects of urban complexity.

Is the Real Estate Market of New Housing Stock Influenced by Urban Vibrancy? / Barreca, Alice; Curto, Rocco; Rolando, Diana. - In: COMPLEXITY. - ISSN 1099-0526. - ELETTRONICO. - 2020:(2020), pp. 1-22. [10.1155/2020/1908698]

Is the Real Estate Market of New Housing Stock Influenced by Urban Vibrancy?

Barreca, Alice;Curto, Rocco;Rolando, Diana
2020

Abstract

The attractiveness and vibrancy of an urban area are very complex aspects that both Public Administrations and real estate developers and construction companies have to carefully consider in order to correctly address their investments and sustainable urban development projects. 'e aim of this paper is to study urban vibrancy and its relationship with the neighbourhood services and the real estate market of new housing stock. Spatial analyses are performed to study the influence of the Neighbourhood Services Index (NeSI) and its Principal Components (PCs) on listing prices and the construction activity. Spatial autoregressive (SAR) models are applied both with lattice data and data points, in order to manage spatial dependence and to identify the variables that significantly influence housing prices and construction site density. Findings highlight that the NeSI significantly influences the real estate market of new housing stock and that above the analyzed neighborhood services and the retail activities have a great, significant, and positive influence on the density of housing construction sites. 'e results of this study represent a real support for both public and private bodies to identify the most and least attractive and vibrant urban areas and to deal with important aspects of urban complexity.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2850359