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© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Adaptive reuse is a rapidly expanding frontier study area across the world. Adaptive reuse can have a significant influence in relation to contemporary trends in (peri-)urban sustainability, especially considering the past decades of the human-caused depletion of natural resources and environmental pollution. Adaptive reuse developments, which manage to incorporate a (scientifically) predefined set of conceptual theories, policy principles, and practical tools, as all the available data suggest, can achieve a good balance between invested capital, ecological conservation, the preservation of the cultural heritage, and sustainable urban regenerative renewal. This study focused on the recent FIX Brewery adaptive reuse project in Athens, Greece, as a means to establish the key public perception determinants of the adaptive reuse practice impacts on (peri-)urban sustainable development. Evidence for the relationships among five factors was provided through multiple linear regression analysis. The new empirical findings are likely to encourage concerned parties and stakeholders, and particularly regulatory entities, to pursue essential actions to set adaptive reuse at the core of urban and spatial masterplans, paving the way toward sustainable and circular cities.

Details

Title
Adaptive Reuse for Sustainable Development and Land Use: A Multivariate Linear Regression Analysis Estimating Key Determinants of Public Perceptions
Author
Vardopoulos, Ioannis  VIAFID ORCID Logo 
First page
809
Publication year
2023
Publication date
2023
Publisher
MDPI AG
ISSN
25719408
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2779511827
Copyright
© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.