Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/19637
Title: Enhancing sustainability through designing for adaptive reuse from the outset: A comparison of adaptstar and adaptive reuse potential (ARP) models
Authors: Conejos, S
Langston, C
Smith, J
Keywords: Adaptive reuse
AdaptSTAR model
ARP model
Australia
Rating tool
Sustainability
Issue Date: 2015
Publisher: Emerald Group Publishing Limited
Source: Facilities, 2015, v. 33, no. 9-10, p. 531-552 How to cite?
Journal: Facilities 
Abstract: Purpose – This paper aims to make the case for the development of an adaptive reuse rating tool targeted to new building design that maximizes the embedded adaptive reuse potential of these buildings later in their life, thereby adding to built environment sustainability. Design/methodology/approach – This exploratory study retrospectively analyses successful adaptive reuse projects to establish and test a multi-criteria decision-making model for new design projects. This paper contains a report on the final stages of the research methodology (quantitative approach) used in the development of the adapt STAR model that critically assesses the list of design criteria identified in the first stage of the study. Improvements to the case studies that would have further enhanced their reuse potential later in life are proposed. The results are compared to an established decision tool (adaptive reuse potential [ARP] model) to determine their level of consistency. Findings – The findings of this research show that design criteria can be identified and weighted according to seven categories to calculate a building’s adaptive reuse star rating. Both the adapt STAR and ARP models exhibit a strong relationship and are positively correlated. Originality/value – The research demonstrates that by applying adapt STAR to new designs, it will contribute to greater sustainability for the built environment in the long term via reducing the rate of building obsolescence.
URI: http://hdl.handle.net/10397/19637
ISSN: 0263-2772
EISSN: 1758-7131
DOI: 10.1108/F-02-2013-0011
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