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Redefining the Impact Assessment of Buildings: An Uncertainty-Based Approach to Rating Codes

Caputo, Silvio, Gaterell, Mark R. (2018) Redefining the Impact Assessment of Buildings: An Uncertainty-Based Approach to Rating Codes. Impact Assessment and Project Appraisal, 36 (4). pp. 348-357. ISSN 1461-5517. (doi:10.1080/14615517.2018.1473138)

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https://doi.org/10.1080/14615517.2018.1473138

Abstract

Discrepancies between predicted and in-use building performance are well documented in impact assessments for buildings, such as rating codes. This is a consequence of uncertainties that undermine predictions, which include procedural errors, as well as users’ behaviour and technological change. Debate on impact assessment for buildings predominantly focuses on operational issues and does not question the deterministic model on which assessments are based as a potential, underlying cause of ineffectiveness. This article builds on a non-deterministic urban planning theory and the principles it outlines, which can help manage uncertain factors over time. A rating code model is proposed that merges its typical steps of assessment (i.e. classification, characterisation and valuation) with those principles, applied within the impact assessment of buildings. These are experimentation (of other criteria than those typically appraised), exploration (the process of identifying the long-term vulnerability of such criteria) and inquiry (iterating and critically evaluating the assessment over time).

Item Type: Article
DOI/Identification number: 10.1080/14615517.2018.1473138
Uncontrolled keywords: Impact assessment of buildings, rating codes, uncertainty, uncertainty-based planning
Subjects: N Visual Arts > NA Architecture
Divisions: Faculties > Humanities > Architecture
Depositing User: Silvio Caputo
Date Deposited: 17 Sep 2019 14:41 UTC
Last Modified: 14 Feb 2020 12:58 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/76569 (The current URI for this page, for reference purposes)
Caputo, Silvio: https://orcid.org/0000-0002-8344-0321
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