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id ddss9214
authors Friedman, A.
year 1993
title A decision-making process for choice of a flexible internal partition option in multi-unit housing using decision theory techniques
source Timmermans, Harry (Ed.), Design and Decision Support Systems in Architecture (Proceedings of a conference held in Mierlo, the Netherlands in July 1992), ISBN 0-7923-2444-7
summary Recent demographic changes have increased the heterogeneity of user groups in the North American housing market. Smaller households (e.g. elderly, single parent) have non-traditional spatial requirements that cannot be accommodated within the conventional house layout. This has created renewed interest in Demountable/Flexible internal partition systems. However, the process by which designers decide which project or user groups are most suited for the use of these systems is quite often complex, non-linear, uncertain and dynamic, since the decisions involve natural processes and human values that are apparently random. The anonymity of users when mass housing projects are conceptualized, and the uncertainty as to the alternative to be selected by the user, given his/her constantly changing needs, are some contributing factors to this effect. Decision Theory techniques, not commonly used by architects, can facilitate the decision-making process through a systematic evaluation of alternatives by means of quantitative methods in order to reduce uncertainty in probabilistic events or in cases when data is insufficient. The author used Decision Theory in the selection of flexible partition systems. The study involved a multi-unit, privately initiated housing project in Montreal, Canada, where real site conditions and costs were used. In this paper, the author outlines the fundamentals of Decision Theory and demonstrates the use of Expected Monetary Value and Weighted Objective Analysis methods and their outcomes in the design of a Montreal housing project. The study showed that Decision Theory can be used as an effective tool in housing design once the designer knows how to collect basic data.
series DDSS
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