Stochastic DEA with ordinal data applied to a multi-attribute pricing problem |
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Authors: | Desheng Wu Chi-Guhn Lee |
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Affiliation: | 1. School of Science and Engineering, Reykjavik University, Kringlunni 1, 1S-103 Reykjavik, Iceland;2. Risklab, University of Toronto, 1 Spadina Crescent Toronto, ON, Canada M5S 3G3;3. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, Ontario, Canada M5S 3G8 |
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Abstract: | Multiple attribute pricing problems are highly challenging due to the dynamic and uncertain features in the associated market. In this paper, we address the condominium multiple attribute pricing problem using data envelopment analysis (DEA). In this study, we simultaneously consider stochastic variables, non-discretionary variables, and ordinal data, and present a new type of DEA model. Based on our proposed DEA, an effective performance measurement tool is developed to provide a basis for understanding the condominium pricing problem, to direct and monitor the implementation of pricing strategy, and to provide information regarding the results of pricing efforts for units sold as well as insights for future building design. A case study is executed on a leading Canadian condominium developer. |
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Keywords: | Data envelopment analysis Stochastic DEA Multi-attribute pricing Ordinal data Condominium Non-discretionary |
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