| Summary: | 碩士 === 國立中央大學 === 營建管理研究所 === 102 === Customer preference affects selection and transaction price for real estate. Appraisers by their own experience usually select housing attributes and their corresponding weights for customers, creating possible impropriate assessment for those with different favorites. The research objective is to determine attributes and the corresponding weights that affect house pricing based on customer preference. Literature review and expertise qualified 39 attributes, followed by the house transactions collected from the Taiwan transaction database of real estate. A total of 5000 sets in the most prosperous urban area of Taiwan in recent 3 years are randomly selected. Each set contains 39 GIS calibrated environmental attributes suggested by citations and expertise. The swarm-inspired projection (SIP) algorithm is employed for clustering, yielding 5 clusters for a close-up analysis. The findings form the analysis can be summarized as: 1. each cluster presents a significant preference. There are 5 major customer preferences of leisure, education, transportation, medical care, and shopping convenience. 2. The weight of any attribute is mostly different from that in the other clusters. 3. The common hostile attribute among 5 clusters is police station and has significantly negative impact to housing price. 4. Sale time has positively impact to sale price. The longer sale time is the higher sale price presents.
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