| Summary: | 碩士 === 國立臺北大學 === 不動產與城鄉環境學系 === 99 === This study develops a decision-making support system for the house-purchasing process, integrating the consumer decision process (CDP) model, simple additive weighting (SAW), and analytic hierarchy process (AHP) to enable decision-makers to evaluate house-purchasing decisions logically. Previous literature used experts to establish the weightings of the evaluation criteria of the AHP method, but this study enables the decision makers to establish the weightings. Considering their housing demands, affordability, and residential quality preference, this paper plans a comprehensive system and integrates with an intelligent agent system in searching for housing items to design a support system that integrates the viewing records of housing items and a decision-making system to enable decision-makers to compare and evaluate items. The web-based system was developed and constructed by integrating the CDP model in the decision-making method to establish an expandable prototype of the system framework.
This study further investigates the suitability of SAW and AHP regarding house-purchasing decisions. The results indicate that SAW is only suitable for use when decision makers are unfamiliar with the evaluation criteria or when they must evaluate numerous criteria; while AHP is suitable for use when decision makers are relatively familiar with the evaluation criteria and when they prefer relatively precise decision results. If the significance of the compared items is weak using the AHP method, the criteria selection method must be modified to improve the precision of the results. This study found that consistency test may become an issue regarding house-purchasing decisions using the AHP method. The six major causes are as follows: (1) decision makers are unfamiliar with the weighting of the evaluation criteria; (2) differences in the description scales; (3) the evaluation criteria the decision maker selected contain extreme conditions; (4) decision makers tend to neglect the relation to other criteria than the two criteria decision makers are comparing; (5) decision makers simultaneously assess two types of housing markets in one evaluation criterion; and (6) the threshold values of consistency test are too high.
The results of the case study reveal that house buyers prefer the evaluation criteria to be centralized, but the subjects to have different weightings. Additionally, they prefer that the inner quality of houses concentrates on the “size of the houses,” “ventilation and lighting,” “configuration and residential comfort,” and “feng shui;” the environmental quality of the community focuses on the “behavior of neighbors,” “size of the community,” “management committee and comprehensive regulations,” “security system and clean community environment,” and “fire-fighting equipment and evacuation routes;” and finally, that the environmental quality in the neighborhood centers on the “convenient access to public transport,” “air quality and noise level,” “public security and neighbor behavior in neighborhood,” “distance from homes to employment/school,” and “the convenience of shopping.”
There are three obstacles for developing a support system for house-purchasing decision. First, the dimension of the system limitations includes “different evaluation criteria for various types of housing markets” and “various evaluation criteria—decision makers must select suitable decision-making methods according to the relations between evaluation criteria.” Second, the expert dimension includes “suggestions for housing loan types,” “suggestions for housing area change,” “change of preferred housing market types,” and “special demands.” Finally, the functional dimension includes “technical difficulty of customizing intelligent agent system,” “fixed and unchangeable bargaining zone,” “difficulty defining the detailed operating indicators of evaluation criteria,” “method for presenting detailed evaluation,” and “lack of complete actual trading information for integration.” Therefore, this paper suggests that these three major obstacle dimensions must be addressed first when developing a decision-making support system in terms of house-purchasing.
|
|---|
