結合模糊層級分析法與類似度理想解順序偏好法於中古車選購排序之模式

Ranking Model for Used Car Selection Employing a Fuzzy Analytic Hierarchy Process and the Technique for Order Preference by Similarity to Ideal Solution

國內中古車的交易量約為新車的 2 倍以上，因此新車品牌車廠及汽車集團相繼投入中古車市場。選購中古車時，排氣量、使用年數、價格、廠牌和油耗等為購買者的主要評估準則，本文以兼顧主觀、模糊不確定的模糊層級分析法（FAHP），計算評估準則之相對權重值；針對購買中古車之屬性值，以類似度求理想解之順序偏好法（TOPSIS），結合評估準則之權重值後，排列出符合購買者需求之候選中古車的相對優先順序。中古車商可透過此評估模式更精準的給予購買者最佳建議，進而提升成交機率及消費者滿意度，並為中古車商帶來更多的收益。

The sales volume of used cars is twice as high as that of new cars. Automobile manufacturers and auto dealers are part of the used car market. When purchasing used cars, buyers are commonly concerned about engine displacement, years used, price, brand, and fuel consumption. The aim of this study was to help buyers calculate relative weights of criteria through a fuzzy analytic hierarchy process, which is based on subjective, fuzzy, and uncertain characteristics. For determining elements of used cars that match buyers' basic needs, the technique for order preference by similarity to ideal solution was adopted along with the relative weights of decision-making criteria, which can be applied to indicate the relative ranking of used cars. Used car dealers can improve service quality through this evaluation model, and more precisely, provide suggestions for buyers, thereby enhancing customer satisfaction, promoting sales, and engendering more profit.