在現今競爭激烈的商業環境中，資訊的優勢成為超越其他企業的重要因素之一。商業智慧的其中功能的一個功能為決策支持系統。此研究建立關於效用函數的決策支持系統，以幫助企業做出決策。效用函數已經廣泛得應用以表達出消費者對需求的喜好程度。我們假設一個產品由許多的特徵組成。基於此概念，消費者將對每個不同獨特的特徵所組成的不同的產品進行評價且排名。根據評價後的分數，每個客戶將獲得自己對於每個產品的效用。因此，客戶願意購買最滿意的產品，意即，此產品在一個特定市場中具有最高的效用。我們建立消費者效用函數的純特徵需求模型。接著，我們設計了一個具有二次目標式和互補限制式的數學規劃作為最小化測量誤差函數的逆問題。藉由推導數學規劃的參數，我們可以利用推導得出的參數計算消費者的效用。我們使用真實的車輛數據來證實數學規劃的有效性。藉由不同的觀點，企業觀點和消費者觀點，我們能更加地了解市場的需求。

Nowadays, the advantage of information becomes one of the important factors to beat other businesses in the competitive business environment. One of the functions of Business intelligence is decision support systems. This research deploys the decision support systems (DSS) about utility function to help the business make decisions. Utility function has been prevalent expressing one consumer's preference representing consumer's demand. We assume that one product is composed of many characteristics. Based on this concept, the consumer will rank different products by a unique score toward each characteristic. According to the scores, each customer will get his own utilities to each product. As a result, the customer is willing to buy the most satisfying product, i.e., the product with the highest utility within one specific market. We establish the pure characteristic demand model for consumer's utility function. We then formulate a mathematical program with quadratic objective function and complementarity constraints as the inverse problem that minimizes the error of the utility measured function. By deriving the parameters for the program, we can calculate the consumer's utility with the parameters. We use the real vehicle data to prove the validity of the program. Through different views, both business view and consumer view, we are able to understand more for the demand of the market.

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