半導體產業廠商家數眾多、產品零件種類複雜、各供應商產品間重疊性高，導致客戶詢價次數頻繁，供應商若能夠快速回應客戶的諮詢，就能提高訂單機會；但是產業上、中、下游整合垂直分工緊密連結，間接地加速了半導體供應商與客戶間交易時綜合評估的複雜程度，由於客戶與客戶訂單的條件經常變動，供應商的定價策略就不易做出理性立即的判斷，也容易產生不一致決策行為現象出現；而供應商為了促使交易成交，與客戶間的議價行為會一直重覆，定價策略也不斷修正，直到找出滿足雙方的合理價格；由於供應商參與定價的人員經常以直覺或透過經驗、和情境組合的反應來制定價格，習慣性的決策思考會因個人認知難免有錯誤或偏差而造成損失；因此若有一套有效的半導體供應商產品定價決策模型，除了可因應動態市場的情境變化也可加強客戶屬性判斷的理性基礎，這樣對供應商在產品定價考量時就有一個決策支援輔助工具以創造實質的效益價值及貢獻。
本研究以半導體產業的二家供應廠商為實際案例，訪談具有參與定價實務經驗的專業人員，採用德爾菲法(Delphi Method)及模糊理論(Fuzzy Theory)之應用，把定價考量因素加以分析、推導及歸納，建立一套可動態推估調整產品定價的模糊邏輯推論系統(Fuzzy logic inference system, FLIS)，運用實務情境模擬來檢驗定價決策模型的效度與可行性，研究結果顯示供應商產品定價決策模型能讓供應商之專業定價人員用來做為定價或議價事前評估的決策支援工具，並促成更快速且具有一致性的定價模式。
The considerable manufacturers in the semi-conductor industry, various components and highly similar products made by all suppliers lead to frequent inquiries from customers. If suppliers are able to promptly respond to customers’ inquiries for quotation, order may increase. However, the upstream, midstream and downstream companies in the industry are vertically integrated and closely work together that indirectly accelerates the complexity in overall evaluation of trading between semi-conductor suppliers and customers. As the condition regarding customers and their orders often changes, suppliers are not likely to rationally and promptly determine the pricing strategy, and apt to have inconsistent decision making. To close a deal, suppliers repeatedly negotiate prices with customers and constantly modify the pricing strategy until a reasonable price is achieved that satisfies both parties. Suppliers’ personnel associated with pricing often make a price instinctively or based on experience and reaction from scenario portfolio; such customary decision making may cause loss due to error or deviation in individual perception. Thus, if there is an effective model of product pricing strategy for semi-conductor suppliers, it reacts to change in the dynamic market situation as well as strengthens a rational judgment of customer’ attributes. This assists suppliers in determination of product pricing that creates the real benefit value and contribution.
The study has two semi-conductor suppliers for the case study. The professionals with experience in pricing are interviewed. Delphi Method and Fuzzy Theory are adopted for analysis, deduction and conclusion of pricing factors to build a fuzzy logic inference system (FLIS) that dynamically estimates and adjusts pricing. In addition, scenario simulation is used to test validity and feasibility of the pricing strategy model. It is found that the model of product pricing strategy is taken by suppliers’ professionals associated with pricing as the decision support tool for evaluation before pricing or price negotiation which facilitates a faster and consistent pricing model.
