服務業營運管理量化輔助決策模式---以效用創造組合分類架構結合類神經網路分析我國旅館業為例

Abstract

服務業的蓬勃發展及快速成長，已成為未來經濟發展的主要趨勢，有關服務業營運管理之研究，對於該產業及整體經濟之發展確有其必要性。服務業營運管理的目的是以系統化的方式，有效率地將資源投入(Input)經由轉換流程輸出(Output)及增值(Create Value)，以達到企業的目標。事實上，如何運用有限的資源以產生最大價值的決策，仍是引導服務業營運管理邁向成功及維持競爭優勢的關鍵要項。 顯然，為有效運用資源，正確引導服務業營運管理及維持競爭優勢，需對服務業商品相關特性的界定及分類進行深入研究，期望透過分類架構的探討，以掌握不同類型的服務業特性。此外，並針對影響營運管理決策的相關特性進行計量分析，以量化的模式輔助經理人具體瞭解企業發展的條件與限制，藉此確認企業關鍵成功因素，進而提昇營運管理的決策品質。 本研究探討服務業特性的描述與分類理論，以及近來在分類相關文獻中常被選用的方法，並以我國旅館業為例，結合效用創造組合的分類架構與類神經網路的辨識功能，建構服務業營運管理量化輔助決策模式，提供經理人一種簡化且可解釋的綜合指標，以快速獲得顧客需求及營運現況等重要資訊，使經理人瞭解市場區隔位置及競爭優勢，於發展策略及執行方案時，能以有限的資源，發揮較大之效用。

The rapid and flourishing development of service industries has become a key player in the economic growth and certainly leads the trend. Researches of its operations and management (O&M) are necessary for the growth of the industries and the associated economies. The purpose of O&M of service industries is to systematically and effectively transfer the input resources to valuable outputs to meet the enterprise’s goals. Therefore the key success factors of service industries lies in the transfer process to produce most valuable outputs using limited resources. Achieving the above purpose relies on a thorough understanding of the products’ characteristics of service industries, including the definition and classification of those characteristics. Through the above understanding those characteristics affecting the industries O&M can be found, quantified and modeled to help managers understand the opportunities and constraints, identify key success factors, and finally raise the quality of O&M decisions. This thesis intends to construct a quantitative decision support model for the service industries by first studying researches about the industries’ characteristics definition and classification, together with the common theories and methodologies for classification. The above study leads to a combination of Utility Creation Mix Theory and Artificial Neural Network to produce the quantitative decision support model. And using the R.O.C. hotel industry as an example to demonstrate the model’s operations and outputs for decision support.