整合獨立成份分析與網路資料包絡分析法評估營運績效

Abstract

由於精確的績效評估對於組織發展中營運控制的重要性，本論文提出一整合獨立成份分析(Independent component analysis, ICA)與網路差額變數衡量(Network slacks-based measure, NSBM)之績效評估模式來提升績效評估的區別能力。由於資料包絡分析法的評估模式受到所選取變數的影響，所選取變數的高度自我相關性將影響績效評估的有效性與區別能力，因此將所選取的變數透過獨立成份分析並分解成數個統計上獨立性的獨立成份（Independent components, ICs）並選取解釋能力高的數個獨立成份為投入、中介及產出變數，再投入網路差額變數衡量建構績效評估模式。本研究主要係以整合獨立成分分析和網路差額變數衡量之提升績效評估模式探討台灣國際觀光旅館於2009年之營運績效表現，並將營運績效劃分為生產效率與獲益效能兩階段架構。實證結果顯示如下：首先，獲益效能對於整體營運績效貢獻度與重要性顯著優於生產效率；再者，本論文提出之整合績效分析模式顯著優於傳統的網路資料包絡分析評估模式有較好的評估區別能力，能提供較佳的績效管理意涵。

Given the importance of accurate performance evaluation for the operational control of organizational development, this dissertation proposed an enhanced performance evaluation framework combines the network slacks-based measure (NSBM) model with a variable selection method, the independent component analysis (ICA), herein termed the ICA-NSBM model, and uses a two-stage network performance structure incorporating the production efficiency and profit effectiveness as measures of performance. ICA is related to the search for latent information; in it, independent components (ICs) from the observed data and selected statistically unrelated ICs are treated as new input, intermediate, and output variables for the NSBM. The NSBM is then used in the investigation of multiple-dimension efficiencies, along with operating performance. This dissertation used empirical data on Taiwanese international tourist hotels and examined the problems of discriminative ability of data envelopment analysis used when a large number of variables are present. The empirical results indicate that the proposed ICA-NSBM model effectively points out that the performance of the profit effectiveness significantly hampers operational performance. Moreover, compared with the NSBM model, this novel performance evaluation analysis has a high discriminatory ability in order to assess the efficiency or inefficiency of the studied hotels.