基於多目標決策之資料包絡分析法評估標準普爾五百指數資訊科技公司之經營效率

Abstract

資訊科技，主要是利用電腦科學和通訊技術來設計、開發、安裝和實施資訊系統及應用軟體。資訊科技的研究範疇包括科學、技術、工程以及管理等學科；而資訊科技主要的應用範圍包括電腦硬體和軟體、網路和通訊技術、應用軟體開發工具等。因此，資訊科技也常被稱為資訊和通訊技術。現今，電腦和網際網路的普及，人們日漸普遍的使用電腦及網際網路來生產、處理、交換和傳播各種形式的資訊。換句話說，資訊科技已經成為人類日常生活中不可或缺的一個部份。有鑑於此，深入了解資訊科技公司的生產力與效率，並作績效評估對於資訊科技公司的管理者及投資者都非常重要。至今，著墨於資訊科技公司的績效評估研究並不多，因此，本研究將利用傳統資料包絡分析法來對資訊科技公司做經營效率的評估。本研究將以標準普爾五百指數資訊科技公司來做為受評估的決策單位。然而，傳統資料包絡分析法是從不合適的權重去做推導，而得到的不公平模型。因此，此研究將利用多目標決策之資料包絡分析法來評估標準普爾五百指數資訊科技公司之經營效率。利用多目標決策之資料包絡分析法來評估之下，每個決策單位將會在相等的標準下做評估，而評估結果將會比傳統資料包絡分析法還要更公平。本研究將藉由歷年的財務報表對標準普爾五百指數資訊科技公司的領導廠商作績效評估。除此之外，本研究將會利用多目標決策之資料包絡分析法與傳統資料包絡分析法做比較，並做更準確性的修正。在未來，本研究所評估的結果將會做為公司管理者或是投資者的一個重要的管理或投資依據。

Information technology (IT) is defined as the obtainment, procedure, storage and propagation of sounding, drawing, and textual information by combining microelectronics-based computing and telecommunications. Nowadays, IT is starting to spread further from the conventional personal computer and network technologies to integrations of other fields of technology such as the use of cell phones, televisions, automobiles, etc. In other words, IT has penetrated in daily life of human beings and become one part of the whole society. The importance of IT has become momentous. Therefore, to understand the performance of efficiency and productivity of the IT firms is critical for managers as well as for personal investors. Until now, there are very few researches tried to analyze final performance of the IT firms. As a result, this research intends to use traditional Data Envelopment Analysis (DEA) CCR or BCC models to evaluate the performance of IT firms. The Decision Making Units (DMUs) on this research are chosen from IT firms in S&P 500. However, the traditional DEA models are not fair models from the aspect of improper weight derivations. Thus, this paper intends to analyze the efficiency of IT firms in S&P 500 efficiencies by using multiple objective programming (MOP) based Data Envelopment Analysis (DEA). In a MOP based DEA approach, DMUs will be evaluated based on an equal standard and the results will be evaluated more fairly. The world’s leading IT firms in S&P 500 will be evaluated based on publicly available financial reports of the fiscal year. In addition, the newly developed MOP can improve the traditional DEA’s unfair weights problems and benchmark the efficiency of IT firms in S&P 500 correctly. In the future, performance evaluation results can be served as foundations for investment strategies definition.