近年來，隨著環保意識抬頭，企業開始注意到資料中心能源消耗的問題，用電成本更是資料中心總成本中不斷增加的一部分。傳統的資料中心，要節省電能的消耗是很困難的，必須重新檢討並藉由綠色科技（Green IT）來做最佳改善，將現有的資料中心轉換成高效能的綠色資料中心（Green Data Center）。在轉換的過程中，需考慮的因素及其重要性，成為本研究之動機。
然而，企業在有限的時間、人力及預算下，大多無法一次完成所有的改善工作，因此，本研究嘗試建立了一個公正且客觀的決策模式。在第一階段的工作主要是先透過文獻探討，彙整出影響綠色資料中心的構面及要素，並對6位專家進行深度訪談，確認資料中心能源效率改善之衡量指標及評估準則，並依此建立層級架構。第二階段再運用AHP專家問卷，對15位專家進行問卷調查，並使用Super Decisions軟體計算各項權重與一致性檢定。
分析結果顯示，整體專家認為評估構面改善優先順序為：「冷卻系統」（0.3466）、「減少資源浪費」（0.2666）、「電源管理」（0.2084）、「儲存設備」（0.1784）。

Recently, with the rise of the sense of environment protection, enterprises get aware of the problem of energy consumption in the data centers while the cost of electricity for data centers also keeps increasing. It is fairly difficult to reduce the energy consumption for traditional data center; instead, Green IT should be considered for the best solution to turn the existing data center into Green Data Center with high efficiency. In the process of this transformation, the factors and importance that should be taken into account become the research motive for the present study.
However, with the limited time, human resource, and budget, enterprises are not able to accomplish all the jobs at a time. Therefore, the present study attempts to establish an impartial and objective model for decision making. In phase 1, the key elements and scopes for Green Data Center are summarized and categorized through bibliography investigation. In addition, profound interviews with 6 experts are conducted to confirm the standards and criteria for measuring and evaluating the energy efficiency of data centers and to build up the hierarchy structures. In phase 2, AHP questionnaire is performed by 15 experts and Super Decision software is applied to calculate the weight of each factor and test the consistence.
The analysis result shows that the priority of improvement for all the evaluated factors is cooling system (0.3466), reduction of resource wasting (0.2666), power management (0.2084), and storage device (0.1784).

中文部分
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網站部分
Google. (2011). Data Center Efficiency Measurements. Retrieved November 8, 2011, from Google: http://www.google.com/corporate/datacenters/measuring.html