本研究以中國大陸商業銀行名列World Bank Top 1000名單前五百大的銀行為研究對象，運用資料包絡分析法(DEA)來進行研究，以2007年~2009年之數項財務指標為投入及產出項目，除應用CCR模式、BCC模式、Super SBM模式評估各家商業銀行(受評單位)的效率值外，更以Malmquist Index去評估跨期間受評單位的效率值，應用DEA可同時處理多項投入及多項產出的效率評估模式來衡量中國大陸商業銀行之經營效率。
就CCR模型分析結果再進行敏感度分析，發現移除投入項目「利息支出」、「股本」與產出項目「貸款淨額」造成總體效率單位家數的變化較明顯。以BCC模式技術效率值進行敏感度分析則發現：移除投入項目「利息支出」及「業務及管理費」及產出項目「貸款淨額」時，技術效率單位數也會減少。
2007~2009年間有7家銀行，其總體效率、技術效率、規模效率以及Super SBM VRS效率值均為有效率單位。再以Malmquist模式進行分析，則會發現前述銀行有3家銀行的Catch-up Effect、Frontier Effect及Malmquist Index均>1，表示其相對效率有成長趨勢、技術進步且總要素生產力呈現成長。以Malmquist指數分析得到總要素生產力居末位之銀行，其三年度平均Super SBM效率值表現高居第1名，但2009年Super SBM效率值則有退步，顯示有效率單位要持續其成長步調可能會有難度。

Using data envelopment analysis (DEA) to conduct a study in efficiency of Chinese commercial banks, those were included in World Bank Top 500 list, from 2007 to 2009. Some financial indicators were selected as inputs and outputs, with the employment of CCR, BCC, Super SBM, and Malmquist Index Models, to assess the efficiency value of commercial banks. Through the advantage of DEA, being able to handle multiple inputs and outputs in one single model, and availability of various DEA models, to evaluate the efficiency of commercial banks has become possible.
The sensitivity analysis on the outcome of CCR shows that to remove the input items "interest expense", "equity" and output item "net lending" will lead to big change to the number of overall-efficient DMUs. Using BCC model to run sensitivity analysis shows that: remove the input items "interest", "business and management fees" and output item "net lending" will also reduce the number of technically efficient units.
From 2007 to 2009, seven banks have shown consistently efficient over overall efficiency, technical efficiency, scale efficiency and Super SBM VRS efficiency. Malmquist analysis identifies three banks, included in the aforementioned banks, with Catch-up Effect, Frontier Effect and Malmquist Index being higher than 1, indicating improvement on their relative efficiency growth, technology progress and total factor productivity. On the other hand, the DMU with lowest Malmquist index has the highest average Super SBM efficiency score give us a hint that the efficient DMUs may have the difficulty to maintain their growth rate.

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