在過去許多有關評估經營績效的文獻，多採用量化資料為變數，忽略會影響效率值之質化指標，如專業能力、服務品質及保單品質等。有鑑於此，本文僅以理賠申訴率及解約失效率作為質化指標納入產出變數中，視為衡量效率值的另一種指標。因此，本文以無參數法中的資料包絡分析法(data envelopment analysis，簡稱DEA)為基礎架構，延伸出其他評估績效的方法，為曲線式效率衡量法及產出導向方向距離函數，目的就是為了處理意欲產出(各項責任準備金及放款)和非意欲產出(即為質化指標)同時存在下之效率衡量。 此外，由於過去許多有關評估經營績效的文獻，亦多以單年度來進行績效評估，且考量的投入變數皆為變動的情況，無法確切得知壽險公司在跨期實証期間的經營績效表現。因此，本文除了使用上述兩種方法針對質化指標進行績效評估外，並將考慮投入變數(內勤人員數及固定資產)為準固定投入變數，投入變數(外勤人員數)為變動投入變數及產出變數(各項責任準備金、放款)，利用DEA法，計算在跨期的實證期間下，各壽險公司技術效率及經濟效率，並探討納入準固定投入要素後，對於效率分析結果，是否有重大差異。 In the past, most relevant papers which evaluated efficiency used the quantification data as the variable. Ignoring the qualitative variables , such as professional ability, service quality and policy quality. Therefore, this paper takes the ratio of claims and the ratio of cancellation and lapse which measure efficiency into output variables as another index. So, this paper used the data envelopment analysis of the nonparametric approach as fundamental structure, extending other evaluating efficiency approaches which include graph efficiency measurement and directional output distance function, in order to treat the problem which is in the presence of desirable outputs and undesirable outputs simultaneously. In addition, the past papers evaluated efficiency by single year, and considered input variables as variable which could not learn operational performance clearly in the intertemporal period. Hence, this paper excepts for utilizing the above-mentioned two approaches (Graph efficiency measurement and directional output distance function) to measure efficiency in the presence of quality data, this paper will consider output variables and input variables which including quasi-fixed inputs and variable inputs to calculate the technical efficiency and overall efficiency of each life insurance company using DEA in the intertemporal period, and discuss that the empirical results whether or not exist the significant difference as if the input variables include quasi-fixed inputs..
