本論文目的是探討勞動生產力評估的方式，使勞動生產力透過多項投入與產出項目評估其效率值，並且找出貼近實際生產面的勞動生產力最適效率值，而不是利用單一投入與產出項目的比率值來評估勞動生產力的優劣。彙整實證公司的生產資料，利用生產投入與產出項目，透過資料包絡分析法（Data Envelopment Analysis, DEA）可分析多項投入與產出的特性，使用CCR模式的固定規模報酬（Constant return to scale）與BCC模式的變動規模報酬（Variable Return to Scale）分析勞動生產力的技術效率（Technical Efficiency）、純技術效率（Pure Technical Efficiency）、規模效率（Scale Efficiency）與配置效率（Allocative Efficiency）。所設定的A～R之18組DMU（Decision making unit），每組DMU包含投入玻璃片數（In-sheet）、投入model數量（In-model）、人員編制（Man-power）、人員實際出勤工時（Act-HRS）、產出TFT玻璃片數（Out-sheet）、產出model數量（Out-model），共6項因子，經過CCR模式與BCC模式分析結果得知，判定為有效率的DMU共10組，其中「L、N、P」3組的配置效率為相對有效率，並在最小成本下生產，另外「L」為所有DMU相對有效率與穩健度（Robustness）最佳的DMU。若以成本效率（Cost Efficiency）為考量，則DMU「L、N、P」3組，為最適合的目標設定。本研究結果可讓生產單位在訂定勞動生產力KPI的需求上，有明確的方向可依循，並訂定出利於生產單位管控的勞動生產力目標。The purpose of this thesis is to explore that the evaluation of efficiency value of labor productivity through perspectives of multi-input and multi-output. In addition, in order to acquire the optimal efficiency of labor productivity to meet actual production aspect so that the methodology of a single input and output is eliminated.Utilizing the methodology of Data Envelopment Analysis (DEA) and the production information of case study including input and output and could obtain the analysis of characteristics of the multi-input and multi-output. Literally, the CCR model (Constant return to scale) and BCC model (Variable Return to Scale) in DEA have been applied to gain a number of indicators of efficiency such as Technical Efficiency, Pure Technical Efficiency, Scale Efficiency and Allocative Efficiency. As a result, the 18 units of DMU (Decision making unit) of results through the CCR model and BCC model reveal that the 10 units of DMU are more efficient than others. Besides, L unit, N unit and P unit are the relative efficiency under minimum cost of production. Additionally, the DMU of L is not only the most efficiency and robustness in but also the best DMU in the 18 units. Therefore, L DMU, N DMU and P DMU are the most appropriate units for goal setting in this thesis in terms of Cost Efficiency.To conclude, the results of this study may support the manufacturing unit to set up the Key Performance Indicator of labor productivity and the target of labor productivity of manufacturing unit explicitly.
