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  • 學位論文

研發績效之系統動態分析

Research and Development Performance Analysis by System Dynamics

指導教授 : 黃啟祐
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摘要


績效評估為最重要的管理工具,實時掌控組織績效,預測績效,並進而及時修正錯誤決策,對於組織效能的提升亟有助益。研發績效直接關係著成本、良率、產能,並影響企業營收。近年來,資訊科技公司面臨之競爭日增,技術生命週期日益縮減,研發績效如何提升,已經成為全球科技業最關注之議題。研發績效之評估雖然為研發管理最重要之議題,唯現有文獻多聚焦於靜態之績效分析,少有研究探討組織長時間變遷之研發績效變動狀況,唯影響研發績效之因子為數眾多,關係複雜,且難以預測,本研究將定義一基於多準則決策方法與系統動態學之分析架構以解決前述研發績效動態分析的問題。為分析研發組織之動態,本研究首先將回顧文獻,歸納影響研發組織績效之因素,並邀集專家,以修正式德菲法確認之,其次,本研究將以決策實驗室分析法建構影響研發績效關鍵要素之影響關係。基於前述影響關係,本研究進而導入系統動態學,預測未來研發績效之變遷。本研究將以全球主要之電子系統代工廠商為例,實證本分析架構之可行性。驗證完整之系統動態分析架構,將可作為科技公司研發績效評估之用。

並列摘要


Performance Evaluation is one of the most important management tools which can real-time control the performance of an organization, predict future performance, and thus, correct wrong decisions on time. However, most existing literature focused more on static analysis of the R&D performance. Very few scholars investigated how the R&D performance of some specific organization changes continuously over a period time, or the dynamic analysis. Furthermore, the factors which can influence the R&D performance evaluation include numerous and complex mutual influence relationships which are difficult to predict. The analytic and prediction framework will first be derived by using the historic data being derived during past five years. Then, the verified model will further be used to predict the R&D performance in the future. One of the world's leading electronic manufacturing service (EMS) provider will be used to verify the feasibility of the analytic and prediction framework. The well verified analytic and forecast framework will be used by EMS in the future.

並列關鍵字

R&D management System Dynamics (SD)

參考文獻


Amaratunga, D., Baldry, D., & Sarshar, M. (2001). Process improvement through performance measurement: the balanced scorecard methodology. Work study, 50(5), 179-189.
Amrina, E., & Vilsi, A. L. (2015). Key Performance Indicators for Sustainable Manufacturing Evaluation in Cement Industry. Procedia CIRP, 26, 19-23.
Barlas, Y. (1989). Multiple tests for validation of SD type of simulation models. European journal of operational research, 42(1), 59-87.
Barlas, Y. (1996). Formal aspects of model validity and validation in SD.
SD Review, 12(3), 183-210.

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