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Title: 以動態網絡資料包絡分析法評估汽車產業經營績效
Evaluating the Management Performance of Automotive Industry Using the Dynamic Network DEA Model
Authors: 呂有豐
Lue, Yeou-Feng
Lu, Pei-Ling
Keywords: 資料包絡分析
Network DEA
Dynamic Network DEA
Performance Evaluation
Issue Date: 2018
Abstract: 為了正確衡量公司績效,績效評估需要包含不同特性的因子來提供決策者更完整的資訊。然而,傳統的績效評估往往侷限於固定的影響因子,或是只針對產業鏈上的單一組織做績效評估,單以資料包絡法導入投入、產出值評估績效,無法分析網路的績效。網路資料包絡分析法改進了傳統的資料分析法,考慮組織結構,探討系統內部結構與內部流程之間的互動及影響並評估績效,為可以分析無明確關聯因子間之效率的方法,近年來廣為學界採用。惟評估跨期之績效時,網路資料包絡分析法有其侷限,因此,導入一分析跨期效率變動之績效評估法,有其必要性。本研究美國汽車產業實證之,結果顯示在本研究範圍內之汽車公司的生產階段績效優於市場階段,另外利用BCG矩陣分析顯示專業公司與分層公司佔了大多數,表示在投入與產出資源配置仍有改善空間,整體上有必要檢討其公司管理方針與經營策略。未達效率之決策單位應檢討投入與產出資源配置,設法提升市場競爭力,擴展市場佔有率及提升其在產業競爭地位,努力改善整體經營績效為汽車產業作為經濟成長發展的動力。
Operating an efficient evaluation should include multidimensional affecting factors to provide integrated information to the executive personnel. However, the traditional evaluation method was limited by rigid affecting factors or targeting on a single object in industry chains. Network performance was not assessed while using solely data envelopment analysis input-output. Network DEA improves traditional data analysis method by analyzing the organizational structure, discussing and assessing the impact of the interaction between the internal structure and progress. It has been popularly used academically to assess the level of correlation between factors for performance verification. However, the performance assessment method must be introduced while analyzing the intertemporal efficiency changes in multi-periods. Data was collected from the automotive industry in the US. The evidence of this study supported that the performance is better at the production stage than in the marketing stage within study objects. BCG matrix analysis supports that professional and divisional companies are the majority. It indicates the needs for improvement of the resources allocation of the input-output, also the necessity to review the management approach and operation strategy. Reviewing the input-output resources allocation on the inefficient decision-making unit could enhance market competitiveness, increase marketing share and upgrade industrial value. Focusing on improving business performance to motivate the development of economic growth in the automotive industry.
Other Identifiers: G0005702315
Appears in Collections:學位論文

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