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dc.contributorLue, Yeou-Fengen_US
dc.contributor.authorLu, Pei-Lingen_US不公開
dc.description.abstractOperating 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.en_US
dc.subjectNetwork DEAen_US
dc.subjectDynamic Network DEAen_US
dc.subjectPerformance Evaluationen_US
dc.titleEvaluating the Management Performance of Automotive Industry Using the Dynamic Network DEA Modelen_US
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