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- 저자 : John C.S. Tang (검색결과 4 건)
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김경술,John. C. S. Tang,Thierry Lefevre 한양대학교 경제연구소 2004 JOURNAL OF ECONOMIC RESEARCH Vol.9 No.2
Economic impacts from the introduction of dual system - carbon tax plus emission trading - to the Korean economy were analyzed. For the comprehensive analysis, a Computable General Equilibrium (CGE) model was developed in which dual system can be comprehensively analyzed. When emission trading can not be introduced to all emitters in the economy, dual system with carbon tax for small emitters and emissions trading for large emitters could be the best approach in domestic carbon dioxide abatement strategy. In dual system, monetary interests of the participants in emission trading and carbon tax payer are dependent on their marginal cost to reduce carbon emission. By the introduction of dual system, GDP, private consumption and value-added are evaluated to be decreased while international trade balance is estimated to be improved.
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An Integrated Approach to Measuring Supply Chain Performance
Theeranuphattana, Adisak,Tang, John C.S.,Khang, Do Ba Korean Institute of Industrial Engineers 2012 Industrial Engineeering & Management Systems Vol.11 No.1
Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.
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An Integrated Approach to Measuring Supply Chain Performance
Adisak Theeranuphattana,John C.S. Tang,Do Ba Khang 대한산업공학회 2012 Industrial Engineeering & Management Systems Vol.11 No.1
Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.
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