中国光伏上市企业效率的实证分析——基于IAHP保证域的DEA模型
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摘要
近几年,受国际经济环境衰退的影响,国内光伏产业进入行业整合时期.如何发挥企业竞争优势,提高企业生产效率,成为企业在整合潮中能够继续生存的关键.依据保证域(AR)的设置特点,结合IAHP方法的指标权重偏好,提出一种基于IAHP保证域的DEA模型.通过对中国18家光伏企业效率的测评和分析发现:基于IAHP保证域的DEA模型能够克服传统DEA模型权重选取的随意性,评价结果与传统的DEA方法相比存在较高的区分度;纯技术效率是导致企业综合效率降低的主要原因;"生产过剩"现象依然存在于组件、硅片企业中.
In recent years, the market macro environment changed due to the financial crisis,the domestic photovoltaic industry stepped into a period of integration. How to develop its strength, improve the efficiency of enterprise production, become the key to survival in the integration. In this paper, we propose the DEA model with assurance regions(AR) based on IAHP in terms of the characteristics of AR and the preferences of index weight in the IAHP.The analyzed objects are 18 specialized photovoltaic companies, and it is found that the improved model combined with subjective preferences of experts, overcome the randomness of the traditional DEA model weights selection, high consistency with the practical operation of the enterprises; Pure technical efficiency is the main reason for the result in the decrease of enterprises' overall efficiency; "Overproduction" phenomenon still exists in PV components,silicon enterprises.
In recent years, the market macro environment changed due to the financial crisis,the domestic photovoltaic industry stepped into a period of integration. How to develop its strength, improve the efficiency of enterprise production, become the key to survival in the integration. In this paper, we propose the DEA model with assurance regions(AR) based on IAHP in terms of the characteristics of AR and the preferences of index weight in the IAHP.The analyzed objects are 18 specialized photovoltaic companies, and it is found that the improved model combined with subjective preferences of experts, overcome the randomness of the traditional DEA model weights selection, high consistency with the practical operation of the enterprises; Pure technical efficiency is the main reason for the result in the decrease of enterprises' overall efficiency; "Overproduction" phenomenon still exists in PV components,silicon enterprises.
引文
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[4]Zhou Z, Zhao L, Lui S, et al. A generalized fuzzy DEA/AR performance assessment model[J].Mathematical and Computer Modelling, 2012, 55(11):2117-2128.
[5]Khalili M, Camanho A S, Portela M C A S, et al. The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs[J]. European Journal of Operational Research, 2010, 203(3):761-770.
[6]Lee A H, Lin. C Y, Kang H, et al. An integrated performance evaluation model for the photovoltaics industry[J]. Energies, 2012, 5(4):1271-1291.
[7]Lee A H, Kang H, Lin C. A Performance Evaluation Model Using FAHP/DEA and the Malmquist Productivity Index to Assess the Photovoltaics Industry in Taiwan[J]. Journal of Testing and Evaluation, 2014, 42(1).
[8]Saaty T L. The analytic network process[M]. Decision making with the analytic network process,Springer, 2006:1-26.
[9]Sugihara K, Tanaka H. Interval evaluations in the analytic hierarchy process by possibility analysis[J]. Computational intelligence, 2001, 17(3):567-579.
[10]Tseng F, Chiu Y, Chen J. Measuring business performance in the high-tech manufacturing industry:a case study of Taiwan's large-sized TFT-LCD panel companies[J]. Omega, 2009, 37(3):686-697.
[11]虞晓雯,雷明,王其文,邓洁.中国商业银行效率的实证分析(2005-2011):基于时间序列回归和随机DEA的机会约束模型[J].中国管理科学,2012,(20):356-362.
[2]Thompson R G, Lee E, Thrall R M. DEA AR-efficiency of united-states independent oil gas producers over time[J].Computers&Operations Research, 1992, 19(5):377-391.
[3]Yu P, Lee J H. A hybrid approach using two-level SOM and combined AHP rating and AHP/DEAAR method for selecting optimal promising emerging technology[J]. Expert Systems with Applications, 2013, 40(1):300-314.
[4]Zhou Z, Zhao L, Lui S, et al. A generalized fuzzy DEA/AR performance assessment model[J].Mathematical and Computer Modelling, 2012, 55(11):2117-2128.
[5]Khalili M, Camanho A S, Portela M C A S, et al. The measurement of relative efficiency using data envelopment analysis with assurance regions that link inputs and outputs[J]. European Journal of Operational Research, 2010, 203(3):761-770.
[6]Lee A H, Lin. C Y, Kang H, et al. An integrated performance evaluation model for the photovoltaics industry[J]. Energies, 2012, 5(4):1271-1291.
[7]Lee A H, Kang H, Lin C. A Performance Evaluation Model Using FAHP/DEA and the Malmquist Productivity Index to Assess the Photovoltaics Industry in Taiwan[J]. Journal of Testing and Evaluation, 2014, 42(1).
[8]Saaty T L. The analytic network process[M]. Decision making with the analytic network process,Springer, 2006:1-26.
[9]Sugihara K, Tanaka H. Interval evaluations in the analytic hierarchy process by possibility analysis[J]. Computational intelligence, 2001, 17(3):567-579.
[10]Tseng F, Chiu Y, Chen J. Measuring business performance in the high-tech manufacturing industry:a case study of Taiwan's large-sized TFT-LCD panel companies[J]. Omega, 2009, 37(3):686-697.
[11]虞晓雯,雷明,王其文,邓洁.中国商业银行效率的实证分析(2005-2011):基于时间序列回归和随机DEA的机会约束模型[J].中国管理科学,2012,(20):356-362.