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Two-Stage Network Structures with Undesirable Intermediate Outputs Reused: A DEA Based Approach

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Abstract

The rapid development in economy of China has intensified the country’s many problems, such as environmental pollution and energy shortage. Thus, establishing a society with resource conservation and environmental harmony, typically reusing the pollution and waste from the industrial production, has attracted attention from both the government and the public in recent years. Data envelopment analysis (DEA) has been widely used in measuring two-stage network structures that constituted with homogenous decision making units. However, previous works failed to take the undesirable intermediate products into account in the two-stage network structures including production system and disposal system. In this study, we build an additive DEA approach to evaluate the efficiency of the proposed new two-stage network structures, and propose a better efficiency decomposition to the individual system. Finally, our approach is applied to analyze the industrial production in 30 provincial level regions in mainland China and some implications are given.

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References

  • Amirteimoori, A. (2013). A DEA two-stage decision processes with shared resources. Central European Journal of Operations Research, 21(1), 141–151.

    Article  Google Scholar 

  • Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.

    Article  Google Scholar 

  • Chen, Y., Du, J., David Sherman, H., & Zhu, J. (2010). DEA model with shared resources and efficiency decomposition. European Journal of Operational Research, 207(1), 339–349.

    Article  Google Scholar 

  • Chen, Y., Cook, W. D., Li, N., & Zhu, J. (2009). Additive efficiency decomposition in two-stage DEA. European Journal of Operational Research, 196(3), 1170–1176.

    Article  Google Scholar 

  • Chen, Y., Liang, L., Yang, F., & Zhu, J. (2006). Evaluation of information technology investment: A data envelopment analysis approach. Computers and Operations Research, 33(5), 1368–1379.

    Article  Google Scholar 

  • Chen, Y., & Zhu, J. (2004). Measuring information technology’s indirect impact on firm performance. Information Technology and Management, 5(1–2), 9–22.

    Article  Google Scholar 

  • Coelli, T. J., Prasada Rao, D. S., & O’ Donnell, C. J. (2005). An introduction to efficiency and productivity analysis (2nd ed.). New York: Springer.

    Google Scholar 

  • Cook, W. D., Liang, L., & Zhu, J. (2010). Measuring performance of two-stage network structures by DEA: A review and future perspective. Omega, 38, 423–430.

    Article  Google Scholar 

  • Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-Solver Software (2nd ed.). New York: Springer. ISBN 387452818, 490.

    Google Scholar 

  • Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Handbook on data envelopment analysis. Vienna: Springer Science & Business Media.

    Book  Google Scholar 

  • Fukuyama, H., & Weber, W. L. (2010). A slacks-based inefficiency measure for a two-stage system with bad outputs. Omega, 38(5), 398–409.

    Article  Google Scholar 

  • Geng, Y., Zhu, Q., Doberstein, B., & Fujita, T. (2009). Implementing China’s circular economy concept at the regional level: A review of progress in Dalian, China. Waste Management, 29(2), 996–1002.

    Article  Google Scholar 

  • Halkos, G. E., Tzeremes, N. G., & Kourtzidis, S. A. (2014). A unified classification of two-stage DEA models. Surveys in Operations Research and Management Science, 19(1), 1–16.

    Article  Google Scholar 

  • Hu, J. L., & Wang, S. C. (2006). Total-factor energy efficiency of regions in China. Energy Policy, 34(17), 3206–3217.

    Article  Google Scholar 

  • Hu, J., Xiao, Z., Zhou, R., Deng, W., Wang, M., & Ma, S. (2011). Ecological utilization of leather tannery waste with circular economy model. Journal of Cleaner Production, 19(2), 221–228.

    Article  Google Scholar 

  • Hua, Z., Bian, Y., & Liang, L. (2007). Eco-efficiency analysis of paper mills along the Huai River: An extended DEA approach. Omega, 35(5), 578–587.

    Article  Google Scholar 

  • Huang, Z. M., & Li, S. X. (2001). Co-Op advertising models in a manufacturing-retailing supply chain: A game theory approach. European Journal of Operational Research, 135, 527–544.

    Article  Google Scholar 

  • Kao, C., & Hwang, S. N. (2008). Efficiency decomposition in two-stage data envelopment analysis: An application to non-life insurance companies in Taiwan. European Journal of Operational Research, 185(1), 418–429.

    Article  Google Scholar 

  • Liang, L., Cook, W. D., & Zhu, J. (2008). DEA models for two-stage processes: Game approach and efficiency decomposition. Naval Research Logistics (NRL), 55(7), 643–653.

    Article  Google Scholar 

  • Liang, L., Yang, F., Cook, W. D., & Zhu, J. (2006). DEA models for supply chain efficiency evaluation. Annals of Operations Research, 145(1), 35–49.

    Article  Google Scholar 

  • Li, Y., Chen, Y., Liang, L., & Xie, J. (2012). DEA models for extended two-stage network structures. Omega, 40(5), 611–618.

    Article  Google Scholar 

  • Lozano, S., & Gutiérrez, E. (2011). Slacks-based measure of efficiency of airports with airplanes delays as undesirable outputs. Computers & Operations Research, 38(1), 131–139.

    Article  Google Scholar 

  • Maghbouli, M., Amirteimoori, A., & Kordrostami, S. (2014). Two-stage network structures with undesirable outputs: A DEA based approach. Measurement, 48, 109–118.

    Article  Google Scholar 

  • Mathews, J. A., & Tan, H. (2011). Progress toward a circular economy in China. Journal of Industrial Ecology, 5, 435–457.

    Article  Google Scholar 

  • Moriguchi, Y. (2007). Material flow indicators to measure progress toward a sound material-cycle society. Journal of Material Cycles and Waste Management, 9, 112–120.

    Article  Google Scholar 

  • Nordström, H., & Vaughan, S. (1999). Trade and the environment. Geneva: World Trade Organization publications. (Special Studies No. 4).

    Google Scholar 

  • Pearce, D., & Turner, R. K. (1990). Economics of natural resources and the environment. Balti-more: The Johns Hopkins University Press.

    Google Scholar 

  • Seiford, L. M., & Zhu, J. (1999). Profitability and marketability of the top 55 US commercial banks. Management Science, 45(9), 1270–1288.

    Article  Google Scholar 

  • Seiford, L. M., & Zhu, J. (2002). Modeling undesirable factors in efficiency evaluation. European Journal of Operational Research, 142(1), 16–20.

    Article  Google Scholar 

  • Sexton, T. R., & Lewis, H. F. (2003). Two-stage DEA: An application to major league baseball. Journal of Productivity Analysis, 19(2–3), 227–249.

    Article  Google Scholar 

  • Song, M., Wang, S., & Liu, W. (2014). A two-stage DEA approach for environmental efficiency measurement. Environmental Monitoring and Assessment, 186(5), 3041–3051.

    Article  Google Scholar 

  • Thanassoulis, E., Kortelainen, M., Johnes, G., & Johnes, J. (2011). Costs and efficiency of higher education institutions in England: A DEA analysis. Journal of the Operational Research Society, 62(7), 1282–1297.

    Article  Google Scholar 

  • Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3), 498–509.

    Article  Google Scholar 

  • Wang, K., Huang, W., Wu, J., & Liu, Y. N. (2014). Efficiency measures of the Chinese commercial banking system using an additive two-stage DEA. Omega, 44, 5–20.

    Article  Google Scholar 

  • Wang, K., Yu, S., & Zhang, W. (2007). China’s regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation. Mathematical and Computer Modelling, 58, 1117–1127.

    Article  Google Scholar 

  • Wong, E. (2013). As pollution worsens in China, solutions succumb to infighting. New York: he New York Times.

    Google Scholar 

  • Wu, H. Q., Shi, Y., Xia, Q., & Zhu, W. D. (2014a). Effectiveness of the policy of circular economy in China: A DEA-based analysis for the period of 11th five-year-plan. Resources, Conservation and Recycling, 83, 163–175.

    Article  Google Scholar 

  • Wu, J., An, Q. X., Yao, X., & Wang, B. (2014b). Environmental efficiency evaluation of industry in China based on a new fixed sum undesirable output data envelopment analysis. Journal of Cleaner Production, 74, 96–104.

    Article  Google Scholar 

  • Wu, J., An, Q., Xiong, B., & Chen, Y. (2013). Congestion measurement for regional industries in China: A data envelopment analysis approach with undesirable outputs. Energy Policy, 57, 7–13.

    Article  Google Scholar 

  • Wu, J., & Liang, L. (2010). Cross-efficiency evaluation approach to Olympic ranking and benchmarking: the case of Beijing 2008. International Journal of Applied Management Science, 2(1), 76–92.

    Article  Google Scholar 

  • Xue, B., Chen, X., Geng, Y., Guo, X., Lu, C., Zhang, Z., et al. (2010). Survey of officials’ awareness on circular economy development in China: Based on municipal and county level. Resources, Conservation and Recycling, 54, 1296–1302.

    Article  Google Scholar 

  • Yang, S., & Feng, N. (2008). A case study of industrial symbiosis: Nanning Sugar Co., Ltd. in China. Resources, Conservation and Recycling, 52(5), 813–820.

    Article  Google Scholar 

  • Zhang, B., Bi, J., Fan, Z., Yuan, Z., & Ge, J. (2008). Eco-efficiency evaluation of industrial system in China: A data envelopment analysis approach. Ecological Economics, 68(1–2), 306–316.

    Article  Google Scholar 

  • Zhang, W., & Yang, S. Y. (2013). The influence of energy consumption of China on its real GDP from aggregated and disaggregated viewpoints. Energy Policy, 57, 76–81.

    Article  Google Scholar 

  • Zhou, P., Poh, K. L., & Ang, B. W. (2007). A non-radial DEA approach to measuring environmental performance. European Journal of Operational Research, 178(1), 1–9.

    Article  Google Scholar 

  • Zhu, J. (2000). Multi-factor performance measure model with an application to Fortune 500 companies. European Journal of Operational Research, 123(1), 105–124.

    Article  Google Scholar 

Download references

Acknowledgments

The research is supported by National Natural Science Funds of China (No. 71222106), Research Fund for the Doctoral Program of Higher Education of China (No. 20133402110028), Foundation for the Author of National Excellent Doctoral Dissertation of P. R. China (No. 201279) and The Fundamental Research Funds for the Central Universities (No. WK2040160008).

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Authors and Affiliations

  1. School of Management, University of Science and Technology of China, Hefei, 230026, Anhui, People’s Republic of China

    Jie Wu, Qingyuan Zhu, Junfei Chu & Liang Liang

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  1. Jie Wu
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  2. Qingyuan Zhu
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  3. Junfei Chu
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  4. Liang Liang
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Correspondence to Jie Wu.

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Wu, J., Zhu, Q., Chu, J. et al. Two-Stage Network Structures with Undesirable Intermediate Outputs Reused: A DEA Based Approach. Comput Econ 46, 455–477 (2015). https://doi.org/10.1007/s10614-015-9498-3

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