DEA-BASED DYNAMIC ASSESSMENT OF REGIONAL ENVIRONMENTAL EFFICIENCY

Svetlana RATNER

lanarat@ipu.ru
Institute of Control Science, Russian Academy of Science, 65 Profsoyuznaya st., Moscow 117997 (Russian Federation)

Pavel RATNER


* Institute of Control Science, Russian Academy of Science, 65 Profsoyuznaya st., Moscow 117997 (Russian Federation)

Abstract

We apply window Data Envelopment Analysis (DEA) to the solution of the problem of assessment of the efficiency of regional production systems in Southern Russia. The proposed method allows to monitor the changes in efficiency of regional economic systems throughout time and has a high discrimination power. The simplicity of the technical implementation of the proposed method and the availability of the necessary software for its use allow one to hope for its wide implementation in the modern practice of regional environmental management.


Keywords:

data envelopment analysis, non-parametric optimization, dynamic problems, window analysis

Bian, Y., He, P., & Xu, H. (2013). Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach. Energy Policy, 63, 962–971. https://doi.org/10.1016/j.enpol.2013.08.051
DOI: https://doi.org/10.1016/j.enpol.2013.08.051   Google Scholar

Carrillo, M., & Jorge, J. M. (2016). A multi-objective DEA approach to ranking alternatives. Expert Systems with Applications, 50, 130-139. https://doi.org/10.1016/j.eswa.2015.12.022
DOI: https://doi.org/10.1016/j.eswa.2015.12.022   Google Scholar

Charnes, A., Clarke, C., Cooper, W., & Golany, B. (1984). A development study of DEA in measuring the effect of maintenance units in the U.S. Air Force. Annals of Operation Research, 2(1), 95–112.
DOI: https://doi.org/10.1007/BF01874734   Google Scholar

Cook, W. D., & Seiford, L. M. (2009). Data Envelopment Analysis (DEA) – Thirty years on. European Journal of Operational Research, 192, 1–17. https://doi.org/10.1016/j.ejor.2008.01.032
DOI: https://doi.org/10.1016/j.ejor.2008.01.032   Google Scholar

Fare, R., Grosskopf, S., & Lovell, C. A. K. (1994). Production Frontiers. Cambridge University Press.
DOI: https://doi.org/10.1017/CBO9780511551710   Google Scholar

Färe, R., & Grosskopf, S. (2004). Modelling undesirable factors in efficiency evaluation: comment. European Journal of Operational Research, 157(1), 242–245. https://doi.org/10.1016/S0377-2217(03)00191-7
DOI: https://doi.org/10.1016/S0377-2217(03)00191-7   Google Scholar

Forgione, H., Pregitzer, C., Charlop-Powers, S., & Gunther, B. (2016). Advancing urban ecosystem governance in New York City: Shifting towards a unified perspective for conservation management. Environmental Science & Policy, 62, 127–132. https://doi.org/: 10.1016/j.envsci.2016.02.012
DOI: https://doi.org/10.1016/j.envsci.2016.02.012   Google Scholar

Khrustalev, E. Yu., & Ratner, P. D. (2015a). Analysis of ecological efficiency of Russia’s electric energy companies through the data envelopment analysis methodology. Economic Analysis: The Theory and Practice, 35, 33–42.
  Google Scholar

Khrustalev, E. Yu., & Ratner, P. D. (2015b). Eco-innovations in energy generation industry: the assessment of comparative effectiveness. Innovations, 9, 8–14.
  Google Scholar

Korhonen, P. J., & Luptacik, M. (2004). Eco-efficiency analysis of power plants: An extension of data envelopment analysis. European Journal of Operational Research, 154(2), 437–446. https://doi.org/10.1016/S0377-2217(03)00180-2
DOI: https://doi.org/10.1016/S0377-2217(03)00180-2   Google Scholar

Melnikov, R. M. (2016). Development of a methodology for assessing the effectiveness of scientific and innovative programs taking into account foreign experience. Innovations, 10, 65–73.
  Google Scholar

Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de Estatistica, 4, 209–242.
DOI: https://doi.org/10.1007/BF03006863   Google Scholar

Nizhegorodtsev, R. M., & Ratner, S. V. (2016). Trends in the development of industrially assimilated renewable energy: the problem of resource restrictions. Thermal Engineering, 63(3), 197-207. https://doi.org/10.1134/S0040601516030083
DOI: https://doi.org/10.1134/S0040601516030083   Google Scholar

Olejniczak, K., & Lukasik, K. (2016). Building Ecological Organizational Culture in the Modern Enterprise – Case of Henkel. International Journal of Contemporary Management, 15(1), 33-47. https://doi.org/10.4467/24498939IJCM.16.002.4835
  Google Scholar

Perlis, M. L. (2014). The Climate and Energy Policy Basis for EPA’s First-Ever CO2 Emission Standards for Power Plants. The Electricity Journal, 27(3), 35-44. https://doi.org/10.1016/j.tej.2014.03.005
DOI: https://doi.org/10.1016/j.tej.2014.03.005   Google Scholar

Ratner, S. V. (2016). Problems of optimizing the trajectories of the development of regional socioeconomical systems on ecological parameters. Drukerovsky Bulletin, 2, 30–41.
  Google Scholar

Ratner, S. V., & Ratner, P. D. (2016). Regional Energy Efficiency Programs in Russia: The Factors of Success. Region, 3(1), 68–85. https://doi.org/10.18335/region.v3i1.71
DOI: https://doi.org/10.18335/region.v3i1.71   Google Scholar

Ratner, S. V., & Nizhegorodtsev, R. M. (2017). Analysis of renewable energy projects’ implementation in Russia. Thermal Engineering, 64(6), 429–436. https://doi.org/10.1134/S0040601517060052
DOI: https://doi.org/10.1134/S0040601517060052   Google Scholar

Verma, R. L., Borongan, G., & Memon, M. (2016). Municipal Solid Waste Management in Ho Chi Minh City, Vietnam. Current Practices and Future Recommendation. Procedia Environmental Sciences, 35, 127–139. https://doi.org/10.1016/j.proenv.2016.07.059
DOI: https://doi.org/10.1016/j.proenv.2016.07.059   Google Scholar

Wang, K., Shiwei, Y. U., & Zhang, W. (2013). China’s regional energy and environmental efficiency: A DEA window analysis based dynamic evaluation. Mathematical and Computer Modelling, 58(5-6), 1117-1127. https://doi.org/10.1016/j.mcm.2011.11.067
DOI: https://doi.org/10.1016/j.mcm.2011.11.067   Google Scholar

Wu, H., Shi, Y., & Zhu, W. (2014). 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. https://doi.org/10.1016/j.resconrec.2013.10.003
DOI: https://doi.org/10.1016/j.resconrec.2013.10.003   Google Scholar

Download


Published
2017-06-30

Cited by

RATNER, S. ., & RATNER, P. . (2017). DEA-BASED DYNAMIC ASSESSMENT OF REGIONAL ENVIRONMENTAL EFFICIENCY. Applied Computer Science, 13(2), 48–60. https://doi.org/10.23743/acs-2017-13

Authors

Svetlana RATNER 
lanarat@ipu.ru
Institute of Control Science, Russian Academy of Science, 65 Profsoyuznaya st., Moscow 117997 Russian Federation

Authors

Pavel RATNER 

* Institute of Control Science, Russian Academy of Science, 65 Profsoyuznaya st., Moscow 117997 Russian Federation

Statistics

Abstract views: 133
PDF downloads: 13


License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

All articles published in Applied Computer Science are open-access and distributed under the terms of the Creative Commons Attribution 4.0 International License.


Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.