IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i19p12776-d935541.html
   My bibliography  Save this article

The Eco-Efficiency of Russian Regions in North Asia: Their Green Direction of Regional Development

Author

Listed:
  • Natalia Borisovna Lubsanova

    (Baikal Institute of Nature Management, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude 670047, Russia)

  • Lyudmila Bato-Zhargalovna Maksanova

    (Baikal Institute of Nature Management, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude 670047, Russia)

  • Zinaida Sergeevna Eremko

    (Baikal Institute of Nature Management, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude 670047, Russia)

  • Taisiya Borisovna Bardakhanova

    (Baikal Institute of Nature Management, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude 670047, Russia)

  • Anna Semenovna Mikheeva

    (Baikal Institute of Nature Management, Siberian Branch of the Russian Academy of Sciences, Ulan-Ude 670047, Russia)

Abstract

The green economy is one of the important and practical tools of sustainable development, which balances the two directions of regional development: economic growth and preservation of the natural environment. In this paper, we have developed a methodology for investigating the development and implementation of regional green economy policies, using the Russian regions in North Asia as an example. Three main tasks have been accomplished for this purpose: (1) assessment of how sustainable the socio-economic development of the Russian regions in North Asia is; (2) comparative analysis of the sustainability of regional policies (to what extent the federal targets and priorities for the green agenda implementation are reflected in the regional strategic documents); and (3) determination of the green direction for regional development by comparing the results of previous assessments. To assess the sustainability of regional development, we have used a methodology for DEA of eco-efficiency of socio-economic development in the Russian North Asian regions, using a non-oriented slacks-based measure (SBM) model. To assess the sustainability of regional policies, we used a content analysis of regional socio-economic development strategies. We have identified considerable variations among the Russian North Asian regions in the extent to which their socio-economic development is consistent with the principles of a green economy (both in the priorities, tools of regional policies, and the level of eco-efficiency). The content analysis of the regional strategic documents of the Russian North Asian regions, as well as the assessment of the eco-efficiency of their socio-economic development, show that regions with low actual eco-efficiency are planning in their strategies greater efforts for green development than more eco-efficient regions. The approaches we propose can support decision making in the field of eco-economic development as a tool to measure the degree of compliance of regional development with the principles of a green economy.

Suggested Citation

  • Natalia Borisovna Lubsanova & Lyudmila Bato-Zhargalovna Maksanova & Zinaida Sergeevna Eremko & Taisiya Borisovna Bardakhanova & Anna Semenovna Mikheeva, 2022. "The Eco-Efficiency of Russian Regions in North Asia: Their Green Direction of Regional Development," Sustainability, MDPI, vol. 14(19), pages 1-19, October.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12776-:d:935541
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/19/12776/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/19/12776/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Returns to Scale and Damages to Scale with Strong Complementary Slackness Conditions in DEA Assessment: Japanese Corporate Effort on Environment Protection," Energy Economics, Elsevier, vol. 34(5), pages 1422-1434.
    2. Zhang, Bing & Bi, Jun & Fan, Ziying & Yuan, Zengwei & Ge, Junjie, 2008. "Eco-efficiency analysis of industrial system in China: A data envelopment analysis approach," Ecological Economics, Elsevier, vol. 68(1-2), pages 306-316, December.
    3. Golany, B & Roll, Y, 1989. "An application procedure for DEA," Omega, Elsevier, vol. 17(3), pages 237-250.
    4. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    5. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    6. R. Malar MARAN,, 2017. "Green Economy: Challenges And Opportunities," EcoForum, "Stefan cel Mare" University of Suceava, Romania, Faculty of Economics and Public Administration - Economy, Business Administration and Tourism Department., vol. 6(3), pages 1-2, august.
    7. Dariush Khezrimotlagh & Yao Chen, 2018. "Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Decision Making and Performance Evaluation Using Data Envelopment Analysis, chapter 0, pages 217-234, Springer.
    8. Zemtsov, Stepan (Земцов, Степан) & Barinova, Vera (Баринова, Вера) & Kidyaeva, Vera (Кидяева, Вера) & Lanshina, Tatiana (Ланьшина, Татьяна), 2020. "Ecological Efficiency and Sustainable Regional Development in Russia During the 20 Years of Resource-Based Growth [Экологическая Эффективность И Устойчивое Развитие Регионов России За Двадцатилетие," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 2, pages 18-47, April.
    9. Demiral, Elif E. & Sağlam, Ümit, 2021. "Eco-efficiency and Eco-productivity assessments of the states in the United States: A two-stage Non-parametric analysis," Applied Energy, Elsevier, vol. 303(C).
    10. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    11. Zhang, Ning & Kong, Fanbin & Choi, Yongrok, 2014. "Measuring sustainability performance for China: A sequential generalized directional distance function approach," Economic Modelling, Elsevier, vol. 41(C), pages 392-397.
    12. Alexey Bilgaev & Erzhena Sadykova & Fujia Li & Anna Mikheeva & Suocheng Dong, 2021. "Socio-Economic Factor Impact on the Republic of Buryatia (Russia) Green Economic Development Transition," IJERPH, MDPI, vol. 18(20), pages 1-17, October.
    13. Daniel Tyteca, 1997. "Linear Programming Models for the Measurement of Environmental Performance of Firms—Concepts and Empirical Results," Journal of Productivity Analysis, Springer, vol. 8(2), pages 183-197, May.
    14. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
    15. Elena A. Tarkhanova & Elena L. Chizhevskaya & Anhelica V. Fricler & Natalia A. Baburina & Svetlana V. Firtseva, 2020. "Green economy in Russia: the investments’ review, indicators of growth and development prospects," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 8(2), pages 649-661, December.
    16. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model☆," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jialu Su & Zhiqiang Ma & Yan Wang & Xinxing Wang, 2023. "Evaluation and Spatial Correlation Analysis of Green Economic Growth Efficiency in Yangtze River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(3), pages 1-23, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Afzalinejad, Mohammad, 2020. "Reverse efficiency measures for environmental assessment in data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. César Salazar & Roberto Cárdenas-Retamal & Marcela Jaime, 2023. "Environmental efficiency in the salmon industry—an exploratory analysis around the 2007 ISA virus outbreak and subsequent regulations in Chile," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8107-8135, August.
    4. Zhou, Haibo & Yang, Yi & Chen, Yao & Zhu, Joe, 2018. "Data envelopment analysis application in sustainability: The origins, development and future directions," European Journal of Operational Research, Elsevier, vol. 264(1), pages 1-16.
    5. Shih-Heng Yu, 2019. "Benchmarking and Performance Evaluation Towards the Sustainable Development of Regions in Taiwan: A Minimum Distance-Based Measure with Undesirable Outputs in Additive DEA," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(3), pages 1323-1348, August.
    6. Halkos, George & Petrou, Kleoniki Natalia, 2019. "Treating undesirable outputs in DEA: A critical review," Economic Analysis and Policy, Elsevier, vol. 62(C), pages 97-104.
    7. Muhammet Enis Bulak & Murat Kucukvar, 2022. "How ecoefficient is European food consumption? A frontier‐based multiregional input–output analysis," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(5), pages 817-832, October.
    8. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    9. Trinks, Arjan & Mulder, Machiel & Scholtens, Bert, 2020. "An Efficiency Perspective on Carbon Emissions and Financial Performance," Ecological Economics, Elsevier, vol. 175(C).
    10. Khoshroo, Alireza & Izadikhah, Mohammad & Emrouznejad, Ali, 2022. "Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index," Energy, Elsevier, vol. 258(C).
    11. Thomas Bournaris & George Vlontzos & Christina Moulogianni, 2019. "Efficiency of Vegetables Produced in Glasshouses: The Impact of Data Envelopment Analysis (DEA) in Land Management Decision Making," Land, MDPI, vol. 8(1), pages 1-11, January.
    12. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Shadman, Foroogh, 2014. "Power industry restructuring and eco-efficiency changes: A new slacks-based model in Malmquist–Luenberger Index measurement," Energy Policy, Elsevier, vol. 68(C), pages 132-145.
    13. Zhou, Anhua & Li, Jun, 2021. "Investigate the impact of market reforms on the improvement of manufacturing energy efficiency under China’s provincial-level data," Energy, Elsevier, vol. 228(C).
    14. Harald Dyckhoff, 2018. "Multi-criteria production theory: foundation of non-financial and sustainability performance evaluation," Journal of Business Economics, Springer, vol. 88(7), pages 851-882, September.
    15. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    16. Xiong, Beibei & Chen, Haoxun & An, Qingxian & Wu, Jie, 2019. "A multi-objective distance friction minimization model for performance assessment through data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 279(1), pages 132-142.
    17. Song, Malin & Song, Yaqing & An, Qingxian & Yu, Huayin, 2013. "Review of environmental efficiency and its influencing factors in China: 1998–2009," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 8-14.
    18. Xu Wang & Liyan Han & Libo Yin, 2016. "Environmental Efficiency and Its Determinants for Manufacturing in China," Sustainability, MDPI, vol. 9(1), pages 1-18, December.
    19. Andreas Dellnitz & Madjid Tavana & Rajiv Banker, 2023. "A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis," Annals of Operations Research, Springer, vol. 322(2), pages 661-690, March.
    20. Halkos, George & Petrou, Kleoniki Natalia, 2018. "A critical review of the main methods to treat undesirable outputs in DEA," MPRA Paper 90374, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:19:p:12776-:d:935541. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.