IDEAS home Printed from https://ideas.repec.org/a/ine/journl/v2y2013i44p153-163.html
   My bibliography  Save this article

Dimensions Of Sustainable Development In Romania - A Data Envelopment Analysis

Author

Listed:
  • Camelia BURJA

    (1 Decembrie 1918 University of Alba Iulia)

  • Vasile BURJA

Abstract

The efficiency registered by a country in the economic, social and ecological areas determines the growth pattern to achieve sustainable development. The contribution of each system component of sustainable development can be appreciated by various indicators. The main goal of this work is to present a possibility to evaluate the performance of new EU Member States related on the three important directions of sustainable development, using information from international databases. The paper used a Data Envelopment Analysis method for investigating the efficiency levels of sustainable development in the selected group of countries. These efficiency levels depend on each country's specific conditions in resources management. The application of the method led to obtaining an efficiency frontier, and the possibility of ranking the countries in accordance with their relative scores of sustainable performance. The results obtained highlight that Romania did not register enough efficiency in using its economic, social and ecological resources, since consistent possibilities to improve the sustainable performance existed. Some measures are identified for reducing the gaps between the Romanian economy and the other EU countries, which could lead to a better harmonization of the three sustainable development components and could increase their favourable effects.

Suggested Citation

  • Camelia BURJA & Vasile BURJA, 2013. "Dimensions Of Sustainable Development In Romania - A Data Envelopment Analysis," Romanian Journal of Economics, Institute of National Economy, vol. 37(2(46)), pages 153-163, December.
  • Handle: RePEc:ine:journl:v:2:y:2013:i:44:p:153-163
    as

    Download full text from publisher

    File URL: http://www.revecon.ro/articles/2013-2/2013-2-11.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Nataraja, Niranjan R. & Johnson, Andrew L., 2011. "Guidelines for using variable selection techniques in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 215(3), pages 662-669, 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. Isin Ceti̇n, 2017. "Accounting Requirements And Records On Bank Subscribed Capital Compliance With European Directives," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 1, pages 52-68, February.

    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. Patricija Bajec & Danijela Tuljak-Suban, 2019. "An Integrated Analytic Hierarchy Process—Slack Based Measure-Data Envelopment Analysis Model for Evaluating the Efficiency of Logistics Service Providers Considering Undesirable Performance Criteria," Sustainability, MDPI, vol. 11(8), pages 1-18, April.
    2. Peyrache, Antonio & Rose, Christiern & Sicilia, Gabriela, 2020. "Variable selection in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 282(2), pages 644-659.
    3. Esteve, Miriam & Aparicio, Juan & Rodriguez-Sala, Jesus J. & Zhu, Joe, 2023. "Random Forests and the measurement of super-efficiency in the context of Free Disposal Hull," European Journal of Operational Research, Elsevier, vol. 304(2), pages 729-744.
    4. Benítez-Peña, Sandra & Bogetoft, Peter & Romero Morales, Dolores, 2020. "Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach," Omega, Elsevier, vol. 96(C).
    5. Duras, Toni & Javed, Farrukh & Månsson, Kristofer & Sjölander, Pär & Söderberg, Magnus, 2023. "Using machine learning to select variables in data envelopment analysis: Simulations and application using electricity distribution data," Energy Economics, Elsevier, vol. 120(C).
    6. Eskelinen, Juha, 2017. "Comparison of variable selection techniques for data envelopment analysis in a retail bank," European Journal of Operational Research, Elsevier, vol. 259(2), pages 778-788.
    7. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2013. "Dealing with the Endogeneity Problem in Data Envelopment Analysis," MPRA Paper 47475, University Library of Munich, Germany.
    8. Anna Łozowicka & Bartłomiej Lach, 2022. "CI-DEA: A Way to Improve the Discriminatory Power of DEA—Using the Example of the Efficiency Assessment of the Digitalization in the Life of the Generation 50+," Sustainability, MDPI, vol. 14(6), pages 1-22, March.
    9. Raul Moragues & Juan Aparicio & Miriam Esteve, 2023. "Ranking the Importance of Variables in a Nonparametric Frontier Analysis Using Unsupervised Machine Learning Techniques," Mathematics, MDPI, vol. 11(11), pages 1-24, June.
    10. Congcong Yang & Alfred Taudes & Guozhi Dong, 2017. "Efficiency analysis of European Freight Villages: three peers for benchmarking," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 91-122, March.
    11. Maria Elisabete Neves & Carla Henriques & João Vilas, 2021. "Financial performance assessment of electricity companies: evidence from Portugal," Operational Research, Springer, vol. 21(4), pages 2809-2857, December.
    12. Charles Henri DiMaria & Chiara Peroni & Francesco Sarracino, 2020. "Happiness Matters: Productivity Gains from Subjective Well-Being," Journal of Happiness Studies, Springer, vol. 21(1), pages 139-160, January.
    13. Veiga, Gabriela Lobo & Pinheiro de Lima, Edson & Frega, José Roberto & Gouvea da Costa, Sérgio Eduardo, 2021. "A DEA-based approach to assess manufacturing performance through operations strategy lenses," International Journal of Production Economics, Elsevier, vol. 235(C).
    14. Toloo, Mehdi & Keshavarz, Esmaeil & Hatami-Marbini, Adel, 2021. "Selecting data envelopment analysis models: A data-driven application to EU countries," Omega, Elsevier, vol. 101(C).
    15. Tenente, Marcos & Henriques, Carla & da Silva, Patrícia Pereira, 2020. "Eco-efficiency assessment of the electricity sector: Evidence from 28 European Union countries," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 293-314.
    16. Pavala Malar Kannan & Govindan Marthandan & Rathimala Kannan, 2021. "Modelling Efficiency of Electric Utilities Using Three Stage Virtual Frontier Data Envelopment Analysis with Variable Selection by Loads Method," Energies, MDPI, vol. 14(12), pages 1-21, June.
    17. Santos, Sérgio P. & Amado, Carla A.F., 2014. "On the need for reform of the Portuguese judicial system – Does Data Envelopment Analysis assessment support it?," Omega, Elsevier, vol. 47(C), pages 1-16.
    18. Adler, Nicole & Liebert, Vanessa & Yazhemsky, Ekaterina, 2013. "Benchmarking airports from a managerial perspective," Omega, Elsevier, vol. 41(2), pages 442-458.
    19. Huang, Yuti & Coelho, Vânia R., 2017. "Sustainability performance assessment focusing on coral reef protection by the tourism industry in the Coral Triangle region," Tourism Management, Elsevier, vol. 59(C), pages 510-527.
    20. Cordero, José Manuel & Santín, Daniel & Sicilia, Gabriela, 2015. "Testing the accuracy of DEA estimates under endogeneity through a Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 244(2), pages 511-518.

    More about this item

    Keywords

    sustainable development; sustainable performance; DEA model; assessment;
    All these keywords.

    JEL classification:

    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development
    • O47 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
    • Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation

    Statistics

    Access and download statistics

    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:ine:journl:v:2:y:2013:i:44:p:153-163. 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: Valentina Vasile (email available below). General contact details of provider: https://edirc.repec.org/data/inacaro.html .

    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.