Wed, Jan 22, 2025
[Archive]
.png)
Volume 8, Issue 1 (3-2022)
jhehp 2022, 8(1): 49-61 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Rezaei A, Dehghan Dehnavi H, Babaei Meybodi H, Anvari A. Evaluating Environmental Efficiency of European Union Countries with the Approach of Network Data Envelopment Analysis. jhehp 2022; 8 (1) :49-61
URL: http://jhehp.zums.ac.ir/article-1-465-en.html
URL: http://jhehp.zums.ac.ir/article-1-465-en.html
1- Department of Industrial Management, Yazd Branch, Islamic Azad University, Yazd, Iran.
2- Department of Management, Meybod University, Meybod, Iran.
3- Department of Industrial Management, Gachsaran Branch, I.A.U. Gachsaran, Iran.
2- Department of Management, Meybod University, Meybod, Iran.
3- Department of Industrial Management, Gachsaran Branch, I.A.U. Gachsaran, Iran.
Abstract: (4791 Views)
Background: Today, increasing the world’s population and efforts of countries to achieve economic growth, this research, aims to study the variables affecting economic and environmental efficiency.
Methods: In the first part of the envelopment analysis of network data the economic efficiency of European Union (EU) countries was calculated according to the input variables. In the second part, the environmental efficiency of EU countries was evaluated based on the two important outputs of greenhouse gas emissions and the absorption of polluting gases. Finally, countries were ranked accordingly.
Results: Correlation analysis showed that almost all input and output variables are positively correlated and thus meet the isotonic need. Likewise, all of them can be selected for evaluation using the DEA technique. Also the results indicated that 5 countries, including Denmark, France, Germany, the Netherlands, and the United Kingdom were efficient in the first stage. Besides, Cyprus, the Czech Republic, Ireland, Latvia, and Luxembourg were in the second step.
Conclusion: The results of this study showed that none of the countries was recognized as total efficiency. Thus, none of the countries were able to operate simultaneously in both the economic efficiency and the environmental efficiency phase.
Methods: In the first part of the envelopment analysis of network data the economic efficiency of European Union (EU) countries was calculated according to the input variables. In the second part, the environmental efficiency of EU countries was evaluated based on the two important outputs of greenhouse gas emissions and the absorption of polluting gases. Finally, countries were ranked accordingly.
Results: Correlation analysis showed that almost all input and output variables are positively correlated and thus meet the isotonic need. Likewise, all of them can be selected for evaluation using the DEA technique. Also the results indicated that 5 countries, including Denmark, France, Germany, the Netherlands, and the United Kingdom were efficient in the first stage. Besides, Cyprus, the Czech Republic, Ireland, Latvia, and Luxembourg were in the second step.
Conclusion: The results of this study showed that none of the countries was recognized as total efficiency. Thus, none of the countries were able to operate simultaneously in both the economic efficiency and the environmental efficiency phase.
Type of Study: Original Article |
Subject:
Environmental Health, Sciences, and Engineering
Received: 2021/11/27 | Accepted: 2022/01/24 | Published: 2022/03/16
Received: 2021/11/27 | Accepted: 2022/01/24 | Published: 2022/03/16
References
1. Baah C, Opoku Agyeman D, Acquah IS, Agyabeng Mensah Y, Afum E, Faibil D, et al. Examining the Correlations between Stakeholder Pressures, Green Production Practices, Firm Reputation, Environmental and Financial Performance: Evidence from Manufacturing SMEs. Sustain Prod Consum. 2021; 27:100-14. [Crossref] [Google Scholar]
2. Ahmad S, Wong KY, Elahi H. Sustainability Assessment and Analysis of Malaysian food Manufacturing Sector—A Move towards Sustainable Development. Adv Sci Lett. 2017; 23(9): 8942-6. [Crossref] [Google Scholar]
3. Jiang B, Li Y, Lio W, Li J. Sustainability Efficiency Evaluation of Seaports in China: an Uncertain Data Envelopment Analysis Approach. Soft Comput. 2020; 24(4): 2503-14. [Crossref] [Google Scholar]
4. Liu HH, Huang JJ, Chiu YH. Integration of Network Data Envelopment Analysis and Decision‐Making Trial and Evaluation Laboratory for the Performance Evaluation of the Financial Holding Companies in Taiwan. MDE Manage Decis Econ. 2020; 41(1): 64-78. [Crossref] [Google Scholar]
5. Grigoroudis E, Petridis K. Evaluation of National Environmental Efficiency underUncertainty Using Data Envelopment Analysis. Underst Risks Uncertain Energy Clim Policy. 2019; 161. [Crossref] [Google Scholar]
6. Robaina Alves M, Moutinho V, Macedo P. A New Frontier Approach to Model the Eco-Efficiency in European Countries. J Clean Prod. 2015; 103: 562-73. [Crossref] [Google Scholar]
7. Geamănu M. Economic efficiency and profitability. Studia Universitatis Vasile Goldiş, Arad-Seria Ştiinţe Economice. 2011; 21(2): 116-9 . Available from: URL: https://www.ceeol.com/search/article-detail?id=156526.
8. Pang R, Zhang X. Achieving Environmental Sustainability in Manufacture: A 28-year Bibliometric Cartography of Green Manufacturing Research. J Clean Prod. 2019; 233: 84-99. [Crossref] [Google Scholar]
9. Liu Y, Sun D, Wang H, Wang X, Yu G, Zhao X. An Evaluation of China’s Agricultural Green Production: 1978–2017. J Clean Prod. 2020; 243: 118483. [Crossref] [Google Scholar]
10. Wang K, Yu S, Zhang W. China’s Regional Energy and Environmental Efficiency: A DEA Window Analysis based Dynamic Evaluation. Math Comput Model. 2013; 58(5-6): 1117-27. [Crossref] [Google Scholar]
11. Yang Q, Wan X, Ma H. Assessing Green Development Efficiency of Municipalities and Provinces in China Integrating Models of Super-Efficiency DEA and Malmquist Index. Sustain. 2015; 7(4): 4492-510. [Crossref] [Google Scholar]
12. Zhou P, Poh KL, Ang BW. Data Envelopment Analysis for Measuring Environmental Performance. In Handbook of Operations Analytics Using Data Envelopment Analysis. Springer, Boston; MA. 2016; p. 31-49. [Crossref] [Google Scholar]
13. Liu X, Jie X. A Malmquist Index- Based Dynamic Industrial Green Efficiency Evaluation in Sichuan Province. Int Conference Manag Sci Eng Manag. Springer, Cham. 2017; 1361-73 . [Crossref] [Google Scholar]
14. Moutinho V, Madaleno M, Robaina M. The Economic and Environmental Efficiency Assessment in EU Cross- Country: Evidence from DEA and Quantile Regression Approach. Ecol Indic. 2017; 78: 85-97. [Crossref] [Google Scholar]
15. Vaninsky A. Energy- Environmental Efficiency and Optimal Restructuring of the Global Economy. Energy. 2018; 153: 338-48. [Crossref] [Google Scholar]
16. Halkos G, Petrou KN. Assessing 28 EU Member States' Environmental Efficiency in National Waste Generation with DEA. J Clean Prod. 2019; 208: 509-21. [Crossref] [Google Scholar]
17. Yang Z, Wei X. The Measurement and Influences of China's Urban Total Factor Energy Efficiency under Environmental Pollution: Based on the Game Cross-Efficiency DEA. J Clean Prod. 2019: 439-50. [Crossref] [Google Scholar]
18. Färe R. Measuring Farrell Efficiency for a Firm with Intermediate Inputs. Academia Eco Papers. 1991; 19(2): 329-40. [Article]
19. Tone K, Tsutsui M. Dynamic DEA: A Slacks-Based Measure Approach. Omega. 2010; 38(3-4): 145-56. [Crossref] [Google Scholar]
21. Yu MM. Assessing the Technical Efficiency, Service Effectiveness, and Technical Effectiveness of the World’s Railways Through NDEA Analysis. Transp Res Part A Policy Pract. 2008; 42(10): 1283-94. [Crossref] [Google Scholar]
22. Hsieh LF, Lin LH. A Performance Evaluation Model for International Tourist Hotels in Taiwan—an Application of the Relational Network DEA. Int J Hosp Manag. 2010; 29(1): 14-24. [Crossref] [Google Scholar]
23. Holod D, Lewis HF. Resolving the Deposit Dilemma: A new DEA Bank Efficiency Model. J Bank Financ. 2011; 35(11): 2801-10. [Crossref] [Google Scholar]
24. Tavassoli M, Ketabi S, Ghandehari M. Developing a Network DEA Model for Sustainability Analysis of Iran’s Electricity Distribution Network. Int J Electrical Power Energy Syst. 2020; 122: 106187. [Crossref] [Google Scholar]
25. Cook WD, Zhu J, Bi G, Yang F. Network DEA: Additive Efficiency Decomposition. Eur J Oper Res. 2010; 207(2): 1122-9. [Crossref] [Google Scholar]
26. Greenland SJ. Future Sustainability, Innovation and Marketing: A Framework for Understanding Impediments to Sustainable Innovation Adoption and Corporate Social Responsibility. In the Components of Sustainable Development . Springer; Singapore. 2019; p. 63-80. [Crossref] [Google Scholar]
27. Ulman SR, Mihai C, Cautisanu C. Inconsistencies in the Dynamics of Sustainable Development Dimensions in Central and Eastern European Countries. Pol J Environ Stud. 2021; 30(3): 2779-98. [Crossref] [Google Scholar]
28. Rezaee Z, Tsui J, Cheng P, Zhou G. Business Sustainability in Asia: Compliance, Performance, and Integrated Reporting and Assurance. John Wiley Sons; 2019. [Crossref] [Google Scholar]
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
© 2024 The Author(s)
