IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v209y2025ics1364032124008633.html
   My bibliography  Save this article

Evaluating efficiency of green innovations and renewables for sustainability goals

Author

Listed:
  • Alnafrah, Ibrahim

Abstract

Understanding the efficiency dynamics of green innovations is essential for advancing sustainable economic systems. This study evaluates the efficiency of forty-two countries in producing and utilizing green innovations for clean energy production and in achieving sustainable development goals from 2000 to 2020. Employing a network bias-corrected data envelopment analysis (DEA) and Malmquist productivity analysis, this study explores the adoption of green technology and its effects on economic and environmental efficiency. Findings reveal limited progress in clean energy efficiency across most countries, indicating suboptimal use of green innovations for the goals of affordable and clean energy and climate action). The results show that the efficiency pattern of green innovations follows a U-shaped curve, with initial inefficiencies followed by long-term gains. South American nations and the European Union demonstrate strong performance in integrating green technologies. However, green innovations alone appear insufficient; supportive policies, such as green taxes on emissions and renewable energy initiatives, are crucial for enhancing impact and achieving environmental sustainability.

Suggested Citation

  • Alnafrah, Ibrahim, 2025. "Evaluating efficiency of green innovations and renewables for sustainability goals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
    • Handle: RePEc:eee:rensus:v:209:y:2025:i:c:s1364032124008633
    DOI: 10.1016/j.rser.2024.115137
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032124008633
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2024.115137?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Masaaki Hirooka, 2003. "Nonlinear dynamism of innovation and business cycles," Journal of Evolutionary Economics, Springer, vol. 13(5), pages 549-576, December.
    2. Chen, Xun-Qi & Ma, Chao-Qun & Ren, Yi-Shuai & Lei, Yu-Tian, 2023. "Carbon allowance auction design of China's ETS: A comprehensive hierarchical system based on blockchain," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1003-1019.
    3. Sachs,Jeffrey D. & Kroll,Christian & Lafortune,Guillame & Fuller,Grayson & Woelm,Finn, 2022. "Sustainable Development Report 2022," Cambridge Books, Cambridge University Press, number 9781009210034, June.
    4. Alois Kneip & Léopold Simar & Paul Wilson, 2011. "A Computationally Efficient, Consistent Bootstrap for Inference with Non-parametric DEA Estimators," Computational Economics, Springer;Society for Computational Economics, vol. 38(4), pages 483-515, November.
    5. Emrouznejad, Ali & Yang, Guo-liang, 2018. "A survey and analysis of the first 40 years of scholarly literature in DEA: 1978–2016," Socio-Economic Planning Sciences, Elsevier, vol. 61(C), pages 4-8.
    6. Sohag, Kazi & Sokolova, Yulia & Vilamová, Šárka & Blueschke, Dmitri, 2023. "Volatility transmission from critical minerals prices to green investments," Resources Policy, Elsevier, vol. 82(C).
    7. 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.
    8. Léopold Simar & Paul Wilson, 2011. "Inference by the m out of n bootstrap in nonparametric frontier models," Journal of Productivity Analysis, Springer, vol. 36(1), pages 33-53, August.
    9. Chen, Wei & Zou, Wandan & Zhong, Kaiyang & Aliyeva, Alina, 2023. "Machine learning assessment under the development of green technology innovation: A perspective of energy transition," Renewable Energy, Elsevier, vol. 214(C), pages 65-73.
    10. Jan Fagerberg & Maryann P. Feldman & Martin Srholec, 2014. "Technological dynamics and social capability: US states and European nations," Journal of Economic Geography, Oxford University Press, vol. 14(2), pages 313-337.
    11. Chien, Fengsheng & Ananzeh, Mohammed & Mirza, Farhan & Bakar, Abou & Vu, Hieu Minh & Ngo, Thanh Quang, 2021. "The effects of green growth, environmental-related tax, and eco-innovation towards carbon neutrality target in the US economy," MPRA Paper 109664, University Library of Munich, Germany.
    12. Susskind, Lawrence & Chun, Jungwoo & Gant, Alexander & Hodgkins, Chelsea & Cohen, Jessica & Lohmar, Sarah, 2022. "Sources of opposition to renewable energy projects in the United States," Energy Policy, Elsevier, vol. 165(C).
    13. Liao, Jixiang & Liu, Xingye & Zhou, Xueyan & Tursunova, Nargiza Rakhimovna, 2023. "Analyzing the role of renewable energy transition and industrialization on ecological sustainability: Can green innovation matter in OECD countries," Renewable Energy, Elsevier, vol. 204(C), pages 141-151.
    14. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    15. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    16. Karlilar, Selin & Balcilar, Mehmet & Emir, Firat, 2023. "Environmental sustainability in the OECD: The power of digitalization, green innovation, renewable energy and financial development," Telecommunications Policy, Elsevier, vol. 47(6).
    17. Tchorzewska, K.B. & Garcia-Quevedo, J. & Martinez-Ros, E., 2022. "The heterogeneous effects of environmental taxation on green technologies," Research Policy, Elsevier, vol. 51(7).
    18. Sachs,Jeffrey D. & Kroll,Christian & Lafortune,Guillame & Fuller,Grayson & Woelm,Finn, 2022. "Sustainable Development Report 2022," Cambridge Books, Cambridge University Press, number 9781009210089, June.
    19. Heffron, Raphael J. & McCauley, Darren, 2022. "The ‘just transition’ threat to our Energy and Climate 2030 targets," Energy Policy, Elsevier, vol. 165(C).
    20. Wang, Mei Ling, 2023. "Effects of the green finance policy on the green innovation efficiency of the manufacturing industry: A difference-in-difference model," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    21. Doğan, Buhari & Chu, Lan Khanh & Ghosh, Sudeshna & Diep Truong, Huong Hoang & Balsalobre-Lorente, Daniel, 2022. "How environmental taxes and carbon emissions are related in the G7 economies?," Renewable Energy, Elsevier, vol. 187(C), pages 645-656.
    22. Chiang Kao, 2014. "Efficiency Decomposition in Network Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Wade D. Cook & Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 0, pages 55-77, Springer.
    23. Romer, Paul M, 1990. "Endogenous Technological Change," Journal of Political Economy, University of Chicago Press, vol. 98(5), pages 71-102, October.
    24. Du, Kerui & Li, Jianglong, 2019. "Towards a green world: How do green technology innovations affect total-factor carbon productivity," Energy Policy, Elsevier, vol. 131(C), pages 240-250.
    25. Sanya Carley & David M. Konisky, 2020. "The justice and equity implications of the clean energy transition," Nature Energy, Nature, vol. 5(8), pages 569-577, August.
    26. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    27. Xie, Peijun & Jamaani, Fouad, 2022. "Does green innovation, energy productivity and environmental taxes limit carbon emissions in developed economies: Implications for sustainable development," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 66-78.
    28. Parrish Bergquist & Christopher Warshaw, 2023. "How climate policy commitments influence energy systems and the economies of US states," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    29. Du, Kerui & Li, Pengzhen & Yan, Zheming, 2019. "Do green technology innovations contribute to carbon dioxide emission reduction? Empirical evidence from patent data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 297-303.
    Full references (including those not matched with items on IDEAS)

    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. Liu, Yin & Alnafrah, Ibrahim & Zhou, Yaying, 2024. "A systemic efficiency measurement of resource management and sustainable practices: A network bias-corrected DEA assessment of OECD countries," Resources Policy, Elsevier, vol. 90(C).
    2. Ibrahim Alnafrah, 2021. "Efficiency evaluation of BRICS’s national innovation systems based on bias-corrected network data envelopment analysis," Journal of Innovation and Entrepreneurship, Springer, vol. 10(1), pages 1-28, December.
    3. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    4. Camanho, Ana Santos & Silva, Maria Conceicao & Piran, Fabio Sartori & Lacerda, Daniel Pacheco, 2024. "A literature review of economic efficiency assessments using Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 315(1), pages 1-18.
    5. Sinuany-Stern, Zilla, 2023. "Foundations of operations research: From linear programming to data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1069-1080.
    6. Koronakos, Gregory & Sotiros, Dimitris & Despotis, Dimitris K. & Kritikos, Manolis N., 2022. "Fair efficiency decomposition in network DEA: A compromise programming approach," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).
    7. Peykani, Pejman & Seyed Esmaeili, Fatemeh Sadat & Pishvaee, Mir Saman & Rostamy-Malkhalifeh, Mohsen & Hosseinzadeh Lotfi, Farhad, 2024. "Matrix-based network data envelopment analysis: A common set of weights approach," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    8. Amirteimoori, Alireza & Kou, Gang, 2024. "Technical efficiency and managerial ability in two-stage production processes with undesirable products: A case on Asian banks," Socio-Economic Planning Sciences, Elsevier, vol. 96(C).
    9. Chen, Lei & Wang, Ying-Ming, 2025. "Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale," European Journal of Operational Research, Elsevier, vol. 322(1), pages 157-170.
    10. Fatemeh Sadat Seyed Esmaeili & Emran Mohammadi, 2024. "Z-number network data envelopment analysis approach: A case study on the Iranian insurance industry," PLOS ONE, Public Library of Science, vol. 19(7), pages 1-26, July.
    11. Georgiou, Andreas C. & Thanassoulis, Emmanuel & Papadopoulou, Alexandra, 2022. "Using data envelopment analysis in markovian decision making," European Journal of Operational Research, Elsevier, vol. 298(1), pages 276-292.
    12. Simar, Léopold & Wilson, Paul W., 2020. "Technical, allocative and overall efficiency: Estimation and inference," European Journal of Operational Research, Elsevier, vol. 282(3), pages 1164-1176.
    13. Pejman Peykani & Farhad Hosseinzadeh Lotfi & Seyed Jafar Sadjadi & Ali Ebrahimnejad & Emran Mohammadi, 2022. "Fuzzy chance-constrained data envelopment analysis: a structured literature review, current trends, and future directions," Fuzzy Optimization and Decision Making, Springer, vol. 21(2), pages 197-261, June.
    14. Dariush Akbarian, 2021. "Network DEA based on DEA-ratio," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-26, December.
    15. Mohammad Tavassoli & Mahsa Ghandehari & Masoud Taherinia, 2023. "Rang-adjusted measure: modelling and computational aspects from internal and external perspectives for network DEA," Operational Research, Springer, vol. 23(4), pages 1-34, December.
    16. Yang, Guo-liang & Fukuyama, Hirofumi & Chen, Kun, 2019. "Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach," Omega, Elsevier, vol. 84(C), pages 141-159.
    17. Moraes, Ricardo Kalil & Wanke, Peter Fernandes & Faria, João Ricardo, 2021. "Unveiling the endogeneity between social-welfare and labor efficiency: Two-stage NDEA neural network approach," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    18. Andrey V. Lychev & Svetlana V. Ratner & Vladimir E. Krivonozhko, 2023. "Two-Stage Data Envelopment Analysis Models with Negative System Outputs for the Efficiency Evaluation of Government Financial Policies," Mathematics, MDPI, vol. 11(24), pages 1-21, December.
    19. Kao, Chiang, 2022. "A maximum slacks-based measure of efficiency for closed series production systems," Omega, Elsevier, vol. 106(C).
    20. Vitor Miguel Ribeiro & Celeste Varum & Ana Dias Daniel, 2021. "Introducing microeconomic foundation in data envelopment analysis: effects of the ex ante regulation principle on regional performance," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(3), pages 1215-1244, September.

    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:eee:rensus:v:209:y:2025:i:c:s1364032124008633. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .

    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.