IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v159y2018icp599-610.html
   My bibliography  Save this article

Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model

Author

Listed:
  • Wu, Yunna
  • Ke, Yiming
  • Zhang, Ting
  • Liu, Fangtong
  • Wang, Jing

Abstract

Based on the idea of coordinated and sustainable development, the photovoltaic poverty alleviation project (PPAP) supplies clean electricity and assists poverty-stricken households, which receives widespread attention from the society. However, the existing efficiency assessment models can neither well consider both the economic and social benefits of the PPAP nor provide pertinent site selection suggestions. To accurately evaluate the performance efficiency and explore the influencing factors, a modified three-phase model is proposed: First of all, a two-step approach combining Pearson correlation coefficient and super-efficiency analysis is adopted to screen out unreasonable variables and outliers, which improves the reliability of subsequent calculations; Next, the bootstrapping algorithm is introduced to optimize the data envelopment analysis model, which effectively corrects the bias and guarantee the model accuracy; Finally, the potential environment variables are extracted from both the electricity conversion process and the poverty alleviation procedure, and further verified by Tobit regression, which provides managers with more comprehensive decision support. According to the results, the performance efficiency of PPAPs in China is generally low due to the unreasonable production scale. Most projects are suffering excessive labor input. Moreover, improper site selection is also a cause for low efficiency, and some corresponding suggestions are proposed.

Suggested Citation

  • Wu, Yunna & Ke, Yiming & Zhang, Ting & Liu, Fangtong & Wang, Jing, 2018. "Performance efficiency assessment of photovoltaic poverty alleviation projects in China: A three-phase data envelopment analysis model," Energy, Elsevier, vol. 159(C), pages 599-610.
    • Handle: RePEc:eee:energy:v:159:y:2018:i:c:p:599-610
    DOI: 10.1016/j.energy.2018.06.187
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218312520
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2018.06.187?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. Jinpeng Liu & Yun Long & Xiaohua Song, 2017. "A Study on the Conduction Mechanism and Evaluation of the Comprehensive Efficiency of Photovoltaic Power Generation in China," Energies, MDPI, vol. 10(5), pages 1-22, May.
    2. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    3. Worthington, Andrew C. & Zelenyuk, Valentin, 2018. "Data envelopment analysis, truncated regression and double-bootstrap for panel data with application to Chinese bankingAuthor-Name: Du, Kai," European Journal of Operational Research, Elsevier, vol. 265(2), pages 748-764.
    4. Sueyoshi, Toshiyuki & Goto, Mika, 2017. "Measurement of returns to scale on large photovoltaic power stations in the United States and Germany," Energy Economics, Elsevier, vol. 64(C), pages 306-320.
    5. Moon, Hana & Min, Daiki, 2017. "Assessing energy efficiency and the related policy implications for energy-intensive firms in Korea: DEA approach," Energy, Elsevier, vol. 133(C), pages 23-34.
    6. Baurzhan, Saule & Jenkins, Glenn P., 2016. "Off-grid solar PV: Is it an affordable or appropriate solution for rural electrification in Sub-Saharan African countries?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1405-1418.
    7. Wang, Zhaohua & Feng, Chao & Zhang, Bin, 2014. "An empirical analysis of China's energy efficiency from both static and dynamic perspectives," Energy, Elsevier, vol. 74(C), pages 322-330.
    8. 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.
    9. Zhimin Dai & Lu Guo & Zhengyi Jiang, 2016. "Study on the industrial Eco-Efficiency in East China based on the Super Efficiency DEA Model: an example of the 2003–2013 panel data," Applied Economics, Taylor & Francis Journals, vol. 48(59), pages 5779-5785, December.
    10. Simar, Leopold & Wilson, Paul W., 2007. "Estimation and inference in two-stage, semi-parametric models of production processes," Journal of Econometrics, Elsevier, vol. 136(1), pages 31-64, January.
    11. Kadziński, Miłosz & Labijak, Anna & Napieraj, Małgorzata, 2017. "Integrated framework for robustness analysis using ratio-based efficiency model with application to evaluation of Polish airports," Omega, Elsevier, vol. 67(C), pages 1-18.
    12. Simar, Leopold & Wilson, Paul W., 1999. "Estimating and bootstrapping Malmquist indices," European Journal of Operational Research, Elsevier, vol. 115(3), pages 459-471, June.
    13. Hall, Peter, 1984. "Central limit theorem for integrated square error of multivariate nonparametric density estimators," Journal of Multivariate Analysis, Elsevier, vol. 14(1), pages 1-16, February.
    14. Banker, Rajiv D. & Chang, Hsihui, 2006. "The super-efficiency procedure for outlier identification, not for ranking efficient units," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1311-1320, December.
    15. Léopold Simar & Paul W. Wilson, 1998. "Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models," Management Science, INFORMS, vol. 44(1), pages 49-61, January.
    16. Wang, Zhaohua & Li, Yi & Wang, Ke & Huang, Zhimin, 2017. "Environment-adjusted operational performance evaluation of solar photovoltaic power plants: A three stage efficiency analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1153-1162.
    17. Raymond L. Raab & Richard W. Lichty, 2002. "Identifying Subareas That Comprise A Greater Metropolitan Area: The Criterion of County Relative Efficiency," Journal of Regional Science, Wiley Blackwell, vol. 42(3), pages 579-594, August.
    18. Jebali, Eya & Essid, Hédi & Khraief, Naceur, 2017. "The analysis of energy efficiency of the Mediterranean countries: A two-stage double bootstrap DEA approach," Energy, Elsevier, vol. 134(C), pages 991-1000.
    19. Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
    20. Liu, C.H. & Lin, Sue J. & Lewis, Charles, 2010. "Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis," Energy Policy, Elsevier, vol. 38(2), pages 1049-1058, February.
    21. Guo, Xiaoying & Lu, Ching-Cheng & Lee, Jen-Hui & Chiu, Yung-Ho, 2017. "Applying the dynamic DEA model to evaluate the energy efficiency of OECD countries and China," Energy, Elsevier, vol. 134(C), pages 392-399.
    22. 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.
    23. Kristof Witte & Rui Marques, 2010. "Influential observations in frontier models, a robust non-oriented approach to the water sector," Annals of Operations Research, Springer, vol. 181(1), pages 377-392, December.
    24. Chowdhury, Hedayet & Zelenyuk, Valentin, 2016. "Performance of hospital services in Ontario: DEA with truncated regression approach," Omega, Elsevier, vol. 63(C), pages 111-122.
    25. Sueyoshi, Toshiyuki & Wang, Derek, 2017. "Measuring scale efficiency and returns to scale on large commercial rooftop photovoltaic systems in California," Energy Economics, Elsevier, vol. 65(C), pages 389-398.
    26. Emrouznejad, Ali & Rostami-Tabar, Bahman & Petridis, Konstantinos, 2016. "A novel ranking procedure for forecasting approaches using Data Envelopment Analysis," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 235-243.
    27. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    28. Fethi, Meryem Duygun & Pasiouras, Fotios, 2010. "Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey," European Journal of Operational Research, Elsevier, vol. 204(2), pages 189-198, July.
    29. Wang, Derek D. & Sueyoshi, Toshiyuki, 2017. "Assessment of large commercial rooftop photovoltaic system installations: Evidence from California," Applied Energy, Elsevier, vol. 188(C), pages 45-55.
    30. Sueyoshi, Toshiyuki & Goto, Mika, 2014. "Photovoltaic power stations in Germany and the United States: A comparative study by data envelopment analysis," Energy Economics, Elsevier, vol. 42(C), pages 271-288.
    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. Marcel Clermont & Julia Schaefer, 2019. "Identification of Outliers in Data Envelopment Analysis," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 71(4), pages 475-496, October.
    2. Sebastian Kohl & Jan Schoenfelder & Andreas Fügener & Jens O. Brunner, 2019. "The use of Data Envelopment Analysis (DEA) in healthcare with a focus on hospitals," Health Care Management Science, Springer, vol. 22(2), pages 245-286, June.
    3. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    4. Zhang, Zumeng & Ding, Liping & Wang, Chaofan & Dai, Qiyao & Shi, Yin & Zhao, Yujia & Zhu, Yuxuan, 2022. "Do operation and maintenance contracts help photovoltaic poverty alleviation power stations perform better?," Energy, Elsevier, vol. 259(C).
    5. Kristof De Witte & Rui Marques, 2010. "Designing performance incentives, an international benchmark study in the water sector," 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. 18(2), pages 189-220, June.
    6. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    7. Rita Bastião & Nuno de Sousa Pereira, 2020. "Performance in the Delivery of Primary Health Care Services: A Longitudinal Analysis," CEF.UP Working Papers 2002, Universidade do Porto, Faculdade de Economia do Porto.
    8. Quaranta, Anna Grazia & Raffoni, Anna & Visani, Franco, 2018. "A multidimensional approach to measuring bank branch efficiency," European Journal of Operational Research, Elsevier, vol. 266(2), pages 746-760.
    9. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    10. Pontus Mattsson & Jonas Månsson & Christian Andersson & Fredrik Bonander, 2018. "A bootstrapped Malmquist index applied to Swedish district courts," European Journal of Law and Economics, Springer, vol. 46(1), pages 109-139, August.
    11. Barros, Carlos Pestana & Peypoch, Nicolas, 2008. "Technical efficiency of thermoelectric power plants," Energy Economics, Elsevier, vol. 30(6), pages 3118-3127, November.
    12. Chen, Xin & Zhou, Wenjia, 2023. "Performance evaluation of aquavoltaics in China: Retrospect and prospect," Renewable and Sustainable Energy Reviews, Elsevier, vol. 173(C).
    13. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    14. Wang, Zihan & Li, Jiaxin & Liu, Jing & Shuai, Chuanmin, 2020. "Is the photovoltaic poverty alleviation project the best way for the poor to escape poverty? ——A DEA and GRA analysis of different projects in rural China," Energy Policy, Elsevier, vol. 137(C).
    15. Nakamoto, Yuya & Eguchi, Shogo & Takayabu, Hirotaka, 2024. "Efficiency and benchmarks for photovoltaic power generation amid uncertain conditions," Socio-Economic Planning Sciences, Elsevier, vol. 94(C).
    16. Li, Jiaxin & Wang, Zihan & Cheng, Xin & Shuai, Jing & Shuai, Chuanmin & Liu, Jing, 2020. "Has solar PV achieved the national poverty alleviation goals? Empirical evidence from the performances of 52 villages in rural China," Energy, Elsevier, vol. 201(C).
    17. Zervopoulos, Panagiotis & Emrouznejad, Ali & Sklavos, Sokratis, 2019. "A Bayesian approach for correcting bias of data envelopment analysis estimators," MPRA Paper 91886, University Library of Munich, Germany.
    18. Sickles, Robin C. & Song, Wonho & Zelenyuk, Valentin, 2018. "Econometric Analysis of Productivity: Theory and Implementation in R," Working Papers 18-008, Rice University, Department of Economics.
    19. Kaffash, Sepideh & Azizi, Roza & Huang, Ying & Zhu, Joe, 2020. "A survey of data envelopment analysis applications in the insurance industry 1993–2018," European Journal of Operational Research, Elsevier, vol. 284(3), pages 801-813.
    20. Dag Edvardsen & Finn Førsund & Sverre Kittelsen, 2008. "Far out or alone in the crowd: a taxonomy of peers in DEA," Journal of Productivity Analysis, Springer, vol. 29(3), pages 201-210, June.

    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:energy:v:159:y:2018:i:c:p:599-610. 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.journals.elsevier.com/energy .

    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.