IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v65y2018i5p427-445.html
   My bibliography  Save this article

An alternative metafrontier framework for measuring the heterogeneity of technology

Author

Listed:
  • Qunwei Wang
  • Ye Hang
  • Jin‐Li Hu
  • Ching‐Ren Chiu

Abstract

The metafrontier framework proposed by O'Donnell et al. enables the evaluation of relative efficiencies for decision‐making units (DMUs) operating under heterogeneous technologies. The metatechnology ratio (MTR) constructed under the metafrontier framework helps estimate the gap between group frontiers and the metafrontier, with its score between 0 and 1. However, an unreasonable MTR value (ie, greater than 1) may appear when the traditional metafrontier framework is applied in the nonradial data envelopment analysis (DEA) models. This article proposes an alternative metafrontier framework for addressing this issue. The newly constructed technology gap measurement (TGM) can avoid unreasonable technology gap ratio values in nonradial DEA models and substitute for MTR in radial DEA models. To demonstrate how this alternative metafrontier approach works, this article applies it to the efficiency evaluation of regional transportation sectors in China.

Suggested Citation

  • Qunwei Wang & Ye Hang & Jin‐Li Hu & Ching‐Ren Chiu, 2018. "An alternative metafrontier framework for measuring the heterogeneity of technology," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(5), pages 427-445, August.
    • Handle: RePEc:wly:navres:v:65:y:2018:i:5:p:427-445
    DOI: 10.1002/nav.21815
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.21815
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.21815?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
    ---><---

    References listed on IDEAS

    as
    1. C. J. O’Donnell & Saeideh Fallah-Fini & Konstantinos Triantis, 2017. "Measuring and analysing productivity change in a metafrontier framework," Journal of Productivity Analysis, Springer, vol. 47(2), pages 117-128, April.
    2. Achour, Houda & Belloumi, Mounir, 2016. "Decomposing the influencing factors of energy consumption in Tunisian transportation sector using the LMDI method," Transport Policy, Elsevier, vol. 52(C), pages 64-71.
    3. William Cooper & Kyung Park & Jesus Pastor, 1999. "RAM: A Range Adjusted Measure of Inefficiency for Use with Additive Models, and Relations to Other Models and Measures in DEA," Journal of Productivity Analysis, Springer, vol. 11(1), pages 5-42, February.
    4. A. Charnes & W. W. Cooper & E. Rhodes, 1981. "Evaluating Program and Managerial Efficiency: An Application of Data Envelopment Analysis to Program Follow Through," Management Science, INFORMS, vol. 27(6), pages 668-697, June.
    5. tone, Kaoru, 2010. "Variations on the theme of slacks-based measure of efficiency in DEA," European Journal of Operational Research, Elsevier, vol. 200(3), pages 901-907, February.
    6. Zhang, Ning & Zhou, P. & Choi, Yongrok, 2013. "Energy efficiency, CO2 emission performance and technology gaps in fossil fuel electricity generation in Korea: A meta-frontier non-radial directional distance functionanalysis," Energy Policy, Elsevier, vol. 56(C), pages 653-662.
    7. Yujiro Hayami, 1969. "Sources of Agricultural Productivity Gap Among Selected Countries," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 51(3), pages 564-575.
    8. Toshiyuki Sueyoshi & Yan Yuan, 2016. "DEA Environmental Assessment (II): A Literature Study," International Series in Operations Research & Management Science, in: Shiuh-Nan Hwang & Hsuan-Shih Lee & Joe Zhu (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 0, pages 445-481, Springer.
    9. George Battese & D. Rao & Christopher O'Donnell, 2004. "A Metafrontier Production Function for Estimation of Technical Efficiencies and Technology Gaps for Firms Operating Under Different Technologies," Journal of Productivity Analysis, Springer, vol. 21(1), pages 91-103, January.
    10. Mitropoulos, Panagiotis & Talias, Μichael A. & Mitropoulos, Ioannis, 2015. "Combining stochastic DEA with Bayesian analysis to obtain statistical properties of the efficiency scores: An application to Greek public hospitals," European Journal of Operational Research, Elsevier, vol. 243(1), pages 302-311.
    11. 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.
    12. Dong-hyun Oh, 2010. "A global Malmquist-Luenberger productivity index," Journal of Productivity Analysis, Springer, vol. 34(3), pages 183-197, December.
    13. George E. Battese & D. S. Prasada Rao, 2002. "Technology Gap, Efficiency, and a Stochastic Metafrontier Function," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 1(2), pages 87-93, August.
    14. Cliff Huang & Tai-Hsin Huang & Nan-Hung Liu, 2014. "A new approach to estimating the metafrontier production function based on a stochastic frontier framework," Journal of Productivity Analysis, Springer, vol. 42(3), pages 241-254, December.
    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. 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.
    17. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    18. 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.
    19. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    20. Barros, Carlos Pestana & Managi, Shunsuke & Matousek, Roman, 2012. "The technical efficiency of the Japanese banks: Non-radial directional performance measurement with undesirable output," Omega, Elsevier, vol. 40(1), pages 1-8, January.
    21. Kontolaimou, Alexandra & Tsekouras, Kostas, 2010. "Are cooperatives the weakest link in European banking? A non-parametric metafrontier approach," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1946-1957, August.
    22. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    23. 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.
    24. Emrouznejad, Ali & Parker, Barnett R. & Tavares, Gabriel, 2008. "Evaluation of research in efficiency and productivity: A survey and analysis of the first 30 years of scholarly literature in DEA," Socio-Economic Planning Sciences, Elsevier, vol. 42(3), pages 151-157, September.
    25. Wang, Qunwei & Su, Bin & Zhou, Peng & Chiu, Ching-Ren, 2016. "Measuring total-factor CO2 emission performance and technology gaps using a non-radial directional distance function: A modified approach," Energy Economics, Elsevier, vol. 56(C), pages 475-482.
    26. Pastor, J. T. & Ruiz, J. L. & Sirvent, I., 1999. "An enhanced DEA Russell graph efficiency measure," European Journal of Operational Research, Elsevier, vol. 115(3), pages 596-607, June.
    27. R. G. Chambers & Y. Chung & R. Färe, 1998. "Profit, Directional Distance Functions, and Nerlovian Efficiency," Journal of Optimization Theory and Applications, Springer, vol. 98(2), pages 351-364, August.
    28. Chiu, Ching-Ren & Liou, Je-Liang & Wu, Pei-Ing & Fang, Chen-Ling, 2012. "Decomposition of the environmental inefficiency of the meta-frontier with undesirable output," Energy Economics, Elsevier, vol. 34(5), pages 1392-1399.
    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. Chao Wang & Yue‐Jun Zhang, 2020. "Does environmental regulation policy help improve green production performance? Evidence from China's industry," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(2), pages 937-951, March.
    2. Zhang, Yue-Jun & Jiang, Lin & Shi, Wei, 2020. "Exploring the growth-adjusted energy-emission efficiency of transportation industry in China," Energy Economics, Elsevier, vol. 90(C).
    3. Xingle Long & Chuanwang Sun & Chao Wu & Bin Chen & Kofi Agyenim Boateng, 2020. "Green innovation efficiency across China’s 30 provinces: estimate, comparison, and convergence," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1243-1260, October.
    4. Yusi Cheng & Xuejie Bai & Yung‐Ho Chiu, 2023. "Performance evaluation for health‐care sectors using a dynamic network data envelopment analysis approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(4), pages 2237-2253, June.
    5. Xingyu Dai & Dongna Zhang & Chi Keung Marco Lau & Qunwei Wang, 2023. "Multiobjective portfolio optimization: Forecasting and evaluation under investment horizon heterogeneity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2167-2196, December.
    6. Yu, Ming-Miin & See, Kok Fong & Hsiao, Bo, 2022. "Integrating group frontier and metafrontier directional distance functions to evaluate the efficiency of production units," European Journal of Operational Research, Elsevier, vol. 301(1), pages 254-276.
    7. Chen, Yingwen & Wong, Christina W.Y. & Yang, Rui & Miao, Xin, 2021. "Optimal structure adjustment strategy, emission reduction potential and utilization efficiency of fossil energies in China," Energy, Elsevier, vol. 237(C).
    8. Wang, Ying & Zhang, Dayong & Ji, Qiang & Shi, Xunpeng, 2020. "Regional renewable energy development in China: A multidimensional assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    9. Ching-Ren Chiu & Ming-Chung Chang & Jin-Li Hu, 2022. "Energy intensity improvement and energy productivity changes: an analysis of BRICS and G7 countries," Journal of Productivity Analysis, Springer, vol. 57(3), pages 297-311, June.
    10. Peng, Jiachao & Xiao, Jianzhong & Zhang, Lian & Wang, Teng, 2020. "The impact of China's ‘Atmosphere Ten Articles’ policy on total factor productivity of energy exploitation: Empirical evidence using synthetic control methods," Resources Policy, Elsevier, vol. 65(C).
    11. David Fang & Ming‐Ching Hsueh & Ching‐Ren Chiu, 2020. "An investigation of international hotel productivity considering quasifixed inputs and negative outputs," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(3), pages 380-388, April.
    12. Yu, Ming-Miin & Rakshit, Ipsita, 2023. "Assessing the dynamic efficiency and technology gap of airports under different ownerships: A union dynamic NDEA approach," Omega, Elsevier, vol. 119(C).
    13. Yu, Ming-Miin & Rakshit, Ipsita, 2024. "How to establish input and output targets for airlines with heterogeneous production technologies: A nash bargaining DEA approach within the meta-frontier framework," Journal of Air Transport Management, Elsevier, vol. 116(C).
    14. Arora, Nitin & Talwar, Shubhendra Jit, 2020. "Modelling efficiency in budget allocations for Indian states using window based non-radial non-concave metafrontier data envelopment analysis," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    15. Qian Wang & Jinbao Yang & Yung‐ho Chiu & Tai‐Yu Lin, 2023. "Cross‐regional comparative study on digital finance and finance efficiency in China: The eastern and non‐eastern areas," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 44(1), pages 68-83, January.
    16. Zha, Donglan & Yang, Guanglei & Wang, Qunwei, 2019. "Investigating the driving factors of regional CO2 emissions in China using the IDA-PDA-MMI method," Energy Economics, Elsevier, vol. 84(C).
    17. Ding, Tao & Yang, Jie & Wu, Huaqing & Liang, Liang, 2022. "Land use efficiency and technology gaps of urban agglomerations in China: An extended non-radial meta-frontier approach," Socio-Economic Planning Sciences, Elsevier, vol. 79(C).

    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. Rafael Benítez & Vicente Coll-Serrano & Vicente J. Bolós, 2021. "deaR-Shiny: An Interactive Web App for Data Envelopment Analysis," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    2. Fukuyama, Hirofumi & Weber, William L., 2009. "A directional slacks-based measure of technical inefficiency," Socio-Economic Planning Sciences, Elsevier, vol. 43(4), pages 274-287, December.
    3. Juan Aparicio & Magdalena Kapelko, 2019. "Enhancing the Measurement of Composite Indicators of Corporate Social Performance," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 144(2), pages 807-826, July.
    4. Bolós, V.J. & Benítez, R. & Coll-Serrano, V., 2024. "Chance constrained directional models in stochastic data envelopment analysis," Operations Research Perspectives, Elsevier, vol. 12(C).
    5. Kounetas, Konstantinos & Zervopoulos, Panagiotis D., 2019. "A cross-country evaluation of environmental performance: Is there a convergence-divergence pattern in technology gaps?," European Journal of Operational Research, Elsevier, vol. 273(3), pages 1136-1148.
    6. 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.
    7. Wang, Qunwei & Chiu, Yung-Ho & Chiu, Ching-Ren, 2017. "Non-radial metafrontier approach to identify carbon emission performance and intensity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 664-672.
    8. Ying Li & Yung-Ho Chiu & Liang Chun Lu, 2018. "Regional Energy, CO 2 , and Economic and Air Quality Index Performances in China: A Meta-Frontier Approach," Energies, MDPI, vol. 11(8), pages 1-20, August.
    9. Jesus Pastor & C. Lovell & Juan Aparicio, 2012. "Families of linear efficiency programs based on Debreu’s loss function," Journal of Productivity Analysis, Springer, vol. 38(2), pages 109-120, October.
    10. Cova-Alonso, David José & Díaz-Hernández, Juan José & Martínez-Budría, Eduardo, 2021. "A strong efficiency measure for CCR/BCC models," European Journal of Operational Research, Elsevier, vol. 291(1), pages 284-295.
    11. Akther, Syed & Fukuyama, Hirofumi & Weber, William L., 2013. "Estimating two-stage network Slacks-based inefficiency: An application to Bangladesh banking," Omega, Elsevier, vol. 41(1), pages 88-96.
    12. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali, 2015. "A new slacks-based measure of Malmquist–Luenberger index in the presence of undesirable outputs," Omega, Elsevier, vol. 51(C), pages 29-37.
    13. Aparicio, Juan & Monge, Juan F. & Ramón, Nuria, 2021. "A new measure of technical efficiency in data envelopment analysis based on the maximization of hypervolumes: Benchmarking, properties and computational aspects," European Journal of Operational Research, Elsevier, vol. 293(1), pages 263-275.
    14. Barbero, Javier & Zofío, José L., 2023. "The measurement of profit, profitability, cost and revenue efficiency through data envelopment analysis: A comparison of models using BenchmarkingEconomicEfficiency.jl," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    15. Xiangyu Teng & Danting Lu & Yung-ho Chiu, 2019. "Emission Reduction and Energy Performance Improvement with Different Regional Treatment Intensity in China," Energies, MDPI, vol. 12(2), pages 1-18, January.
    16. Kounetas, Kostas & Zervopoulos, Panagiotis, 2017. "Annex I and non-Annex I countries’productive performance revisited using a generalized directional distance function under a metafrontier framework: Is there any convergence-divergence pattern for tec," MPRA Paper 80904, University Library of Munich, Germany.
    17. Tianqun Xu & Ping Gao & Qian Yu & Debin Fang, 2017. "An Improved Eco-Efficiency Analysis Framework Based on Slacks-Based Measure Method," Sustainability, MDPI, vol. 9(6), pages 1-21, June.
    18. Pastor, Jesus T. & Lovell, C.A. Knox & Aparicio, Juan, 2020. "Defining a new graph inefficiency measure for the proportional directional distance function and introducing a new Malmquist productivity index," European Journal of Operational Research, Elsevier, vol. 281(1), pages 222-230.
    19. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    20. Vicente J. Bolós & Rafael Benítez & Vicente Coll-Serrano, 2023. "Continuous models combining slacks-based measures of efficiency and super-efficiency," 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. 31(2), pages 363-391, June.

    More about this item

    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:wly:navres:v:65:y:2018:i:5:p:427-445. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.