IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v11y2018i3p519-d133938.html
   My bibliography  Save this article

A Nonparametric Economic Analysis of the US Natural Gas Transmission Infrastructure: Efficiency, Trade-Offs and Emerging Industry Configurations

Author

Listed:
  • Corrado Lo Storto

    (Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy)

Abstract

This paper presents a study aimed at measuring the efficiency of the transmission segment of the US natural gas industry from an economic perspective. The gas transmission infrastructure is modeled as an economic production function and a multi-stage modeling approach based on the implementation of Data Envelopment Analysis is employed to obtain an efficiency measure in a two-dimension performance space, i.e., cost and revenue-efficiency. This approach allows taking into account conflicting business goals. The study also performs cluster analysis to uncover homogeneous efficiency profiles relative to the gas transmission systems to explore determinants of efficiency rates, and trade-off situations. A sample containing 80 US gas transmission systems is used in the analysis. Results indicate that the transmission segment of the US gas industry has considerable inefficiencies, while average cost and revenue-efficiency scores are 0.324 and 0.301, and only three transmission systems achieve high scores on both efficiency dimensions. Cluster analysis identified seven configurations. In three of them there are no trade-off situations between cost and revenue efficiencies. However, only in one of them gas transmission systems have high efficiencies. The remaining four configurations exhibit trade-off situations having different intensity. Such trade-offs can be determined by the gas transmission infrastructure size.

Suggested Citation

  • Corrado Lo Storto, 2018. "A Nonparametric Economic Analysis of the US Natural Gas Transmission Infrastructure: Efficiency, Trade-Offs and Emerging Industry Configurations," Energies, MDPI, vol. 11(3), pages 1-24, February.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:3:p:519-:d:133938
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/11/3/519/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/11/3/519/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nieswand, Maria & Cullmann, Astrid & Neumann, Anne, 2010. "Overcoming Data Limitations in Nonparametric Benchmarking: Applying PCA-DEA to Natural Gas Transmission," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 9(2).
    2. Hawdon, David, 2003. "Efficiency, performance and regulation of the international gas industry--a bootstrap DEA approach," Energy Policy, Elsevier, vol. 31(11), pages 1167-1178, September.
    3. Jamasb, Tooraj & Pollitt, Michael & Triebs, Thomas, 2008. "Productivity and efficiency of US gas transmission companies: A European regulatory perspective," Energy Policy, Elsevier, vol. 36(9), pages 3398-3412, September.
    4. Goncharuk, Anatoliy G. & Storto, Corrado lo, 2017. "Challenges and policy implications of gas reform in Italy and Ukraine: Evidence from a benchmarking analysis," Energy Policy, Elsevier, vol. 101(C), pages 456-466.
    5. Tone, Kaoru & Tsutsui, Miki, 2009. "Network DEA: A slacks-based measure approach," European Journal of Operational Research, Elsevier, vol. 197(1), pages 243-252, August.
    6. Daniel Hollas & Kenneth Macleod & Stanley Stansell, 2002. "A data envelopment analysis of gas utilities' efficiency," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 123-137, June.
    7. lo Storto, Corrado, 2018. "Ownership structure and the technical, cost, and revenue efficiency of Italian airports," Utilities Policy, Elsevier, vol. 50(C), pages 175-193.
    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. Glenn Milligan & Martha Cooper, 1985. "An examination of procedures for determining the number of clusters in a data set," Psychometrika, Springer;The Psychometric Society, vol. 50(2), pages 159-179, June.
    10. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    11. Erbetta, Fabrizio & Rappuoli, Luca, 2008. "Optimal scale in the Italian gas distribution industry using data envelopment analysis," Omega, Elsevier, vol. 36(2), pages 325-336, April.
    12. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "A survey of data envelopment analysis in energy and environmental studies," European Journal of Operational Research, Elsevier, vol. 189(1), pages 1-18, August.
    13. 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.
    14. Mardani, Abbas & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Jusoh, Ahmad & Khoshnoudi, Masoumeh, 2017. "A comprehensive review of data envelopment analysis (DEA) approach in energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 1298-1322.
    15. 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.
    16. William W. Cooper & Lawrence M. Seiford & Kaoru Tone, 2007. "Data Envelopment Analysis," Springer Books, Springer, edition 0, number 978-0-387-45283-8, 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. Mocholi-Arce, Manuel & Sala-Garrido, Ramon & Molinos-Senante, Maria & Maziotis, Alexandros, 2022. "Performance assessment of the Chilean water sector: A network data envelopment analysis approach," Utilities Policy, Elsevier, vol. 75(C).
    2. Corrado Lo Storto, 2018. "Efficiency, Conflicting Goals and Trade-Offs: A Nonparametric Analysis of the Water and Wastewater Service Industry in Italy," Sustainability, MDPI, vol. 10(4), pages 1-22, March.

    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. Jindal, Abhinav & Nilakantan, Rahul, 2021. "Falling efficiency levels of Indian coal-fired power plants: A slacks-based analysis," Energy Economics, Elsevier, vol. 93(C).
    2. Corrado Lo Storto, 2018. "Efficiency, Conflicting Goals and Trade-Offs: A Nonparametric Analysis of the Water and Wastewater Service Industry in Italy," Sustainability, MDPI, vol. 10(4), pages 1-22, March.
    3. Tajbakhsh, Alireza & Hassini, Elkafi, 2018. "Evaluating sustainability performance in fossil-fuel power plants using a two-stage data envelopment analysis," Energy Economics, Elsevier, vol. 74(C), pages 154-178.
    4. Capece, Guendalina & Costa, Roberta & Di Pillo, Francesca, 2021. "Benchmarking the efficiency of natural gas distribution utilities in Italy considering size, ownership, and maturity," Utilities Policy, Elsevier, vol. 72(C).
    5. Li, Lan-Bing & Hu, Jin-Li, 2012. "Ecological total-factor energy efficiency of regions in China," Energy Policy, Elsevier, vol. 46(C), pages 216-224.
    6. Vincenzo Patrizii & Anna Pettini & Giuliano Resce, 2017. "The Cost of Well-Being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 985-1010, September.
    7. Gerami, Javad & Mozaffari, Mohammad Reza & Wanke, Peter F. & Correa, Henrique L., 2022. "Improving information reliability of non-radial value efficiency analysis: An additive slacks based measure approach," European Journal of Operational Research, Elsevier, vol. 298(3), pages 967-978.
    8. Kai Xu & Bart Bossink & Qiang Chen, 2019. "Efficiency Evaluation of Regional Sustainable Innovation in China: A Slack-Based Measure (SBM) Model with Undesirable Outputs," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
    9. Liu, John S. & Lu, Louis Y.Y. & Lu, Wen-Min, 2016. "Research fronts in data envelopment analysis," Omega, Elsevier, vol. 58(C), pages 33-45.
    10. Patricija Bajec & Danijela Tuljak-Suban & Eva Zalokar, 2021. "A Distance-Based AHP-DEA Super-Efficiency Approach for Selecting an Electric Bike Sharing System Provider: One Step Closer to Sustainability and a Win–Win Effect for All Target Groups," Sustainability, MDPI, vol. 13(2), pages 1-24, January.
    11. Justas Streimikis & Zhuang Miao & Tomas Balezentis, 2021. "Creation of climate‐smart and energy‐efficient agriculture in the European Union: Pathways based on the frontier analysis," Business Strategy and the Environment, Wiley Blackwell, vol. 30(1), pages 576-589, January.
    12. Sarkis, Joseph & Cordeiro, James J., 2012. "Ecological modernization in the electrical utility industry: An application of a bads–goods DEA model of ecological and technical efficiency," European Journal of Operational Research, Elsevier, vol. 219(2), pages 386-395.
    13. Laura Calzada-Infante & Ana María López-Narbona & Alberto Núñez-Elvira & Javier Orozco-Messana, 2020. "Assessing the Efficiency of Sustainable Cities Using an Empirical Approach," Sustainability, MDPI, vol. 12(7), pages 1-13, March.
    14. Demiral, Elif E. & Sağlam, Ümit, 2021. "Eco-efficiency and Eco-productivity assessments of the states in the United States: A two-stage Non-parametric analysis," Applied Energy, Elsevier, vol. 303(C).
    15. Shixiong Cheng & Jiahui Xie & De Xiao & Yun Zhang, 2019. "Measuring the Environmental Efficiency and Technology Gap of PM 2.5 in China’s Ten City Groups: An Empirical Analysis Using the EBM Meta-Frontier Model," IJERPH, MDPI, vol. 16(4), pages 1-22, February.
    16. June Raymond Leonen Mariano & Mingyu Liao & Herchang Ay, 2021. "Performance Evaluation of Solar PV Power Plants in Taiwan Using Data Envelopment Analysis," Energies, MDPI, vol. 14(15), pages 1-14, July.
    17. Barnabé Walheer, 2020. "Output, input, and undesirable output interconnections in data envelopment analysis: convexity and returns-to-scale," Annals of Operations Research, Springer, vol. 284(1), pages 447-467, January.
    18. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    19. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Impact of emission regulation policies on Chinese power firms’ reusable environmental investments and sustainable operations," Energy Policy, Elsevier, vol. 108(C), pages 163-177.
    20. Chiu, Yung-Ho & Lee, Jen-Hui & Lu, Ching-Cheng & Shyu, Ming-Kuang & Luo, Zhengying, 2012. "The technology gap and efficiency measure in WEC countries: Application of the hybrid meta frontier model," Energy Policy, Elsevier, vol. 51(C), pages 349-357.

    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:gam:jeners:v:11:y:2018:i:3:p:519-:d:133938. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.