IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v284y2020i1d10.1007_s10479-019-03173-7.html
   My bibliography  Save this article

A Malmquist productivity index for network production systems in the energy sector

Author

Listed:
  • Madjid Tavana

    (La Salle University
    University of Paderborn)

  • Kaveh Khalili-Damghani

    (Islamic Azad University)

  • Francisco J. Santos Arteaga

    (Free University of Bolzano)

  • Arousha Hashemi

    (Islamic Azad University)

Abstract

In this paper, a method based on network data envelopment analysis (DEA) is proposed to measure the efficiency and effectiveness of decision making units (DMUs). In this regard, a version of the Malmquist productivity index is designed to accommodate network DEA structures. In this type of environments, sub-DMUs are considered when assessing the efficiency of the main DMU, which helps evaluating the internal structure of the DMUs. The proposed method is applied to measure the productivity of several Iranian oil refineries. After identifying the main factors determining the productivity of these refineries, the operation of nine of them is analyzed using data from the 2015–2016 period. The results show that the management of resource utilization, particularly capital and energy, is inappropriate and investment insufficient. In particular, investment does not aim at upgrading the technology level, despite the fact that the depreciation rate of capital facilities is particularly high in this industry. This particular feature highlights the need to increase the rate of investment in order to replace the depreciated capital.

Suggested Citation

  • Madjid Tavana & Kaveh Khalili-Damghani & Francisco J. Santos Arteaga & Arousha Hashemi, 2020. "A Malmquist productivity index for network production systems in the energy sector," Annals of Operations Research, Springer, vol. 284(1), pages 415-445, January.
  • Handle: RePEc:spr:annopr:v:284:y:2020:i:1:d:10.1007_s10479-019-03173-7
    DOI: 10.1007/s10479-019-03173-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-019-03173-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-019-03173-7?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. Kao, Chiang, 2009. "Efficiency decomposition in network data envelopment analysis: A relational model," European Journal of Operational Research, Elsevier, vol. 192(3), pages 949-962, February.
    2. Stacy Eller & Peter Hartley & Kenneth Medlock, 2011. "Empirical evidence on the operational efficiency of National Oil Companies," Empirical Economics, Springer, vol. 40(3), pages 623-643, May.
    3. 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.
    4. de Lima, Romulo S. & Schaeffer, Roberto, 2011. "The energy efficiency of crude oil refining in Brazil: A Brazilian refinery plant case," Energy, Elsevier, vol. 36(5), pages 3101-3112.
    5. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    6. Kao, Chiang & Hwang, Shiuh-Nan, 2014. "Multi-period efficiency and Malmquist productivity index in two-stage production systems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 512-521.
    7. Sueyoshi, Toshiyuki & Goto, Mika, 2012. "Data envelopment analysis for environmental assessment: Comparison between public and private ownership in petroleum industry," European Journal of Operational Research, Elsevier, vol. 216(3), pages 668-678.
    8. Madjid Tavana & Kaveh Khalili-Damghani & Rahman Rahmatian, 2015. "A hybrid fuzzy MCDM method for measuring the performance of publicly held pharmaceutical companies," Annals of Operations Research, Springer, vol. 226(1), pages 589-621, March.
    9. 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.
    10. Kao, Chiang, 2017. "Measurement and decomposition of the Malmquist productivity index for parallel production systems," Omega, Elsevier, vol. 67(C), pages 54-59.
    11. Gothe-Lundgren, Maud & T. Lundgren, Jan & A. Persson, Jan, 2002. "An optimization model for refinery production scheduling," International Journal of Production Economics, Elsevier, vol. 78(3), pages 255-270, August.
    12. Dr. Sabah M. Al-Najjar & Mustafa A. Al-Jaybajy, 2012. "Application of Data Envelopment Analysis to Measure the Technical Efficiency of Oil Refineries: A Case Study," International Journal of Business Administration, International Journal of Business Administration, Sciedu Press, vol. 3(5), pages 64-77, September.
    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. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    2. Djula Borozan & Dubravka Pekanov Starcevic, 2021. "Analysing the Pattern of Productivity Change in the European Energy Industry," Sustainability, MDPI, vol. 13(21), pages 1-14, October.
    3. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    4. Yu, Ming-Miin & Chen, Li-Hsueh, 2023. "Productivity change of airlines: A global total factor productivity index with network structure," Journal of Air Transport Management, Elsevier, vol. 109(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. 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.
    2. Kremantzis, Marios Dominikos & Beullens, Patrick & Kyrgiakos, Leonidas Sotirios & Klein, Jonathan, 2022. "Measurement and evaluation of multi-function parallel network hierarchical DEA systems," Socio-Economic Planning Sciences, Elsevier, vol. 84(C).
    3. Khoshroo, Alireza & Izadikhah, Mohammad & Emrouznejad, Ali, 2022. "Total factor energy productivity considering undesirable pollutant outputs: A new double frontier based malmquist productivity index," Energy, Elsevier, vol. 258(C).
    4. 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).
    5. Hosseini, Keyvan & Stefaniec, Agnieszka, 2019. "Efficiency assessment of Iran's petroleum refining industry in the presence of unprofitable output: A dynamic two-stage slacks-based measure," Energy, Elsevier, vol. 189(C).
    6. Fenfen Li & Bo Dai & Qifan Wu, 2021. "Dynamic Green Growth Assessment of China’s Industrial System with an Improved SBM Model and Global Malmquist Index," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
    7. 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.
    8. Kao, Chiang, 2017. "Measurement and decomposition of the Malmquist productivity index for parallel production systems," Omega, Elsevier, vol. 67(C), pages 54-59.
    9. Villa, G. & Lozano, S., 2016. "Assessing the scoring efficiency of a football match," European Journal of Operational Research, Elsevier, vol. 255(2), pages 559-569.
    10. Khezrimotlagh, Dariush & Kaffash, Sepideh & Zhu, Joe, 2022. "U.S. airline mergers’ performance and productivity change," Journal of Air Transport Management, Elsevier, vol. 102(C).
    11. Phung, Manh-Trung & Cheng, Cheng-Ping & Guo, Chuanyin & Kao, Chen-Yu, 2020. "Mixed Network DEA with Shared Resources: A Case of Measuring Performance for Banking Industry," Operations Research Perspectives, Elsevier, vol. 7(C).
    12. Kao, Chiang & Liu, Shiang-Tai, 2019. "Cross efficiency measurement and decomposition in two basic network systems," Omega, Elsevier, vol. 83(C), pages 70-79.
    13. 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.
    14. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    15. 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.
    16. Kao, Chiang, 2018. "Multiplicative aggregation of division efficiencies in network data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 270(1), pages 328-336.
    17. Despotis, Dimitris K. & Koronakos, Gregory & Sotiros, Dimitris, 2016. "The “weak-link” approach to network DEA for two-stage processes," European Journal of Operational Research, Elsevier, vol. 254(2), pages 481-492.
    18. Kao, Chiang, 2019. "Inefficiency identification for closed series production systems," European Journal of Operational Research, Elsevier, vol. 275(2), pages 599-607.
    19. 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.
    20. Kao, Chiang, 2017. "Efficiency measurement and frontier projection identification for general two-stage systems in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 261(2), pages 679-689.

    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:spr:annopr:v:284:y:2020:i:1:d:10.1007_s10479-019-03173-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.