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Assessing Container Terminals’ Environmental Efficiency: The Modified Slack-Based Measure Model

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  • Thanh Tam Nguyen

    (Faculty of Economics-Management, Dong Nai Technology University, Bien Hoa 76000, Vietnam)

  • Long Van Hoang

    (Faculty of Management, Ho Chi Minh City University of Law, Ho Chi Minh 700000, Vietnam)

Abstract

The classic Slack-Based Measure (SBM) model has been posited to be a favorable non-parametric tool to cope with undesirable output. Nevertheless, this model has two significant drawbacks that should be addressed in practice. Thus, this paper aims to revise the classic SBM model to estimate container terminals’ environmental efficiency with undesirable output. The originality of this article includes: (1) introducing the energy consumption method to calculate the quantity of CO 2 emitted by container terminal operators (CTOs), (2) adopting cluster analysis to identify homogeneous CTOs acting as Decision-Making Units (DMUs), and (3) introducing the modified SBM model to measure and analyze environmental efficiency for CTOs. Based on this research, the efficiency of the analyzed terminals and the management of the local port sector are improved.

Suggested Citation

  • Thanh Tam Nguyen & Long Van Hoang, 2024. "Assessing Container Terminals’ Environmental Efficiency: The Modified Slack-Based Measure Model," Sustainability, MDPI, vol. 16(11), pages 1-16, May.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4679-:d:1405983
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    References listed on IDEAS

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    1. Ackerman, Frank & Stanton, Elizabeth A., 2012. "Climate risks and carbon prices: Revising the social cost of carbon," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 6, pages 1-25.
    2. Mihail Diakomihalis & Maria I. Kyriakou & Anargyros Sideris, 2021. "Port Efficiency and the Financial Performance of Greek Public Ports Before and During the Economic Crisis," Maritime Policy & Management, Taylor & Francis Journals, vol. 48(5), pages 651-671, July.
    3. Yu, Shiwei & Wei, Yi-Ming & Guo, Haixiang & Ding, Liping, 2014. "Carbon emission coefficient measurement of the coal-to-power energy chain in China," Applied Energy, Elsevier, vol. 114(C), pages 290-300.
    4. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    5. Subhash C. Ray, 1991. "Resource-Use Efficiency in Public Schools: A Study of Connecticut Data," Management Science, INFORMS, vol. 37(12), pages 1620-1628, December.
    6. Zhu, Zhi-Shuang & Liao, Hua & Cao, Huai-Shu & Wang, Lu & Wei, Yi-Ming & Yan, Jinyue, 2014. "The differences of carbon intensity reduction rate across 89 countries in recent three decades," Applied Energy, Elsevier, vol. 113(C), pages 808-815.
    7. Giorgos E. Konstantzos & Georgios K. D. Saharidis & Maria Loizidou, 2017. "Development of a model for assessing Greenhouse Gas (GHG) emissions from terminal and drayage operations," Operational Research, Springer, vol. 17(3), pages 807-819, October.
    8. Chen Chen & Jasmine Siu Lee Lam, 2018. "Sustainability and interactivity between cities and ports: a two-stage data envelopment analysis (DEA) approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 45(7), pages 944-961, October.
    9. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    10. 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.
    11. 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.
    12. Fare, Rolf, et al, 1989. "Multilateral Productivity Comparisons When Some Outputs Are Undesirable: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 71(1), pages 90-98, February.
    13. Martínez-Moya, Julián & Vazquez-Paja, Barbara & Gimenez Maldonado, Jose Andrés, 2019. "Energy efficiency and CO2 emissions of port container terminal equipment: Evidence from the Port of Valencia," Energy Policy, Elsevier, vol. 131(C), pages 312-319.
    14. Sun, Jiasen & Yuan, Yang & Yang, Rui & Ji, Xiang & Wu, Jie, 2017. "Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis," Transport Policy, Elsevier, vol. 60(C), pages 75-86.
    15. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model☆," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
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