IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i20p13007-d939248.html
   My bibliography  Save this article

Evaluation Analysis of the Operational Efficiency and Total Factor Productivity of Container Terminals in China

Author

Listed:
  • Zhuyuan Li

    (College of Business Administration, Wonkwang University, No. 460, Iksandae-ro, Iksan 54538, Korea)

  • Xiaolong Wang

    (College of Business Administration, Wonkwang University, No. 460, Iksandae-ro, Iksan 54538, Korea)

  • Run Zheng

    (Business School, Jiangsu Open University, Nanjing 210036, China)

  • Sanggyun Na

    (College of Business Administration, Wonkwang University, No. 460, Iksandae-ro, Iksan 54538, Korea)

  • Chang Liu

    (College of Business Administration, Wonkwang University, No. 460, Iksandae-ro, Iksan 54538, Korea)

Abstract

As crucial international trade and global logistics players, container terminals worldwide handle more than 80% of the global merchandise trade. After analyzing and summarizing the previous studies, we use container terminal companies as the research object to fill the gap left by previous studies. Based on the above research status, this study analyzes the operational efficiency and total factor productivity of 32 container terminal companies in China using the super -efficiency DEA–SBM model and the Malmquist index method. The results show that (1) the operational efficiency level of 32 container terminals in China from 2017 to 2020 has a huge gap, and 15 container terminal companies have operational efficiency below 0.6, which indicates that most container terminals have excess inputs and a waste of resources. (2) The container terminals in the Bohai Rim, Pearl River Delta and Yangtze River Delta regions have higher operational efficiency. This shows that the development of container terminals cannot be separated from the economic hinterland of the cities where the ports are located. (3) The Malmquist index analysis shows a 2.8% decrease in total factor productivity, a 3.2% increase in the composite technical efficiency index and a 5.8% decrease in the technological progress index, which indicates that most container terminal companies have imperfect management practices and decision making. Based on the study’s results, this research provides relevant and feasible recommendations for policymakers who formulate policies for the development of the shipping industry to promote high quality and sustainable development of the shipping industry and the economy.

Suggested Citation

  • Zhuyuan Li & Xiaolong Wang & Run Zheng & Sanggyun Na & Chang Liu, 2022. "Evaluation Analysis of the Operational Efficiency and Total Factor Productivity of Container Terminals in China," Sustainability, MDPI, vol. 14(20), pages 1-12, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:20:p:13007-:d:939248
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/20/13007/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/20/13007/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hokey Min & Byung-In Park, 2005. "Evaluating the inter-temporal efficiency trends of international container terminals using data envelopment analysis," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 1(3), pages 258-277.
    2. Choonjoo Lee, 2011. "Malmquist Productivity Analysis using DEA frontier in Stata," CHI11 Stata Conference 21, Stata Users Group.
    3. Chun-Chu Liu, 2008. "Evaluating the operational efficiency of major ports in the Asia-Pacific region using data envelopment analysis," Applied Economics, Taylor & Francis Journals, vol. 40(13), pages 1737-1743.
    4. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    5. Wade D. Cook & Julie Harrison & Raha Imanirad & Paul Rouse & Joe Zhu, 2015. "Data Envelopment Analysis with Non-Homogeneous DMUs," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 11, pages 309-340, Springer.
    6. Lee, Chung-Yee & Song, Dong-Ping, 2017. "Ocean container transport in global supply chains: Overview and research opportunities," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 442-474.
    7. Fare, Rolf & Grosskopf, Shawna, 1992. "Malmquist Productivity Indexes and Fisher Ideal Indexes," Economic Journal, Royal Economic Society, vol. 102(410), pages 158-160, January.
    8. Suárez-Alemán, Ancor & Morales Sarriera, Javier & Serebrisky, Tomás & Trujillo, Lourdes, 2016. "When it comes to container port efficiency, are all developing regions equal?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 86(C), pages 56-77.
    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. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    11. Evangelos Mennis & Agapios Platis & Ioannis Lagoudis & Nikitas Nikitakos, 2008. "Improving Port Container Terminal Efficiency with the use of Markov Theory," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 10(3), pages 243-257, September.
    12. Tone, Kaoru & Tsutsui, Miki, 2010. "Dynamic DEA: A slacks-based measure approach," Omega, Elsevier, vol. 38(3-4), pages 145-156, June.
    13. 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.
    14. Liu, Jiaguo & Wang, Xiaoye & Guo, Junyu, 2021. "Port efficiency and its influencing factors in the context of Pilot Free Trade Zones," Transport Policy, Elsevier, vol. 105(C), pages 67-79.
    15. Gang Dong & Jing Zhu & Jin Li & Handong Wang & Yuvraj Gajpal, 2019. "Evaluating the Environmental Performance and Operational Efficiency of Container Ports: An Application to the Maritime Silk Road," IJERPH, MDPI, vol. 16(12), pages 1-15, June.
    16. Nikola Kutin & Thanh Thuy Nguyen & Thomas Vallée, 2017. "Relative Efficiencies of ASEAN Container Ports based on Data Envelopment Analysis," Post-Print hal-03193655, HAL.
    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. Pei Fun Lee & Weng Siew Lam & Weng Hoe Lam, 2023. "Performance Evaluation of the Efficiency of Logistics Companies with Data Envelopment Analysis Model," Mathematics, MDPI, vol. 11(3), pages 1-15, January.

    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. Min Wang & Meng Ji & Xiaofen Wu & Kexin Deng & Xiaodong Jing, 2023. "Analysis on Evaluation and Spatial-Temporal Evolution of Port Cluster Eco-Efficiency: Case Study from the Yangtze River Delta in China," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    2. 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.
    3. Adel Hatami-Marbini & Aliasghar Arabmaldar & John Otu Asu, 2022. "Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(4), pages 1213-1254, December.
    4. Mushtaq Taleb & Ruzelan Khalid & Ali Emrouznejad & Razamin Ramli, 2023. "Environmental efficiency under weak disposability: an improved super efficiency data envelopment analysis model with application for assessment of port operations considering NetZero," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(7), pages 6627-6656, July.
    5. Gang Dong & Jing Zhu & Jin Li & Handong Wang & Yuvraj Gajpal, 2019. "Evaluating the Environmental Performance and Operational Efficiency of Container Ports: An Application to the Maritime Silk Road," IJERPH, MDPI, vol. 16(12), pages 1-15, June.
    6. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2021. "Does China's new energy vehicle industry innovate efficiently? A three-stage dynamic network slacks-based measure approach," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    7. Quintano, Claudio & Mazzocchi, Paolo & Rocca, Antonella, 2021. "Evaluation of the eco-efficiency of territorial districts with seaport economic activities," Utilities Policy, Elsevier, vol. 71(C).
    8. Gómez-Calvet, Roberto & Conesa, David & Gómez-Calvet, Ana Rosa & Tortosa-Ausina, Emili, 2014. "Energy efficiency in the European Union: What can be learned from the joint application of directional distance functions and slacks-based measures?," Applied Energy, Elsevier, vol. 132(C), pages 137-154.
    9. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    10. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.
    11. 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).
    12. Yan Zhang & Zihan Xin & Guoya Gan, 2024. "Evaluating the Sustainable Development Performance of China’s International Commercial Ports Based on Environmental, Social and Governance Elements," Sustainability, MDPI, vol. 16(10), pages 1-16, May.
    13. Zhen Shi & Huinan Huang & Yingju Wu & Yung-Ho Chiu & Shijiong Qin, 2020. "Climate Change Impacts on Agricultural Production and Crop Disaster Area in China," IJERPH, MDPI, vol. 17(13), pages 1-23, July.
    14. Nocera Alves Junior, Paulo & Costa Melo, Isotilia & de Moraes Santos, Rodrigo & da Rocha, Fernando Vinícius & Caixeta-Filho, José Vicente, 2022. "How did COVID-19 affect green-fuel supply chain? - A performance analysis of Brazilian ethanol sector," Research in Transportation Economics, Elsevier, vol. 93(C).
    15. Merkel, Axel & Holmgren, Johan, 2017. "Dredging the depths of knowledge: Efficiency analysis in the maritime port sector," Transport Policy, Elsevier, vol. 60(C), pages 63-74.
    16. Xiang Ji & Jiasen Sun & Qunwei Wang & Qianqian Yuan, 2019. "Revealing Energy Over-Consumption and Pollutant Over-Emission Behind GDP: A New Multi-criteria Sustainable Measure," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1391-1421, December.
    17. Nelson Amowine & Zhiqiang Ma & Mingxing Li & Zhixiang Zhou & Benjamin Azembila Asunka & James Amowine, 2019. "Energy Efficiency Improvement Assessment in Africa: An Integrated Dynamic DEA Approach," Energies, MDPI, vol. 12(20), pages 1-17, October.
    18. Jun-Fei Chu & Jie Wu & Ma-Lin Song, 2018. "An SBM-DEA model with parallel computing design for environmental efficiency evaluation in the big data context: a transportation system application," Annals of Operations Research, Springer, vol. 270(1), pages 105-124, November.
    19. Necmi Kemal Avkiran, 2017. "An illustration of multiple-stakeholder perspective using a survey across Australia, China and Japan," Annals of Operations Research, Springer, vol. 248(1), pages 93-121, January.
    20. Yongrong Xin & Kengcheng Zheng & Yujiao Zhou & Yangyang Han & P. R. Tadikamalla & Qin Fan, 2022. "Logistics Efficiency under Carbon Constraints Based on a Super SBM Model with Undesirable Output: Empirical Evidence from China’s Logistics Industry," Sustainability, MDPI, vol. 14(9), pages 1-24, April.

    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:jsusta:v:14:y:2022:i:20:p:13007-:d:939248. 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.