IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i11p6094-d564266.html
   My bibliography  Save this article

Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market

Author

Listed:
  • Joohwan Kim

    (Transportation Safety Division, Korea Maritime Transportation Safety Authority, Sejong 30100, Korea)

  • Hwayoung Kim

    (Division of Maritime Transportation, Mokpo National Maritime University, Mokpo 58628, Korea)

Abstract

Safety is a key performance indicator for the sustainable management of a coastal ferry service business. An efficiency strategy that balances safety and transport performance should be considered. The purpose of this study is to evaluate the relative transport efficiency of coastal ferry operators through undesirable safety-related output. Coastal ferry operators create added value through logistics activities such as cargo and passenger transport. Accordingly, this study designed a three-stage network-slacks-based measure (SBM) model that delineated production through ferry transport services such as service generation, service execution, and transport value creation. Detention records and marine accidents caused by human errors or technical faults were considered undesirable safety-related outputs. Moreover, the relative transport efficiency of 23 Korean firms that have continuously managed a coastal ferry transport business from 2015 to 2018 was analyzed. The results showed that the differentiation of transport efficiency of firms improved when applying the three-stage network SBM model compared to applying the SBM model that did not consider the internal production stage. This fact suggests that it is more desirable to apply the three-stage network SBM model proposed in this study when a more stringent comparison of transport performance is needed in terms of service quality.

Suggested Citation

  • Joohwan Kim & Hwayoung Kim, 2021. "Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:11:p:6094-:d:564266
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/11/6094/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/11/6094/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Ci & Yan, Hong, 2011. "Network DEA model for supply chain performance evaluation," European Journal of Operational Research, Elsevier, vol. 213(1), pages 147-155, August.
    2. Ester Gutiérrez & Sebastián Lozano & Salvador Furió, 2014. "Evaluating efficiency of international container shipping lines: A bootstrap DEA approach," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 16(1), pages 55-71, March.
    3. Yu, Ming-Miin & Lin, Erwin T.J., 2008. "Efficiency and effectiveness in railway performance using a multi-activity network DEA model," Omega, Elsevier, vol. 36(6), pages 1005-1017, December.
    4. 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.
    5. Boussofiane, A. & Dyson, R. G. & Thanassoulis, E., 1991. "Applied data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 52(1), pages 1-15, May.
    6. 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.
    7. Joe Zhu, 2014. "DEA Cross Efficiency," International Series in Operations Research & Management Science, in: Quantitative Models for Performance Evaluation and Benchmarking, edition 3, chapter 4, pages 61-92, Springer.
    8. Gong, Xiaoxing & Wu, Xiaofan & Luo, Meifeng, 2019. "Company performance and environmental efficiency: A case study for shipping enterprises," Transport Policy, Elsevier, vol. 82(C), pages 96-106.
    9. Hee-Seok Bang & Hyo-Won Kang & Jeffrey Martin & Su-Han Woo, 2012. "The impact of operational and strategic management on liner shipping efficiency: a two-stage DEA approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 39(7), pages 653-672, December.
    10. Cui, Qiang & Li, Ye, 2015. "Evaluating energy efficiency for airlines: An application of VFB-DEA," Journal of Air Transport Management, Elsevier, vol. 44, pages 34-41.
    11. Tzannatos, Ernestos S., 2005. "Technical reliability of the Greek coastal passenger fleet," Marine Policy, Elsevier, vol. 29(1), pages 85-92, January.
    12. Margareta Friman & Katrin Lättman & Lars E. Olsson, 2020. "Public Transport Quality, Safety, and Perceived Accessibility," Sustainability, MDPI, vol. 12(9), pages 1-14, April.
    13. Fukuyama, Hirofumi & Weber, William L., 2010. "A slacks-based inefficiency measure for a two-stage system with bad outputs," Omega, Elsevier, vol. 38(5), pages 398-409, October.
    14. Thi Quynh Mai Pham & Gunwoo Lee & Hwayoung Kim, 2020. "Toward Sustainable Ferry Routes in Korea: Analysis of Operational Efficiency Considering Passenger Mobility Burdens," Sustainability, MDPI, vol. 12(21), pages 1-22, October.
    15. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    16. Chao, Shih-Liang & Yu, Ming-Miin & Hsieh, Wei-Fan, 2018. "Evaluating the efficiency of major container shipping companies: A framework of dynamic network DEA with shared inputs," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 44-57.
    17. Panayides, Photis M. & Lambertides, Neophytos & Savva, Christos S., 2011. "The relative efficiency of shipping companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(5), pages 681-694, September.
    18. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    19. Jianhuan Huang & Juanjuan Chen & Zhujia Yin, 2014. "A Network DEA Model with Super Efficiency and Undesirable Outputs: An Application to Bank Efficiency in China," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-14, April.
    20. Hashem Omrani & Mehdi Keshavarz, 2016. "A performance evaluation model for supply chain of shipping company in Iran: an application of the relational network DEA," Maritime Policy & Management, Taylor & Francis Journals, vol. 43(1), pages 121-135, January.
    21. Wen-Hsien Tsai & Hsiu-Li Lee & Chih-Hao Yang & Chung-Chen Huang, 2016. "Input-Output Analysis for Sustainability by Using DEA Method: A Comparison Study between European and Asian Countries," Sustainability, MDPI, vol. 8(12), pages 1-17, November.
    22. Du, Juan & Cook, Wade D. & Liang, Liang & Zhu, Joe, 2014. "Fixed cost and resource allocation based on DEA cross-efficiency," European Journal of Operational Research, Elsevier, vol. 235(1), pages 206-214.
    23. Yingnan Liu & Ke Wang, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA-based decomposition analysis," CEEP-BIT Working Papers 83, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    24. Wanke, Peter F., 2013. "Physical infrastructure and flight consolidation efficiency drivers in Brazilian airports: A two-stage network-DEA approach," Journal of Air Transport Management, Elsevier, vol. 31(C), pages 1-5.
    25. Yu, Ming-Miin & Chen, Li-Hsueh & Hsiao, Bo, 2018. "A performance-based subsidy allocation of ferry transportation: A data envelopment approach," Transport Policy, Elsevier, vol. 68(C), pages 13-19.
    26. Wanke, Peter F., 2013. "Physical infrastructure and shipment consolidation efficiency drivers in Brazilian ports: A two-stage network-DEA approach," Transport Policy, Elsevier, vol. 29(C), pages 145-153.
    27. Liu, Yingnan & Wang, Ke, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis," Energy, Elsevier, vol. 93(P2), pages 1328-1337.
    28. Chang, Young-Tae & Lee, Suhyung & Park, Hyosoo (Kevin), 2017. "Efficiency analysis of major cruise lines," Tourism Management, Elsevier, vol. 58(C), pages 78-88.
    29. Sebastián Lozano & Ester Gutiérrez, 2014. "A slacks-based network DEA efficiency analysis of European airlines," Transportation Planning and Technology, Taylor & Francis Journals, vol. 37(7), pages 623-637, October.
    30. Pal, Debdatta & Mitra, Subrata K., 2016. "An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 1-12.
    31. Yongjun Li & Xiao Shi & Ali Emrouznejad & Liang Liang, 2018. "Environmental performance evaluation of Chinese industrial systems: a network SBM approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(6), pages 825-839, June.
    32. Angela Stefania Bergantino & Simona Bolis, 2008. "Monetary values of transport service attributes: land versus maritime ro-ro transport. An application using adaptive stated preferences," Maritime Policy & Management, Taylor & Francis Journals, vol. 35(2), pages 159-174, April.
    33. Mahmoudabadi, Mohammad Zarei & Azar, Adel & Emrouznejad, Ali, 2018. "A novel multilevel network slacks-based measure with an application in electric utility companies," Energy, Elsevier, vol. 158(C), pages 1120-1129.
    34. 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.
    35. Roets, Bart & Verschelde, Marijn & Christiaens, Johan, 2018. "Multi-output efficiency and operational safety: An analysis of railway traffic control centre performance," European Journal of Operational Research, Elsevier, vol. 271(1), pages 224-237.
    36. 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.
    37. Barak, Sasan & Dahooei, Jalil Heidary, 2018. "A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation," Journal of Air Transport Management, Elsevier, vol. 73(C), pages 134-149.
    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. Huibing Cheng & Shanshui Zheng & Jianghong Feng, 2022. "A Fuzzy Multi-Criteria Method for Sustainable Ferry Operator Selection: A Case Study," Sustainability, MDPI, vol. 14(10), pages 1-22, May.

    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. H. Pierre Hsieh & Kuo‐Cheng Kuo & Minh‐Hieu Le & Wen‐Min Lu, 2021. "Exploring the cargo and eco‐efficiencies of international container shipping companies: A network‐based ranking approach," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(1), pages 45-60, January.
    2. Gong, Xiaoxing & Wu, Xiaofan & Luo, Meifeng, 2019. "Company performance and environmental efficiency: A case study for shipping enterprises," Transport Policy, Elsevier, vol. 82(C), pages 96-106.
    3. Shih-Liang Chao & Chun-Wei Lai, 2019. "Comparing the efficiency of alliance members and independent liner carriers: a metafrontier analysis," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(2), pages 157-172, June.
    4. Victor John M. Cantor & Kim Leng Poh, 2020. "Efficiency measurement for general network systems: a slacks-based measure model," Journal of Productivity Analysis, Springer, vol. 54(1), pages 43-57, August.
    5. Xu, Xin & Cui, Qiang, 2017. "Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure," Energy, Elsevier, vol. 122(C), pages 274-286.
    6. Tao Xu & Jianxin You & Hui Li & Luning Shao, 2020. "Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review," Energies, MDPI, vol. 13(14), pages 1-20, July.
    7. Eucabeth Majiwa & Boon L. Lee & Clevo Wilson & Hidemichi Fujii & Shunsuke Managi, 2018. "A network data envelopment analysis (NDEA) model of post-harvest handling: the case of Kenya’s rice processing industry," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 631-648, June.
    8. Minh‐Anh Thi Nguyen & Ming‐Miin Yu, 2020. "Decomposing the operational efficiency of major cruise lines: A network data envelopment analysis approach in the presence of shared input and quasi‐fixed input," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(8), pages 1501-1516, December.
    9. Kao, Chiang, 2014. "Network data envelopment analysis: A review," European Journal of Operational Research, Elsevier, vol. 239(1), pages 1-16.
    10. Liu, Yingnan & Wang, Ke, 2015. "Energy efficiency of China's industry sector: An adjusted network DEA (data envelopment analysis)-based decomposition analysis," Energy, Elsevier, vol. 93(P2), pages 1328-1337.
    11. 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.
    12. Evelin Krmac & Mozhgan Mansouri Kaleibar, 2023. "A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(4), pages 817-881, December.
    13. Lampe, Hannes W. & Hilgers, Dennis, 2015. "Trajectories of efficiency measurement: A bibliometric analysis of DEA and SFA," European Journal of Operational Research, Elsevier, vol. 240(1), pages 1-21.
    14. Khalid Mehmood & Yaser Iftikhar & Shouming Chen & Shaheera Amin & Alia Manzoor & Jinlong Pan, 2020. "Analysis of Inter-Temporal Change in the Energy and CO 2 Emissions Efficiency of Economies: A Two Divisional Network DEA Approach," Energies, MDPI, vol. 13(13), pages 1-17, June.
    15. George Halkos & Roman Matousek & Nickolaos Tzeremes, 2016. "Pre-evaluating technical efficiency gains from possible mergers and acquisitions: evidence from Japanese regional banks," Review of Quantitative Finance and Accounting, Springer, vol. 46(1), pages 47-77, January.
    16. 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).
    17. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    18. Chia-Nan Wang & Phi-Hung Nguyen & Thi-Ly Nguyen & Thi-Giang Nguyen & Duc-Thinh Nguyen & Thi-Hoai Tran & Hong-Cham Le & Huong-Thuy Phung, 2022. "A Two-Stage DEA Approach to Measure Operational Efficiency in Vietnam’s Port Industry," Mathematics, MDPI, vol. 10(9), pages 1-21, April.
    19. 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.
    20. Xiangyu Teng & Fan‐peng Liu & Yung‐ho Chiu, 2020. "The impact of coal and non‐coal consumption on China's energy performance improvement," Natural Resources Forum, Blackwell Publishing, vol. 44(4), pages 334-352, November.

    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:13:y:2021:i:11:p:6094-:d:564266. 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.