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Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam

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  • Chia-Nan Wang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
    Department of Industrial Engineering and Management, Fortune Institute of Technology, Kaohsiung 83160, Taiwan)

  • Jen-Der Day

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Nguyen Thi Kim Lien

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Luu Quoc Chien

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

Abstract

The growing trade process is pushing the importing and exporting ratio of products at ports in Vietnam. The total amount of goods is determined by analyzing the effectiveness of products that are delivered at ports. Thus, this research presents a whole performance picture of the port logistics operation process at two airports and six seaport logistics companies in Vietnam to describe exchanging products by utilizing additive trend methods to formulate the efficiency and rank them from previous periods to future terms. Based on the prediction analysis, the best accuracy result is calculated by the additive Holt Winters method when the mean absolute percentage error (MAPE) indicators remain at the standard level, and its average qualification is also the lowest. Combining the actual and prediction values, the ranking of all ports accordingly by year during the past, current, and future time periods from 2011–2022 is obtained after calculating the final efficiency via the super-SBM model. The empirical result of the current and estimated efficiency denotes that Da Nang port logistics is always selected as the best port logistics company and maintained the first ranking with consistently high scores on the basis of the performance qualification. The empirical analysis result proposes the status quo of port logistics companies in Vietnam from the past to future to describe the amount of exchanging goods.

Suggested Citation

  • Chia-Nan Wang & Jen-Der Day & Nguyen Thi Kim Lien & Luu Quoc Chien, 2018. "Integrating the Additive Seasonal Model and Super-SBM Model to Compute the Efficiency of Port Logistics Companies in Vietnam," Sustainability, MDPI, vol. 10(8), pages 1-17, August.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:8:p:2782-:d:162212
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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Dalwon Kang & Sihyun Kim, 2017. "Conceptual Model Development of Sustainability Practices: The Case of Port Operations for Collaboration and Governance," Sustainability, MDPI, vol. 9(12), pages 1-15, December.
    3. 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.
    4. Charnes, A. & Cooper, W. W. & Golany, B. & Seiford, L. & Stutz, J., 1985. "Foundations of data envelopment analysis for Pareto-Koopmans efficient empirical production functions," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 91-107.
    5. Archibald, Blyth C., 1990. "Parameter space of the Holt-winters' model," International Journal of Forecasting, Elsevier, vol. 6(2), pages 199-209, July.
    6. Bartolomei, Sonia M. & Sweet, Arnold L., 1989. "A note on a comparison of exponential smoothing methods for forecasting seasonal series," International Journal of Forecasting, Elsevier, vol. 5(1), pages 111-116.
    7. Luisa Martí & Juan Carlos Martín & Rosa Puertas, 2017. "A DEA-logistics performance index," Journal of Applied Economics, Universidad del CEMA, vol. 20, pages 169-192, May.
    8. Fare, Rolf & Knox Lovell, C. A., 1978. "Measuring the technical efficiency of production," Journal of Economic Theory, Elsevier, vol. 19(1), pages 150-162, October.
    9. Fang, Hsin-Hsiung & Lee, Hsuan-Shih & Hwang, Shiuh-Nan & Chung, Cheng-Chi, 2013. "A slacks-based measure of super-efficiency in data envelopment analysis: An alternative approach," Omega, Elsevier, vol. 41(4), pages 731-734.
    10. Grace Wang & Chen Gao, 2012. "Technical Efficiency and Port Competition: Revisiting the Bohai Economic Rim, China," JRFM, MDPI, vol. 5(1), pages 1-16, December.
    11. 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.
    12. Sarah Gelper & Roland Fried & Christophe Croux, 2010. "Robust forecasting with exponential and Holt-Winters smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 285-300.
    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.
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    2. Thi Kim Lien Nguyen & Thi Lan Huong Nguyen & Tri Long Ngo & Bang An Hoang & Hong Huyen Le & Thi Thanh Hong Tran, 2023. "An Integrated Approach of Fuzzy Analytic Hierarchy Process and Super Slack-Based Measure for the Logistics Industry in Vietnam," Sustainability, MDPI, vol. 15(16), pages 1-18, August.
    3. Xiaohong Jiang & Jianxiao Ma & Huizhe Zhu & Xiucheng Guo & Zhaoguo Huang, 2020. "Evaluating the Carbon Emissions Efficiency of the Logistics Industry Based on a Super-SBM Model and the Malmquist Index from a Strong Transportation Strategy Perspective in China," IJERPH, MDPI, vol. 17(22), pages 1-19, November.
    4. 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.

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