Congestion at Chittagong Seaport: Causes and Consequences. A case study in Malaysia

Redwan Ahamed Kabir (1), Khalid Helal (2)
(1) International Islamic University Malaysia, Jalan Gombak, 53100, Selangor, Malaysia, Bangladesh,
(2) International Islamic University Malaysia, Jalan Gombak, 53100, Selangor, Malaysia, Malaysia

Abstract

The purpose of this study is to investigate the underlying causes of seaport congestion at Chittagong seaport, a critical gateway for international trade and a vital contributor to Bangladesh's economic growth. Seaport congestion is a pervasive issue that not only disrupts the flow of goods but also hampers the economic progress of nations reliant on efficient trade operations. To achieve the study's objectives, a survey-based research design was employed, utilizing convenience sampling to collect data from port employees. The data were analyzed using the SmartPLS 3.2.1 software, focusing on the Importance-Performance Matrix Analysis (IPMA) to identify key factors contributing to congestion. The findings reveal that information technology, equipment, and time management are the most significant factors influencing congestion at the port. The study concludes that enhancing the use of information technology and upgrading cargo-handling equipment are essential steps for reducing congestion. Furthermore, the study highlights the need for a holistic approach involving all stakeholders to improve the operational efficiency of the Chittagong seaport and, consequently, bolster the country’s trade growth. The implications of this study are far-reaching, offering valuable insights for policymakers, port authorities, and industry stakeholders aiming to optimize seaport operations and support sustainable economic development.

Full text article

Generated from XML file

References

Aryee, J. (2011). Analysis of the role of port labour systems and reforms on the competitiveness of West Africa ports. SSRN. https://doi.org/10.2139/ssrn.2625137

Cain, M. K., Zhang, Z., & Yuan, K. H. (2017). Univariate and multivariate skewness and kurtosis for measuring nonnormality: Prevalence, influence, and estimation. Behavior Research Methods, 49(5), 1716-1735. https://doi.org/10.3758/s13428-016-0814-1

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104

Gidado, U. (2015). Consequences of port congestion on logistics and supply chain in African ports. Developing Country Studies, 5(6), 160-167.

Hair, J. F., Risher, J. J. R., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203

Harman, H. H. (1976). Modern factor analysis (3rd ed.). University of Chicago Press.

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135. https://doi.org/10.1007/s11747-014-0403-8

Islam, M. A., & Haider, M. Z. (2016). Performance assessment of Mongla seaport in Bangladesh. International Journal of Transportation Engineering and Technology, 2(2), 15-21.

Jeevan, J., Ghaderi, H., Bandara, Y. M., Saharuddin, A. H., & Othman, M. R. (2015). The implications of the growth of port throughput on the port capacity: The case of Malaysian major container seaports. International Journal of e-Navigation and Maritime Economy, 3, 84-98. https://doi.org/10.1016/j.enavi.2015.12.008

Jiang, C., Wan, Y., & Zhang, A. (2016). Internalization of port congestion: Strategic effect behind shipping line delays and implications for terminal charges and investment. Maritime Policy & Management, 44(1), 112-130. https://doi.org/10.1080/03088839.2016.1237783

Kia, M., Shayan, E., & Ghotb, F. (2000). The importance of information technology in port terminal operations. International Journal of Physical Distribution & Logistics Management, 30(3/4), 331-344. https://doi.org/10.1108/09600030010326118

Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610. https://doi.org/10.1177/001316447003000308

Lu, C. S., Shang, K. C., & Lin, C. C. (2016). Identifying crucial sustainability assessment criteria for container seaports. Maritime Business Review, 1(2), 90-106. https://doi.org/10.1108/mabr-05-2016-0009

Luo, M., & Yip, T. L. (2013). Ports and the environment. Maritime Policy & Management, 40(5), 401-403. https://doi.org/10.1080/03088839.2013.797122

Mahmud, T., & Rossette, J. (2007). Problems and potentials of Chittagong Port: A follow-up diagnostic study. Transparency International Bangladesh (TIB). https://www.ti-bangladesh.org

Meersman, H., Voorde, E. V. de, & Vanelslander, T. (2012). Chapter 4: Port congestion and implications to maritime logistics. In Maritime Logistics: Contemporary Issues (pp. 49-68). Emerald Group Publishing Limited. https://www.emerald.com/insight/publication/doi/10.1108/9781780523415

Michael, K. A. (2006). Logistics and supply chain management: Creating value-adding networks. Journal of Business Logistics, 45(1), 61-62. https://doi.org/10.2307/20713626

Moon, D. (2018). Port performance indicators (PPI) and analysis—Introduction. World Maritime University. https://issuu.com/worldmaritimeuniversity/docs/academic-handbook/31

Nazemzadeh, M., & Vanelslander, T. (2015). The container transport system: Selection criteria and business attractiveness for North-European ports. Maritime Economics & Logistics, 17(2), 221-245. https://doi.org/10.1057/mel.2015.1

Notteboom, T. (2006). The time factor in liner shipping services. Maritime Economics & Logistics, 8(1), 19-39. https://doi.org/10.1057/palgrave.mel.9100148

Nyema, S. M. (2014). Factors influencing container terminal efficiency: A case study of Mombasa entry port. European Centre for Research Training and Development UK, 2(3), 39-78.

Peng, D. X., & Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of Operations Management, 30(6), 467-480. https://doi.org/10.1016/j.jom.2012.06.002

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Annual Review of Psychology, 88(5), 879-903. https://doi.org/10.1037/0021-9010.88.5.879

Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results: The importance-performance map analysis. Industrial Management & Data Systems, 116(9), 1865-1886. https://doi.org/10.1108/IMDS-10-2015-0449

Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (Eds.). (2010). Handbook of Partial Least Squares. Springer-Verlag Berlin Heidelberg. https://doi.org/10.1007/978-3-540-32827-8_29

Welvaarts, W. (2017). Strategic master plan for Chittagong Port [Assessment]. Asian Development Bank. https://www.adb.org/sites/default/files/project-documents/45078/45078-001-tacr-en.pdf

Yeo, G.-T., Roe, M., & Soak, S.-M. S. (2007). Evaluation of the marine traffic congestion of North Harbor in Busan Port. Journal of Waterway, Port, Coastal, and Ocean Engineering, 133(2), 87-93. https://doi.org/10.1061/(ASCE)0733-950X(2007)133:2(87)

Ke, Y., Li, K. W., & Hipel, K. W. (2012). An integrated multiple criteria preferences ranking approach to the Canadian west coast port congestion conflict. Expert Systems with Applications, 39(10), 9181-9190. https://doi.org/10.1016/j.eswa.2012.02.086

Zhang, A., Loh, H. S., & Thai, V. V. (2015). Impacts of global manufacturing trends on port development: The case of Hong Kong. The Asian Journal of Shipping and Logistics, 31(1), 135-159. https://doi.org/10.1016/j.ajsl.2015.03.006

Authors

Redwan Ahamed Kabir
rakabir@outlook.com (Primary Contact)
Khalid Helal
Kabir, R. A., & Helal, K. (2021). Congestion at Chittagong Seaport: Causes and Consequences. A case study in Malaysia. Innovation Journal of Social Sciences and Economic Review, 3(3), 13–21. https://doi.org/10.36923/ijsser.v3i3.103

Article Details

Smart Citations via scite_
Views
  • Abstract 54792
  • Download PDF 556