Analyzing the Impact of Berth Capacity Constraints on Shipping Costs at the Dar es Salaam Container Terminal

Neema Philemon Ndyana; Lucas Mwisila

doi:10.18535/sshj.v9i07.1949

Abstract

This study investigates how berth capacity constraints at the Dar es Salaam Container Terminal drive up shipping costs and proposes targeted interventions to alleviate this bottleneck. A mixed‐methods design combined a structured survey of 90 industry professionals with 18 semi‐structured interviews. Quantitative analysis revealed that average berth occupancy stood at 78.4% (SD 9.2), with mean daily demurrage charges of USD 120.50 (SD 25.4). The berth‐capacity perception scale demonstrated strong reliability (Cronbach’s α = .81). Pearson correlation confirmed a robust association between occupancy and demurrage (r = .68, p < .01), and multiple regression showed berth occupancy as the strongest predictor of demurrage (β = .34, p < .001), explaining 58% of its variance. Qualitative themes excessive vessel queues and manual scheduling inefficiencies corroborated these findings. Building on this evidence, the paper recommends implementing an AI‐driven Port Community System, phased quay expansions, and public–private partnerships to optimize berth utilization, reduce vessel waiting times by up to 20%, and substantially lower demurrage costs.

Keywords

Berth CapacityShipping CostsDemurrageContainer Terminal

References

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[refR-2] Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Sage.Google Scholar ↗

[refR-3] Cullinane, K., & Wang, T.-F. (2021). Gate automation and inland logistics: Impacts on port efficiency. Maritime Economics & Logistics, 23(4), 543–560.Google Scholar ↗

[refR-4] Gupta, A., Verma, R., & Singh, M. (2017). Queuing theory applications in port performance analysis. International Journal of Shipping and Transport Logistics, 9(2), 123–138.Google Scholar ↗

[refR-5] Li, K. X., & Panayides, P. M. (2020). Toward optimal berth scheduling: A review of recent developments. Transportation Research Part E: Logistics and Transportation Review, 135, 101821.Google Scholar ↗

[refR-6] Lun, Y. H. V., Lai, K.-H., & Cheng, T. C. E. (2016). Shipping and logistics management. Springer.Google Scholar ↗

[refR-7] Mangan, J., Lalwani, C., & Gardner, B. (2016). Port and terminal management (2nd ed.). Kogan Page.Google Scholar ↗

[refR-8] Moshi, P. (2019). Digitalization in East African ports: The case of Mombasa. Journal of Transport Geography, 74, 172–180.Google Scholar ↗

[refR-9] Notteboom, T., & Rodrigue, J.-P. (2013). The corporate geography of global container terminal operators. Maritime Policy & Management, 40(5), 483–507.Google Scholar ↗

[refR-10] Ouma, S. (2021). Berth efficiency and performance metrics in sub‐Saharan Africa. Maritime Business Review, 6(1), 22–37.Google Scholar ↗

[refR-11] Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students (8th ed.). Pearson.Google Scholar ↗

[refR-12] TPA. (2024). Annual port performance report 2023. Tanzania Ports Authority.Google Scholar ↗

[refR-13] UNCTAD. (2020). Review of maritime transport 2020. United Nations Conference on Trade and Development.Google Scholar ↗

[refR-14] Wang, T.-F., & Yap, W.-Y. (2018). Cost implications of port demurrage: A comparative study. Maritime Policy & Management, 45(2), 167–182.Google Scholar ↗

[refR-15] Wilmsmeier, G., Sanchez, R. J., & Hoffmann, J. (2014). Optimal container terminal yard storage allocation and handling systems. Transportation Research Record: Journal of the Transportation Research Board, 2410(1), 129–137.Google Scholar ↗