Container terminal efficiency under external shocks: A hybrid DEA-Regression analysis of Dar es Salaam port (2019–2023)
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Issue
Vol. 10 No. 2 (2025)
Keywords:
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container terminal efficiency, data envelopment analysis, contextual regression, port performance measurement, COVID-19 maritime disruption, East African ports, infrastructure capacity constraints
Abstract
Purpose. This paper evaluates the technical Efficiency of Dar es Salaam Port’s container terminal operations over the period 2019–2023, explicitly accounting for the influence of macroeconomic conditions and the COVID-19 pandemic on performance metrics. The study addresses a critical gap in port efficiency research by disentangling internal operational capability from external contextual factors in a developing-economy maritime gateway serving landlocked East and Central African countries. Methodology. A two-stage hybrid analytical framework integrates input-oriented Data Envelopment Analysis (DEA) with Contextual Value Added (CVA) regression. DEA efficiency scores are computed using a three-year rolling window approach with inputs (quay length, gantry cranes, terminal area) and outputs (container throughput, vessel calls). Second-stage ordinary least squares regression isolates the effects of GDP, trade volume, and pandemic disruption on measured efficiency. Quantitative findings are triangulated with qualitative stakeholder surveys (n=45) and semi-structured interviews to capture operational perceptions and institutional constraints. Results. DEA analysis reveals temporal efficiency variation ranging from 0.838 (2019) to 0.966 (2021), with post-pandemic decline to 0.890 (2023). CVA regression identifies a statistically significant negative relationship between trade volume and efficiency (β = −1.76×10⁻⁵, p = 0.03), indicating binding infrastructure constraints. The COVID-19 dummy exhibits a paradoxical positive coefficient (β = +0.090, p = 0.02), reflecting efficiency gains under suppressed demand rather than genuine productivity enhancement. Theoretical contribution. This study advances port efficiency assessment by demonstrating that unadjusted frontier methods can mask capacity deficits when external demand fluctuates. The hybrid DEA-CVA framework enables evidence-based attribution of efficiency sources, enhancing policy relevance. Practical implications. Findings underscore the urgent need for infrastructure expansion and procedural digitalization to accommodate regional trade growth under the African Continental Free Trade Area.
Sustainable Development Goals (SDGs): SDG 8: Decent Work and Economic Growth; SDG 9: Industry, Innovation, and Infrastructure
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References
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Badunenko, O. (2019). Simar and Wilson two-stage efficiency analysis for Stata. The Stata Journal, 19(4), 927–943. https://doi.org/10.1177/1536867X19893640
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Banker, R. D., Cooper, W. W., & Rhodes, E. (1984). Estimating technical and scale inefficiency in production. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
Banker, R. D., Maindiratta, A., Shorrocks, A., & Simar, L. (2019). Two-stage estimation of the impact of contextual variables on Efficiency: A review and recent developments. European Journal of Operational Research, 278(3), 775–792. https://doi.org/10.1016/j.ejor.2019.05.049
Bergantino, A. S., & Musso, E. (2013). Port management performance and contextual variables: Which relationship? Methodological and empirical issues. Research in Transportation Business & Management, 8, 39–49. https://doi.org/10.1016/j.rtbm.2013.04.002
Bichou, K. (2021). Development of a strategic plan for port performance improvement in South African container terminals. Maritime Policy & Management, 48(6), 817–836. https://doi.org/10.1080/03088839.2020.1859149
Bichou, K., & Gray, R. (2005). A critical review of conventional terminology for classifying seaports. Transportation Research Part A: Policy and Practice, 39(1), 75–92. https://doi.org/10.1016/j.tra.2004.11.001
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Carine, C. (2015). Ports and Efficiency in Sub-Saharan Africa: A comparative study of container terminals. Maritime Economics & Logistics, 17(1), 1–22.
Charłampowicz, J., & Mańkowski, C. (2020). Economic efficiency evaluation system of maritime container terminals. Economics and Law, 19(1), 45–54. https://doi.org/10.12775/EiP.2020.002
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision-making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Cong, L., Zhang, D., Wang, M., Xu, H., & Li, L. (2020). The role of ports in the economic development of port cities: Panel evidence from China. Transport Policy, 90, 13–21. https://doi.org/10.1016/j.tranpol.2020.02.003
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software (2nd ed.). Springer. https://doi.org/10.1007/978-0-387-45283-8
Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
Cullinane, K., Song, D.-W., Ji, P., & Wang, T.-F. (2006). An application of DEA windows analysis to container port production efficiency. Review of Network Economics, 5(2), 184–206. https://doi.org/10.2202/1446-9022.1050
Cullinane, K., Song, D.-W., Ji, P., & Wang, T.-F. (2006). The technical efficiency of container ports: Comparing international ports using DEA. Transportation Research Part A: Policy and Practice, 40(4), 354–374. https://doi.org/10.1016/j.tra.2005.07.003
Danladi, C., et al. (2024). Efficiency analysis and benchmarking of container ports operating in lower-middle-income countries: A DEA approach. Journal of Shipping and Trade, 9(1). https://doi.org/10.1186/s41072-024-00163-2
Duru, O., Bulut, E., & Yoshida, S. (2020). Developing a comprehensive approach to port performance assessment. Asian Journal of Shipping and Logistics, 36(4), 169–180. https://doi.org/10.1016/j.ajsl.2020.03.001
Fernandes, F. D. S., Stosic, B., & Sampaio de Souza, M. J. C. (2018). Two-stage DEA–truncated regression: Application in efficiency assessment of Brazilian financial institutions. Expert Systems with Applications, 108, 20–28. https://doi.org/10.1016/j.eswa.2018.04.048
Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs—Principles and practices. Health Services Research, 48(6 Pt 2), 2134–2156. https://doi.org/10.1111/1475-6773.12117
Golany, B., & Roll, Y. (1989). An application procedure for DEA. Omega, 17(3), 237–250. https://doi.org/10.1016/0305-0483(89)90029-7
Gu, Y., Wallace, S. W., & Wang, X. (2023). Impact of COVID-19 epidemic on port operations: A case study of Shanghai Port, Ningbo-Zhoushan Port and Qingdao Port in China. Case Studies on Transport Policy, 12, 100970. https://doi.org/10.1016/j.cstp.2023.100970
Guetterman, T. C., Fetters, M. D., & Creswell, J. W. (2015). Integrating quantitative and qualitative results in health science mixed methods research through joint displays. Annals of Family Medicine, 13(6), 554–561. https://doi.org/10.1370/afm.1865
Ha, M.-H., Yang, Z., Notteboom, T., Ng, A. K. Y., & Heo, M.-W. (2017). Revisiting port performance measurement: A hybrid multi-stakeholder framework for the modelling of port performance indicators. Transportation Research Part E: Logistics and Transportation Review, 103, 1–16. https://doi.org/10.1016/j.tre.2017.04.008
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson.
Hlali, A. (2017). The relationship between port size, infrastructure and Efficiency in North African container ports. Transport Policy, 60, 19–26. https://doi.org/10.1016/j.tranpol.2016.07.003
Holý, V., & Zouhar, J. (2024). Ranking-based second stage in data envelopment analysis: An application to research and development efficiency. Socio-Economic Planning Sciences, 91, 101779. https://doi.org/10.1016/j.seps.2023.101779
Johnson, A. L., & Kuosmanen, T. (2012). One-stage and two-stage DEA estimation of the effects of contextual variables. European Journal of Operational Research, 220(2), 559–570. https://doi.org/10.1016/j.ejor.2012.01.023
Johnson, R. B., Onwuegbuzie, A. J., & Turner, L. A. (2007). Toward a definition of mixed methods research. Journal of Mixed Methods Research, 1(2), 112–133. https://doi.org/10.1177/1558689806298224
Juma, M., & Zhihong, J. (2020). Status, challenges and strategies of Dar es Salaam seaport-hinterland connectivity. MATEC Web of Conferences, 325, 04003. https://doi.org/10.1051/matecconf/202032504003
Krmac, E., & Mansouri, M. (2023). A comprehensive review of data envelopment analysis (DEA) methodology in port efficiency evaluation. Maritime Economics & Logistics, 25(4), 817–881. https://doi.org/10.1057/s41278-022-00239-5
Kunambi, M. M., & Zheng, H. (2024). Contextual comparative analysis of Dar es Salaam and Mombasa port performance by using a hybrid DEA-CVA model. Logistics, 8(1), 2. https://doi.org/10.3390/logistics8010002
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310
Liu, Q. (2010). Efficiency analysis of container ports and terminals [Doctoral dissertation, Newcastle University]. https://theses.ncl.ac.uk/jspui/bitstream/10443/1049/1/Liu10.pdf
Maneno, F. H. (2019). Assessment of factors causing port congestion: A case of the port Dar es Salaam [Master’s thesis, Mzumbe University].
Morgan, D. L. (2014). Pragmatism as a paradigm for social research. Qualitative Inquiry, 20(8), 1045–1053. https://doi.org/10.1177/1077800413513733
Morse, J. M., & Niehaus, L. (2009). Mixed method design: Principles and procedures. Left Coast Press.
Munim, Z. H., & Schramm, H.-J. (2018). The impacts of port infrastructure and logistics performance on economic growth: The mediating role of seaborne trade. Journal of Shipping and Trade, 3(1), 1. https://doi.org/10.1186/s41072-018-0027-0
Notteboom, T., Pallis, T., & Rodrigue, J.-P. (2021). Disruptions and resilience in global container shipping and ports: The COVID-19 pandemic versus the 2008–2009 financial crisis. Maritime Economics & Logistics, 23(2), 179–210. https://doi.org/10.1057/s41278-020-00180-5
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). SAGE Publications.
Perez, I., Diaz-Hernandez, J. J., & Trujillo, L. (2016). Efficiency determinants of container terminals in Latin America and the Caribbean. Utilities Policy, 41, 1–14. https://doi.org/10.1016/j.jup.2016.06.002
Peykani, P., Mohammadi, E., Jabbarzadeh, A., Rostamy-Malkhalifeh, M., & Pishvaee, M. S. (2021). Window data envelopment analysis approach: A review and bibliometric analysis. Expert Systems, 38(7), e12721. https://doi.org/10.1111/exsy.12721
Poitras, G. (1996). Measuring port efficiency: An application of data envelopment analysis. MPRA Paper No. 113953.
Raballand, G., Refas, S., Beuran, M., & Isik, G. (2012). Why does cargo spend weeks in sub-Saharan African ports? Lessons from six countries. World Bank. https://doi.org/10.1596/978-0-8213-9499-1
Ramsey, J. B. (1969). Tests for specification errors in classical linear least-squares regression analysis. Journal of the Royal Statistical Society: Series B (Methodological), 31(2), 350–371. https://doi.org/10.1111/j.2517-6161.1969.tb00796.x
Shawtari, F. A., Ariff, M. S. M., Abdul Razak, S. H., & Mazumder, M. N. H. (2018). Decomposition of Efficiency using DEA window analysis: A comparative evidence from Islamic and conventional banks. Benchmarking: An International Journal, 25(6), 1681–1705. https://doi.org/10.1108/BIJ-12-2016-0183
Simar, L., & Wilson, P. W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), 31–64. https://doi.org/10.1016/j.jeconom.2005.07.009
Sun, B., & Kauzen, R. (2023). The impact of port infrastructure and economic growth in Tanzania: Adopting a structural equation modelling approach. SAGE Open, 13(1), 1–17. https://doi.org/10.1177/21582440221145894
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Moshi, N. R., & Meli, B. M. (2025). Container terminal efficiency under external shocks: A hybrid DEA-Regression analysis of Dar es Salaam port (2019–2023). Journal of Sustainable Development of Transport and Logistics, 10(2), 107–133. https://doi.org/10.14254/jsdtl.2025.10-2.7
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