STRATEGY OF FREIGHT FORWARDER COMPANIES IN RESOLVING IMPORT DELAY

• Bunga Tiur Annisa Rulyanni

  Diponegoro University, Indonesia

• Mashudi Mashudi

  Diponegoro University, Indonesia

Objective: This research is based on recurring problems in the import process delays, particularly those caused by national holidays. Such delays often lead to congestion in the days following the holidays, resulting in container backlogs that must be cleared immediately. Additional contributing factors include limited availability of trucking vendor fleets, hindered communication with related parties, and overloaded service systems. The objective of this study is to identify strategies for resolving import delays and to evaluate the supporting and inhibiting factors within the process. Method: The research method employed is descriptive qualitative, with data collected through interviews, observations, and documentation. Results: The results of the study indicate that the strategies implemented by the company include the optimization of documentation processes, coordination with relevant agencies, and the use of information technology for cargo tracking. The key supporting factor is the availability of competent human resources, while the main obstacles stem from regulatory changes and delays caused by third parties such as customs or logistics partners. Novelty: These findings are expected to contribute to the development of logistics management in the import sector.

World Bank, “World Bank Data (2023, 2024 estimates),” 2024.

D. D. Pane and A. A. Patunru, “The Role of Imported Inputs in Firms’ Productivity and Exports: Evidence from Indonesia,” Rev. World Econ., vol. 159, no. 3, pp. 629–672, 2022, doi: 10.1007/s10290-022-00459-0.

M. Christopher, Logistics & Supply Chain Management, 5th ed. Pearson Education, 2016.

N. Moini, M. Boile, S. Theofanis, and W. Laventhal, “Estimating the determinant factors of container dwell times at seaports,” Marit. Econ. & Logist., vol. 14, no. 2, pp. 162–177, 2012, doi: 10.1057/mel.2012.3.

Y. Lee and others, “Identifying key factors influencing import container dwell time using process mining and explainable AI,” Marit. Transp. Res., vol. 5, p. 100116, 2024, doi: 10.1016/j.martra.2024.100116.

P. Chhetri, S. Nguyen, V. Gekara, and S. Sharma, “Container dwell time predictive modelling: an application of ML algorithms,” Marit. Policy & Manag., pp. 1–31, 2025, doi: 10.1080/03088839.2025.2501010.

N. Servos, X. Liu, M. Teucke, and M. Freitag, “Travel Time Prediction in a Multimodal Freight Transport Relation Using Machine Learning Algorithms,” Logistics, vol. 4, no. 1, p. 1, 2019, doi: 10.3390/logistics4010001.

S. Ewamer, M. Alhossainy, M. Elbarkouky, and S. El-Seoud, “Applying Artificial Intelligence to Reduce the Seasonal Variation of Containers Dwell Time at Port Said Port,” Int. J. Eng. Manag. Sci., vol. 9, no. 2, pp. 1–15, 2022, doi: 10.21791/IJEMS.2022.2.1.

K. M. Eisenhardt, “Building Theories from Case Study Research,” Acad. Manag. Rev., vol. 14, no. 4, pp. 532–550, 1989, doi: 10.5465/amr.1989.4308385.

A. Dubois and L.-E. Gadde, “Systematic combining: an abductive approach to case research,” J. Bus. Res., vol. 55, no. 7, pp. 553–560, 2002, doi: 10.1016/S0148-2963(00)00195-8.

C. Voss, N. Tsikriktsis, and M. Frohlich, “Case research in operations management,” Int. J. Oper. & Prod. Manag., vol. 22, no. 2, pp. 195–219, 2002, doi: 10.1108/01443570210414329.

M. Barratt, T. Y. Choi, and M. Li, “Qualitative case studies in operations management: Trends, research outcomes, and future research implications,” J. Oper. Manag., vol. 29, no. 4, pp. 329–342, 2011, doi: 10.1016/j.jom.2010.06.002.

M. Ketokivi and T. Choi, “Renaissance of case research as a scientific method,” J. Oper. Manag., vol. 32, no. 5, pp. 232–240, 2014, doi: 10.1016/j.jom.2014.03.004.

W. Liu, D. Xie, and X. Xu, “Quality supervision and coordination of logistic service supply chain under multi-period conditions,” Int. J. Prod. Econ., vol. 142, no. 2, pp. 353–361, 2013, doi: 10.1016/j.ijpe.2012.12.011.

K. Selviaridis and A. Norrman, “Performance-based contracting for advanced logistics services: Challenges in its adoption, design and management,” Int. J. Phys. Distrib. & Logist. Manag., vol. 45, no. 6, pp. 592–617, 2015, doi: 10.1108/IJPDLM-11-2014-0267.

• VIEW ARTICLE

This work is licensed under a Creative Commons Attribution 4.0 International License.