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All Journal Dinasti International Journal of Management Science
Rahmaddiansyah Rahmaddiansyah
Universitas Krisnadwipayana, Jakarta, Indonesia
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Other

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Operational Risk Management in Digital Logistics Companies Rahmaddiansyah Rahmaddiansyah; Budi Supriyatno; Aziz Hakim
Dinasti International Journal of Management Science Vol. 7 No. 2 (2025): Dinasti International Journal of Management Science (November - December 2025)
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijms.v7i2.6056

Abstract

The development of the digital logistics industry, driven by the rapid growth of e-commerce, has led to increasing complexity of operational risks that directly affect service quality and corporate performance. This study aims to analyze operational risk management in digital logistics companies, with a particular focus on the processes of risk identification, assessment, and mitigation arising from operational activities, especially in last-mile delivery, warehouse management, and information technology systems. The research adopts a descriptive approach, employing data collection techniques such as interviews, observations, and document analysis. Risk analysis is conducted using a risk matrix to determine the likelihood and impact levels of operational risks. The results indicate that the dominant risks faced by the company include delivery delays, digital system disruptions, scanning errors (mis-scans), courier human error, and an increase in return-to-sender (RTS) cases. Risk mitigation strategies implemented by the company include improving the reliability of information technology systems, providing courier training, standardizing operational SOPs, and conducting real-time monitoring of delivery processes. However, the effectiveness of these mitigation measures is still constrained by high shipment volumes, dependence on third-party applications, and environmental variables in the field. This study recommends strengthening enterprise risk management, integrating AI-based tracking systems, and developing periodic risk evaluation mechanisms to enhance operational efficiency and sustainability in digital logistics companies.
Co-Authors Azis Hakim Budi Supriyatno