Port safety: Seeing accidents before they happen
Publication Type
Case
Publication Date
2-2026
Abstract
Despite increasing mechanisation, port operations remain labour-intensive and inherently high-risk. Port workers are routinely exposed to multiple hazards, including heavy machinery, hazardous chemicals, adverse weather conditions, slippery surfaces, excessive noise, and congested traffic environments.
Common port-related incidents include slips, trips, and falls, as well as collisions involving vessels or vehicles, and cargo-handling accidents. These incidents not only generate substantial direct costs (e.g., injuries, equipment damage, operational delays), but also indirect costs such as productivity loss, reputational damage, and regulatory penalties. In addition, ports face low-probability but high-impact risks including fuel and chemical spills, fires, and explosions, etc. Such serious consequences further highlight the importance of preparedness and effective emergency response planning.
Given the critical importance of preventing safety incidents, proactive intervention requires a systematic understanding of the cause-and-effect relationships that give rise to such events. Rather than focusing solely on isolated hazards or post-incident analyses, this case study demonstrates how safety incidents can be anticipated and intervened in advance by extracting and analysing causal information from real-world incident reports.
This case is designed for junior- and senior-level undergraduate students to develop an appreciation of data analytics in operations management. After completing this case, students will be able to identify and interpret cascading effects within causality networks, explain the implications of direct and indirect cause-effect relationships leading to undesired safety outcomes, link analytical findings to real-world incidents, and design and evaluate leading and lagging safety indicators.
Keyword(s)
Analytics and data science, Risk analysis, Operations and supply chain management, Data processing, Data visualization
Discipline
Business Administration, Management, and Operations | Operations and Supply Chain Management
Research Areas
Operations Management
Data Source
Published Sources
Industry
Shipping Industry
Geographic Coverage
South Korea
Temporal Coverage
2025
Education Level
Executive Education; Postgraduate; Undergraduate
Publisher
Singapore Management University
Case ID
SMU-25-0038
Additional URL
https://ccx-shop.smu.edu.sg/products/port-safety-seeing-accidents-before-they-happen?variant=44106572365866
Comments
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