From Digitalization to Data-Driven Decision Making in Container Terminals
This work targets terminal planners and managers by proposing a data-driven perspective to improve decision-making, but it is incremental as it builds on existing digitalization trends without introducing new methods.
The chapter addresses the lack of data-driven approaches in container terminal operations by introducing business analytics to extract insights from operational data, aiming to reduce uncertainties and identify inefficiencies, thereby complementing traditional optimization methods.
With the new opportunities emerging from the current wave of digitalization, terminal planning and management need to be revisited by taking a data-driven perspective. Business analytics, as a practice of extracting insights from operational data, assists in reducing uncertainties using predictions and helps to identify and understand causes of inefficiencies, disruptions, and anomalies in intra- and inter-organizational terminal operations. Despite the growing complexity of data within and around container terminals, a lack of data-driven approaches in the context of container terminals can be identified. In this chapter, the concept of business analytics for supporting terminal planning and management is introduced. The chapter specifically focuses on data mining approaches and provides a comprehensive overview on applications in container terminals and related research. As such, we aim to establish a data-driven perspective on terminal planning and management, complementing the traditional optimization perspective.