# From Digitalization to Data-Driven Decision Making in Container Terminals

## TL;DR

This paper advocates for integrating business analytics and data mining techniques into container terminal planning and management to enhance decision-making and address operational complexities.

## Contribution

It introduces a data-driven framework for terminal management, emphasizing the role of business analytics and providing a comprehensive overview of data mining applications.

## Key findings

- Data-driven approaches help reduce uncertainties in terminal operations.
- Business analytics can identify inefficiencies and disruptions.
- The chapter offers a comprehensive overview of data mining in container terminals.

## Abstract

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.