Proposed Model for the Role of Decision Support Systems in Reducing Container Parking Time

Efficient port operations are crucial to global trade and supply chain performance. One of the key performance indicators for port efficiency is container dwell time—the duration containers spend at the port before being cleared or shipped. Prolonged dwell times can lead to congestion, increased operational costs, and reduced customer satisfaction. In this context, Decision Support Systems (DSS) have emerged as powerful tools to assist port authorities and logistics managers in making informed, data-driven decisions. This research explores the role of DSS in minimizing container dwell time by integrating advanced decision-making and predictive tools such as data analytics, machine learning, and simulation models. These tools enable real-time monitoring, accurate forecasting of container flow, and proactive planning, leading to improved resource allocation and streamlined operations. By analyzing how DSS contributes to faster, smarter decision-making, this study aims to highlight their potential to enhance port productivity and overall logistics efficiency.