This paper examines the role of digital twins (DTs) in promoting sustainability within seaport operations and logistics. DTs have emerged as promising tools for enhancing seaport performance. Despite the recognized potential of DTs in seaports, there is a paucity of research on their practical implementation and impact on seaport sustainability. Through a systematic literature review, this study seeks to elucidate how DTs contribute to the sustainability of seaports and to identify future research and practical applications. We reviewed and categorized 68 conceptual and practical digital applications into ten core areas that effectively support economic, social, and environmental objectives in seaports. Furthermore, this paper proposes five preliminary potential applications for DTs where practical implementations are currently lacking. The primary findings indicate that DTs can enhance seaport sustainability by facilitating real-time monitoring and decision-making, improving safety and security, optimizing resource utilization, enhancing collaboration and communication, and supporting the development of the seaport ecosystem. Additionally, this study addresses the challenges associated with DT implementation, including high costs, conflicting stakeholder priorities, data quality and availability, and model validation. The paper concludes with a discussion of the implications for seaport managers and policymakers.

In a world facing unprecedented challenges, such as climate changes and growing social problems, the pharmaceutical industry must ensure that its supply chains are environmentally sustainable and resilient, guaranteeing access to key medications even when faced with unanticipated disruptions or crises. The core goal of this work is to develop an innovative simulation-based approach to support more informed and effective decision making, while establishing reasonable trade-offs between supply chain robustness and resiliency, operational efficiency, and environmental and social concerns. Such a decision-support system will contribute to the development of more resilient and sustainable pharmaceutical supply chains, which are, in general, critical for maintaining access to essential medicines, especially during times of crises or relevant disruptions. The system will help companies to better manage and design their supply chains, providing a valuable tool to achieve higher levels of resilience and sustainability. The study we conducted has two primary contributions that are noteworthy. Firstly, we present a new advanced approach that integrates multiple simulation techniques, allowing for the modeling of highly complex environments. Secondly, we introduce a new conceptual framework that helps to comprehend the interplay between resiliency and sustainability in decision-making processes. These two contributions provide valuable insights into understanding complex systems and can aid in designing more resilient and sustainable systems.

The recent COVID-19 pandemic has highlighted the key role of the pharmaceutical industry and its supply chain operations in society. Like in many other sectors, this pandemic has unveiled important vulnerabilities and weaknesses across the pharmaceutical distribution network, calling the attention for the importance of resiliency, flexibility, and sustainability strategies. One of the key challenges regarding resiliency is the ability to understand and anticipate the supply chain behaviour under uncertainty and dynamically manage capacity. In order to address this challenge, this paper proposes a simulation-based approach with a twofold goal: i) to understand the pharmaceutical supply chain network dynamics, in order to fast-track vulnerabilities and anticipate risks propagation across the network; and ii) to support decisionmaking for enhancing resiliency and flexibility, through capacity management strategic decisions. The main contributions of this work are grounded on the integration and exploitation of different simulation paradigms, in order to understand the cause-effect relationships in complex systems, under several disruption scenarios. In this way, the disruption risks and their propagation are identified throughout the supply chain network, providing insights for the proactive and timely development of contingency and risk mitigation plans.