Grant: Discovery Grants Program - Individual

The aim of this research program is to construct innovative, data-empowered decision-support models that drive the digitalization and sustainability of resilient maritime supply chains. The models will harness advanced machine learning and optimization techniques, extracting insights from diverse data to inform strategic, tactical, and operational decision-making while maintaining robust oversight of maritime supply chains in uncertain contexts. The program will evolve through four stages: (i) Data Analytics, (ii) Diagnostic Analytics, (iii) Predictive Analytics, and (iv) Prescriptive Analytics. � Data Analytics: The initiative commences with the identification, accumulation, pre-processing, elucidation, and visualisation of data influencing performance metrics defining sustainable and resilient maritime supply chains. � Diagnostic Analytics: This phase will enable a comprehensive understanding of these performance metrics, selection of the most significant ones, and potential development of new metrics for optimized supply chain monitoring. � Predictive Analytics: The chosen metrics will be predicted based on the historical data collected following diagnostics. � Prescriptive Analytics: This stage optimizes predicted performance metrics to guide decision-making at diverse supply chain levels while ensuring continuous monitoring. The expected significant contributions of this research program span both theoretical and practical realms, with a distinct focus on real-world impacts and sustainable transformations in the maritime sector. Theoretically, this project will: (i) establish novel techniques to assess the degree of digital maturity, sustainability, and resilience in maritime supply chains, (ii) develop ground-breaking models merging machine learning algorithms with physical models to account for uncertainty in selected metrics, and (iii) devise data-driven strategies for enhancing and managing predicted metrics, speeding up the optimization process and facilitating real-time control. The models developed will be implemented in collaboration with governmental bodies from two provinces and three ports across Canada. Their involvement will assist in the data collection, validation, and maturity assessment during the initial stages. Furthermore, during the predictive and strategic phases, this collaboration will allow for the validation, deployment, and assessment of the novel strategies developed. The potential outcomes of this research program are far-reaching. It will generate a new knowledge framework around digitalization, sustainability, and resilience in maritime supply chains. Moreover, it will provide empirical evidence to guide policymaking, enrich academic discourse, and promote sustainable practices within the maritime industry. Ultimately, this project can redefine how maritime supply chains embrace digitalization and sustainability, leading to economically efficient and environmentally conscious operations.