This line of investigation focuses on the understanding of how supply chain coordination and collaboration in such complex and dynamic networks take place and the (mis)fit with different business environments.
Environmental and social sustainability of such networks is often questioned and under public scrutiny. Thus, we investigate how structural and relational characteristics of such networks affect sustainability and what supply chain management strategies enable sustainable practices adoption in the network.
This line of research delves into how data, theory, and AI can be leveraged to drive actionable decisions in inventory management, sourcing strategies, and operational processes. It spans a variety of industries, including consumer goods, transportation, manufacturing, and retail, showcasing the transformative potential of data-driven and AI-enabled approaches in solving complex operational challenges.
The aim of this line is to study the socio-technical processes by which digital infrastructures and platforms are designed, extended, managed and governed and their effects on the business networks.