Phd in INDUSTRIAL AND MANAGEMENT ENGINEERING

Thesis title: Digital Transformation in a Hyper-Connected World. Transforming legacy systems through blockchains, IoT and AI

In the contemporary business landscape, Digital Transformation (DT) is a defining trend, driven by rapid technological advancements. However, a clear conceptual agreement on DT remains elusive, with diverse perspectives in research. DT involves complex innovations in cultural, technological, and organizational aspects integrated with digital technologies, leading to transformative changes in society. This integration of technology and business models, essential for organizational and cultural transformation, requires a shift from legacy systems to advanced, decentralized IT architectures. However, DT is not just about adopting new technologies but also about successfully responding to ongoing discoveries, necessitating continuous strategic adaptation and experimentation. Business Process Management (BPM) plays a pivotal role in guiding organizations through these changes, and aligning IT systems with organizational strategies. The interplay between DT and BPM becomes crucial when examining organizational resilience, coopetitive strategies, and the shift to autonomous systems. This thesis explores three research pillars (RPs): Resilient processes through IoT, Coopetitive processes through Blockchain, and Efficient public processes through AI. These RPs aim to address challenges and leverage technologies synergistically in the dynamic landscape of DT. RP1 focuses on resilient processes through IoT, aiming to develop a Maturity Model for resilient business process design. RP2 explores coopetitive processes through Blockchain, addressing business confidentiality challenges in transparent supply chains. RP3 aims to enhance public processes through AI, addressing resource scarcity in public administrations, particularly in the judicial domain. A Design Science methodology is adopted to bridge theoretical frameworks with practical implementation, aligning with the dynamic landscape of DT and BPM.