From Niche to Norm: Digital Servitization for Circularity in Manufacturing. A Multi-Level Perspective

Manufacturing industry is shaped by rising sustainability demands and rapid technological innovation. As a sector responsible for nearly a third of global carbon emissions, it faces growing pressure to reconcile productivity with sustainability. Circular economy strategies and digital technologies particularly artificial intelligence (AI) offer a promising path forward. This research explores how manufacturers can transition from linear, product-based systems to circular, service-oriented business models such as Outcome-as-a-Service (OaaS), enabled by digital innovation. Grounded in Sustainability Transition Theory and the Multi-Level Perspective (MLP), the study investigates how digital technologies act as mechanisms to overcome systemic barriers and enable sustainable transformation. Background and Purpose The transition toward sustainable manufacturing has become increasingly urgent due to environmental pressures, regulatory change and shifting customer expectations. While circular economy (CE) strategies and servitization have gained momentum, the mechanisms through which digital technologies enable these transitions remain underexplored. This thesis addresses two key research questions: 1. What mechanisms enable digital technologies to support manufacturers’ transitions to circular OaaS models across niche and regime levels? 2. How can manufacturers leverage digital technologies to transform barriers into opportunities for circular OaaS models? Research Methods The study adopts a qualitative multiple case study approach, guided by an enhanced MLP framework. Secondary data were collected and triangulated from three leading manufacturers: Rolls-Royce, Signify, and Caterpillar - each exemplifying different stages of digital maturity and circular service model innovation. A theory-informed analytical framework was used to explore the interaction between digital technologies, circularity goals, and servitization strategies across MLP levels. Findings The research identifies three distinct AI-enabled transformation mechanisms: • Barrier Digitization: Converts physical limitations into digital visibility and prediction • Barrier Reconfiguration: Shifts business logic from product-centric to outcome- based models • Barrier Elimination: Removes systemic frictions through full-spectrum digital integration These mechanisms enable firms to overcome multilevel transition barriers and reconfigure value creation through data-driven, circular service models. Contributions and Implications Theoretical Contributions: • A mechanism-based extension of the MLP tailored to digital innovation in manufacturing • Clarification of AI’s role as a catalyst for system-level transformation • Integration of perspectives from Servitization, Service-Dominant Logic (SDL) and Disruptive Innovation Practical Implications: • A roadmap to help manufacturers transform barriers into enablers of circular value • Strategic insights for technology providers, educators and policymakers • Emphasis on scalable digital models balancing economic performance with sustainability