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AbstractThis thesis investigates the complex landscape surrounding the adoption of Circular Business Models (CBMs) in the manufacturing industry, focusing on both the enabling factors and existing roadblocks. Two main research questions guide the inquiry: (1) What are the drivers and barriers for the adoption of CBMs in manufacturing? (2) What impact do emerging technologies like AI, IoT, and Blockchain have on this adoption, considering their capability to manage vast data quantities? This study identifies several key challenges such as financial constraints, technological limitations, and organizational resistance to change. These challenges are examined in the light of existing governmental initiatives and regulations, technological innovations like Industry 4.0, and factors concerning supply chain management. It can be found that while AI, IoT, and Blockchain technologies have a generally positive influence on CBMs, their integration is hampered by technological and organizational barriers. Through qualitative interviews with industry experts and an in-depth literature review, this study provides valuable practical recommendations for overcoming these hurdles. Recommendations include a multi-stakeholder approach involving governmental bodies, organizational change management strategies, and the leveraging of technological advancements for more efficient CBM deployment. The findings of this thesis contribute to academic discourse while offering actionable insights for manufacturing companies and policymakers alike. Given the increasing importance of sustainable development and circularity in business, this study serves as a timely resource for navigating the challenges and opportunities in implementing CBMs.

ObjectiveThis thesis aims to identify challenges that affect the adoption of Circular Business Models (CBMs) in manufacturing. It also investigates how emerging technologies like Artificial Intelligence, Internet of Things and Blockchain impact CBM feasibility. The study provides recommendations on overcoming roadblocks for successful implementation.

Key FindingsThe manufacturing sector faces financial, technological, and market barriers to implementing Circular Business Models (CBMs), but the adoption of AI, IoT, and Blockchain technologies can improve data management. However, integration requires overcoming technical challenges while government policies impact CBM implementation. Organizational resistance is a significant challenge that could be addressed through supplier engagement and industry partnerships. Companies should increase organizational readiness for change by adopting a phased approach to technology integration and lobbying for favorable policies. To achieve sustainable development in the face of environmental crises and market changes, adopting CBMs is necessary. A multidimensional approach involving different stakeholders must be taken for meaningful progress as there are no universal solutions.

ReasoningTransitioning to circular practices in manufacturing enables the generation of value through increased resource efficiency and revenue diversification. Addressing industry-specific challenges, will drive sustainable growth and enhance the overall business performance.