This research develops and assesses a model based on capabilities that explains how platform-based open innovation networks enhance sustainability through sequential mediation processes. By relying on concepts of reflexive innovation, ecosystem learning, and knowledge co-creation, the research shows that participation in platforms enhances the maturity of the circular learning ecosystems; therefore, promoting collaborative reflexive practice. Reflexivity leads to two outcomes: (a) an individual-level increase in circular literacy, which implies an increase in knowledge, skills, and behavioral orientation to circularity, and (b) system-level sustainable platform-based innovation outcomes, comprising the social and environmental impacts of the innovational processes. The outcomes endorse the proposed mediation directions. Interestingly, the digital inclusivity orientation was not associated with the reflexivity-literacy relationship, signifying that inclusion requires a deeper organizational integration in order to generate high capability impacts. The study enhances the literature on circular economy and innovation by introducing the concepts of reflexivity and circular literacy as the strategic abilities of a company and providing managers and policymakers with insights on how to build inclusive and sustainability-oriented platform ecosystems.

The role of artificial intelligence (AI) in achieving sustainability goals has garnered attention in academic literature. While AI has been argued to be crucial in addressing circularity challenges, organizations face challenges in configuring a business model. Designing new business calls for insights on how AI can be integrated into value creation and capture mechanisms. There is a lack of clarity on how organizations deploy AI as they transition to circular business model innovation. The purpose of the study is to explore how AI is integrated into organizational processes while adopting circular business models. We conducted online open-ended interviews with 55 participants to explore the potential role of AI in enabling the adoption of circular business models. Our findings have implications for theory building relating to AI business model innovation and provide a novel avenue for further research on business model innovation literature. Building on a natural resource-based view, the findings indicate that while implementing a circular business model is challenging, AI enables organizations to create, transfer, and capture value through resource efficiency and the reuse of resources. As AI technologies continue to evolve, organizations must develop adaptive capabilities to continually explore opportunities. AI enables organizations to reduce costs, develop novel value-creation strategies, and capture opportunities, resulting in improved efficiency. Transitioning to a circular business model requires developing routines, and organizations must adapt existing systems to ensure these systems result in pollution prevention, product stewardship, and sustainable development. It is important for managers to develop organizational resources and capabilities that enable the development of AI capabilities.

Moving towards a circular economy needs development of digital platforms and organizational capabilities for innovation, reconfiguration and capture for sustainable value. This study enquires the influence of institutional pressures (namely coercive, normative, and mimetic) on the circular performance of firms, resulting in better ecosystem innovation synergy as well as dynamic circular reconfiguration, circular value capture and circular financial performance. The goal of this study is to develop a theory-based model that links institutional theory, dynamic capabilities, and circular economy with circular economic value added. The data comprises 207 valid responses collected from companies in the logistics and supply chain sector. SmartPLS 4 is used to analyze data. The three institutional pressures have a significant impact on the circular economy capabilities. Coercive pressure and normative pressure influence ecosystem innovation synergy while mimetic pressure predicts dynamic circular reconfiguration. Moreover, dynamic circular reconfiguration is associated with measurable improvements in cost efficiency and revenue generation, thereby strengthening circular financial performance and circular economic value added. The study reveals that circular value capture has a significant impact on circular economic value added. The data indicates that ecosystem innovation synergy does not have a significant effect on circular value capture or circular financial performance. Ecosystem collaboration does not produce changes in firm economic performance unless it brings about internal reconfiguration. The findings suggest that both dynamic circular reconfiguration and circular performance became significant for circular economic value added in the context of circular finance. The routes of ecosystem innovation synergy and circular value capture, by their nature, are not sources of pressure. The findings enhance the understanding of how institutional pressures and potential capabilities enabled by digital platforms facilitate the transition to the circular economy. This paper finally provides theoretical and managerial insights for achieving sustainable value creation.