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.

The role of AI is changing and reshaping auditing processes. However, the adoption of AI in financial auditing remains limited due to auditors' lack of expertise, resistance to change, and unclear regulatory laws. The present study uses Innovation Resistance Theory (IRT) as a base to identify several functional (active) or psychological (passive) barriers on resistance to adopting AI in financial auditing. Open-ended survey questions were used to gather the responses from 41 auditors. The analysis identified five barriers: tradition, image, value, risk, and usage barriers associated with AI adoption. The study identified several concerns, including poor data quality, AI-biased outputs, regulatory and compliance issues, lack of qualitative and subjective judgment skills, lack of knowledge and technical expertise, high cost, and many more. The study extends the IRT framework and evaluates the relevance of both psychological and functional barriers when adopting AI. The study examines the five barriers' impact on users and the significance of each on their resistance to AI adoption.