The increasing urgency for sustainable practices has motivated this research to explore the barriers hindering the adoption of digital technologies in circular systems. As industries seek to leverage IoT for enhanced efficiency and sustainability, understanding these barriers is crucial for effective implementation. This study employs a comprehensive, multi–dimensional approach, integrating insights from a literature review and expert interviews with industry professionals. Key findings reveal that technological complexity and high initial costs are the most significant barriers, highlighting the need for targeted strategies to address these challenges. Additional barriers include regulatory compliance issues and unclear return on investment, which further complicate the adoption process. The study's conclusion emphasizes that overcoming these barriers is essential for facilitating the successful integration of digital technologies in circular economies. Furthermore, the research identifies the necessity for future investigations into the interactions between these barriers and the effectiveness of various interventions. The novelty of this study lies in its holistic examination of the multifaceted barriers, combining qualitative insights with a structured analytical framework. This approach not only contributes to the existing literature on Digitization but also offers practical implications for stakeholders aiming to enhance sustainability and efficiency in their operations. By addressing the identified challenges, organizations can pave the way for a more circular and resilient future, ultimately driving innovation and growth in the rapidly evolving digital landscape.

The process of health insurance policy selection is a critical decision with far–reaching financial implications. The complexity of health insurance policy selection necessitates a structured approach to facilitate informed decision-making amidst numerous criteria and provider options. This study addresses the health insurance policy selection problem by employing a comprehensive methodology integrating Spherical Fuzzy Analytic Hierarchy Process (SF–AHP) and Combined Compromise Solution (CoCoSo) Algorithm. Eight experienced experts, four from academia and industry each, were engaged, and eleven critical factors were identified through literature review, survey, and expert opinions. SF–AHP was utilized to assign weights to these factors, with Claim settlement ratio (C9) deemed the most significant. Subsequently, CoCoSo Algorithm facilitated the ranking of insurance service providers, with alternative A6 emerging as the superior choice. The research undertakes sensitivity analysis, confirming the stability of the model across various scenarios. Notably, alternative A6 consistently demonstrates superior performance, reaffirming the reliability of the decision-making process. The study’s conclusion emphasizes the efficacy of the joint SF–AHP and CoCoSo approach in facilitating informed health insurance policy selection, considering multiple criteria and their interdependencies. Practical implications of the research extend to individuals, insurance companies, and policymakers. Individuals benefit from making more informed choices aligned with their healthcare needs and financial constraints. Insurance companies can tailor policies to customer preferences, enhancing competitiveness and customer satisfaction. Policymakers gain insights to inform regulatory decisions, promoting fair practices and consumer protection in the insurance market. This study underscores the significance of a structured approach in navigating the intricate health insurance landscape, offering practical insights for stakeholders and laying a foundation for future research advancements.