Resumo

Industry 4.0 technologies transform the processes of value creation, capture, and delivery for companies transitioning to circular business models (Chauhan et al., 2022). These technologies facilitate the circularization of business models by continuously collecting and analyzing data, thereby supporting strategic decisions (Rosa et al., 2020). I4.0 technologies are acknowledged in scientific literature as enablers of circular practices within organizations; however, it remains unclear how these technologies are implemented in circular business models (Rosa et al., 2020).

Circular business models (CBMs) are essential for the transition to a circular economy, as they employ four key strategies to mitigate socio-environmental impacts: reducing, slowing down, closing, and regenerating material cycles (Bocken et al., 2022). Smart technologies can facilitate the adoption of circularization strategies and promote changes in companies' value chain, providing efficient transition to CBMs (Belhadi et al., 2022). Therefore, this work addresses the following research question: How can Industry 4.0 technologies facilitate the implementation of circular business models?

Circular business models (CBMs) are essential for the transition to a circular economy, as they employ four key strategies to mitigate socio-environmental impacts: reducing, slowing down, closing, and regenerating material cycles (Bocken et al., 2022). Smart technologies can facilitate the adoption of circularization strategies and promote changes in companies' value chain, providing efficient transition to CBMs (Belhadi et al., 2022). Therefore, this work addresses the following research question: How can Industry 4.0 technologies facilitate the implementation of circular business models?

The article conducts a systematic literature review and analyzes illustrative CBM cases at the micro level. The review, performed in January 2024 using Scopus, analyzed 20 articles to create a framework detailing key Industry 4.0 technologies and their functionalities in circular business models. This framework was tested on companies listed in the Circular X database, resulting in 66 categorized circular business models.

Five key technologies—Artificial Intelligence (AI), Big Data, Blockchain, Cloud Computing, and the Internet of Things (IoT)—are fundamental in enabling circular strategies within organizations. These technologies are crucial for data collection, integration, and analysis, each offering specific functionalities. Big Data provides essential infrastructure for data virtualization, supporting all data management stages. AI, Big Data, and IoT are vital in operational circular business models, aiding in value creation and delivery, thus supporting the development of circular business models.

Key technologies—AI, Big Data, Blockchain, Cloud Computing, and IoT—are crucial for data collection, integration, and analysis. These technologies transform data into actionable insights, aiding decision-makers. The study presents a framework outlining these technologies' roles and investigates real-world cases, offering practical insights and challenges. However, limited integration of Industry 4.0 technologies in CBMs and low circularization levels in operational models were noted. Further research on circular startups and case studies from the Global South is needed.

Bocken et al (2022) The sufficiency-based circular economy—an analysis of 150 companies. Frontiers Sustainability Belhadi et al (2022) A self-assessment tool for evaluating the integration of circular economy and I4.0 principles in closed-loop supply chains. Int. Journal of Production Economics Chauhan et al (2022) Linking circular economy and digitalisation technologies: A systematic literature review of past achievements and future promises. Technological Forecasting and Social Change Rosa et al (2020) Assessing relations between Circular Economy and I4.0: a systematic literature review. IJP