The role of artificial intelligence in circular value creation : a conceptual framework and evidence from case studies

Abstract

The digital transformation and circular economy (CE) are two megatrends that have been discussed not only among practitioners and policy makers, but also as an interesting topic of research in the scientific world. While CE aims to transform the world economy model to a more sustainable and eco-friendlier version, digital technologies (DTs) are revolutionizing our everyday lives by offering innovative connected solutions. Implementing CE strategies offers considerable value by decoupling our production and consumption system from the linear model of ‘take-make-use-dispose’. However, applying CE principles requires a radical change in the way companies create and deliver value to their customers. Companies face challenges in aligning CE principles to their current system to offer service-oriented models instead of physical products. This raises the role of DTs as enablers of CE. In this sense, AI has been identified as one of the key DTs that can enhance circularity through advanced analytics capabilities. Utilising AI enables resource and energy efficiency that can help companies in making more resourceful decision-making. However, research on the effective utilisation of AI in circular value creation has been very limited and companies struggle to understand how AI can change their value creation model based on CE strategies. Addressing this gap, it is essential to develop the understanding of potential of AI in circular value creation.

This thesis employs a mixed methods approach to answer the main research question: “How can AI enhance circular value creation for companies and related business models?”, starting with a conceptual approach to improve the concept of value creation in CE and reveal the role of AI in the ReSOLVE framework. This is followed by empirical investigations through qualitative studies on product design and business model (BM) aspects of circular value creation. Since qualitative studies of this dissertation emphasise the role of data in digitally enabled CE, a literature review was conducted to identify the aspects and value of data in AI-enabled BMs, following by an empirical examination of the conceptual model by the last study.

The results contribute and add new knowledge to the field of AI and value creation in CE by providing detailed information on how AI can enhance resource and energy efficiency when applied in circular solutions. The findings demonstrate that AI can enhance circularity by enabling data-driven BMs such as product-service systems and the sharing economy. In addition, the results highlight the value of data for example in product design and prototyping, and the entire lifecycle of products to innovate AI-enabled BMs. The thesis identifies that an innovative business ecosystem which is connected by different DTs can enhance circularity for all the actors and partners of ecosystem through sharing transparent data that circulates within the supply chain.