Exploring How Usage-Focused Business Models Enable Circular Economy through Digital Technologies

Abstract

Recent studies advocate that digital technologies are key enabling factors for the introduction of servitized business models. At the same time, these technologies support the implementation of the circular economy (CE) paradigm into businesses. Despite this general agreement, the literature still overlooks how digital technologies enable such a CE transition. To fill the gap, this paper develops a conceptual framework, based on the literature and a case study of a company implementing a usage-focused servitized business model in the household appliance industry. This study focuses on the Internet of Things (IoT), Big Data, and analytics, and identifies eight specific functionalities enabled by such technologies (improving product design, attracting target customers, monitoring and tracking product activity, providing technical support, providing preventive and predictive maintenance, optimizing the product usage, upgrading the product, enhancing renovation and end-of-life activities). By investigating how these functionalities affect three CE value drivers (increasing resource efficiency, extending lifespan, and closing the loop), the conceptual framework developed in this paper advances knowledge about the role of digital technologies as an enabler of the CE within usage-focused business models. Finally, this study shows how digital technologies help overcome the drawback of usage-focused business models for the adoption of CE pointed out by previous literature.

Integrating Virtual Reality and Digital Twin in Circular Economy Practices: A Laboratory Application Case

“…Internet of Things (IoT) is the digital technology that can be most easily integrated in CE practices [18,24,25]. Its role lies in collecting data from the field and then transferring that data (for example, through CPS [3]) to other I4.0 technologies (e.g., Big Data & Analytics (BDA) and CC) tools that are able to analyze them and extrapolate information for better decision-making at either the product or process level [18,[26][27][28].…”

“…Its role lies in collecting data from the field and then transferring that data (for example, through CPS [3]) to other I4.0 technologies (e.g., Big Data & Analytics (BDA) and CC) tools that are able to analyze them and extrapolate information for better decision-making at either the product or process level [18,[26][27][28]. Under this perspective, IoT may intrinsically increase resource efficiency, extend product lifespan, and close the loop [24]. By collecting and analyzing product-related data through IoT, they can be redesigned, maintained, upgraded, disassembled, or recycled more easily [25,29].…”

“…By collecting and analyzing product-related data through IoT, they can be redesigned, maintained, upgraded, disassembled, or recycled more easily [25,29]. In addition, IoT also provides process-related data by optimizing remanufacturing and recycling practices and enabling better production planning and control [24,28]. For these reasons, IoT adoption in CE practices can enable (i) new waste management strategies, (ii) improvement of the processes circularity level, and (iii) creation of smart industrial environments or dynamic feedback control loops [5,30,31].…”

“…RFIDs have been exploited for recovering data from obsolete laptops and, basing on that, for deciding the best EoL strategy to adopt through a multi-criteria decision-making model based on linear physical programming. Bressanelli et al [24] explored how CPS, IoT, and BDA can improve remanufacturing performances in terms of monitoring, data gathering and process optimization of washing machines. Marconi et al [50] presented a method for calculating the disassembly times of target components in washing and coffee machines.…”

The Millennials’ Effect: How Can Their Personal Values Shape the Future Business Environment of Industry 4.0?

“…Put in simple words, digitalization is a process of representing the real world with digital symbols using digital technologies (Scholz et al, 2018). But nowhere are its effects more evident than in the manufacturing and industrial sector, which gave rise to the phenomenon of Industry 4.0, where business digitalization is at its strongest (Bressanelli et al, 2018). Industry 4.0 aims for a new industrial revolution while integrating automation, Internet of Things, cyber-physical systems, artificial intelligence, and smart manufacturing (Wang et al, 2016;Roblek et al, 2016).…”