Keywords

1 Introduction

Circular business model has recently emerged as a new research field in the Circular Economy research to call scholars and practitioners in strategic and innovation management research streams for analyzing the transition of companies from a linear to a circular model (Geissdoerfer et al. 2017; Lewandowski 2016).

Among the several managerial practices that companies can put in place to allow this transition, the adoption of digital technologies, such as Big Data and Analytics (BDA), Internet of Things (IoT), and Cyber-Physical Systems (CPSs), is becoming of paramount importance (Papadopoulos et al. 2017a, b). However, the role that these technologies can play both in terms of functionalities and circular value targets, such as energy efficiency, product lifecycle extension, etc. (MacArthur and Waughray 2016; Bressanelli et al. 2018), which can be reached because of their adoption, is still largely unexplored.

Starting from this premise, this chapter is aimed to depict how digital technologies can be adopted by companies to support the shift from a linear to a circular business model. In particular, this study presents a set of digital technologies that can effectively improve the circular practices in the built environment and shows, through the analysis of exemplary projects in which a leader company operating in the building industry was involved, how digital technologies can be used to support the business model transition of companies toward Circular Economy.

We focused on case studies of projects in the building industry as this industry is particularly interesting to analyze both in terms of Circular Economy and digital technologies adoption. First, “buildings accounted for 32% of total global final energy use in 2010. Moreover, the building industry consumes 40% of the materials entering the global economy, while only an estimated 20–30% of these materials are recycled or reused at the end of life of a building” (Leising et al. 2018, p. 977). Second, the building sector is rather unexplored from the point of view of digital technologies adoption, although a few emerging studies have shown their potential in this industry (Elmualim et al. 2018).

The chapter is structured as follows. After the Introduction, Sect. 2 presents the current state of research about the role of digital technologies in the Circular Economy. Section 3 presents the rationale of the methodology and the case study analysis. Finally, Sect. 4 presents and discusses the results, whereas Sect. 5 summarizes the conclusions, also depicting the limitations and avenues for future research.

2 State-of-the-Art

Circular Economy has undoubtedly become an interesting topic over the last years both in academia and among practitioners and companies, with the goal to overcome the linear, open, models of production and resource consumption (Kirchherr et al. 2017; Ghisellini et al. 2016), which rely on the “take, make, dispose” paradigm. The Circular Economy approach aims to minimize the utilization of input raw material, enhance as much as possible the product lifetime, exploiting the maximum value from it, and when reached the end of life, repurpose, reuse, and/or recycling spare parts and raw materials in order to decrease the total demand of input material (Stahel 2016; Potting et al. 2017).

Circular business model has recently emerged as a new research field in the Circular Economy literature to analyze the transition of companies from a linear to a circular business model (Ranta et al. 2018). In particular, studies in this direction are aimed to deepen the managerial practices that companies can implement at the business model level, and among three major dimensions of a company’s business model, namely value creation, value transfer, and value capture, to design their own circular business model (Urbinati et al. 2017; Ünal et al. 2019). The value creation dimension involves a set of (1) activities, such as modularization, standardization, design for products’ disassembly, design for products’ recycling, and (2) resources’ usage, such as natural, recyclable, durable, easy-to-separate materials, which are necessary for establishing a circular value proposition (Moreno et al. 2016). The value transfer dimension concerns how companies interact with customers to share and promote explicitly the circular value proposition (Linder and Williander 2017; Shao and Ünal 2019). The value capture dimension, finally, involves a set of mechanisms, such as pay-as-a-service, to properly gather the circular value generated and to convert it into revenue streams, cost savings, and value preservation of resources (Geissdoerfer et al. 2017; Jiao and Evans 2017).

Among the several managerial practices that companies can adopt to allow this transition, it is interesting to investigate the use of digital technologies to support the design of the above three dimensions of companies’ business model (Centobelli et al. 2020). In particular, several digital technologies have proliferated in recent years to support companies in improving the performance of their products and services, production processes, and in redesigning their organizational structures (Del Vecchio et al. 2018). These technologies may represent promising levers to foster the transition toward Circular Economy (Bressanelli et al. 2019).

A recent theoretical contribution in the intersection between Circular Economy and digital technologies has proposed a five-categories classification of main technologies that can contribute to reach Circular Economy targets (Rosa et al. 2020):

  • Cyber-Physical Systems (CPSs): CPSs are an integration of hardware and software components; computers and integrated networks monitor and control physical processes, generally through feedback systems, in which physical processes influence calculations and vice versa (Lee et al. 2015).

  • Internet of Things (IoTs): IoTs is a set of technologies that allows the interaction and cooperation between devices, things, or objects, using modern wireless telecommunications, such as radio frequency identification (RFID), but also sensors, tags, actuators, and cell phones (Nasiri et al. 2017).

  • Big Data and Analytics (BDAs): BDAs represent the application of advanced data analysis techniques for the management, processing, and storage of large data sets (Urbinati et al. 2019; Soroka et al. 2017).

  • Additive Manufacturing (AM): AM consists of a suite of technologies that allows producing a growing range of products through the layering or 3D printing of materials (Mandolla et al. 2019; Dutta et al. 2001).

  • Simulation Systems (SSs): SSs are decision support tools based on a wide range of mathematical programming techniques that allow achieving objectives related to both Circular Economy and digitalization, such as the modeling of material flows in recycling processes or the regeneration of products or urban areas (Akanbi et al. 2018; Lieder et al. 2017).

Table 1 summarizes the main functionalities of the above categories of digital technologies for a Circular Economy transition.

Table 1 Digital technologies for a Circular Economy transition (adapted from Rosa et al. 2020)
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For example, the AM is clearly related to the recycling of products and materials and allows an innovative way to reintroduce them on the market—as in the case of the SEB Group, a French multinational world leader in the production of small appliances, which has undertaken a spare parts 3D molding project to facilitate assistance and repair processes (Perona et al. 2018). CPSs can support the development of innovative services, in particular for maintenance applications—as in the case of the Hera Group, one of the major Italian multiutilities, which through this technology collects data from the water recovery process to generate knowledge and implement interventions (Luksch 2018). Finally, BDA and IoT can allow reaching circular value targets in several ways, such as the digitalization of circular managerial practices (e.g., maintenance, reuse/redistribute, refurbish/remanufacture, etc.), the life cycle management, the development of smart services, and a more effective management of the supply chain—as in the case of Rolls-Royce, which through the “Power-by-the-Hour” program has implemented the IoT to monitor the engine performance data in real time and to process automatically such data collected through the BDAs (Perona et al. 2018).

However, the role that these technologies can play both in terms of functionalities and circular value targets, such as energy efficiency, product lifecycle extension, etc. (MacArthur and Waughray 2016; Bressanelli et al. 2018), which can be reached because of their adoption, is still unexplored. Moreover, the role these technologies can play to support the design of value creation, transfer, and capture dimensions of companies’ business model, and thus, the transition of companies from a linear to a circular business model deserves further investigation. Although the presence of a few interesting examples, further empirical analysis is needed to analyze the role of digital technologies in a business model transition of companies toward a Circular Economy (Chiaroni et al. 2020).

Accordingly, the aim of the chapter is to answer the following research question: “How can digital technologies be adopted by companies operating in the building industry to support the transition of their business model toward Circular Economy?”

3 Methodology

3.1 Using a Case Study Analysis

The chapter leverages an empirical analysis of projects in which a leader company operating in the building industry was involved to gain a better understanding of the role of digital technologies to support the design of a circular business model. The choice of a case study analysis is favored when addressing complex organizational and managerial issues through a qualitative-oriented approach (Yin 2003). In addition, case studies across longitudinal information sources are suited to answer “how” questions, as in our case, and to investigate a phenomenon in its whole complexity and to obtain initial insights on the phenomenon under investigation adopting an inductive approach in the interpretive tradition (Siggelkow 2007). In addition, case studies avoid the weaknesses inherent in retrospective reconstruction, and the associated reinterpretation errors, by real-time data collection. Although the identification of the case study has followed theoretical and convenience sampling criteria (Voss et al. 2002), its selection was made due to its high involvement in Circular Economy activities, especially driven by digital technologies adoption, and thus it fits with the above research question.

For the collection of the information, we established a semi-structured interview protocol with open-ended questions, which we used to make the interviewees with the key respondents of the company. We append the interview protocol in the Appendix (Table 5). Data were collected during March–April 2020. Key informants of our case study belong to the Technology Team of the Italian business unit of the selected company, which deals with technologies for enhancing a Circular Economy transition of the company and its clients. The team is guided by a Team Leader, who is responsible for all the team’s activities. The first round of interviews was followed by a second and, in some cases, a third round, to consolidate information collected and to crosscheck relevant data and clarify important issues. In some cases, interviews were also followed up by emails with questions of clarification. Once permission had been granted, all the interviews were recorded and were later transcribed by the co-authors of the paper, enabling the inclusion of additional notes, comments, and ideas.

Interview data were coded using an iterative process that attempted to capture all the relevant information. A within-case analysis was conducted (Weber 1990) and, again, a cross-information analysis to identify and corroborate the recurrent pattern of useful information. All the information gathered from the key informants was triangulated with secondary sources of information to avoid post-hoc rationalizations (Yin 2003). For the purpose of enhancing data triangulation, in particular (Eisenhardt and Graebner 2007), various documents or archival records regarding the company (such as annual reports or internal firm-specific documentation related to processes and outcomes) were used (Amankwah-Amoah 2016). Finally, to support the reliability and validity of the whole collected and analyzed information, the Technology Team Leader was responsible for revising the manuscript and given his contribution to refine and enrich the empirical investigation was definitely involved as third co-author of the present research.

We continuously compared the results of the empirical evidence with the information deriving from the scientific research to refine, enrich, and modify the theoretical setting. To describe the case, we adopted a narrative approach in the form of a “narrative report” (Langley 1999), as follows.

3.2 Presentation of the Company and the Industry

3.2.1 The Company

The company chosen as a case study is Arup, a multinational firm of designers, planners, engineers, architects, consultants, and technical specialists, working across every aspect of the built environment, from buildings to infrastructures, committed to shaping the digital built environment. Born in 1946 in London, over time the company “has pushed the boundaries of what design and engineering can achieve”, with the vision that a more collaborative and open-minded approach to engineering would lead to work of greater quality and enduring relevance. Arup continues to be recognized for bravely imaginative solutions to the world’s most challenging projects. The company “has always nurtured pioneers and original thinkers, and for decades those creative and ambitious have come to the company to do their best work.” “From concert halls that led to new definitions of acoustic engineering, to its long history of developing the digital tools the building industry relies upon, that of the company is a story of relentless innovation.” Globally, Arup has annual revenues accounting for approximately £1.71 billion with more than 15,000 staff members and almost 7000 customers served across the world (year 2019). Employees are also “independent by nature, with the confidence to take on some of the world’s most challenging projects.” In addition, in 2016 the company started a strategic partnership with the Ellen MacArthur Foundation, the pioneer international organization for developing Circular Economy. Arup is present with several business units in America, Australia, East Asia, Middle East, and Europe, including Italy. The Italian business unit, named Arup Italia, was established in the year 2000 in response to an ever-increasing demand for specialist consultancy and the number of complex projects being developed.

3.2.2 The Industry

The building industry is the world’s largest consumer of raw materials. It represents 50% of world steel production and consumes over 3 billion tons of raw materials (WEF 2016). The demand for the building resources is also increasing by global demographic and lifestyle changes, and many of them are becoming scarcer and more difficult to extract. For example, natural resources are currently consumed at twice the speed with which they are produced. By 2050, this speed rate could be three times (Arup 2016). In addition, the growth of the world population and, especially, of its middle class (which will expand from 2 to 5 billion by 2030) is putting unprecedented pressure on natural resources (Pezzini 2012). Competition for resources and supply disruptions are already contributing to volatile materials prices, creating short-term uncertainty, and increasing overall costs. Stricter global environmental regulations to protect fragile ecosystems are also making it more difficult and expensive to extract and use certain resources. The built environment is under increasing pressure to minimize its impact. A Circular Economy approach could help the sector to reduce its environmental footprint, avoiding rising costs, delays, and other consequences of volatile commodity markets. Given the potential to save £60 billion of primary resources by 2030 in the European Union (EU) (Ellen MacArthur Foundation and McKinsey Center for Business and Environment 2015), there are clear advantages in adopting Circular Economy practices across the EU sector. This would involve remodeling the way projects are purchased, designed, built, managed, and reused. A recent study from Arup (2016) has highlighted how the Circular Economy approach can be applied in the built environment. For example: efficient and circular building performance (e.g., net zero energy strategies) reduce negative externalities, consumption of primary resources and waste, and help safeguarding, restoring, and increasing the resilience of ecosystems; sharing of spaces and infrastructure (e.g., peer-to-peer sharing, and co-living) allows for optimizing asset use; modular buildings may optimize also the efficiency and resource consumption in the production phase; remanufacturing, recovering, and recycling loops allow for closing the materials and components flows that take place in both the biological and technical cycles, creating new uses for materials.

3.2.3 Digitalization Initiatives

The role of digital technologies across the built environment is enormous. As underlined by Will Cavendish, Global Digital Services Leader at Arup, “digital technologies are transforming every aspect of the built environment. We help clients take advantage of this new, connected world.” Indeed, digital technologies allow organizations “to make informed decisions about the design, management, and performance of their assets, helping them to be more sustainable and resilient to change.” Among the several solutions, the built environment can especially benefit from the exploitation of a digital twin, i.e., “a digital representation of a real-world entity—a building, a bridge, a rail network, even an entire city—aimed at making that entity safer, more efficient, and more resilient to change.” Digital twins are also undergoing a period of rapid innovation. Arup, for example, uses the digital twin for predicting traffic patterns, energy usage, building stresses, develop predictive maintenance, assess fire risk and other resource and risk profiles. In this perspective, the Digital Transformation Plan of the company is based on four main work streams: Data, Automation, Services, and Products. Along these workstreams, six main digital services can be identified: (1) Building Information Modeling (BIM), (2) Data insights and analytics, (3) Geographic Information Systems (GISs), (4) Information and Communication Technology (ICT) infrastructure design, (5) Software products, and (6) Visualization. In particular, (1) BIM represents “the bedrock of intelligent assets, embedding data in every aspect of a smarter built environment. It consists of an advanced design process that brings to life the interactions between designers and between each design element.” As pointed out by Volker Buscher, Chief Data Officer, “digital tools like data-driven analysis are already helping us improve how assets are designed and constructed. We can enhance the experience of the people who interact with them and analyze how these assets will perform in future”; (2) data insights and analytics are aimed to “provide important insights, create a single point of truth on project performance, answer key commercial questions, and help organizations to predict and react to future trends”; (3) in addition, the company leverages the Geographic Information Systems (GISs) technology to visualize, manage, analyze, and collate data based on geo-referenced locations. The services range from web-based mapping tools to 3D models, often incorporating BIM. GIS solutions “make it simpler and quicker to manage assets geographically, to identify opportunities, reduce risk, and adapt to better face the future”; (4) moreover, ICT infrastructure and integrated technology designs support buildings and businesses to operate effectively. The company’s “consultants combine technology expertise with built environment knowledge to design network and ICT infrastructure solutions, which ensure operations are never compromized and reach their full potential”; (5) the company also began developing its own software suites more than 40 years ago in response to the building environment evolving challenges. Today, the company’s software house brings relevant, flexible, tools to organizations and leads the field in structural, geotechnical, crowd simulation, and document management solutions; (6) finally, the company combines “design data from across all disciplines to create robust representations for architects, engineers, developers, planners, and governments. Multidisciplinary visualizations bring future projects to life, aiding decision-making, and engagement. These benefit any stage of a project—feasibility, early design, planning, consultation, detailed design, or marketing.”

4 Results and Discussion

The information included in the Results and Discussion was elaborated from the combination of interviews and Arup website: https://www.arup.com/.

The intersection between digital technologies and Circular Economy becomes tangible in a large variety of consultancy and projects where Arup is involved. We had the chance to access data and discuss exemplary projects, involving different usage of digital technologies.

Interestingly the company focused one of its major development on Simulation Systems (SSs). The goal of the company was to build a digital twin that could be used for supporting decisions at different levels and at different stages of development of the project and operation of the building. The SS of Arup is named Neuron and its main characteristics are reported in Table 2.

Table 2 The Neuron tool of Arup
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The tool Neuron is a clear example of how far digital models of buildings can go and where data analytics and Artificial Intelligence & Machine Learning (AI/ML) techniques are used to perform advanced analysis, collect real-time data, and autonomously predict the user profiles of the building, the energy and water consumptions and then set maintenance scenarios. These outcomes are fundamental for clients and facility management teams to make informed decisions about achieving the most efficient use of resources and save energy costs. Maintenance activities and replacement of components can be scheduled according to business models based on a circular approach. For example, lighting fixtures may follow a product-as-a-service scheme, where the provider will guarantee a performance rather than selling a product; other components might require a replacement at a point of their lifetime that can be set when they still have a value on the secondary market or can be reused for other purposes, thus generating an opportunity for cost savings or additional revenues.

To have an effective SS like Neuron, however, the company had to build several layers of related digital technologies, namely Cyber-Physical Systems (CPSs), Internet of Things (IoTs), and Big Data and Analytics (BDAs). Therefore, Neuron consolidates and links data from disparate equipment and devices and turn them into customized insights for energy and building system optimization through interactive and responsive dashboards. Accordingly, the adoption of digital technologies is fundamental to support the decision-making process toward the adoption of specific circular managerial practices and to increase the awareness of all the stakeholders. In particular, the adoption of live dashboards, shared on cloud platforms, can be also used to identify projects’ ambitions, needs, and actions to be implemented in the design process. Since the early stages, a shared view of the workstreams and the areas of actions is essential for a holistic definition of project deliveries. Decision-making or framework definition dashboards can be developed at different levels of detail. On the one hand, they can be focused on Circular Economy only, thus identifying sub-workstream areas (e.g., technical, energy, economy, and social). On the other hand, they can be adopted at a broader level, where Circular Economy is one of the project drivers in a wider sustainability strategy. Both the two configuration frameworks of the dashboard require the end client to define initial aims and then all the stakeholders and the design team to be called in and provide proposals to populate the dashboard. It is initially evaluated through quantitative and qualitative Key Performances Indicators (KPIs); finally, through a series of buy-in sessions, the managerial actions to be implemented in the next stage of work are defined.

In addition to the focus on SSs, the company started exploring the usage of Additive Manufacturing (AM). Additive Manufacturing (AM) has been applied in several exemplary projects of Arup to enable a circular transition: (1) the 3D Housing 05 in Milan, (2) the MX3D bridge in Amsterdam, (3) the Daedalus Pavilion, and (4) the Cloud Pergola at the Biennale in Venice, are all projects where the digitalization of the design, manufacturing, and construction processes was the key to empower an approach based on the principles of Circular Economy. Table 3 summarizes the key aspects of each project.

Table 3 The role of AM in exemplary Arup projects
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Also in this case, the use of Big Data and Analytics (BDAs), empowered by Artificial Intelligence (AI), particularly on robotics and image recognition techniques, have allowed for the manufacturing of building and components capable to use the minimum amount of materials required, thus minimizing waste and pushing for the development of innovative and sustainable materials mix.

The overall results of the empirical analysis were finally mapped onto the dimensions of a company’s business model, which have been particularly addressed by the analyzed digitalization projects, i.e., the value creation and value transfer dimensions (Table 4).

Table 4 Empirical findings mapped onto the dimensions of a company’s business model
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In particular, Additive Manufacturing (AM) was necessary to support the digitalization of the design, manufacturing, and construction processes of modular buildings. It is worth highlighting that Big Data and Analytics (BDAs), also empowered by Artificial Intelligence (AI), were useful to Additive Manufacturing (AM) for the manufacturing of buildings and components.

On the other hand, the value transfer dimension was especially enabled by Simulation Systems (SSs), which have required to build several layers of related digital technologies, namely Cyber-Physical Systems (CPSs), Internet of Things (IoTs), and Big Data and Analytics (BDAs), for exploiting the most of their effectiveness. In addition, although it is true that SSs require a direct involvement of customers, the company is still in the transition phase and we do not have yet available information and tools for deepening the business model dimension of value capture.

5 Conclusions

The chapter was aimed to depict how digital technologies can be adopted by companies to support the transition of their business model toward Circular Economy. The main outcome of the study is twofold. On the one hand, the chapter takes stock of the main research in the intersection between Circular Economy and digital technologies, by highlighting a set of relevant digital technologies, as well as their main functionalities, which allows to improve the circularity of business models. The chapter, moreover, sheds light on the different contributions of digital technologies to the value creation, transfer, and capture, in the building industry, pointing out that the transition toward Circular Economy requires a long journey and therefore is still far from being achieved. On the other hand, the findings of the empirical analysis allow managers and practitioners to reflect on the potentialities offered by the digital technologies to improve the effectiveness of circular initiatives in companies’ business model operating in the building industry.

The transition toward Circular Economy is nowadays increasingly important, and although an increasing number of studies dedicated to this topic has proliferated, only a few, more recent, contributions have tried to deepen the relationship between digital technologies and Circular Economy. In other words, research still needs more theoretical and practical effort into the analysis of how companies design a circular business model while adopting digital technologies.

The present chapter offers an important contribution to the current scientific debate that crosses the themes of Circular Economy and digital technologies from a strategic perspective, posing the attention to how digital technologies can be adopted by companies to support the shift from a linear to a circular business model, especially in the building industry. Practitioners and managers with roles of responsibility in strategic and innovation departments of companies can benefit from our research, as it shows how digital technologies can increase the degree of circularity of companies’ business model operating in the building industry, being more sustainable while profitable.

However, although we have leveraged a case study analysis of exemplary projects in which a leader company operating in the building industry is involved, our analysis has several limitations that claim for further studies. For example, studies are needed to deepen the analysis of the role of digital technologies in a circular business model, even beyond the boundaries of a single firm. Indeed, digital technologies can support the interactions of the several actors operating in the supply chain and enable a more effective exchange of information across the supply chain itself. This is of particular interest in the building industry as well. Therefore, the role that digital technologies can play within the circular supply chain management can be a particularly interesting point of study. Moreover, our results and conclusions are so far hard to statistically generalize or transfer across different companies and industries. Furthermore, a higher number of companies operating in the same sector of activity or in different industries could be involved, and more projects could be investigated, in order to enrich our findings and extend the knowledge into the building industry and other contexts, thus claiming for more studies to come in the field of Circular Economy.