What term refers to processes or activities that are completed by suppliers?

10.4 Supply chain management

Supply chain management (SCM) is the management of the flow of goods and services. Supply chain (SC) includes the movement and storage of raw materials, work-in-process inventory, and the transportation of goods from point of origin to point of consumption. Optimization of supply chain may result in significant energy saving and related carbon emissions reduction.

Businesses—from manufactures, wholesalers, and retailers to warehouses, healthcare providers and government agencies—use supply chain management principles to plan, assemble, store, ship, and track products from the beginning to the end of the supply chain. The detail is as follows: In the procurement area, SCM focuses on supplier selection, sourcing cost improvement, and sourcing risk management. In the manufacturing area, SCM focuses on production planning and control, production R&D, maintenance and diagnosis, and quality management. In the logistics and transportation area, SCM focuses on logistics planning, in-transit inventory, and management. In the warehousing area, SCM focuses on storage assignment, order picking, and inventory control. In the demand management area, SCM focuses on sensing current demand, shaping future demand, and demand forecasting.

With the use of advanced analytics techniques to extract valuable knowledge from big data facilitating date-driven decision-making, SCM is extensively applying a large variety of technologies, such as sensors, barcodes, and internet of things to integrate and coordinate every linkage of the chain. Main big data techniques used in SCM include support vector machine in classification models; heuristic approaches along with spatial/temporal-based visual analysis, which are the key approaches in the development of optimization models, and K-means clustering algorithm applied in clustering, classification, forecasting, and simulation models. Empirical evidence demonstrates obvious advantages of big data analytics in SCM in reducing operational costs, improving supply chain agility, and increasing customer satisfaction.

The graphical classification framework of SCM consists of four layers [38] as follows:

The first layer refers to five SC functions, including procurement, manufacturing, logistics/transportation, warehousing, and demand management.

The second layer gives three levels of data analytics, namely descriptive analytics, predictive analytics, and prescriptive analytics, where the descriptive analytics describes what happened in the past; the predictive analytics predicts future events, and the prescriptive analytics refers to decision-making mechanism and tools. For descriptive analytics, association is the most widespread as it has been applied throughout every stage of the SC process from procurement, manufacturing, warehousing, and logistics/transportation to demand management. Visualization is the least used model in descriptive analytics. For predictive analytics, classification is the most used model, which can classify a huge set of data objects into predefined categories, thereby generating predictions with high levels of accuracy. Other popular models for predictive analytics are semantic model and forecasting model. For prescriptive analytics, the popular models are optimization model and simulation model, which are adopted to support decision-making.

The third layer consists of nine big data analytic models: association, clustering, classification, semantic analysis, regression, forecasting, optimization, simulation, and visualization. The final layer gives some techniques on big data mining, machine learning, et cetera.

5.3 Strong focus on the economic dimension

CLSC management is about maximizing multiple value creation over the entire life cycle of a good. Hence, explicitly setting societal and/or ecological goals in addition to economic goals is inevitable. It seems incredibly positive that the respondents claim to take the ecological and societal value just as much into account as the economic value. However, answers to various open questions seem to provide a contradictory picture. For instance, a public client states that the “uncertainties are mainly related to the financial costs and the quantities of reusable material.” Various architects, construction firms, and manufacturers also argue that “often the costs are a primary point of discussion.” Hence, for CLSC management, more consideration must be given by the supply chain actors to the ecological and societal dimensions.

2 Sustainable supply chain management

Supply chain management (SCM) is broadly defined as “the systemic, strategic coordination of the traditional business functions and the tactics across these business functions within a particular company and across businesses within the supply chain, for the purpose of improving the long-term performance of the individual companies and the supply chain as a whole” (Mentzer et al., 2001, p. 18). The incorporation of environmental concerns into SCM literature gave rise to the term “Green supply chain management” (GSCM). GSCM refers to the integration of environmental issues in all functions of the SC. In this regard, Srivastava (2007, pp. 54–55) defined GSCM as “integrating environmental thinking into supply-chain management, including product design, material sourcing and selection, manufacturing processes, delivery of the final product to the consumers as well as end-of-life management of the product after its useful life.” However, the concept of GSCM limits sustainability to environmental practices (Yawar and Seuring, 2017), and researchers have also identified the relevance of social problems (Ashby et al., 2012; Martins and Pato, 2019) due to the growth of global trade activities.

The Brundtland definition of sustainability includes the social, environmental, and economic pillars (WCED, 1987). In the same line, the term “Triple Bottom Line” coined by Elkington (1998) also takes into consideration economic, environmental, and social criteria. John Elkington argued that organizations should take into account the traditional financial profit and loss bottom line as well as the social and the environmental dimensions. Moreover, Carter and Rogers (2008) argued that environmental, social, and economic goals are interdependent, and organizations should strive to combine them.

The concept of SSCM emerged with the objective of taking goals from all three dimensions of sustainability. Ahi and Searcy (2013) asserted that SSCM extends the concept of GSCM by integrating the social and economic dimensions along with the environmental dimension. Although more than 16 definitions of SSCM exist, definitional consensus has yet to be achieved (Dubey et al., 2017). Most authors define SSCM as the integration of the three pillars of sustainability into SCM (e.g., Pagell and Shevchenko, 2014; Seuring and Müller, 2008; Wittstruck and Teuteberg, 2012). In this respect, SSCM is conceived as “the creation of coordinated supply chains through the voluntary integration of economic, environmental, and social considerations with key inter-organizational business systems designed to efficiently and effectively manage the material, information, and capital flows associated with the procurement, production, and distribution of products or services in order to meet stakeholder requirements and improve the profitability, competitiveness, and resilience of the organization over the short and long-term” (Ahi and Searcy, 2013, p. 339).

SSCM integrates environmental and social issues in the product design, materials sourcing and selection, purchasing, manufacturing processes, packaging, warehousing, transport and disposal phases of products and services (Haake and Seuring, 2009).

Some scholars contend that sustainability must be implemented simultaneously from the top-down and bottom-up approaches (Meadows et al., 2004). In this regard, the integration of sustainability in SCs could take place simultaneously at different strategic levels (1) in governance mechanisms and top management; (2) in operations; (3) in products/services; and (4) through SC partners (Fritz, 2019).

First, sustainability could be acknowledged as a fundamental value by top management (Labella-Fernández and Martínez-del-Río, 2019). From a top-down perspective, organizations could introduce sustainability into their mission and vision statements with the objective of creating a truly sustainable chain (Pagell and Wu, 2009). However, achieving the sustainability of the SC requires much more effort by top management to increase the awareness of middle management and employees. This could be achieved through the formulation and implementation of corporate sustainability policies, goals, and practices. Top-level managers and entrepreneurs tend to be more proactive and innovative and take more risks in turbulent and uncertain environments (Rauch et al., 2009; Zhu et al., 2008). Thus, the leadership and commitment of top-level management with environmental and social issues are important aspects in the implementation of SSCM activities and programs (Lambert et al., 1998). In addition, according to Kaur and Sharma (2018), in order to maintain sustainability as a strategy within the organization not only is it necessary to establish complete organizational inclusion but is also important to ensure employee involvement in the decision-making process along the value chain.

Second, sustainably managing the SC also requires integrating sustainability at the operational level into the different departments or functions of the firm (e.g., marketing, R&D, accountancy, operations, human resource management). This step is of paramount importance in order to incorporate social, environmental, and economic criteria into the SC. In this regard, companies should devote all efforts to guaranteeing collaboration among all functional areas that take part in activities related to product design, sourcing, procurement and logistics, as well as use and postuse (Ahi and Searcy, 2013; Badurdeen et al., 2009). This collaboration could lead organizations to explore and implement environmental and social opportunities. For this purpose, it is essential to have a robust information management system to control all processes along the SC.

Third, at the product level, organizations should incorporate social and environmental criteria in the design of the product and service in order to reduce or even eliminate its negative environmental and social impacts. The integration of such criteria in the design of the product and service involves taking into consideration all stages of a product life cycle, from the extraction of raw materials to final product disposal. For this purpose, one of the most commonly used methods to evaluate the environmental and social impact of a product during its production, use, and end-of-life phase is the LCA, as will be seen below.

Finally, with the objective of achieving social and environmental sustainability along the SC, it is especially important to extend sustainability to other SC partners such as suppliers (Krause et al., 2009; Sancha et al., 2016). This is due to the fact that stakeholders, especially customers, are not in contact with all the different actors in the SC (Seuring and Gold, 2013) and, therefore, focal firms should be responsible for their suppliers (Hartmann and Moeller, 2014; Sancha et al., 2016). Extending sustainability to SC partners implies that suppliers can attain the same sustainability performance so that a firm’s sustainability performance cannot be damaged by its suppliers (Faruk et al., 2001). Successfully achieving this endeavor involves the integration of sustainable criteria (environmental, social, and economic considerations) into supplier selections, collaboration, and assessment. On the one hand, collaboration with suppliers entails the cooperation between a focal firm and a supplier and is intended to enhance performance in collaboration (Gavronski et al., 2011; Klassen and Vereecke, 2012). This collaboration entails sharing knowledge and information with suppliers, coordinating resources with suppliers such as design, sourcing, and production, and providing assistance, for example, dedicating firm workforce temporarily to the supplier (Lee and Klassen, 2008; Rao, 2002; Sancha et al., 2016; Vachon and Klassen, 2008). In this light, Green et al. (2012) found empirical evidence that environmental collaboration not only improves environmental performance of the focal firm but also its organizational performance.

On the other hand, supplier evaluation is also crucial to secure a valuable relationship between a focal firm and a supplier which improves the social and environmental performance of the focal firm and, ultimately, the sustainability performance of the supplier. Moreover, supplier evaluation allows focal firms to measure progress, assess sustainability performance, and identify what suppliers need to improve (Fritz, 2019; Hahn et al., 1990; Sancha et al., 2016). In this regard, companies conduct audits of their suppliers to ensure they meet social and environmental requirements (Sancha et al., 2016).

Managing sustainability implies the adoption of socially and environmentally responsible practices throughout the SC to achieve sustainability outcomes: social and environmental performance. Social performance considers compliance with human rights, employment of minority groups, improved health and safety, fair labor practices, and impact on local communities (Koberg and Longoni, 2019; Yawar and Seuring, 2017). Environmental performance considers the reduction of resource consumption, pollution, waste and emissions, and recycling (Koberg and Longoni, 2019; Rao and Holt, 2005).

2.1 Electricity Generation and Transmission Issues

The supply chain management of electron energy is very different from that of fuel energies (gas, liquid, or solid form). Fig. 3 presents a general schematic of the conventional electricity transmission and distribution network, which comprises a generator, transmission and distribution network (analogous to the pipeline for NG), and end user. On the one hand, electricity can be transmitted instantaneously from one location to another, where it would be very costly and time consuming for fuel energies. On the other hand, management of electron during oversupply periods is a challenge compared with that of fuels. This limitation immediately provoked the need for energy storage from the very early days of electricity market development.

Abstract

In supply chain management, network design and planning take an important place, and design decisions should be viable enough to create a supply chain that operates efficiently under today’s complex and uncertain business environments. In an uncertain decision environment, the decision-maker confronts the challenge of accurately predicting the impact of possible actions on supply chain behavior. Uncertainties complicate the assessment of investment decisions and affect the performance of production chains. To avoid such problems, a flexible supply chain network has to be established. It is necessary to handle and treat the inherent uncertainties to cope with imprecise nature of flexible supply chains. To identify the most effective strategies in a specific design or operational scenario, identification and management of the sources of uncertainties should be incorporated into the decision-making processes. Considering this fact, this chapter covers the main sources of uncertainty in biomass-based production chains and the methods and modeling techniques to incorporate these uncertainties in the decision-making process.

Organizational Perspective

Integrated supply chain management has developed in response to new modes of production, in the context of globalization, and with respect to a highly competitive market environment. The focus of supply chain management is shifting from maintaining inventories aimed at approximately satisfying a demand toward a comprehensive data collection system insuring that supply matches more closely with demand. This is mainly to be achieved through on-demand distribution. Thus, physical flows also involve a significant amount of information flows. This trend was accelerated by the use of logistics, namely a better integration between transport modes and inventory control.

One of the main rationales for eliminating inventories is the need for cost reduction at all levels of corporate activity. Also essential is achieving a high market presence in terms of timely delivery, particularly since inventories no longer buffer against supply problems, disruptions in the transport chain, etc. In order to fulfill these requirements, specialized coordinators and integrators (third- and fourth-party logistics providers) have emerged, focusing on improving parts of the supply chain or providing their coordination and control. While push logistics involves a limited level of integration between suppliers, manufacturers, and distributors, a pull logistics system tries to achieve a higher level of efficiency through integration. Freight flows between components of the supply chain tend to be more frequent and in smaller batches. In addition, the sharing of demand-dependant data helps better synchronize supply with demand. Reverse logistics also tends to be better integrated in the system to achieve a higher level of customer service, as well as to promote environmental strategies such as recycling.

The conventional forward channel in freight distribution is well understood with raw materials, parts and finished goods flowing from suppliers to producers, distributors and, finally, to consumers. There is also a reverse channel where waste, packages, and defective/obsolete products are ‘climbing back’ the supply chain (Figure 3). In some cases (such as a defective product), distributors will take back the merchandises, but in many others, a specialized segment of the distribution industry aims at collecting and then recycling goods and parts. Thus, reverse logistics (or reverse distribution) is concerned about the movements of previously shipped goods from customers back to manufacturers or distribution centers due to repairs, recycling, or returns.

Major changes in the manufacturing systems have led to the emergence of ‘platform corporations’ that bundle a core of research and development, finance, marketing, and distribution activities while removing (outsourcing) the manufacturing component, or having never had manufacturing in the first place. They have done so by focusing on the activities that provide the most added value and subcontracted the manufacturing of the products they design. Their core activities include research and development, finance, marketing, retail, and distribution. Many of them own globally recognized brand names and are actively involved in the development of new products. Their net worth is thus more a function of their brand names and capacity at innovation than from some tangible production assets. They outsource as much of the low-margin work as possible and are flexible in their choice of suppliers. Thus, the term platform is used to characterize a mobile core establishing temporary relationships with manufacturers.

Platform corporations particularly thrive in the context of free trade; the mobility of factors of production is facilitated so that products can be produced wherever costs are the lowest and exported back to major markets. Telecommunications have also allowed corporations to decentralize their process while maintaining a level of control over their supply chain and informing their suppliers about changes in the demand. Since platform corporations provide the specification of the products/parts they require, there are a potentially high number of manufacturers that can bid to become suppliers. This works to the advantage of platform corporations by keeping costs low and it even creates a situation of recurrent overcapacity. Dell, IKEA, and Wal-Mart are examples of such corporations that outsource the low-margin manufacturing activities to low-cost locations and establish effective networks of supply and production. Corporations are thus becoming ‘logistical entities’ since they manage a complex structure of production, distribution, and retailing.

3.21.3.1.2 The BIM + GIS enabled LSCM process in future site development

To improve existing LSCM in site development, one vision is to have bidirectional information flow in parallel with the physical logistics and supply chain. To realize the vision, BIM has increasingly become a centralized platform based on which the design is finalized and turned to production plans as shown in the logistic and supply chain. The Internet of Things (IoT) has been enthusiastically advocated to increase the responsiveness of the myriad of decision-making that is decentralized along the construction logistic and supply chain, which nowadays increasingly links onsite and offsite activities. LSCM is not only simply about the site, but also, or probably more importantly, about the prolonged offsite management. The spatiotemporal information included in a GIS becomes the key information to coordinate the onsite and offsite activities related to construction LSCM. The seamless coordination is further supported by the widespread portable devices, abundant apps, and ubiquitously accessible networking technologies. Auto-ID technologies (e.g., barcode, radio frequency identification technologies (RFID), Quick Response (QR) code) have been widely adopted to link the IoT, GIS, and BIM (Lu et al., 2011a; Flanagan et al., 2014). If a myriad of physical materials within the IoT will generate data (e.g., position, GIS information, volume, and other semantic data) and synchronize in the joint system formed by BIM and GIS, it will help achieve the big data, by harnessing which the construction LSCM can be improved.

Using Auto-ID technologies for big data collection along the construction logistic and supply chain has received its fair share of criticism. It only generates identification information while richer data is desired for making informed decisions in construction LSCM. In addition, users feel that to stop the ongoing process to scan the RFID tags or QR codes is ‘disruptive’. This disruption becomes overwhelming when the technologies are applied to the complicated LSCM processes. Notably, Niu et al. (2016) develop the concept of smart construction objects (SCOs), which are Construction resources (e.g., machinery, tools, device, materials, components, and even temporary or permanent structures) that are made smart by augmenting them with sensing, processing, and communication abilities so that they have autonomy and awareness, and can interact with the vicinity to enable better decision making. SCOs allow a new way of capturing, processing, and communicating information to support decision-making in LSCM for site development. SCOs are like basic particles flowing through the LSCM process; sensing, carrying, processing, and communicating information with different attributes to support decision-making.

The BIM + GIS-enabled LSCM process can be illustrated in Fig. 4. A smart management platform (SMP) is developed by infusing BIM and GIS and connected to the physical material flow using Auto-ID or SCOs. When the material flow remains relatively the traditional way, the information flow throughout the whole LSCM process is revolutionarily changed. The SMP serves as a shared platform for the supplier and the contractor, allowing these parties to exchange information in a real-time manner. Thus, there is a two-way information flow via the SMP as a hub. The procurement list, orders for production, and delivery can be issued online in the SMP and the supplier can be alerted to receive these documents and confirm receipts. Meanwhile, the off-site supplier can submit queries through the SMP to seek clarification from the contractor’s side. The system enables a bidirectional flow of information between physical material flow, the SMP, and the decision-makers.

A real-life BIM + GIS enabled LSCM system has been developed as shown in Fig. 5. In this system, the BIM model is the centralized data hub for containing the design information, material ordering information, assembly information and many others. It is linked to the physical materials, which are augmented with smartness. When the physical materials are transported from the factory to the site, the embedded technologies will transmit the real-time information such as locations, time, speed, temperature, etc. and be displayed immediately on the GIS. Real-time information visibility and traceability (Lu et al., 2011a) are realized. The collected data relating to all the materials can be used for big data analytics such as productivity analyses, behvaior mapping, and business process reengineering.

1.3 Supply Chain Management

The key elements of supply chain management are purchasing, operations, distribution, and integration (Wisner et al., 2005). The supply chain of coking coal primarily consists of exploration, extraction, processing, carbonization, and steel making, while storage and transportation form the connecting links. In recent years, supply chain management has grown in popularity and usage. The Internet forms tighter links between key business processes, from initial extraction of raw coal to end customers to different stages of process techniques. Successful units are those with a good supplier–customer relationship. Each unit should make good use of recycling and reuse wherever possible. Transportation and logistics play an important role within the supply chain by reducing the overall costs of the whole operation. Enterprise resource planning (ERP) has enhanced the integration process and helped to make organizations globally competitive. At the same time, communications technology has advanced significantly as a result of computer networking. The important technical parameters in the business of coking coal are presented in Figure 1.3. Each process identified should be able to work under optimum conditions, commonly by vertically integrating processing with mining – something called “forward integration.” In contrast to vertical integration, outsourcing may provide many advantages for mining enterprises like CIL. Outsourcing of coal preparation plants can provide better quality and cost savings. Acquiring a mining lease outside the country is called offshoring, and this adds a new dimension to the supply chain strategy of globalization. Offshoring is the practice of locating mining interests in other countries; a practice that is closer to vertical integration than outsourcing. Offshoring firms are motivated to secure the supply of coal; however, this carries opportunities, challenges, and threats (Ritzman et al., 2007). There is a new focus on global mining management. In some cases, steel makers own all the units of the coking coal chain.

Transparency Demands

As described in Section Global Supply Chain Management and Logistics, besides sensory, health and convenience (intrinsic) product attributes, consumers increasingly put demands on process (extrinsic) attributes. These extrinsic demands pose a number of information exchange challenges to actors in the food supply chain as people and organizations must be informed with integrity about these attributes.

For the government the main incentives to support food supply chain transparency include protection of public health through timely withdrawal of unsafe products, to prevent fraud regarding food product authenticity, and to control livestock diseases (such as classical swine fever).

The industry motivation regarding transparency is four-fold: first, companies need to comply with differentiating demands from consumers as well as legislative demands as described in the previous section. Second, when incidents occur companies are required and want to be able to quickly recall products from markets or links downstream the supply chain to limit the impact of the incident and minimize costs. Third, by improving information exchange through integrated information systems, optimization of business processes will be much easier as product and process attributes can be coupled with process performance. Fourth, an important way for food companies to add value is by paying attention to and labeling products according to distinguishing intrinsic and extrinsic food product attributes, such as those listed in the previous section. In the last decade, many companies in the food sector have been stimulated to implement corporate social responsibility strategies in which special attention is paid to ethical aspects of production and procurement. For example, supermarkets increasingly sell ethical responsible products, such as chocolate, with cacao produced according to fair-trade principles (Box 6).

Box 6

StarBucks' Coffee and Farmer Equity practices

The Starbucks' Coffee and Farmer Equity (CAFÉ) Practices Program includes a broad set of social, economic, environmental, and quality guidelines developed by Starbucks in collaboration with Conservation International. The program started in 2001, as a response to pressure placed on Starbucks during the late 1990s by NGOs. The CAFÉ practices standard promotes coffee production practices that protect biodiversity, maintain healthy ecosystems, and support economic and social development in coffee production. To support the quality guidelines, Starbucks offers technical support via farmer support centers. Compliance with the standard is verified by a range of third-party verification organizations.

By implementing transparent and integrated information systems supporting transparency aims, organizations can improve their image as they can propagate that products satisfy specific quality (intrinsic and extrinsic) demands. As referred to earlier, other motivations are logistical optimization, quality assurance, and process optimization.

2.2 Toward a systemic perspective on value creation in the circular economy

A recent strand of literature on supply chain management has pointed out that research on circular economy stands to gain from adopting more comprehensive conceptual frameworks. According to Tate et al. (2019), system analysis could be useful in this regard. They invite researchers to shift from “linear supply chain thinking” to “interconnected, circular, ecosystem thinking.” They argue that this new focus could contribute to addressing global ecological and social challenges. Unfortunately, current research at the intersection of circular economy and supply chain management still lacks a systemic perspective. Bals et al. (2020) argue that literature in this area “frames the world in dyads instead of ‘networks’ or ‘systems’. In order to move beyond short-sighted recycling solutions that still result in waste, a systemic perspective is needed that embraces cross-industry flows and more actors (e.g., taking care of the reverse logistics) than in traditional supply chains, establishing circular value cycles.”

Different avenues for developing such a systemic perspective on value creation are possible. Tate et al. (2019) have opted for exploring direct analogies with natural ecosystems and formulating “biomimetic insights” that could be helpful for transitioning toward more circular business practices. Looking at natural ecosystems for inspiration is indeed a popular way of conceptualizing circular economy (Athanassiadis and Kampelmann, 2021).

Moving from simple models of value chains to the analysis of value systems implies being able to get a grip on complexity in the form of a larger number of interrelated variables. Several academic traditions have successfully explored and analyzed complex systems. While theological worldviews have long crowded out scientific forms of system analysis, the study of systems has reappeared in Western philosophy in the wake of Enlightenment. The foundations of ecology as a scientific discipline were laid in the 1930s; ecology pioneers such as Eugene P. and Howard T. Odum built on them to develop the ecosystem concept and apply it to forest and ocean systems in the 1960s (Odum and Bartlett, 1971). In the 1970s, system analysis started to develop formalized tools for describing complex biotopes, notably the notion of interconnected biogeochemical cycles within ecosystems (Duvigneaud, 1974). Almost simultaneously, a group of MIT scientists applied system analysis to the evolution of a matrix of biophysical and economic variables to estimate the “limits to growth” beyond which global production systems would become unstable. Historically and intellectually rooted in engineering science, today system analysis is a full-fledged academic discipline. In parallel, other disciplines have developed specific theories on monetary, solar, scholar, or legal systems.

As stated by Kampelmann (2017), one of the most relevant theories for applying system thinking to circular economy research can be extracted from the interdisciplinary literature concerned with the analysis of social-ecological systems and their metabolism (Fischer-Kowalski and Haberl, 2007). While most authors study social-ecological systems at the macroscopic scale, a rapidly expanding literature looks at territorial metabolism, and more specifically at the metabolism of urban agglomerations (Duvigneaud and Denayer-De Smet, 1975; Barles, 2010; Kampelmann and De Muynck, 2019). These advances could build on earlier research including the so-called Brussels School under the influence of Paul Duvigneaud, who initiated a first wave of progress in the understanding of social-ecological systems in the 1970s. Indeed, the book L’écosystème Belgique [Ecosystem Belgium] by Billen et al. (1983) is an early attempt at applying methods of scientific ecology to the analysis of the industrial system of Belgium. Its subtitle “A study in industrial ecology” is a hint that the book already anticipated the distinction between linear and circular economic systems.

In terms of methods, the system analysis of Duvigneaud and colleagues was mostly based on elaborate flow diagrams informed by biogeochemical data and analyses. This echoed the kind of representations used in scientific ecology to describe phenomena like the nitrogen or the carbon cycle. Unsurprisingly, the complexity of a social-ecological object such as the Belgian industrial system was framed by Billen and his coauthors in analogy to Duvigneaud's seminal representation of a forest, in which the interconnections of numerous cycles give rise to an overarching ecosystem. By contrast, frameworks developed by social scientists such as Elinor Ostrom and others put the emphasis on the roles of agency, as well as on the rules and institutions that govern social-ecological systems (Ostrom, 2009a). Tate et al. (2019) draw on network theory and complex adaptive systems (CAS) to formulate biomimetic insights on networked business systems. Such a strategy has helped to stress the need for interorganizational balance in value systems, for instance in the form of a balance between producers, consumers, scavengers, and decomposers (Babbitt et al., 2018).

We argue that the analysis of circular value systems implies accounting for both types of variables: on one hand, material flows that have formed the backbone of the analysis of economic systems in the tradition of industrial ecology based on Duvigneaud and, on the other hand, agencies and institutions that have received more attention by social scientists like Ostrom. To achieve such a combination, Kampelmann (2017) has proposed a framework for analyzing systemic relationships in the context of circular economy and applied it to the case of organic waste management. In the next section, we summarize the structure of this framework and submit our case that it can be a valuable tool for organizing and analyzing case study material on emerging circular value systems.