Understanding supply networks from complex adaptive systems.
| Autor | Marchi, Jamur Johnas |
Introduction
In recent decades, businesses searching for competitive advantages became fragmented through reengineering (Davenport, 1994) and outsourcing (Porter, 1989). On the other hand, companies stopped working in isolation, resulting in distinct organizational configurations, such as alliances, groups, networks and other forms of organization becoming significant strategic alternatives (Gulati, Nohria, & Zaheer, 2000; Lorange & Roos, 1996).
The supply network (Lamming, Johnsen, Zheng, & Harland, 2000) is one such configuration, and is primarily studied regarding aspects related to the integration and management of all the companies involved (Power, 2005). Research shows the difficulties in overcoming static and deterministic approaches supply network levels (Harland, 1996; Mills, Schmitz, & Frizelle, 2004). The need for studying dynamic aspects of business networks continues (Dagnino, Levanti, Mocciaro, & Destri, 2008). Other studies indicate that traditional approaches to managing supply chains are difficult to adapt to uncertain and turbulent environments, and suggest that the complex systems approach contributes to new understandings for management of supply networks (Christopher & Holweg, 2011; Dong, 2014).
An analytical framework based in a holistic and complex perspective may contribute towards this purpose (Dagnino et al., 2008; Power, 2005). Complex Adaptive Systems (CAS) is an approach that gathers aspects to understand the dichotomy between control and emergency in a supply network (Choi, Dooley, & Rungtusanathamal, 2001). Therefore, this theoretical essay aims to discuss supply networks as complex adaptive systems. In order to achieve this goal, the methodological design consisted of a deep reflection on these two approaches. This design is suitable when the aim of the research is to deepen or broaden the discussion (Meneghetti, 2011) about a particular topic. In this way, the concepts between the two approaches are approximated.
Supply Networks
In the beginning, in operation management fields, logistics was the discipline that had the responsibility of offering solutions for companies' integration (Christopher, 2009). However, researchers and practitioners perceived that the new established dynamic required other solutions beyond the ones that had already been offered by the logistic. Therefore, logistics would focus on supply flow (Cooper, Lambert, & Pagh, 1997; Lambert, Cooper, & Pagh, 1998), but require the addition of supply chain management.
Supply chain management can be defined as the "management of upstream and downstream relationships with suppliers and customers to deliver more value to the customer, at a lower cost to the supply chain as a whole" (Christopher, 2009, p. 4). Supplies, information, finances and knowledge are involved in such relationships. The term supply network refers to a set of supply chains (Harland, 1996; Lamming et al., 2000). In this article, we use the term network in order to understand that a company works with a network of suppliers and suppliers' suppliers, forming a system of connected autonomous organizations.
Different levels of supply networks analysis
The dynamic aspects of supply networks are linked to more strategic levels of analysis (Harland, 1996; Mills et al., 2004). Harland (1996) proposed four levels of analysis to study supply chains. The first level refers to the supply and information flow in a company, that is, the internal focus. The second level involves relationships with immediate suppliers, which is called the dyad-level. The third level of analysis involves suppliers' suppliers, as well as customers and customers' customers, comprising chain links. Finally, the fourth level is concerned with the network management of interconnected companies and involves providing products and services demanded by final customers.
From a company's point of view, four perspectives are recommended for supply chain management (Mills et al., 2004). The first perspective is the upstream: as a purchaser dealing with suppliers. The second one is the downstream: as a supplier dealing with customers. The third perspective is the static network: as an auditor of positions within its supply network, with a static and comparative view. The fourth perspective is the dynamic network, in which a company is a strategist seeking opportunities to improve its position within the network or to create new networks, using a strategic, dynamic and long-term view.
Harland's network perspective has advantages as it allows the selection of partnerships in the network, and it establishes a competitive position in a network, allowing comparisons among competitors (Harland, 1996). Mills, Schmitz and Frizelle (2004) third perspective (the static perspective) corroborates this. Notably, this view is concerned with network structure; i.e., the bonds that tie companies to their competitive positions, either internal or external.
The network dynamic perspective is concerned with perceiving how a supply network develops, and which dynamic is involved in an evolutionary process (Mills et al., 2004). It also dedicates itself to comprehend how new supply networks can be shaped, and which choice mechanisms are relevant to this process. For instance, they show how supply networks are developed through decision making, such as deciding between making and buying.
Nevertheless, Mills et al. (2004) approach, even though concerned with the dynamic features of a supply network over time, fails to point out behaviors and effects produced by the choices between purchasing and producing. Mainly, how such behaviors and effects can modify a network structure for new adaptations or creations of new networks, when responding to new market situations. Mills et al. (2004) suggest that theory complexity helps to elucidate supply network behavior.
In this sense, our argument is close to the IMP Group study. They adopt an approach of relationship networks to study business relations. They developed the ARA model, which is based on actors, resources and activity on a network (Hakansson & Snehota, 1995). In the ARA model, network actors are perceived according to the activities they perform and resources they possess and consume. Actors are linked to each other through these resources and activities. The activities can be very different, for example, production, marketing or transportation. The resources could be technological, productive or even knowledge.
Despite being relatively old, the ARA model has, in itself, elements that are still quite current. For instance, according to Hakansson and Snehota (1995), in a supplier-company the relationships are recurring structural aspects, such as continuity, complexity, symmetry and informality, and also, procedural aspects, such as adaptations, cooperation and conflict, social interaction and routinization. However, ARA is a strongly situational model, which can only be useful for analysis of a supply network if it is presented in a static manner. For example, what activities are linked, what resources are being combined, used or developed in the network, and which links the actors have to facilitate or constrain partnerships.
The CAS view might contribute to and amplify the dynamic capability of the ARA model by including behaviors and effects into present-future relationships in supply networks, increasing the space for predictability and possibilities. In the CAS view, the supply network evolves and self-organizes when companies make choices related to survival over time (Pathak, Day, Nair, Sawaya, & Kristal, 2007). The CAS view can see an intertwined relationship between cooperation and competition, in which disputes, agreements and alliances change the process from static to dynamic, adaptive and co-evolutionary.
Complex Adaptive Systems
One of the complex theories is complex adaptive systems. Complex systems consist of systems with multiple interactions among their parts or agents (Holland, 1992). This abstraction allows visualizing that the human brain, an individual, a group, an organization, society, the global community and even the environment might be understood to be complex adaptive systems (Stacey, 1996).
A number of problems can be confronted through CAS, among them, encouraging economic innovation, anticipating changes in global trade, understanding markets and preserving ecosystems (Holland, 2006). For instance, McCarthy (2003) used CAS to elaborate a technology management model, and Rammel, Stagl and Wilfingal (2007) utilized the CAS to build an agenda for natural resource management. In organizational studies, some essential elements of CAS models that can help shape organizational systems are highlighted as agents with schemas, self-organizing networks supported by energy imports, co-evolution at the edge of chaos, systemic...
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