Taking into account the continuous generative nature of socio-technical systems, actor intentions and behavior, and, thus, relations may constantly change. We need to delineate their nature, as being transactional, organic, or semi-organic, since they lead to deep changes in the way we act and “produce” and finally affect behavior in and of organizations and societies (Bonfour, 2016). As already discussed in Part I, taking a CAS perspective enables delineation while preserving system thinking in terms of networked but modular elements acting in parallel. In socio-technical settings, these elements can be individuals, technical systems, or their features. As CAS elements, they form and use internal models to anticipate the future, basing current actions on expected outcomes. According to CAS theory, in CAS settings, each element sends and receives signals in parallel, as the setting is constituted by each element’s interactions with other elements. Actions are triggered upon other elements’ signals. In this way, each element also adapts and, thus, evolves through changes over time.

Self-regulation and self-management have become crucial assets in dynamically changing settings. Self-organization of concerned system elements is considered key in handling requirements for adaptation. However, for self-organization to happen, actors need to have access to relevant information of a situation. Since the behavior of autonomous actors cannot be predicted, some structure is required to guide behavior management according to the understanding of actors and their capabilities to change their situation individually.

From the interaction of the individual system elements arises some kind of global property or pattern, something that could not have been predicted from understanding each particular element. A typical emergent phenomenon is a momentum stemming from an emergency handling actor when deciding upon a certain behavior, such as contacting other actors for specific requests. Global properties result from the aggregate behavior of individual elements.

Applying System-of-Systems (SoS) thinking is considered an effective way of handling CAS, in particular when developing complex artifacts in a structured way (Jamshidi, 2011). According to the Institute of Electrical and Electronics Engineers (IEEE’s) Reliability Society, a system is “a group of interacting elements (or subsystems) having an internal structure which links them into a unified whole. The boundary of a system is to be defined, as well as the nature of the internal structure linking its elements (physical, logical, etc.). Its essential properties are autonomy, coherence, permanence, and organization” (IEEE-Reliability Society Technical Committee on Systems of Systems, 2014).

A System-of-Systems (SoS) is a system that involves several systems “that are operated independently but have to share the same space and somehow cooperate” (ibid., p.2). As such, they have several properties in common: operational and managerial independence, geographical distribution, emergent behavior, evolutionary development, and heterogeneity of constituent systems (ibid.). These properties affect setting the boundaries of SoS and the internal behavior of SoS and, thus, influence methodological SoS developments (Jaradat et al., 2014). SoS are distinct with respect to:

  • Autonomy where constituent systems within SoS can operate and function independently and the capabilities of the SoS depend on this autonomy

  • Belonging (integration), which implies that the constituent systems and their parts have the option to integrate to enable SoS capabilities

  • Connectivity between components and their environment

  • Diversity (different perspectives and functions)

  • Emergence (foreseen or unexpected) (ibid.)

Several structures and categorization schemes have been used when considering complex systems as System-of-Systems, ranging from close coupling (systems within systems) to loose coupling (assemblage of system). They constitute embodied systems cooperating in an interoperable way (Weichhart et al., 2018), allowing for the autonomous behavior of each system while contributing through collaboration with other systems, in order to achieve the objective of the networked systems (SoS) (Maier, 2014).

Referring to structural and dynamic complexity, structural complexity derives from (1) heterogeneity of components across different technological domains due to increased integration among systems and (2) scale and dimensionality of connectivity through a large number of components (nodes) highly interconnected by dependences and interdependences. Dynamic complexity manifests through the emergence of (unexpected) system behavior in response to changes in the environmental and operational conditions of its components (IEEE-Reliability Society Technical Committee on Systems of Systems, 2014).

A typical technical SoS example is contextualized apps available on a smartphone. Each of them can be considered as a system. When adjusting them along a workflow, for example, to raise alert and guide a patient to the doctor, in case certain thresholds with respect to medical conditions are reached for a specific user, several of these systems, such as the blood pressure app, calendar app, and navigation app, need to be coordinated and aligned for personal healthcare, updating the task manager of the involved users. In this case, the smartphone serves as SoS carrier, supporting the patient-oriented redesign of the workflow and, thus, the SoS structure. The apps of the smartphone can still be used stand-alone, while the smartphone serves as a communication infrastructure and provider of networked healthcare-relevant subsystems. It is the latter property that qualifies the smartphone as a carrier of an SoS.

When we project this concept on understanding complex ecosystem, system elements can become aware of their capability to act autonomously while at the same time being part of a bigger whole, namely, the business organization (or even of several organizations). Awareness of active elements being part of a complex system as a System-of-Systems is considered according to their specific roles in a certain situation. Actors need to become aware of which System-of-Systems they are part of (they can be part of various System-of-Systems). For instance, a digital self can be part of a System-of-Systems consisting of two systems, with one role part of system one and another role in another, larger system.