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This paper presents the results of our research into cooperation in Government Extended Enterprises, a type of system of systems. The effort proposed and evaluated a novel theory that these decisions are the result of the interaction of four canonical forces—Sympathy, Trust, Fear, and Greed. A computational simulation involving the Stag Hunt game examined information sharing decisions in a series of key decision points in three large case studies. For the five hypotheses tested, exploratory data analysis and nonparametric statistical testing show strong support for three of the hypotheses (cooperation is positively correlated with actors’ levels of Sympathy and Trust and negatively correlated with actors’ levels of Fear) and moderate support for the fourth (cooperation is negatively correlated with actors’ levels of Greed). Indications are that the fifth hypothesis (cooperation is correlated with history of behavior) is not needed to explain observed behavior. Multiple correspondence analysis showed significant interactions both among pairs of forces and when a force is paired with decision making strategies. These results can form the basis for: 1) analysis of additional case studies; 2) development of an agent-based simulation; and 3) creation of training programs for current and future organizational leaders. [ABSTRACT FROM AUTHOR]

In order to understand how we may engineer system of systems (SoS), we will have to rely significantly on our abilities in modeling and simulation. While there are some models of non-specific SoS, few attempts have been made to demonstrate these models with simulation. Simulations of SoS are usually specific cases. Likewise, in the description of a SoS, most of the approaches have focused on their characterization, yet this characterization has not been greatly utilized as an underlying feature in the modeling and simulation of SoS. We review different modeling techniques and use two converse techniques, i.e. agent-based and event-based modeling, to run a simulation of hypothetical systems collaborating into a SoS. The results of the empirical comparison indicate an agent-based modeling approach would achieve a characterization model better with validation achieved through an event-based approach. [ABSTRACT FROM AUTHOR]

ABSTRACT The Schelling segregation model is a well-established representation of social issues in a neighbourhood. On the basis of the systems approach, a model of system of systems (SoS) that is validated through comparison with the Schelling model and applies to more neighbourhoods is proposed. The systems model of an SoS empirically demonstrates the potential for conflict to arise as the autonomy of systems within a geographically distributed SoS increases. The results may contribute to future international policy as well as ecological management. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The designation System of Systems (SoS) applies to many types of system structures. We consider a collaborative SoS, which forms through the apparent voluntary decisions of its component systems. However, many collaborative SoS do not possess the intellectual capacity to make human-like decisions. To understand the formation of SoS better, properties are modeled mathematically. An agent-based model (ABM) simulation validates the model via a mock chemical reaction of atoms forming molecules. In the engineering and management of these systems, this information allows better decisions that support or deny SoS formation. [ABSTRACT FROM PUBLISHER]

This paper will propose to do as von Bertalanffy once did, and that is to draw on the biological sciences, now hugely advanced beyond that ever imagined by von Bertalanffy and his peers, and use its findings, architectures, and emergent behaviors to argue for a biology of system of systems (SoS). We seek a science and approach that we believe will provide richer insight into SoS failure, "health"maintenance, repair, replication, growth, and mutation--all those features of the evolution of systems which constantly challenge us and which, thus far, we have only been able to explain via macrolevel models and tools. We propose to go deeper into the structure of these systems and to discover their "DNA" (building blocks), thus establishing a foundation to understand their behavior using biological analogies, which we believe will turn out to be more than metaphors. We assert that these systems have microstructures which will explain their individual life cycle and their communal ecology. [ABSTRACT FROM AUTHOR]

Knowledge for managing projects, for the development of systems, has not kept pace with the increasing complexity and integration of the projects themselves. This increased complexity has permitted some to reason distinctions between systems projects and propose a form of system called a "system of system" (SoS). Faced with this situation, we argue that a single point solution cannot be the answer to how to manage these systems. We suggest the remedy is a form of project management predicated on four principles that underline SoS thinking: problem demystification, legacy assessment, state-space solutioning, and integration framework. Using these principles as a foundation, we provide a set of characteristics (i.e. autonomy, belonging, connectivity, diversity, and emergence) that can be applied as fundamental building blocks to actualize the management of an SoS, or any system. More importantly, we present an architecture predicated on the paradoxes that exist in realizing and formalizing these characteristics. [ABSTRACT FROM AUTHOR]

In order to remain competitive, organizations have to make themselves accessible to a diversity of alternatives, which could be a direct influence on their flexibility; however, flexibility introduces a new context by which these organizations manage the systems they realize. In this paper, we present a theoretical perspective on the management of flexibility of a type of system called a System of Systems (SOS). We first define flexibility as it has been described with respect to the management of a system, how this may relate to SoS and establish that there is a deficiency for understanding how the SoS should be managed near the optimization region of flexibility. We then propose a theoretical model for managing flexibility in a SoS that begins to address this optimization region of flexibility. We demonstrate our model with an empirical case study of the New York City Yellow Cab SoS and conclude with potential implications this research has on flexible systems management. [ABSTRACT FROM AUTHOR]