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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]

At the 2006 IEEE International Conference on Systems of Systems Engineering, Boardman and Sauser presented a set of characteristics based on an integrative review of the literature. These characteristics are the foundation of the Boardman–Sauser system of systems (SoS) theory. We accept this theory as the basis of collaborative SoS and desire a means to validate this assertion. While numerous simulations have been published, the target SoS is usually a specific implementation. These specialized simulations produce results applicable primarily to the system under study but not necessarily SoS in general. Simulating the mathematical model of the Boardman–Sauser SoS theory in the form of an agent-based model produces results that can be compared with chemical reactions. This paper contends that the formation of molecules from atoms is an analog of systems forming any collaborative SoS, which we call our molecule organization model. The result is a supported logical argument that validates the Boardman–Sauser SoS theory as definitive of a generic SoS with behavior applicable to collaborative SoS. This paper seeks to provide a unique contribution to the SoS body of knowledge by increasing our understanding of collaboration in an SoS, so we may better understand their health, maintenance, replication, and evolution. [ABSTRACT FROM PUBLISHER]

This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles. [ABSTRACT FROM PUBLISHER]

A fundamental challenge for system engineers is to capture a problem with an effective model or framework and then facilitate transferring the information of that captured problem to practical systems engineering tools and methods. The early problem definition phase requires an application of systems thinking with adequate modeling tools and methods. Then, the later problem definition phase and early system architecting phase requires transferring the captured problem to systems engineering tools and methods through emerging techniques such as model-based systems engineering (MBSE) using SysML (MBSE is the practice of using a modeling tools to capture systems engineering diagrams). This paper presents a method for capturing a problem through systemigrams and the Boardman soft systems methodology and then directly translating the systemigrams into SysML diagrams. With MBSE increasing in usage, this method could provide a time savings opportunity during model development along with the possibility of lowering information distortion or loss that can occur during transformation of systems thinking to systems engineering activities. This paper includes a case study which demonstrates how the proposed approach was applied on a problem being considered by the U.S. Army—Contingency Basing for Small Combat Units. Finally, this paper will provide the conclusion on the development of the method and describe future research directions that can allow systems thinking and MBSE to function in a congruent methodology. [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]

As part of this, we identified some of the possible constituents of the systemic risk of SoS. It is valuable to note that the constituents could vary from case-to-case and are also time-dependent due to the dynamic nature of SoS and the environment in which it operates. Furthermore, the authors pointed out the importance of the application of systemic risk in the SoS domain and thus understanding the interconnectedness between the various constituents. [ABSTRACT FROM PUBLISHER]

Recently, a system maturity scale, i.e., system readiness level (SRL), was proposed to measure the maturity that a system achieves during development. However, this SRL assesses maturity for systems from only a single function and capability perspective, and is unable to assess maturity for multifunction multicapability (MFMC) systems. With ever increasing systems that provide multiple functions and capabilities, it is challenging for managers to properly allocate resources to ensure the achievement of critical capabilities and functions. In order to prioritize the allocation of resources for component development, it is common to perform importance analysis during system development and maintenance. Therefore, this paper first enhances the original SRL definition for maturity assessment at the capability, function, and system levels, and then, proposes the use of component importance analysis for the identification of the most important components for system development. This paper approaches component importance by introducing three important measures with respects to three main factors: technology readiness level/integration readiness level, developing cost, and developing effort. The paper uses an illustrative example of a MFMC system to show the proposed methodology and enhanced definitions and concludes with a discussion of the added value and future work. [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]