The systemic mind and a conceptual framework for the psychosocial environment of business enterprises: Practical implications for systemic leadership training

This chapter introduces a research-based conceptual framework for the study of the inner psychosocial reality of business enterprises. It is called the Inner Organizational Ecosystem Approach (IOEA). This model is systemic in nature, and it defines the basic features of small and medium-size enterprises, such as elements, structures, borders, social actors, organizational climate, processes and resources. Further, it also covers the dynamics of psychosocial reality, processes, emergent qualities and the higher-order subsystems of the overall organizational ecosystem, including the global business environment, which is understood as a macro-system where all the individual organizational ecosystems co-exist. In the applied part of the chapter, cognitive changes emerging within systemic leadership training are defined. Participation in systemic training causes changes in the cognitive processing of reality, more specifically improvements in layer-based framing, relativistic contextual orientation, temporality drift and meaning generation. All of these changes are components of the systemic mind, which is a concept newly proposed and defined by the present study. The systemic mind is a living matrix that is extremely open to acquiring new skills and new patterns of thinking, analyzing and meaning generation. It is processual and it can be considered as an ongoing process of continuous absorption of new cognitive patterns. Both the Inner Organizational Ecosystem Approach and the concept of the systemic mind provide a new theoretical background for empirical investigation in the fields of systemic and systems psychology, complexity psychology, organizational psychology, economic anthropology and the social anthropology of work

A formal support to business and architectural design for service-oriented systems

Architectural Design Rewriting (ADR) is an approach for the design of software architectures developed within Sensoria by reconciling graph transformation and process calculi techniques. The key feature that makes ADR a suitable and expressive framework is the algebraic handling of structured graphs, which improves the support for specification, analysis and verification of service-oriented architectures and applications. We show how ADR is used as a formal ground for high-level modelling languages and approaches developed within Sensoria

Gradient and Passive Circuit Structure in a Class of Non-linear Dynamics on a Graph

We consider a class of non-linear dynamics on a graph that contains and generalizes various models from network systems and control and study convergence to uniform agreement states using gradient methods. In particular, under the assumption of detailed balance, we provide a method to formulate the governing ODE system in gradient descent form of sum-separable energy functions, which thus represent a class of Lyapunov functions; this class coincides with Csisz\'{a}r's information divergences. Our approach bases on a transformation of the original problem to a mass-preserving transport problem and it reflects a little-noticed general structure result for passive network synthesis obtained by B.D.O. Anderson and P.J. Moylan in 1975. The proposed gradient formulation extends known gradient results in dynamical systems obtained recently by M. Erbar and J. Maas in the context of porous medium equations. Furthermore, we exhibit a novel relationship between inhomogeneous Markov chains and passive non-linear circuits through gradient systems, and show that passivity of resistor elements is equivalent to strict convexity of sum-separable stored energy. Eventually, we discuss our results at the intersection of Markov chains and network systems under sinusoidal coupling