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Complex systems adapt to survive, but little comparative literature exists on various approaches. Adaptive complex systems are generic, this referring to propositions concerning their bounded instability, adaptability and viability. Two classes of adaptive complex system theories exist: hard and soft. Hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and softer theories, which we refer to as Viable Systems Theories (VSTs), that include Management Cybernetics at one extreme and Humanism at the other. This paper has a dual purpose distributed across two parts. In Part 1, the purpose of this paper is to identify the conditions for the complementarity of the two classes of theory. In Part 2, the purpose is to explore (in part using Agency Theory) the two classes of theory and their proposed complexity continuum.

A detailed analysis of the literature permits a distinction between hard and softer approaches towards modelling complex social systems. Hard theories are human-incommensurable, while soft ones are human-commensurable, therefore more closely related to the human condition. The characteristics that differentiate between hard and soft approaches are identified.

Hard theories are more restrictive than the softer theories. The latter can embrace degrees of “softness” and it is explained how hard and soft approaches can be mixed, sometimes creating Harmony.

There are very few explorations of the relationship between hard and soft approaches to complexity theory, and even fewer that draw in the notion of harmony.

This article explores how complexity theory can help marketers to understand a market and to operate within it. Essentially, it argues that complexity theory has the potential to provide both global and some local explanations of markets and is complementary to local theories like relationship marketing that may be more familiar to marketing managers. It establishes four types of complex systems that might be used to model social systems. Of these four types, complex adaptive systems seem most appropriate to describe markets. This is illustrated in an investigation of Honda in the global automobile industry. Implications for marketing managers centre on the need to understand feedback loops at many levels of a path‐dependent system that are inherently difficult to predict and control.

Complex systems adapt to survive, but little comparative literature exists on various approaches. Adaptive complex systems are generic, this referring to propositions concerning their bounded instability, adaptability and viability. Two classes of adaptive complex system theories exist: hard and soft. Hard complexity theories include Complex Adaptive Systems (CAS) and Viability Theory, and softer theories, which we refer to as Viable Systems Theories (VSTs), that includes Management Cybernetics at one extreme and Humanism at the other. This paper has a dual purpose distributed across two parts. In part 1 the purpose was to identify the conditions for the complementarity of the two classes of theory. In part 2 the two the purpose is to explore (in part using Agency Theory) the two classes of theory and their proposed complexity continuum.

Explanation is provided for the anticipation of behaviour cross-disciplinary fields of theory dealing with adaptive complex systems. A comparative exploration of the theories is undertaken to elicit concepts relevant to a complexity continuum. These explain how agency behaviour can be anticipated under uncertainty. Also included is a philosophical exploration of the complexity continuum, expressing it in terms of a graduated set of philosophical positions that are differentiated in terms of objects and subjects. These are then related to hard and softer theories in the continuum. Agency theory is then introduced as a framework able to comparatively connect the theories on this continuum, from theories of complexity to viable system theories, and how harmony theories can develop.

Anticipation is explained in terms of an agency’s meso-space occupied by a regulatory framework, and it is shown that hard and softer theory are equivalent in this. From a philosophical perspective, the hard-soft continuum is definable in terms of objectivity and subjectivity, but there are equivalences to the external and internal worlds of an agency. A fifth philosophical position of critical realism is shown to be representative of harmony theory in which internal and external worlds can be related. Agency theory is also shown to be able to operate as a harmony paradigm, as it can explore external behaviour of an agent using a hard theory perspective together with an agent’s internal cultural and cognitive-affect causes.

There are very few comparative explorations of the relationship between hard and soft approaches in the field of complexity and even fewer that draw in the notion of harmony. There is also little pragmatic illustration of a harmony paradigm in action within the context of complexity.

This chapter uses the theory of complex systems as a conceptual lens through which to compare the work of Friedrich Hayek with that of Vincent and Elinor Ostrom. It is well known that, from the 1950s onwards, Hayek conceptualised the market as a complex adaptive system. It is argued in this chapter that, while the Ostroms began explicitly to describe polycentric systems as a class of complex adaptive system from the mid-to-late 1990s onwards, they had in fact developed an account of polycentricity as displaying most if not all of the hallmarks of organised complexity long before that time. The Ostromian and Hayekian approaches can thus be seen to share a good deal in common, with both portraying important aspects of society – the market economy in the case of Hayek, and public economies, legal and political systems, and environment resources in the case of the Ostroms – as complex rather than simple systems. Aside from helping to bring out this aspect of the Ostroms’ work, using the theory of complex systems as a framework for comparing the Hayekian and Ostromian approaches serves two other purposes. First, it can be used to show how one widely criticised aspect of Hayek’s theory of society as a complex system, namely his account of cultural evolution via group selection, can be strengthened by an appeal to the work of Elinor Ostrom. Second, it also helps to resolve a tension – ultimately acknowledged by the Ostroms themselves – between some of their explicit methodological pronouncements and the actual, substantive approach they adopted in their analysis of polycentric systems.

The purpose of this paper is to seek to develop a theoretical framework for understanding the structure of effective knowledge sharing networks in professional organizations.

A literature review is performed to achieve the purpose. This article integrates two streams of literature: related to knowledge network structure and related to professional complex systems, to gain insight into the structure of effective knowledge sharing networks in professional complex systems. This preliminary theoretical framework is then used to put forth strategies for knowledge management and collective learning in professional organizations.

An analysis of knowledge networks and complex systems literatures suggests that effective knowledge sharing networks in complex systems may be richer in density compared to brokerage. However, integrating this analysis with the literature on professional organizations, including “subgoals” theory, suggests that the reverse may be true in professional complex systems, i.e. that effective knowledge sharing networks in professional complex systems may be richer in brokerage and hierarchy, rather than in density.

The paper provides a foundation for future research avenues in the professional organizational context. For instance the framework could be used to explore effective knowledge sharing structures across professional subgroups and hierarchical levels in a hospital context; and across faculty, staff, and administrators in a college/university context.

A key implication is that, in order to enable collective learning in professional organizations, senior executives must make proactive and unceasing efforts to: coordinate knowledge exchange across professional subgroups; create cognitive linkages between subgroup actions and organizational outcomes; and connect professional subgroups with the changing external environment.

The theoretical framework lays a foundation for addressing the gap in the literature related to knowledge creation and collective learning in professional organizations.

This paper aims to initiate a new, formal theory of sociocultural physics.

Its intended scope is limited to predicting either long‐term, large‐scale or short‐term, small‐scale sociocultural events. The theory that the authors develop, called sociohistory, links three independent but relatable approaches: part of Sorokin's epistemological theory of sociocultural dynamics, Frieden's epistemological theory of extreme physical information (EPI), and Yolles's social viable systems (SVS) theory.

Although not all of Sorokin's ideas are universally accepted, a subset of them is found to be extremely useful for describing the conceptual context of complex systems. This includes how sociocultural processes link closely into political processes.

The theory that develops helps explain how opposing, cultural enantiomers or yin‐yang forces (represented, for instance, by the polar mindsets represented in Islamic fundamentalism and global enterprise) can result in violent conflict, or in either viable or non‐viable social communities. The informations I and J of EPI theory are regarded, respectively, as sensate and ideational enantiomers.

While the resulting sociocultural physics is in its infancy, an illustrative application to the developmental dynamics of post‐colonial Iran demonstrates its potential utility.

The purpose of this paper is to argue that the epistemology of the strategic literature is dominated by a Modernist (scientific) and Cybernetic system approach and that other epistemological options especially critical management studies and complex self‐adapting systems, might provide greater insight for strategic thinking.

An extensive review of the literature was undertaken.

The current dominant way of thinking about management is based on closed system notions of causality in which good enough long‐term prediction is possible. The process PLOC depends totally on this foundation. If a system's long‐term behaviour is unpredictable, then using the PLOC model is questionable. In the current turbulent business environment long‐term prediction may not be possible.

The life expectancy of a firm is only 40 years. Using closed system concepts to drive businesses to the equilibrium of a business plan may be killing the business, because a complex self‐adapting system in equilibrium is dead.

Very little work, especially in strategy has been done outside the Modernist paradigm. This paper explores the possibility of incorporating open system ideas into a strategic methodology.

The purpose of this paper is to address the problem of designing artificial complex adaptive systems, like information systems and organisations, by developing a proof‐of‐concept conceptual proto‐agent model.

The paper develops an exploratory proto‐agent model and evaluates its suitability for implementation as agent‐based simulation.

The paper focuses on understanding the effect of emergence when designing artificial complex adaptive systems and produces a proto‐agent model that identified agents and their behavioural rules for modelling.

In deferred action, agents act in emergent organisation to achieve predetermined goals. Since emergence cannot be predicted, information systems and organisation design approaches that cater for emergent organisation are required.

The deferred action construct is a synthesis of planned approaches and contingency approaches to design information systems. It recognises the effect of emergence on information systems.

The purpose of this paper is to show that transmission of information and information storage or registration depends on structures. Structures emerge from coordinated sets of constraints. Complex systems depend on their structures to function. The temporal sequence of changes in the levels of the complex system determines its behavior. These three concepts are intimately linked with the environment. Environment, structure, function and behavior form a complex system–environment unit, which is the operational unit of existence for all open complex systems. Therefore, it becomes a point in the directional propagation of the cause, where stimulus environment becomes a Creaon, and then the Creaon becomes a Genon, becoming in turn the response to the experienced environment. The formation of structures is the main phenomenon of evolution. Evolution can also be accepted as free, in the sense that it does not cost additional deaths.

Mathematical and logical development of the structure and thermodynamics in complex systems.

Based on the above considerations, the authors are going to introduce two fundamental principles in Complex systems Theory: the Matthew Effect and the Principle of Sagan.

But as the authors’ purpose is to give a formal definition of a complex system from a totally theoretical point of view, they establish a relationship between concepts of General Systems Theory, Theory of the Environment, linguistics, Information Theory and thermodynamics.

The purpose of this research is to provide a theoretical and practical theory and application that provides understanding and means to manage complex infrastructures.

In this research, complexity, nonlinear, noncontinuous effects and aleatoric and data unknowns are bypassed by directly addressing systems' responses. Graph theory, statistics and digital signal processing (DSP) tools are applied within a theoretical framework of the theory of faults (ToF). Motivational complex infrastructure systems (CISs) are difficult to model. Data are often missing or erroneous, changes are not well documented and processes are not well understood. On top of it, under complexity, stalwart analytical tools have limited predictive power. The aleatoric risk, such as rain and risk cascading from interconnected infrastructures, is unpredictable. Mitigation, response and recovery efforts are adversely affected.

The theory and application are presented and demonstrated by a step-by-step development of an application to a municipal drainage system. A database of faults is analyzed to produce system statistics, spatio-temporal morphology, behavior and traits. The gained understanding is compared to the physical system's design and to its modus operandi. Implications for design and maintenance are inferred; DSP tools to manage the system in real time are developed.

Sociological systems are interest driven. Some events are intentionally created and directed to the benefit and detriment of the opposing parties in a project. Those events may be explained and possibly predicted by understanding power plays, not power functions. For those events, sociological game theories provide better explanatory value than mathematical gain theories.

The theory provides a thematic network for modeling and resolving aleatoric uncertainty in engineering and sociological systems. The framework may be elaborated to fields such as energy, healthcare and critical infrastructure.

ToF provides a framework for the modeling and prediction of faults generated by inherent aleatoric uncertainties in social and technological systems. Therefore, the framework and theory lay the basis for automated monitoring and control of aleatoric uncertainties such as mechanical failures and human errors and the development of mitigation systems.

The contribution of this research is in the provision of an explicatory theory and a management paradigm for complex systems. This theory is applicable to a wide variety of fields from facilities and construction project management to maintenance and from academic studies to commercial use.