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This chapter addresses two identified weaknesses in entrepreneurial ecosystem studies: there is a lack of focus on the relationships between the components of entrepreneurial ecosystems and little understanding of the underlying processes that determine how entrepreneurial ecosystems change over time. Both entrepreneurial ecosystems and solutions ecosystems from social entrepreneurship studies are place-based complex adaptive systems that are emergent in nature. While neither of these ecosystem types can be controlled, they can be influenced and guided to follow a direction by designing conditions for emergence and transitions. In this chapter, the proposition that an online tool, that is used to strengthen solution ecosystems and support their emergence and transition, could also be used to strengthen entrepreneurial ecosystems and guide their emergence and transition is examined. Two cases are used to investigate this proposition: a food security solution ecosystem case study that demonstrates how the online tool is used for solution ecosystems, and an impact economy entrepreneurial ecosystem case study that highlights how the online tool could be used for an entrepreneurial ecosystem. It is demonstrated in this chapter that the online tool can be used to address the current weaknesses of entrepreneurial ecosystem studies. In addition, it is suggested that by combining solution ecosystems with an impact economy entrepreneurial ecosystem, the online tool can be used to support the creation of conditions for social entrepreneurial places to emerge that are capable of addressing the most pressing problems that places face including the sustainable development goals.

The purpose of this conceptual paper is to explore the role of strategic leadership under conditions of uncertainty and unpredictability. The authors argue that highly improbable, but high-impact events require the upper echelons of management, traditionally the custodians of strategy formulation to offer a new kind of strategic leadership focused on new mindsets, organizational capabilities, more in tune with high uncertainty and unpredictability.

Drawing on strategic leadership, and complexity leadership theory, the authors review the literature and present a conceptual framework for exploring the nature of strategic leadership under uncertainty. The authors conceptualize organizations as complex adaptive systems and discuss the imperatives for developing new mental models for emergent leadership.

Strategic leaders have a key role to play in preparing their organizations for episodic disruptions. These include developing their adaptive capabilities and building resilient organizations to ensure their organizations cannot only bounce back after a disruption but have the capacity for transformation to new fitness levels when necessary. Strategic leaders must engage with complexity leadership by seeing their organizations as complex adaptive systems, reconfigure their leadership approaches and organizations to build strategic adaptive capability.

This is a conceptual paper and the authors cannot make any claims of causality.

Organizational leaders need to reconfigure their mental models and leadership approaches to reflect the new normal of uncertainty and unpredictability. Developing the strategic adaptive capability of organizations should prepare them for dealing with high impact events. To assure business continuity in the face of disruptions requires building flexible, adaptable business models.

The paper focuses on how managers can offer strategic leadership for a new normal that challenges some of our most cherished leadership and strategic management paradigms. The authors explore the new mental models and leadership models in an era of great uncertainty.

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.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

The purpose of this paper is to deepen the understanding of adaptive governance, which is advocated for as a manner to deal with dramatic changes in society and/or environment. To re-think the possible contributions of organizations and organization theory, to adaptive governance.

Based on social systems theory this study makes a distinction between “governance organizations” and “governance communities.” Organizations are conceptualized as the decision machines which organize and (co-)steer governance. Communities are seen as the social environments against which the governance system orients its operations. This study considers the adaptive mechanisms of organizations and reflect on the roles of organizations to enhance adaptive governance in communities and societies.

Diverse types of organizations can link or couple in different ways to communities in their social environment. Such links can enhance the coordinative capacity of the governance system and can also spur innovation to enable adaptation. Yet, linking with communities can also slow down responses to change and complexify the processes of deliberation in governance. Not all adaptive mechanisms available to organizations can be used in communicating with communities or can be institutionalized, but the continuous innovation in the field of organizations can inspire continuous testing of small-scale adaptive mechanisms at higher levels. Society can thus enhance its adaptive capacity by managing the role of organizations.

The harnessing of insights in organization theory and systems theory for improving understanding of adaptive governance. The finding that both experiment and coordination at societal level are needed, toward adaptive governance, and that organizations can contribute to both.

This paper aims to question the utility of addressing food insecurity through food assistance programmes and by separating food security into pillars, and it argues for a systemic innovation and complexity approach. This is achieved by demonstrating that food insecurity is a wicked problem and therefore needs to be addressed holistically.

To establish that food insecurity is a wicked problem, characteristics of food insecurity are aligned to characteristics of wicked problems. The need to address wicked problems holistically through a systemic innovation approach and an understanding of complexity theory is discussed by referring to the literature. How to take such an approach for addressing food insecurity is illustrated by describing the use of an online tool that takes a systemic innovation and complexity approach.

Given food insecurity is a wicked problem and needs to be addressed holistically, the focus when addressing food insecurity should not be on programmes or pillars. Instead, it needs to be on increasing the coherence and building the adaptive capacity of food insecurity solution ecosystems.

This paper provides insights into the nature of food insecurity and how to address food insecurity.

For the first time, this paper aligns characteristics of food insecurity to characteristics of wicked problems and demonstrates how an online tool for systemic innovation can assist food insecurity solution ecosystems to address food insecurity.

The purpose of this paper is to advance supply chain network theory by applying theoretical and empirical developments in complex network literature to the context of supply chains as complex adaptive systems. The authors synthesize these advancements to gain an understanding of the network properties underlying efficient supply chains. To develop a suitable theory of supply chain networks, the authors look to mirror the properties of complex network models with real‐world supply chains.

The authors review complex network literature drawn from multiple disciplines in top scientific journals. From this interdisciplinary review a series of propositions are developed around supply chain complexity and adaptive phenomena.

This paper proposes that the structure of efficient supply chains follows a “scale‐free” network. This proposal emerges from arguments that the key properties of efficient supply chains are a short characteristic path length, a high clustering coefficient and a power law connectivity distribution.

The authors' discussion centres on applying advances found in recent complex network literature. Hence, the need is noted to empirically validate the series of propositions developed in this paper in a supply chain context.

If efficient supply chains resemble a scale‐free network, then managers can derive a number of implications. For example, supply chain resilience is derived by the presence of hub firms. To reduce the vulnerability of supply chains to cascading failures, it is recognized that managers could build in redundancy, undertake a multi‐sourcing strategy or intermediation between hub firms.

This paper advances supply chain network theory. It offers a novel understanding of supply chains as complex adaptive systems and, in particular, that efficient and resilient supply chain systems resemble a scale‐free network. In addition, it provides a series of propositions that allow modelling and empirical research to proceed.

The purpose of this research is to explore core contributions from two different approaches to complexity management in organisations aiming to improve their sustainability,: the Viable Systems Model (VSM), and the Complex Adaptive Systems (CAS). It is proposed to perform this by summarising the main insights each approach offers to understanding organisational transformations aiming to improve sustainability; and by presenting examples of applied research on each case and reflecting on the learning emerging from them.

An action science approach was followed: the conceptual framework used in each case was first presented, which then illustrates its application through a case study; at the first one the VSM framework supports an organisational transformation towards sustainability in a community; the second one is a quantitative case study of intended greening of two firms in the supermarket industry, taken from a CAS perspective. The learning from each case study on how they support/explain organisational learning in transformations towards more sustainable organisations was illustrated.

It wase found that the VSM and the CAS approaches offer internally consistent and complementary insights to address issues of self‐organisation and adaptive management for sustainability improvement: while CAS explains empowerment of bottom‐up learning processes in organisations, VSM enables a learning context where self‐organised networks can co‐evolve for improved sustainability.

The main aspects of both theories and examples of their explanatory power to support learning in practical applications in organisations were introduced. The initial findings indicate that it will be worth studying in greater depth the contributions to organisational learning from both conceptual models and more widely comparing their applications and insights.

The paper offers some guidance to both researchers and practitioners interested in using complex systems theories in action research‐oriented projects, regarding the usability and applicability of both approaches.

It is considered that, by better understanding organisational ability to adapt and self‐regulate on crucial issues for sustainability, it may help to develop one path through the ongoing socio‐ecological crisis. While much has been written about sustainability initiatives and governance from conventional perspectives, much less is known about how a complex systems framework may help to address one's pressing sustainability needs. These issues from two innovative complexity approaches as well as the value of using them in action research were illustrated.

Quality management constructs related to management leadership and workforce involvement have consistently shown strong correlation with firm success for years. However, there is an increasing body of research based on complexity theory (CT) suggesting that constructs such as these should be viewed as variables in a complex system with inter-dependencies, interactions, and potentially nonlinear relationships. Despite the significant body of conceptual research related to CT, there is a lack of methodological research into these potentially nonlinear effects. The purpose of this paper is to demonstrate the theoretical and practical importance of non-linear terms in a multivariate polynomial model as they become more significant predictors of firm success in collaborative environments and less significant in more rigidly controlled work environments.

Multivariate polynomial regression methods are used to examine the significance and effect sizes of interaction and quadratic terms in operations scenarios expected to have varying degrees of complex and complex adaptive behaviors.

The results find that in highly collaborative work environments, non-linear and interaction effects become more significant predictors of success than the linear terms in the model. In more rigid, less collaborative work environments, these effects are not present or significantly reduced in effect size.

This study shows that analytical methods sensitive to detecting and measuring nonlinearities in relationships such as multivariate polynomial regression models enhance our theoretical understanding of the relationships between constructs when the theory predicts that complex and complex adaptive behaviors are present and important.

This study demonstrates that complex adaptive behaviors between management and the workforce exist in certain environments and provide greater understanding of factor relationships relating to firm success than more traditional linear analytical methods.

This bibliometric mapping study aimed to provide comprehensive insights into the global research landscape of cybernetics. Utilizing the biblioshiny function in R Studio, we conducted an analysis spanning 1958 to 2023, sourcing data from Scopus. This research focuses on key terms such as cybernetics, cybernetics systems, complex adaptive systems, viable system models (VSM), agent-based modeling, feedback loops and complexity systems.

The analysis leveraged R Studio’s biblioshiny function to perform bibliometric mapping. Keyword searches were conducted within titles, abstracts and keywords, targeting terms central to cybernetics. The timespan, 1958–2023, provides a comprehensive overview of the evolution of cybernetics-related literature. The data were extracted from Scopus to ensure a robust and widely recognized source.

The results revealed a rich and interconnected global research network in cybernetics. The word cloud analysis highlights prominent terms such as “agent-based modeling,” “complex adaptive systems,” “feedback loop,” “viable system model” and “cybernetics.” Notably, the journal Kybernetes has emerged as a focal point, with significant citations, solidifying its position as a key source within the cybernetics research domain. The bibliometric map provides visual clarity regarding the relationships between various concepts and their evolution over time.

This study contributes original insights by employing advanced bibliometric techniques in R Studio to map the cybernetics research landscape. The comprehensive analysis sheds light on the evolution of key concepts and the global collaborative networks shaping cybernetics research. The identification of influential sources, such as Kybernetes, adds value to researchers seeking to navigate and contribute to the dynamic field of cybernetics. Furthermore, this study highlights that cybernetics not only provides a useful framework for understanding and managing major economic shocks but also offers perspectives for understanding phenomena in various fields such as economics, medicine, environmental sciences and climate change.