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This chapter aims to identify the main determinants that define the architectural properties of network emergence and significantly influence the dynamics underlying network evolution in time. The identification and analysis of these determinants, as well as the dynamic processes tied to them, allows to appreciate the competitive bases and consequences of network morphology. To this purpose, using a complex systems perspective as an integrative conceptual approach, we represent networks as complex dynamic systems of knowledge and capabilities. We perform a comparative in-depth analysis of the processes underlying the emergence and evolution of STMicroelectronic's global network and of Toyota's supplier network in the US so as to allow an elucidatory empirical assessment of the theoretical representation elaborated in the article.

This chapter discusses the emerging network science approach to the study of complex adaptive systems and applies tools derived from statistical physics to the analysis of tourism destinations. The authors provide a brief history of network science and the characteristics of a network as well as different models such as small world and scale free networks, and dynamic properties such as resilience and information diffusion. The Italian resort island of Elba is used as a case study allowing comparison of the communication network of tourist organizations and the virtual network formed by the websites of these organizations. The study compares the parameters of these networks to networks from the literature and to randomly created networks. The analyses include computer simulations to assess the dynamic properties of these networks. The results indicate that the Elba tourism network has a low degree of collaboration between members. These findings provide a quantitative measure of network performance. In general, the application of network science to the study of social systems offers opportunities for better management of tourism destinations and complex social systems.

The purpose of this chapter was to describe the development of an early childhood learning network and to understand that development through the lens of complexity theory and trans-organization development. It explores the unfolding dynamics and emerging meaning that became central to facilitating the design, development, and implementation of the complex multi-stakeholder network.

The chapter identifies 12 implications from complexity theory for practitioners of trans-organization development, and then applies those implications to the process and understanding of development stages of an NP’s early childhood education network.

The use of complexity theory as a framework allowed for identifying five key observations and conclusions, in particular the significant role that meaning-making dialogue holds as a driver of common understanding and engagement among stakeholders. Additionally, the use of building responsive processes, understanding contextual shift, impact of power as an attractor pattern, and capacity of flexibility and adaptability all become essential elements of complex network leadership.

The findings of this chapter will help trans-organization development practitioners and leaders alike. Both the implications and lessons learned will assist in building the capacity of leaders and practitioners as a means of improving effectiveness in dealing with emerging dynamics and leading in unknown contexts and complex contexts environments.

Purpose – To present the connection between modern network theory and Hayek's ideas on the brain and spontaneous orders.

Methodology/approach – To show that Hayek's ideas on the brain, spontaneous order, and why socialism cannot work are confirmed by network and self-organization theory, and to use network and self-organization theory to bridge Hayek's theory of the mind to his work on spontaneous orders.

Findings – Spontaneous orders are scale-free networks, but humans evolved a preference for hierarchical networks, which are typical of tribes and firms – and socialism. However, hierarchies only work for teleological organizations, not for ateleological spontaneous orders like economies. Part of the human preference for human-organized networks comes from our “intentional stance,” which automatically sees patterns as evidence of an organizer.

Research limitations/implications – This work acts as an introduction to possible directions in spontaneous order research. New work in bridging evolutionary and cognitive psychology (which includes Hayek's work) with self-organization and network theory acts as a promising development for neuro-Hayekians.

Social implications – Understanding there is an evolutionary bias for certain kinds of networks, even though those are not appropriate for certain kinds of social orders, and understanding the nature of these networks should help us understand the true relationships among individuals, organizations, and spontaneous orders.

Originality/value of chapter – This work brings Hayek “up to date,” with network theory and self-organization, showing to what extent Hayek was talking about these concepts. Seeing the similarities and differences between hierarchical and scale-free networks helps one understand how they come about, and in what contexts.

Companies inevitably interact and entrench in complex organic systems of business relationships with other. These business networks are not objectively defined, instead they are shaped by the subjective perception of actors. This inherent subjectivity is associated with the notion of network pictures, that is, a research tool that researchers or managers can use to grasp practitioner theories. In this chapter, we discuss how the importance of identifying these theories results mainly from underlying principles of sense-making theory, as well as from the idea around performativity. Drawing on these theoretical groundings, this chapter has two objectives: to explore how practitioners actually perceive their business surroundings and to assess the extent of overlapping between (IMP Group) academic theories and practitioner theories. To achieve these objectives, the researchers use a dimensional network pictures model previously developed in the literature to analyze the network pictures of 49 top-level managers across 17 companies from two very distinct contexts or networks: a product-based network and a project-based network. Among other practices, findings illustrate how practitioners tend to simplify what is going on in their complex surroundings, to personalize their relationships with those surroundings, and to think in a stereotyped way. Moreover, the juxtaposition between the captured practitioner theories and academic (IMP Group) theories show that these are not always overlapping, and are in some cases quite the opposite. This research contributes to the ongoing discussion of the importance of grasping actors’ views of the world, arguing that sense-making theory and the notion of performativity are the two main conceptual drivers justifying the urgency in making those views more visible. This research also adds to the research on the impact and suitability of IMP Group theories on managerial thinking and practice. Finally, this research reinforces the current call for further practice-based research in business network contexts.

As the demand for new services strains library resources, directors of research libraries must practice efficient cost management and demonstrate alignment with institutional objectives. For technical services, this requires managing the effective cost of metadata services, assessing core functions, and evaluating operational performance. This paper uses Complex Adaptive Systems (CASs) as a framework to expose the network of local and global dependencies that currently define the field of operation for technical services. Comparative analyses using a CASs framework were conducted on reports by the Library of Congress, the Heads of Technical Services in Large Research Libraries Interest Group, and the British Library. Each report addresses financial pressures placed on bibliographic control services in response to the 2008 recession. Statements within the reports were assigned to one of three dominant systems: bibliographic control, institutional identification, and distributive networks. The statements were then mapped to the CASs characteristics to determine environmental pressures and areas of adaptation. The reports exposed long-standing dependencies that tie local bibliographic control to a complex network of external agencies. Institutional shifts toward user-centered services coupled with growing fiscal restraint has disrupted the stability of these networks. The analyses found that in all cases network instability led to localized institutional adaptation to existing economic pressures. The paper recommends applying a CASs model to assess the alignment of distributed metadata standards and systems development to local institutional objectives.

To create circular economies, we need supply systems to convey materials between their use lives. Often, though, it is not possible to control an entire supply network. Without a coordinator to implement circular economy principles, how can circular supply systems come to be? This chapter sets out to build on complex adaptive systems (CAS) theory and circular economy research to conceptualize how information flows between actors can facilitate the emergence of a circular supply system. It begins by outlining why a supply network can be considered a CAS, as well as the CAS progression from information to adaptation to emergence. Next, it argues that information on local supply networks, extended supply systems, and biosphere impacts is particularly important for circular production. Finally, it concludes with two potential types of emergence that can stem from these information flows: (1) new actor roles and networks and (2) new spatial and temporal patterns. Ultimately, this conceptual overview aims to give researchers and practitioners a CAS frame for thinking about how continual adaptation to information flows can enable change toward circular supply systems.

This chapter focuses on the treatment and characterization of networks as an emerging discipline. Networks are defined. The authors call out and explain the importance of network domains, network geographies and topologies, network behaviors, network nodes, network links, relationships and flows, and network messages. While network sciences provide a strong foundation for research and analysis, the authors note the lack of knowledge networks. This chapter highlights the need to expand coverage to include knowledge networks.

We discuss the impact of complexity science on the design and management of health care organizations over the past decade. We provide an overview of complexity science issues and their impact on thinking about health care systems, particularly with the rising importance of information systems. We also present a complexity science perspective on current issues in today’s health care organizations and suggest ways that this perspective might help in approaching these issues.

We review selected research, focusing on work in which we participated, to identify specific examples of applications of complexity science. We then take a look at information systems in health care organizations from a complexity viewpoint.

Complexity science is a fundamentally different way of understanding nature and has influenced the thinking of scholars and practitioners as they have attempted to understand health care organizations. Many scholars study health care organizations as complex adaptive systems and through this perspective develop new management strategies. Most important, perhaps, is the understanding that attention to relationships and interdependencies is critical for developing effective management strategies.

Increased understanding of complexity science can enhance the ability of researchers and practitioners to develop new ways of understanding and improving health care organizations.

This analysis opens new vistas for scholars and practitioners attempting to understand health care organizations as complex adaptive systems. The analysis holds value for those already familiar with this approach as well as those who may not be as familiar.