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Dr Kurt A. Richardson and Andrew Tait

Understanding the structure of complex networks and uncovering the properties of their constituents has been for many decades at the center of study of several fundamental sciences, especially in the fields of biological and social networks. Given the large scale and interconnected nature of these types of networks, there is a need for tools that enable us to make sense of these structures. This chapter explores how, for a given network, there are a range of emergent dynamic structures that support the different behaviors exhibited by the network’s various state space attractors. We use a selected Boolean Network, calculate a variety of structural and dynamic parameters, explore the various dynamic structures that are associated with it and consider the activities associated with each of the network’s nodes when in certain modes/attractors. This work is a follow-up to past work aiming to develop robust complexity-informed tools with particular emphasis on network dynamics.

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Professor James K. Hazy and Professor Peter R. Wolenski

The chapter presents a general mathematical framework to study discontinuous change in human interaction dynamics. There are two complementary perspectives: macro and micro. Regarding the macro context, the chapter proposes that levels of ordered structure in complex human organizing can be represented by a category theoretic representation that reflects informational influence acting on individual agents from sources external to the population and those internal to the population. These independent influences interact to change the set of interaction rules that are enacted locally. Regarding micro context, the authors position contagion as the mechanism whereby a common organizing state is adopted across multiple agents. They show that as a general matter, the ordered structure that emerges within a population can be indexed as the number of active degrees of freedom embedded in local rules of interaction that are guiding groups of agents. Category theoretic mathematical approaches should be more used in social science research to suggest deductive hypotheses that can be tested empirically with definitive results.

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Edited by Eve Mitleton-Kelly, Alexandros Paraskevas and Christopher Day

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Dr Robin Durie, Dr Craig Lundy and Professor Katrina Wyatt

A number of drivers for contemporary research are focusing attention on how to achieve public engagement in research undertaken by Higher Education Institutes (HEIs). In 2008, RCUK funded six ‘Beacons for Public Engagement’. We sought to understand how each Beacon had created the conditions for two-way engagement in the research design and delivery. We undertook an initial scoping study of the organisational culture within each Beacon and, using maximum variation sampling, selected seven projects which were our case studies. The analysis of the findings from these case studies from a complex systems perspective led us to conceptualise an ‘engagement cycle' which has three phases or elements: creating the conditions; co-creation of research; and, feedback loops to inform ongoing and future research. In this chapter, we discuss the approach we used to gather the data, how complexity theory underpins the approach and the interpretation of the findings, and how the results led to the engagement cycle.

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Assistant Professor G. Christopher Crawford and Professor Bill McKelvey

Life is not normally distributed – we live in a world of extreme events that skew what we consider ‘average.’ The chapter begins with a brief explanation of the basic causes of skewed distributions followed by a section on horizontal scalability processes. These are generated by scale-free mechanisms that result in self-similar fractal structures within organizations. The discussion then focuses on one of the most cited mechanisms purported to cause power law distributions: Bak’s (1996) ‘self-organized criticality’. Using three longitudinal datasets of entrepreneurial ventures at different states of emergence, the chapter presents a method to determine whether data are power law distributed and, subsequently, how critical thresholds can be calculated. The analysis identifies the critical point in both founder inputs and venture outcomes, highlighting the threshold where systems transition from linear to nonlinear and from normal to novel. This provides scholars with a conceptual–empirical link for moving beyond loose qualitative metaphors to rigorous quantitative analysis in order to enhance the generalizability and utility of complexity science.

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Professor Alexandros Paraskevas

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Alexandra (Sasha) Cook and Bertolt Meyer

Although most definitions of leadership acknowledge the act of leading itself as being an interactional behavior between at least two individuals, we know surprisingly little about what leaders actually do and in which ways the concrete and observable behavior of formal or informal leaders in organizations and teams is related to outcomes such as leadership success or subjective leadership impressions by employees or team members. This chapter aims at summarizing existing methods for observing leadership behavior and leadership behavior coding schemes. Additionally, the authors take a closer look at current empirical evidence from emergent leadership research on behavioral parameters and their automated measurement with wearable sensors. Based on this review, they discuss the prospective operational capability of measures such as automated movement and interaction analyses in observational studies on leadership behaviors and their possible contribution beyond the limits of existing behavioral coding systems.

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Edited by Birgit Schyns, Rosalie J. Hall and Pedro Neves

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Wen-Dong Li, Remus Ilies and Wei Wang

Behavioral genetics approaches to the study of individual differences have been widely applied in various disciplines in social sciences to investigate the “nature versus/and nurture” issue through disentangling influences from genetic factors (i.e., influences from nature) and environmental factors (i.e., influences from nurture). However, leadership research has only recently embraced such approaches. This is unfortunate considering the long-standing debate on whether leaders are born or made, and the more recent emphasis on person–environment interplay in leadership research. In this chapter, the authors first discuss the importance of the behavioral genetics approach to organizational research. They then introduce two types of behavioral genetics research that have been adopted so far: classic twin studies and molecular genetic research capitalizing on specific DNA information. Specifically, they explain how univariate biometric analyses, and bivariate biometric analyses based on twin studies can be applied to study important issues in leadership research. With respect to molecular genetic research, they discuss the candidate gene approach and genome-wide association studies, and how they can be useful in advancing leadership research. They also provide brief research examples based on previous research in which such approaches can be employed in addressing critical questions in leadership.

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Miguel Pina e Cunha, Marianne Lewis, Arménio Rego and Wendy K. Smith

The chapter discusses the role of biographical methods in leadership research. Biographical methods refer to a variety of approaches that include self-narratives, autobiographies, and historical biographies. The authors explore an individual’s life story to elucidate its dynamics over time. Biographical methods engage with the lived experience of leadership and aim to explore the richness of the experience of leading. They aim to generate deep-level and holistic insights into the behaviors, relationships, thoughts, and emotions of leaders, and help to make sense of how such behaviors, relationships, thoughts, and emotions dynamically unfold over time and in context. Biographical methods provide a rich combination of breadth (the dimensions across a leader’s life) and depth (the intimate details about the leader’s life and circumstances over time). Such combination of breadth and depth favors the creation of insight into factors often excluded from leadership research, namely the paradoxical tensions and inconsistencies inherent in leadership processes.