How and Why Effective Leaders Construct and Evolve Structural Attractors to Overcome Spatial, Temporal, and Social Complexity

This chapter discusses the challenges, complexities, and benefits of using agent-based modelling in the study and practice of leadership in teams and organizations. After acknowledging these challenges, the chapter proposes a formal approach to defining leadership as an influence process for computational models and simulation purposes as well as in real-world organizations. This is intended to clarify how leadership can be specified, modelled, and operationalized more rigorously in the context of both research and practice. State-of-the-art studies in computational leadership research, including those with adaptive agents, adaptive environments, and emergent intelligence, are reviewed. These studies are organized and described along three distinct dimensions of leadership influence: aligning expectations in a collective with respect to opportunities and threats in its environment, initiating or sustaining repeatable instrumental momentum within organizations, and engendering an observable cooperating valence within a collective that reflects the presence of trust among agents at various levels of scale. The chapter closes with a proposed framework to guide future research in areas such as emergent leadership in hybrid human–machine environments and decision-making in the presence of localized deception during interactions as well as the potential to respond effectively to misinformation attacks from malicious actors on a much broader scale.

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When the Value of Cooperating Scales: Collective Intelligence, Information Processing, and the Leadership Meta-Capability

Hazy

2021

Front. Hum. Dyn.

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This article explores the nexus where purposeful individual-driven collective action, what is called organizational leadership, interacts with collective intelligence and agency. Based on recent numerical models from complex network theory and empirical studies of collective dynamics in social biology, it describes how intelligent collective agency forms around three order parameters: expectancy alignment, instrumentality inside the collective, and a subjective belief by individual agents in the generalized trustworthiness of other members of a collective. When the value of one or more of these scaling metrics becomes dynamically stable, fractal structures in the collective provide useful information to individuals that informs their choices during interactions including leadership activities. The theory contributes fifteen testable assertions that if supported empirically suggest fruitful ways that new information technology applications could enhance organizational effectiveness.

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How and Why Effective Leaders Construct and Evolve Structural Attractors to Overcome Spatial, Temporal, and Social Complexity

Cited by 3 publications

References 14 publications

Complexity and Corruption Risk in Human Systems

Complexity and Corruption Risk in Human Systems

Modelling the Leadership Influence Process

When the Value of Cooperating Scales: Collective Intelligence, Information Processing, and the Leadership Meta-Capability

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