CSLT uses insights from complexity science, social networks, and computer and agent based modeling (ABM) to inform research on organizations, social influence, team formation, strategy determination and execution, and individual choice and action as these relate to leadership. CSLT is different than traditional leadership research in that leadership is not assumed to be situated in an individual. Rather, it is assumed to be a system function that enables semi-autonomus individuals to engage in unified collective action in the context of emergent collective properties such as organzational performance, innovation, adaptation, and a sense of unity or collective identity.

In sum, Complex Systems Leadership Theory (CSLT) considers leadership to be a system function which enables adaptive action by changing the going-forward rules of interaction among agents both in terms of ends and of means. An approach known as Complexity Leadership Theory argues that three types of leadership: administrative, adaptive and enabling can be observed in organizations. The third perspective builds upon the evolutionary theory of the firm (Nelson & WInter, 1982) and looks at leadership as an organizational metacapability that manages other capabilities that engage in both exploration and exploitation. Finally, there are multiple studies that explore leadership using computational and mathematical models. Additional details on recurring themes and research questions can be found by clicking those terms.

Complex Systems Leadership Theory (CSLT)

CSLT is a different approach than traditional leadership approaches in that it begins with the assumption that human interaction dynamics can be explored using complex systems models and then focuses on identifying what leadership might mean in a complex adaptive system composed of human beings interacting in a social network (Hazy, 2008). In particular, CSLT defines leadership as a system function that operates to "changes the rules of interaction" among people or groups within a complex adaptive system of interactions, both in terms of ends - where the system is going - and means - how to get there (Hazy, Goldstein, & Lichtenstein, 2007; Goldstein, Hazy & Lichtenstein, 2010). To explore this approach, two books as well as many articles, papers and book chapters have been published that describe how leadership can be considered in this way. See annotated bibliography for additional references.

Complexity Leadership Theory

There have been several articles, papers and book chapters and an edited volume (Uhl-Bien & Marion, 2008) that describe how complexity science can inform leadership thinking as it has traditionally been studied. These papers explore how complexity theory informs the role of leadership in organizations. See annotated bibliography for references. Complexity theory is a science of complexly interacting systems; it explores the nature of interaction and adaptation in such systems and how they influence such things as emergence, innovation, and fitness. Thos research argues that complexity theory focuses leadership efforts on behaviors that enable organizational effectiveness, as opposed to determining or guiding effectiveness. Complexity science broadens conceptualizations of leadership from perspectives that are heavily invested in psychology (e.g., human relations models) to include processes for managing dynamic systems an interconnectivity. This stream develops a definition of organizational complexity and apply it to leadership science, discusses strategies for enabling complexity theory and other currently important leadership theories.

Leadership as a Metacapability of Organizations

In parallel, there has been research that explores how a leadership function impacts success or failure at the organization level. This approach recognizies that if leadership is considered as emerging from among multiple agents rather than as an individual or even a dyadic phenomenon, then the instrumental impacts of leadership must be observed within the organization independent of individuals. It must be observed not only in the agents and what they do, but also in how the agents are connected into organizational capabilities. In other words, if complex systems leadership constructs are meaningful, in the hierarchy of dynamic organizational capabilities, leadership must be observable as a metacapability that connects and organizes disparate agents into a complex adaptive system that acts as a unity in the environment (Hazy, 2006; 2008). See annotated bibliography for references. Click below for a PowerPoint description of this metacapability that was presented at the Academy of Management in 2007.

In this formulations, it is posited that there are three contexts in which this metacapability is expressed within a complex adaptive system as it adapts to the environment (Hazy, 2006): leadership in the generative context catalyzes choice, actions and communications that generate variety in capabilities configurations (Goldstein, Hazy & Lichtenstein, 2010; Surie & Hazy, 2006); leadership in the convergent context catalyzes the dynamics of agent interactions toward an efficient and effective configuration once an approach is selected; and leadership in a unifying context holds the system together as an identity, establishes, extrapolates and redefines boundaries and resonates the overall dynamics of the system as it oscillates among local generative and convergent dynamics.

Computational and Mathematical Models

In support of a developing body of theory supporting leadership in complex systems, computational and mathematical models have begun to be developed. For a survey of models developed in this arena, visitors are referred to the following journal articles and book chapter (Hazy, 2007, 2008; Hazy Millhiser, Solow, 2007): See below and the annotated bibliography for references.

Additional topics of interest

In addition to the above there are many other topics that are under this umbrella.

Complexity topics of interest that have been addressed through modeling and empircal studies include: complex adaptive systems, nonlinear dynamical systems and catastrophe theory, emergence and self-organization, random and social networks, organizational boundaries and boundary spanning, rugged fitness or performance landscapes, bifurcation and attractors, game theory, and sensitivity to initial conditions and chao theory.

Leadership topics addressed include: group formation, entrepreneurial leadership, groups embedded in organizations, project teams, and organizational transformation in for-profit, not-for-profit and govenment settings. In more general terms, studies on trust or reputation and how these impact influence in social networks and thus leadership are also relevant.


Hazy, J. K. (2006). Measuring leadership effectiveness in complex socio-technical systems. Emergence: Complexity and Organization (E:CO), 8((3)), 58-77. Abstract.

Hazy, J. K. (2007). Computer models of leadership: Foundation for a new discipline or meaningless diversion? The Leadership Quarterly, 18(4), 391-410. Abstract

Hazy, J. K. (2008) Toward a theory of leadership in complex systems: Computational modeling explorations. Nonlinear Dynamics, Psychology, and Life Sciences, 12(3) 281-310. Abstract.
Hazy, J. K. (2007). "Computer models of leadership: Foundation for a new discipline or meaningless diversion?" The Leadership Quarterly, 18(4) 391-410.

Hazy, J. K. (2008). "Toward a theory of leadership in complex systems: Computational modeling exploration." Nonlinear Dynamics, Psychology, and Life Sciences.12(3) 281-310. Abstract.

Hazy, J. K., Goldstein, J. A. & Lichtenstein, B. B. (Eds.). (2007) Complex Systems Leadership Theory. Mansfield, MA: ISCE Publishers. Table of Contents

Hazy, J. K., Millhiser, W., & Solow, D. (2007). "Mathematical and Computational Models of Leadership: Past and Future." in Hazy, J.K., Goldstein, J. A. and Lictenstein, B. B. (eds.). Complex Systems Leadership Theory Mansfield, MA: ISCE Publishers.

Goldstein, J., Hazy, J. K., & Lichtenstein, B. (2010). Complexity and the Nexus of Leadership: leveraging nonlinear science to create ecologies of innovation. Englewood Cliffs: Palgrave Macmillan.

Nelson R.R. & Winter, S. G. (1982). An Evolutionary Theory of the Economic Change. Cambridge MA: Belknap Press.

Uhl-Bien, M & Marion, R. (Eds.) (2008) Complexity & Leadership, Volume I: Conceptual Foundations. Information Publishing Associates. Table of Contents