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Complex Systems Leadership Theory
Changing the rules: The implications of complexity science for leadership research and practice
James K. Hazy Adelphi University Department of Management, Marketing and Decision Sciences Mary Uhl-Bien University of Nebraska Professor and Howard Hawks Chair in Business Ethics and Leadership Department of Management January 30, 2012
Please do not quote prior to publication. Cite as: Hazy, J. K. & Uhl-Bien, M. (in press). Changing the Rules: The implications of complexity science for leadership research and practice. David Day (ed.) The Oxford Handbook of Leadership and Organizations. Oxford: Oxford University press.
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Complex Systems Leadership Theory
Changing the rules: The implications of complexity science for leadership research and practice James K. Hazy Adelphi University Department of Management, Marketing and Decision Sciences Mary Uhl-Bien University of Nebraska Professor and Howard Hawks Chair in Business Ethics and Leadership Department of Management ABSTRACT The study of complexity has become an important lens through which to view and understand the causes and potencies of individual action and interaction in organizations as well as their meaning for leadership research and practice. This review of key complexity ideas and their theoretical implications for leadership describes emerging theories in the field, highlights the growing empirical support for these approaches, and sets an agenda for future research. The thesis averred is this: Just as complexity has become an overarching theoretical paradigm in the natural sciences, it is providing the basis for a paradigm shift in the social sciences, particularly in leadership and organizational studies. Complex systems leadership theory describes the process whereby the rules governing local interactions are changed in response to and anticipation of changing circumstances. In shifting the focus from the individual to the organizing process itself, the complexity leadership perspective has important implications for both research and practice. Keywords: Complexity leadership, complex systems leadership theory, human interaction dynamics, generative leadership, adaptive leadership, unifying leadership, adaptation, innovation, chaos theory
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Complex Systems Leadership Theory INTRODUCTION Complex Systems Leadership Theory (CSLT) is about interactions and emergence. It is about events and how these shape future action (Lichtenstein et al., 2006), and it is about how human activity is organized into a system of choices and actions when organizations are considered to be complex adaptive systems (Marion & Uhl-Bien, 2001). By describing an overarching dynamic theory of human organizing, CSLT transcends traditional approaches to leadership research by offering a theoretical framework within which prior results can be better understood, evaluated, and integrated into a common view of how human agency drives collective performance and adaptation. In the complexity approach, “leadership” is not considered to be a person or persons. Rather, it is the recognizable pattern of organizing activity among autonomous heterogeneous individuals as they form into a system of action (Lichtenstein et al., 2006; Hazy, Goldstein & Lichtenstein, 2007a; Uhl-Bien, Marion & McKelvey, 2007). At the same time, for organizing to occur, leadership must perform certain functions, what Katz and Kahn (1966) called the “influential increment.” Interpreting Katz and Kahn (1966), Hazy (2011a) argues that when human interactions are considered as complex systems, leadership performs three functions as it organizes human activity. First, it influences human interactions in ways that unify individuals into organized groups. This includes what might be called the strategic functions, such as setting vision and strategy (Boal & Schultz, 2007) and establishing identities and ethics (Hazy, in press-a). Second, leadership changes the rules so as to generate a variety of ideas and plans of action (Hazy, 2006) as a mechanism for adapting to changing circumstances (Uhl-Bien et al., 2007). Creativity and problem solving (Guastello, 2007) are important elements of this function, as are the constraints
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Complex Systems Leadership Theory on action that enable the emergence of novelty (Goldstein, Hazy & Lichtenstein, 2010). Third, rules are changed in ways that enable the convergence of disparate, sometimes conflicting individual perspectives, preferences and activities into effective and predictable collective action (Phelps & Hubler, 2007; Dal Forno & Merlone, 2007; Hazy, 2008b). In sum, leadership is about changing the rules that guide individual choices and interactions. In complex adaptive systems, “changing the rules of interaction” locally can also change organizational outcomes more globally. CSLT studies this process. Individuals, of course, enact pieces of this functional puzzle, and as such, the complexity paradigm implies certain things about individuals and their capacity to succeed as they engage in leadership situations (Hannah, Eggers, & Jennings, 2008; Lord, Hannah, & Jennings, 2011). But isolated individual behaviors are not leadership per se. Leadership is in the whole; it serves to form, sustain and grow the system, just as product development or accountability processes are parts of the whole system. No one person is “governance”; likewise, no one person is “leadership.” At the same time, individuals must enact the leadership process just as they enact other organizational processes. In this sense, CSLT offers a systems’ perspective within which traditional views of leadership that include individual skills and actions can be integrated into a process perspective (Hazy, 2011b). For the purposes of the analysis herein, we define complex systems leadership as system processes that change the rules of interaction and do so in specific ways that form human interaction dynamics (HID) into a complex adaptive system (Hazy et al., 2007) in a manner analogous to how physical and biological interactions are understood as systems. Core to complexity is the realization that the rules governing the individual human interactions of day-today experience are what determine the social structures that emerge (Goldstein, 1989, 2007,
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Complex Systems Leadership Theory 2011; Holland, 1975; McKelvey, 2004). These emergent forms can sometimes be recognized as stable properties, and when they are, they can be evaluated and managed within a particular economic, political, social and technological context. However, interventions cannot directly cause outcomes to change. Emergent forms can only be affected by judiciously changing the local rules that govern the interactions of others and from which the relevant outcomes emerge (Goldstein et al., 2010). It is within the nexus connecting local rules to emergent forms that leadership gathers its potency. This is why leadership is central to human experience. It is important for both organizing to succeed as a group, and as a means to enable individual success through others. Both of these have been the focus of leadership research. CSLT connects these complementary aspects of leadership within a systems framework. Leadership guides both performance (i.e., “exploitation,” March 1991) and survival of the system in the short-term, and adaptation (i.e., “exploration,” March, 1991) and thus its prospects for survival over the longer-term. It does this by processing and using information gathered as feedback from the environment and from within the system itself (Gell-Mann, 2002). It senses this feedback and channels it to individuals who are in a position to use the information it contains to find new ways of organizing in an effort to acquire, store and allocate resources of all types. As such, complex system leadership theory (CSLT) transcends and integrates prior research and offers a platform for understanding leadership in fundamentally new ways. Thesis and overview Our thesis is summarized as follows: Just as complexity has become an overarching theoretical paradigm in the natural sciences, it is serving as the basis for a paradigm shift (Kuhn, 1962) in the social sciences, particularly in the areas of leadership and organizational studies. By
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Complex Systems Leadership Theory shifting the focus from the individual to the organizing process itself, a key value of complexity is its strong implications for practice: Individual action must be considered in nonlinear systems terms. In the fast-changing global ecosystem, approaches to management grounded in linear assumptions may overly emphasize applying controls on interactions, thus failing to stimulate information flows, learning and growth. New techniques that exploit nonlinearities and embrace fast-paced interaction are needed. To explain this, we begin with some of the challenges a complexity paradigm brings to the field. We then describe how complexity thinking is applied to theorizing about leadership, the growing empirical support for this approach, and the new methods that might change the research process going forward. Because one of the key ideas of complexity is the continual unfolding of newness, we conclude by looking ahead. COMPLEXITY BRINGS CHALLENGES The paradigm shift (Kuhn, 1962) towards complexity in leadership research brings with it certain challenges, particularly to those who have traditionally seen leadership as something to be admired in, or executed by, especially gifted or specially trained individuals. In this mindset, individual “leaders” cause things to happen. As these traditional observers might see it, when organizing is needed, that is, when one observes that leadership is necessary, this “leadership vacuum” is translated into the idea that someone, some person, should “step up” to “take charge” causing something to happen (MacGillivray, 2010). With complexity, however, the scenario is different. While the need for leadership remains, causality—at least much of the causality that really matters—is assumed to be indirect and diffuse (Streatfield, 2002). When circumstances require leadership, individual observations and experiences, connections and shared values, relative status, and the interaction dynamics
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Complex Systems Leadership Theory themselves, force the issue until leadership structures that cross levels-of-analysis emerge through the constructive actions of individuals (Goldstein et al., 2010). These leadership structures provide downward influence on individual interactions even as they are themselves the emergent outcome of those same interactions, in a dynamic process that complexity pioneer Haken (2006) calls circular causality. Certainly people “step up,” but they are not seen as providing leadership for others. Rather, they are seen as being drawn into the leadership process along with others. The system properties that begin to emerge are then sustained, evolved or replaced within the system of interaction, as leadership unfolds dynamically (Panzar, Hazy, McKelvey & Schwandt, 2007). One difference in this perspective stems from the fact that complexity science has found that the order we observe and are able to create in the world manifests itself simultaneously at multiple levels of scale. Not only do unique dynamics unfold within individual interactions, but also at the group level, the department level, the firm level and the institutional level. Each of these levels, provides feedback to all of the other levels, influencing the dynamics of the others. These changes in turn feed back once again to the other levels, and so on in an ongoing adaptive spiral. In short, feedback is all over the place and in all kinds of directions, making it exceedingly difficult to meaningfully control events or to cause specific outcomes in the traditional sense (Tobin, 2009). This would seem to account for the common practice in management to attempt to control events by containing the flow of information and thus limiting all diverging nonlinear effects that often accompany reinforcing feedback in complex systems. Because a lot is happening at once, this logic goes, if one doesn’t control events and information flows there can be unintended consequences, and it is better to stop them before they happen
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Complex Systems Leadership Theory rather than risk that they might challenge one’s assumptions about strategy and direction. CSLT suggests ways for thoughtfully relaxing control and letting constructive deviations build upon their successes, while identifying and dampening destructive deviations before they threaten to pull the organization apart. A note on terminology: To help clarify for the reader where we are focusing discussion in this paper, we will follow Gell-Mann (2002) and use the term “fine-grained” to refer to individuals interacting with one another, and “coarse-grained” to refer to the higher scale properties of organizations that are of interest to leadership researchers, such as profits, employee turnover, regulatory regimes, or even the leadership capability itself. In truth, however, the experience of leadership floats between the fine- and the coarse- grained levels, crossing scale and effectively becoming scale-free (Boisot & McKelvey, 2007). Organizational life thus challenges people to act both individually and collectively at the same time in the face of this complexity. We describe some of these challenges next. Stability and Attractors: Coarse-Grained Prediction with Fine-Grained Uncertainty One of the key insights from complexity science is that organizing, and thus leadership, drives change at the fine-grained level of individual human interaction. Leadership does this by changing the rules that govern the nature of connections and exchanges between individuals. From these fine-grained interactions, persistent patterns emerge as coarse-grained system properties that are sometimes quite stable at a higher level of scale. For example, warehouses and logistics processes that at one point emerged almost by chance may remain at the center of stable activities for months, years or even decades, attracting behaviors to them (Allen, 2001). Stable properties like these can be recognized and modeled as organizational capabilities (e.g., the logistics example we mentioned, but also accounting or customer service) (Dosi, Nelson, &
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Complex Systems Leadership Theory Winter, 2000; Helfat et al., 2007). To change these coarse-grained properties of organizations, however, one must first change the rules governing fine-grained interactions of the people who are implementing them. CSLT defines leadership in complex adaptive systems as the social process that changes the rules of interaction across levels of analysis, i.e., among individuals, work groups, departments, organizations, and institutions. The leadership meta-capability in particular, is defined as the routines, knowledge management, and decision making processes (Helfat et al., 2007) that serve the coarse-grained function of changing the rules of interaction inside the organization or the broader system (Hazy, 2004, 2006; Hazy, Goldstein & Lichtenstein, 2007b). Thus, coarse-grained properties are changed only indirectly: they change when the rules of interaction are changed at a finer-grained scale. This is an intuitive result: one must change the way that people do what they do in order to change the outcomes they produce. CSLT seeks to discover and specify the mechanisms, both direct and indirect, that enable this top-down/bottomup iterative process in real organizations, as well as how individuals learn to recognize and become proficient in enacting this capability. As alluded to above, stable coarse-grained properties are often associated with a dynamical attractor within the system of HID, like for example, the logistics capability described previously (Allen, 2001; Hazy & Ashley, 2011). This complexity term means that there is a subset of all possible coarse-grained states of the system such that the state is “sticky,” meaning that these attractor states effectively “pull” the system back to their original state if something disturbs its normal functioning. After a storm that destroys some logistics equipment, for example, activities are “automatically” enacted to return to the “normal” state. As an even more general example, firms that maintain their profitability can be stable for a time. When
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Complex Systems Leadership Theory profits are threatened, they take action to return to profitability. At the same time, firms that lose money will eventually implode or disband. They are not dynamically stable. Patterns of activity that enable stable profitable operations (i.e., “exploitation,” March 1991) form an attractor of coarse-grained properties. These in turn drive what is happening at the fine-grained interaction level. As individual behavior patterns and choices at the fine-grained level converge towards a pattern of interaction they reinforce the coarse-grained organizing form in what amounts to an iterative stabilizing feedback process that extends back and forth across levels of scale (Hazy & Ashley, 2011). Convergent interactions that enable stability and thus predictability are achieved through information feedback processes, wherein coarse-grained structure provides information to individual agents, and their actions in turn influence the specific characteristics of the coarse-grain structures in order maintain their relative stability (Hazy, 2011b). These feedback loops, both positive or reinforcing and negative or stabilizing, can shape the emergent, dynamically stable coarse-grained state of the system. In turn, coarse-grain stability can imply fine-grained choices and actions, such that their emergent outcomes become to some degree predictable in the aggregate even though any particular event remains difficult to predict, a circumstance that is called statistical complexity (Prokopenko, Boschetti, & Ryan, 2009). For example, one roughly knows what to expect when entering a retail store, a coarsegrained structure. At Wal-Mart, a greeter will greet you somewhere with high probability. At the same time, there is no way to predict exactly when or where such an event will occur. Thus, although there is a level of stability and predictability at the coarse-grained level, there is always unavoidable uncertainty at the fine-grained level. Individual interactions are neither random nor
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Complex Systems Leadership Theory completely predictable. They are constrained, but not determined, by attractors (Hazy & Ashley, 2011; Hazy, 2011b). Emergence: Fine-Grained Prediction with Coarse-Grained Uncertainty On the flip side of the comfortable stability and general predictability of familiar coarsegrained aspects of organizational life is the reality that things sometimes change. When this happens, old coarse-grained institutional structures must change as well. This implies a conundrum: If coarse-grained properties are recognizable patterns that emerge from within individual interactions, how does adaptive change actually happen at the coarse-grained level when human interaction is experienced and predicted at the fine-grained level? In evolutionary systems, this occurs through the process of variation, selection and retention among genetically related but distinct entities over many generations. In cognitively-enabled systems, this occurs through an intra-generational learning process whereby organisms learn to respond to stimuli in their environment in a single lifetime. CSLT offers a framework that describes how organizations both evolve through variation, selection and retention over many generations and also learn to adapt within a single organization in a given generation. How well organizations learn impacts their ability to survive and thus to contribute to the evolution of organizational forms (Hannan & Freeman, 1989). The process wherein organizing forms evolve and learn is the purview of a key area of complexity research: emergence. Much has been written about emergence as a general matter in complexity (Goldstein, 2007, 2010; Lichtenstein & McKelvey, 2007) as well as with regard to leadership (Plowman et al. 2007a,b; Lichtenstein & Plowman, 2009). The idea is that under certain exogenous constraints, a changing system of fine-grained interactions can cause the emergent coarse-grained properties that are observed to undergo a qualitative transformation in
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Complex Systems Leadership Theory their coarse-grained patterns and structure. Examples of this phenomenon that are taken from the natural sciences—such as the phase transition from liquid to gas—have provided metaphorical insights for leadership researchers. One important natural science example of emergence is the appearance of what are called dissipative structures (Prigogine, 1995; Prigogine & Stengers, 1984; MacIntosh & MacLean, 1999). An occurrence of this phenomenon is described in some detail by Goldstein et al. (2010) to illustrate how coarse-grained structures emerge in quasi-closed systems of fluids during what are called far-from-equilibrium conditions. In the case described, this type of emergence happens when heat is continually applied to the bottom of a closed container of liquid. As the intensity of heat crosses a certain critical threshold, internal fluctuations interact with one another in the presence of the exogenous force of gravity to cause an observable qualitative shift in the coarsegrained behavior of the system. The system’s dynamic behavior rather suddenly shifts from a relatively calm state where heat is transferred by the mechanism of conduction to an orderly state of circular flow that transfers heat through the mechanism of convection. As this occurs, the emergence of persistent, coarse-grained hexagonal convection cells can be observed. Prigogine (1995) calls these “dissipative structures” because convection dissipates heat more quickly than conduction does. The onset or settling down of this qualitative change in structure can be “toggled” by the experimenter by increasing or decreasing the heat applied to the bottom of the container. Thus, changing patterns in fine-grained interaction behavior among the molecules can be seen to relate to a qualitative change in the coarse-grained properties that emerge in the system, and these are themselves shaped by external constraints on the system, the shape of the container for example.
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Complex Systems Leadership Theory Another example of emergence relates to what Haken (2006) calls “order parameters” that emerge through a process of circular causality (Haken, 2006). Using the example of a laser, Haken shows how under the right conditions the light waves emitted by individual atoms eventually synchronize their phases as represented by an order parameter. This occurs as constructive interference reinforces a particular phase determined by interaction with external constraints while destructive interference dampens others that are not reinforced by the environment. This means than bottom up processes can lead to emerging order. And emergent order places downward pressure on bottom up events, “enslaving” them to be in phase with the order parameter, a process called “entrainment.” This is what is meant by circular causality. Related to the above, is the subset of systems whose order parameters characterize phase transitions. This well-studied phenomenon of circular causality in natural systems involves a change in physical state as energy that is being added to the system modifies the internal structure of the system to change how the system processes energy and information. Water freezing, iron becoming magnetized, and the onset of superconductivity are examples of this. Well-established mathematical models describe how external constrains—for example, ambient temperature and pressure in the case of water freezing—interact to influence the “order” that emerges within the system of interactions. The progress of these changing dynamics is described by mathematical models that relate an order parameter to the change in state (Goldstein et al., 2010). Common to these examples is the idea that the breakdown of order within extant coarsegrained properties is a prerequisite for emergence. This condition has been called the “edge of chaos” (Kauffman, 1995; Mitchell, Hraber, & Crutchfield, 1993), “far-from equilibrium” (Prigogine, 1995; Meyer, Gaba, & Colwell, 2005) and “criticality” (Bak & Paczuski,1995) in
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Complex Systems Leadership Theory varying complexity situations. To emphasize the dynamic nature of this condition and of its potential to enable a qualitative transition from one stability regime to another, we prefer the Goldstein et al. (2010) term for the onset of these conditions: criticalization. The term criticalization highlights the potential for change when a certain parameter crosses a critical threshold, what is called a bifurcation in mathematical modeling. In the case where complex systems of human interaction dynamics (HID) experience adaptive tension that pushes the system beyond a critical threshold, Uhl-Bien, Marion, and McKelvey (2007) describe the requisite complexity of the system as a prerequisite for the onset of emergence. The interaction between the complexity present in the environment and that which develops within the system has been codified by Boisot & McKelvey (2010) in what they call “Ashby Space,” to recognize Ashby’s law of requisite variety (1956). The challenge when going beyond complexity metaphors to develop a theory of emergence in human systems is to explicate the emergence phenomenon in the HID case while taking into account the differences inherent in human interactions when compared to physical systems. Prietula (2011) describes some of the practical differences in the context of agent-based modeling. Hazy and Ashley (2011) explore the implications of these differences when developing a theory of emergence in HID. According to these researchers, the difference boils down to this: In contrast to physical systems where many agents of a particular class (like water molecules) interact with one another in the same way, human interactions are heterogeneous, each being determined by individual preferences, personal histories, social connections and perceived difference in power and status, all of which are stored in the individuals’ memories. Prediction becomes problematic since these memories are largely hidden from the observer.
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Complex Systems Leadership Theory Further, human connections are interdependent rather than independent since individuals incorporate into their choices not only information from their direct experiences, but also information and knowledge that is received through communication with others. This interdependent heterogeneity implies that many of the statistical methods used in the natural sciences are not appropriate in the human case since traditional methods assume independence and consistency across time. In many cases, neither of these assumptions is valid with human beings (Hazy & Ashley, 2011). As a result, the development of a well-specified and robust model describing the mechanisms of emergence in HID remains an ongoing challenge for the field (Hazy, 2011b). Complexity: A Journey from Novelty to New Paradigm In the late 1980s and 1990s, complexity thinking for organizations had not yet come into sharp focus. Still the application of complexity was all the rage within the social sciences (Anderson, 1999; Cilliers, 1998; Dooley, 1997; Goldstein, 1989; Levinthal, 1997; McKelvey, 1997; Thietart & Forgues, 1995). Exotic concepts that were discovered in the natural sciences, like chaos, strange attractors and the possibilities implied by emergence - where entirely new order springs forth seemingly in whole cloth - led researchers to look for complexity applications in management and human organizations (Wheatley, 1999). Initial interpretations of complexity often led to an unfortunate tendency to recommend to practitioners a version of laissez-faire leadership - arguing that a hands-off style was all that was needed and that employees would simply “self-organize” to solve business problems. In contrast, Marion and Uhl-Bien (2001) saw the promise of complexity as beyond metaphoric and suggested specific areas for theoretical exploration and empirical research. This article follows in their direction and that of others (Schneider & Somers, 2006) and reviews what
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Complex Systems Leadership Theory has happened since these early days, and it explores what these activities might mean for the future of leadership research and practice. Ontological and epistemological issues Relevant to the complexity framing of business and organization has been the distinction between ontology and epistemology. The philosophic challenge is to determine the extent to which the complexity mindset is a reflection of what is real in the world (that is identifiable through observation - ontology) versus the extent to which complexity is just a new or different way of knowing or understanding what is happening or perceived to be happening in the world (Boisot & McKelvey, 2010). In this latter way of thinking, complexity is just an analytical “toolkit.” The distinction is not a trivial one. It exposes the question of how human beings deal with experienced complexity. As this paper explores, some interesting questions this implies include: Is the world a complex system? Is it essentially a computation that is unfolding (Dooley, 2007; Richardson, 2010)? If so, what are its algorithms? Are there better, more complex ways to model and predict the world? How does complexity science inform the study of cognitive neuroscience? What about the study and practice of psychology? And of course, what can it tell us about study of leaders and leadership? These concerns can be considered from various philosophical perspectives, for example, as constructionist, constructivist, objective realism, critical realism, etc. From the practical perspective of epistemology, the increased use of nonlinear techniques and probabilistic prediction models in management are aspects of the complexity revolution in the social sciences that have already established their value in practice. Monte Carlo analyses, information theoretic approaches, game theory modeling, and system dynamics approaches are
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Complex Systems Leadership Theory all now in the mainstream decision support tool-kit in business. All of these are complexityinformed tools that support managers in their decision-making. The adoption of these tools, presumably because of their usefulness, supports the notion that ontologically, human organizations appear to act like complex systems. What is missing is a holistic modeling approach - something analogous to a statistical mechanics of human interaction dynamics (HID) - that would represent and study organizations using complexity theories framed in a useful epistemology. Such an approach would be invaluable to practice as it would allow managers to forgo their need to apply controls, which can dampen both learning and growth in the service of a perceived sense of stability and predictability, a practice that can be counterproductive. One additional point is relevant here. There are particular ontological implications of the complexity notion of emergence. Does an organization exist ontologically, in other words, does it have agency? There is an argument that insect colonies do in fact exhibit ontological agency. Tens of thousands of honeybees swarm as a collective to find a new nest without central control. Choosing a proper nest is critical for survival of the swarm, and thus for evolutionary adaptation. This is also true for the individual bees, all of which carry the DNA of the queen (Seeley, 2010). Can the same argument be made for a firm or a nation? Does the diversity of DNA in human organizations make the super-organism argument untenable (Nowak, Tarnita, & Wilson, 2010)? This is a fundamental question for leadership researchers. Stated differently, is anthropomorphizing the organization wrongheaded, or forward thinking? Do individuals actually “lead” organizations, or is something else going on, something akin to the emergence of collective agency?
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Complex Systems Leadership Theory COMPLEXITY APPROACHES TO LEADERSHIP RESEARCH With the above background, we now turn to the various applications of complexity to leadership. Although there are copious studies that apply conceptual ideas to leadership metaphorically, such as the idea of fractals (Levick & Kuhn, 2007), the onset of chaos (Brown & Eisenhardt, 1998), emergence and attractors (Shoup & Studer, 2010), and sensitivity to initial conditions (Peterson & Meckler, 2001), others have cautioned against such metaphorical applications (Simpson, 2007; Goldstein et al., 2010). Moving beyond metaphor, we focus only on the approaches that uniquely assume a complexity ontology or that apply one of the complexity inspired epistemologies: agent-based modeling (ABM), dynamic network analysis, nonlinear dynamical systems (NDS) modeling, or information theoretic framings such as game theory, and non-Gaussian statistical methods. (For a description of these methods see, for example, Hazy, Millhiser & Solow, 2007, Boisot & McKelvey, 2007, and Guastello, 2002). Because we are for the most part assuming a complex systems perspectivei, presumably the studies of emergent properties within HID would unfold in a manner analogous to dynamical systems models of weather patterns, ecological models or epidemiology studies, or in the way that agent-based models represent conditions of criticalization or uncertainty that signal an impending phase transition, for example when a system changes its properties qualitatively—as when water freezes into ice. As Goldstein et al. (2010) point out, in human systems, situations of “criticalization” occur when conditions in the environment combine with the state of the organization to create uncertainty and unpredictability about where things are going. Researchers studying knowledge generation in organizations describe the unfolding of plans and strategies during everyday practice (Tsoukas, 2005). Often different individuals are observed espousing multiple different
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Complex Systems Leadership Theory plausible futures, and individuals are left to decide which approach is likely to “win” in the end (Hazy & Ashley, 2011). Other authors have referred to conditions like this as “disequilibrium” (Lichtenstein & Plowman, 2009) and identified these conditions as a prerequisite for emergence. Given how little is known about the relationship between fine-grained interactions and the emergence of coarse-grained properties (Hazy, 2011b), we first explore how leadership can be relevant at the coarse-grained level. We begin with an overarching model as context for the other approaches we will describe. The Leadership and Capabilities Model (LCM) Although many articles begin with a statement that the authors are assuming organizations are complex adaptive systems (Boal & Schultz, 2007; Brown & Eisenhardt, 1997; Levinthal, 1997), their use of complexity is usually limited to the assumption that semiautonomous agents interact, and that organizations somehow emerge from this process. Little has been written about the course-grained properties that emerge, how they emerge, and what leadership has to do with this. The Leadership and Capabilities Model (LCM) developed by Hazy (2006; 2011a) addresses this gap by explicitly describing human organizing as a complex adaptive system of interactions that performs certain functions. To address the cross-level definitional issue with regards to the term “leadership,” Hazy (2006, 2011a) builds upon Katz and Kahn (1966) to define “complex systems leadership” to be a special kind of organizational capability (Dosi et al., 2000; Helfat, et al. 2007) that performs particular system functions wherein the human organization is formed and evolved as a complex adaptive system. In particular, complex systems leadership is the organizational capability that iterates changes to the system’s configuration (by changing local rules of interaction) to test its performance in the environment. As such, complex systems leadership is not what individuals
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Complex Systems Leadership Theory do; it represents an organizational capability in the sense described in business strategy (Helfat et al., 2007): it is a set of routines, knowledge management, and decision making processes that perform leadership functions in the same way that marketing and accounting are capabilities that perform more instrumental system functions. All of these capabilities, including leadership, are enacted by individuals and collectives in furtherance of functional requirements as the system gathers and processes information, resources and energy to create order. Because complex systems leadership reconfigures other capabilities, Hazy (2006) calls it a meta-capability. Organizations with well-developed complex systems leadership meta-capabilities are able to iteratively act on the system itself, changing the rules governing fine-grained interactions within the system in response to success or failure (Hazy et al., 2007; Hazy 2011b). The coarsegrained properties that emerge enable subsequent success of the system in changing and adapting as the situation develops. The complex systems leadership meta-capability guides this process. The idea of complex systems leadership as a meta-capability extends the work on organizational capabilities, both dynamic and operational (Barney, 1991; Helfat et al., 2007; Nelson & Winters, 1982; Teece, Pisano, & Shuen, 1997). However, in contrast to the capabilities literature, individuals in the organization aren’t actualizing these capabilities; rather they are enacting the leadership meta-capability of the organization that is acting on the system to test configurations of other capabilities, and to identify those that work better than others. Using the complex systems agent-based epistemology of system dynamics, Hazy (2004, 2006) built a system dynamics model of the leadership meta-capability that is called the leadership and capabilities model (LCM). When the model is run, the leadership meta-capability performs an iterated operation on the coarse-grained properties within the system that: i) implements the exploitation (March 1991) of current capabilities, ii) promotes the exploration
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Complex Systems Leadership Theory and generative process of new capability creation (March, 1991), and iii) unifies the system to maintain it as an entity with regard to local and global criticalization conditions as required by the environment. It changes the properties or capabilities that have previously emerged, and presumably it does this by changing local rules of interaction among individuals. By changing the rules, the properties characterizing the system, including its capabilities, also change. Depending upon the context, the complex systems leadership operation acts on the system to perform three functions: The convergent operation within the system adjusts the properties of the system to make them more predictable (Hazy & Ashley, 2011) and thus improve exploitation. Rules are changed to dampen deviations by increasing individual productivity and leveraging cooperative activities with technology and other assets. This is called the exploitation value-gathering loop (Hazy, 2011a). The generative operation responds to changing constraints in the environment and promotes exploration, collaboration, creativity and innovation in system properties (Hazy, 2004, 2006; Surie & Hazy, 2006; Uhl-Bien et al., 2007). If changing constraints on the system implies that a qualitative change in coarse-grained properties is needed, the system often passes through a period of criticalization as requisite complexity is engendered. For this to occur, fine-grained rules of interaction are changed to promote experimentation and to reduce or eliminate premature convergence. Because a variety of possible futures coexist, this is a manifestation of Ashby’s (1956) notion of requisite variety. The exploration value-identifying loop enables adaptation (Hazy, 2011a). The unifying operation uses communication and symbolic activities, such as policies and boundary rules for the proprietary use of information, to more clearly specify acceptable and expected rules for system properties by promoting locally stable collective identities and systems
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Complex Systems Leadership Theory of ethics (Hazy, in press-a). This tunes the level of criticalization and requisite complexity (UhlBien & Marion, 2009) both locally and globally within and across the organization. One implication of the LCM is that, as is the case for other organizational capabilities, individuals learn to implement aspects of the leadership meta-capability in the same way they learn to implement manufacturing, customer service, business planning, or any other capability (Hazy, 2007a, 2008b). The acquisition of leadership skills by individuals is the result of social learning of the meta-capability within organizations, just as the acquisition of marketing skills results from social learning in marketing organizations. Individuals are not born to leadership competency; they learn how to exercise this capability by being involved in organizing efforts that exhibit the coarse-grained property of an effective leadership meta-capability. Leadership and Emergence Given how little is known at present about the emergence of coarse-grained properties in the unique manifestation of the distinctly human social context, it is at present difficult to offer specific suggestions about how any given individual should behave. The process of emergence has been explored, however. Lichtenstein and Plowman (2009) draw on case studies of emergent leadership in organizational settings, the case of a mission church (Plowman et al., 2007 a, b) for example, to argue that there are four phases in the emergence process. First there must be disequilibrium, unstable conditions that were described in the earlier section as criticalization. During these periods of uncertainty, reinforcing feedback is offered to certain process fluctuations through amplifying actions that seem to offer promising new ways to bring back stability. Hazy (2011a) calls these experiments in novelty “constructive deviations” because they deviate from what had previously been the norm, but they do so intentionally and constructivelyii The constructive deviations that are working are then combined with other
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Complex Systems Leadership Theory fragments of collective activities that are at work in other parts of the organization in a recombination process. In this way, new structures grow through the gradual accretion of constructive deviations that work. Eventually, stabilizing feedback that operates on this new way of doing things—for example, lack of funds or time limitations, or a saturated market—bring the organization back into a stable, albeit qualitatively different, approach to organizing. In the end, one can observe that distinctly new properties (at the coarse-grained level) have emerged. As further support for this classification, Beck & Chong (2009) identified these stages in social entrepreneurship ventures they studied in Indonesia. Aspects of these phases were also apparent to Butterfield, Shepherd and Woods (2011) in a social enterprise that was studied in New Zealand, and Baker, Onyx and Edwards (2011) found evidence of recombination of network components in a developing community of social enterprises in Australia. The next stage of CSLT research in this area is to uncover the specific mechanisms at work in each of these stages, that is, the mechanisms of emergence at work in HID (Hazy, 2011b). A series of research projects in Sweden have provided some hints about these mechanisms. These studies explored how first-line managers provide the pre-conditions to influence both the interactions between individuals and the collective organizing which emerges from them (Backström, 2009; Backström, Hagström, & Göransson, 2011; Backström, Wilhelmson, Olsson, Åteg, & Åberg, 2011). Backström and his colleagues refer to this aspect of management as the “directing task” which focuses on enabling a dynamical balance between the autonomy of individuals and their integration into the emerging organizing structures. The communicative competence of the employees and the reasons, places and times for them to meet and to communicate were found to be important conditions for the emergence of structures like
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Complex Systems Leadership Theory collective culture and identity, institutionalized collective behavior, and patterns of work relations (Backström, Wilhelmson et al., 2011). As the above discussion highlights, at present it may be theoretical overreach to posit that any one person is in control of the emergence process whereby the coarse-grained patterns that characterize organizational capabilities come into being, at least as regards what is currently known about complexity (Hazy, 2008b). The assertion that complexity implies a good deal of ambiguity when linking fine-grained action to coarse-grained properties has found support in the literature (Siggelkow & Rivkin, 2005). Morrison (2010) showed how the process of gathering information, analyzing it, recommending approaches, and implementing projects can be a very challenging undertaking for managers. When this occurs within a network of positive and negative feedback loops, as is often the case, the challenge is even more daunting. There is a point where predicting the resulting outcomes in the face of this nonlinearity is problematic (Siggelkow & Rivkin, 2005; Morrison, 2010). Interdependent, heterogeneous connections between individuals as they interact seem to make each case unique. This is not to say these dynamics are not understandable in a general way, only that they are not yet understood. We next describe work that focuses on discovering additional coarse-grained and fine-grained leadership activities needed in organizations when they are considered to be complex adaptive systems. Complexity Leadership Theory An approach that is compatible with, but varies somewhat, from the LCM model just described is Complexity Leadership Theory (CLT) (Uhl-Bien et al., 2007; Uhl-Bien & Marion, 2009, 2010). Complexity leadership theory draws from concepts of complex adaptive systems (CAS) to offer an organizational theory (OT) framework of leadership.
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Complex Systems Leadership Theory Consistent with OT (Barnard, 1938; March, 1991; Selznick, 1948), complexity leadership theory identifies two primary functions in organizations: an administrative function and an adaptive function. The administrative function is associated with the bureaucratic structures of the organization, and focuses on productivity and efficiency through choice, execution and variance reduction to enhance efficiency and effectiveness (i.e., “exploitation,” March, 1991). The adaptive function is associated with CAS structures and dynamics in organization, and engages individuals and organizations in search, experimentation, and variation to enhance creativity and learning (i.e., “exploration,” March, 1991). CLT also identifies leadership forms associated with these functions. Administrative leadership manages in the formal systems and structures (i.e., the administrative function) to produce results through alignment (e.g., standardization) and control (e.g., visioning, motivating, inspiring, directing, controlling). Adaptive leadership is a distributed form of leadership generated in the informal structures and systems of the organization (i.e., the adaptive function). It is associated with the bottom-up emergent dynamics within organizations. Adaptive leadership is defined as a dynamic, interactive influence process among individuals and collectives for which the objective is to lead one another to adaptability, innovation and learning (Uhl-Bien & Marion, 2009; 2011). Recognizing that the administrative and adaptive functions often operate in tension with one another (Boisot & McKelvey, 2010; Heifetz & Laurie, 2001), and that organizations operate in states of dynamic equilibrium (Boisot & Child, 1999; Davis, Eisenhardt & Bingham, 2009; Galunic & Eisenhardt, 2001; Meyer, Gaba & Colwell, 2005; Stacey, 1995), CLT adds a third leadership function called complexity leadership. Complexity leadership (formerly referred to as enabling leadership) works to achieve requisite complexity through a dynamic combination of
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Complex Systems Leadership Theory loosening-tightening the administrative function and enabling-inhibiting the adaptive function (Havermans, Den Hartog, Keegan, & Uhl-Bien, 2010; cf. McKelvey’s 2010 discussion of complexity leadership action disciplines). Complexity leadership differs from administrative leadership in that administrative leadership is only able to affect the former (loosening-tightening the administrative function)—it is not associated with the adaptive function. It is because of this that current frameworks of leadership often fall short for practitioners in complex environments (IBM CEO Report, 2010). Traditional leadership theories are grounded in assumptions of hierarchy and authority (i.e., the administrative function) that do not recognize complexity dynamics or adaptive leadership associated with the adaptive function. Therefore they are inadequate with respect to how to engage the adaptive function, manage in and for emergence, or enable the requisite complexity required for firm fitness and adaptability (Uhl-Bien & Marion, 2008). In including both organizational-level (administrative) and micro-level (adaptive) leadership behaviors, CLT addresses both coarse-grained and fine-grained leadership activities. Coarse-grained leadership is considered in the administrative function and administrative leadership roles that occur in organizational structures and systems. Fine-grained is considered in the adaptive function and adaptive leadership roles and dynamics that are associated with leadership and emergence. Complexity leadership helps enable transition between fine-grained and coarse-grained by both operating in the interface between the adaptive and administrative functions (Uhl-Bien et al., 2007; Uhl-Bien & Marion, 2009). Leadership and the Implementation of Strategy: The Unifying Process One of the anomalies that confronts organization and leadership researchers is the perception that individuals, and in particular executive managers, are in charge of
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Complex Systems Leadership Theory organizations—they set the directions, they make things happen. As we can see from the above discussion, this does not square with a complex system viewpoint that organizing patterns emerge through interactions. One point of synthesis, however, is the realization that there are variations in the roles and the impact that individuals have in the system—i.e., the influence of all individuals is not equal. Status and reputation differences have significant impacts on outcomes (Axelrod, 1984; Simon, 1997). For example, executives typically set the strategy and direction for the organization; they define the organizations boundaries, its identity, and its ethics, and they hold it together (Hazy, in press-a). In short, they drive the unifying process at the highest relevant level of coarse-graining. Thus, contrary to the complex adaptive systems most often studied in the natural sciences, it does appear that in the case of human interactions, through intentional action that recognizes and seeks to exploit emergent patterns, individual agents can make a difference even in properties that are coarse-grained. Strategy, “Tags,” and the Unifying Process For example, Boal and Shultz (2007) focus on the strategic aspects of leadership at the top of the organization. Amid their discussion about how communication strategies and story-telling are core to business strategy-making, they assert that individuals performing leadership functions use the complexity idea of “tags,” as defined by Holland (1975), to compartmentalize large organizations into differentiated sub-structures. They argue that this process is useful because, as Holland shows, the use of tags in interactions enables individuals who share the same assumptions and aspirations to identify one another. Tags thus promote higher levels of quality interaction within same-tagged identity groups. The use of tags also results in lower levels of interaction across groups with different tags, which can make communication more efficient.
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Complex Systems Leadership Theory In a more general sense, the implications of Boal and Schultz (2007) suggest that tags are useful in furthering the unifying process identified by Hazy (2011a). Tags can be thought of as a unifying mechanism which clarifies and helps resolve identity tensions locally and globally, and tunes criticalization conditions locally in the face of further tension between adaptive versus performance concerns. In complexity leadership theory terms (Uhl-Bien et al., 2007), administrative leadership exploits innovations generated by their adaptive leadership to benefit the firm, which also seems to be relevant to the strategic unifying process Boal and Schultz describe. Perhaps, the use of tags is a mechanism of administrative leadership that serves to further the unifying process within the organization. Unifying leadership across scale One might note, however, that the unifying process requires that these activities occur across the organization and are not limited to the actions of top management. They occur at all levels of the organization. To further explore the mechanisms of individual influence within HID, particularly when organizing large-scale efforts, Hunt, Osborn and Boal (2009) describe the application of complexity to what they call Level VI leadership (Jaques, 1989), the level below strategic leadership. For Jaques, Level VI implies individual cognitive capacity that enables a task horizon and job focus of three to five years for mid-career executives. Citing the Siggelkow and Rivkin (2005) results, Hazy (2007b) argues that at the senior management level, successful leadership is more about picking strong subordinates and advising and supporting them with resources than it is about choosing actual projects. The process whereby these decisions are taken has recently been explored by Anneloes et al. (2011) in the context of the nature and quality of the interactions between top managers and their middle management subordinates who are responsible for directly delivering operating results. At this
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Complex Systems Leadership Theory level, it may be more appropriate to worry about picking the right individuals, i.e., the right champions, who have proven they can pick and drive winners, than to try to identify winning projects oneself. Extending this line of thinking, Hazy (in press-b) argues that when reputation and status accrue to individuals who are successful, and when these changes are publicized to the organization’s members, the organization gets smarter as a system. In his model, relative status and reputation determine relative influence among individuals in a manner analogous to the synaptic weights connecting neurons in the brain. These weightings determine which neurons are activated in response to stimuli in the environment. Similarly, relative status and reputations play a role in determining who is involved and to what degree when an organization is forming a response to events in the environment. In this way, the organization “learns” in a manner analogous to the learning algorithm in the brain’s neural network. As an example, a successful merchant bank in Sweden, with a record of success even during the financial crises, illustrates a complexity-aware structure of this type. Each department operates as its own company, and each employee has full responsibility for a group of customers. The company’s culture unifies these activities as a major mechanism for integrating different groups into the company. Activities such as appointing managers with values that closely match those of the company, and ensuring high quality communication among individuals were shown to be central for integration into a unified firm with a common identity (Backström, Hagström et al., 2011). The bank uses a very simple feedback process at the departmental level and uses this to clarify the relative success, and thus the relative status and reputations of departments (and thus of individuals), by publishing a monthly ranking of all departments.
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Complex Systems Leadership Theory Based upon these complexity ideas, Hazy (in press-b) argues that one of the most important aspects of effective management is to focus on structuring projects so as to receive clear and unbiased feedback about success or failure and to act on the feedback by adjusting the status and reputations of those involved. Thus, an important imperative of leadership is to hold people to account. This would be an element of administrative leadership (Uhl-Bien et al., 2007). We turn next to the question of what it might take for an individual, a “leader,” to differentiate his or her actions in order to successfully engage a system that has complex characteristics. The Individual in Complex Organizing Core to the challenge of developing complex systems leadership theory is the unique role played by individual human beings, particularly high status ones, or powerful ones, in complex organizations (Denis, Langley & Pineault, 2000). Does complexity suggest what it takes to be a successful individual “leader” in this context? Building on the work of Zaccaro (1999) and Hooijberg (1996) this challenge has been taken up by Hannah, Lord, Jennings and others (Hannah, Jennings & Nobel, 2010; Hannah, Woolfolk & Lord, 2009; Hannah, Eggers and Jennings, 2008; Lord, Hannah, & Jennings, 2011) to explore the mental characteristics that support success, as well as the potential for bias, for example, gender bias (Hogue & Lord, 2007). These issues become important to researchers for a number of reasons, one being their implications to leadership development programs (Boyatzis, 2008). As described earlier, Uhl-Bien et al. (2007) extend Ashby’s (1956) idea of requisite variety, which says that in a cybernetic system the regulator must be at least as complex as the environment it hopes to regulate, to argue that organizations must likewise match the complexity of the environment, a condition called requisite complexity (Boisot & McKelvey, 2010). In
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Complex Systems Leadership Theory particular, they argue that complexity leaders must structure the organization to enable requisite complexity. To further define this concept, Hannah, Lord, Jennings and others (Hannah et al., 2010; Hannah et al., 2009; Hannah et al., 2008) have worked to define the characteristics of individuals that enable requisite complexity in action. Most recently, Lord, Hannah, and Jennings (2011) identified two dimensions of complexity, static and dynamic, the latter taking into account the unfolding of complex conditions over time. By analogy, they extend the idea of requisite complexity to groups (Lord, Hannah & Pearce, 2011). The processes of creativity and innovation they describe require different skills, and support the system’s functional demand that new information be gathered and synthesized in an ongoing generative process. Innovation and Adaptation: The Generative Process To sustain itself as an open system (von Bertalanffy, 1950), a complex system needs continuing access to resources within its ecosystem (Hazy, Moskalev & Torras, 2009, 2010). Since opportunities in an ecosystem ebb and flow, a complex system needs mechanisms to explore the environment, identify resource-gathering opportunities and construct structures within the system to begin to exploit these resources (Garud, Gehman, Kumaraswamy, 2011; Garud, Kumaraswamy, & Sambamurthy, 2006). In short, the organization must balance exploration and exploitation (March, 1991). Since ecologies change, this is not a once-and-done process. This is why Hazy (2011a) calls the value-identifying loop a requisite function for complex systems of human interaction dynamics (HID). This system requirement places a functional demand upon the leadership meta-capability: to establish, evolve and regulate this generative operation for the system by changing the interaction rules among individuals. Garud et al. (2011) describe the generative environment at 3M as what they call “complexity arrangements”:
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Complex Systems Leadership Theory We conceptualize the different combinations of practices – manifest structure (e.g., products, patents and platforms), relational processes (e.g., interactions between people within and across platforms and businesses), temporal dynamics (e.g., moments of serendipity enabled by the 15% option) and regulative guidelines (e.g., 30% stretch objective) – that are activated at various stages of an innovation journey at 3M as representing complexity arrangements (p.347). These “complexity arrangements” enable a process of invention, but also innovation, and they are enacted at the individual interaction level. CSLT explores the mechanisms that evolve the rules that govern local interactions to enable the generative process of innovation and adaptation. Divergence through discovery A literal example of this might be the value-identifying loop associated with an as yet undiscovered oil field in the Gulf of Mexico. Resources are allocated to exploration (March 1991), albeit with no a priori knowledge of the likelihood that a new field will be discovered at any particular place. Once indications of potential are identified and the probability of success increases (after a geological study, for example), locally specific capabilities must be constructed to explore this possibility further. With additional positive indications, more resources are allocated to take advantage of this potential, and so on, as long as the opportunity remains viable (meaning the probability of success relative to risk remains high). Complex system leadership evolves local rules of interaction to enact this process. As experiments to acquire resources produce information, feedback (under promising conditions) leads to significant expected value with regards the resources that could be discovered. This positive feedback loop is generative of possible future ecological niches for the system. However, if risks and rewards are not properly recognized and modeled, this feedback doesn’t
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Complex Systems Leadership Theory have to be beneficial for the organization. The unfolding impact of the BP Gulf Oil Spill in 2010 is a value-destroying example of the same positive feedback affect. Thus proper assessment of information about risks and benefits is an important aspect of the interaction rules that are evolved by complex systems leadership. Events caught up in positive feedback loops can build upon themselves rapidly and their effects can come to dominate the HID within an organization, as happened at Intel after the discovery of the microprocessor (Hazy 2008a). Diverging value-identifying loops that build upon themselves exhibit divergence through discovery because information about the opportunity grows rapidly after discovery, often feeding upon itself. This information helps individuals to organize the system to deal with rapid growth and expansion. In the above example, this means that the petroleum industry ecosystem began as a dynamically stable system exploiting known resources. Initially the system had no information about this particular oil field (or about the implications of the Deep Water Horizon’s blowout in the negative case). Upon discovery, and assuming continued investment of resources, change unfolds. For example, researchers (Aasen & Berg, 2008; Aasen & Johannessen, 2007; Johannessen & Aasen, 2007) used the complex responsive processes framework to explore the innovation process at a subsea oil recovery case at Statoil ASA a Norwegian oil company. They observed that “innovation emerges from the experiences of everyday social interaction, where patterns gradually perceived as meaningful are created and adopted” (p. 44). Using systems dynamic modeling, the divergence of discovery as a complexity phenomenon was shown to describe organizational transformations at NCR (Hazy, 2006) and the rise of the microprocessor at Intel (Hazy, 2008a). It was also described in for a technology company (Hazy, 2008c), and in a case study reported by Surie and Hazy (2006). In the latter
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Complex Systems Leadership Theory case, an Indian manufacturing company was working with foreign partners who were seeking to access production capacity to outsource their manufacturing. During the negotiation process, the Indian company discovered and exploited entirely new global markets for its products. New information about global markets gradually changed the Indian firm’s perception of their potential customer sets. Their visible world diverged from a narrow, traditional, domestic-only market, into the wider visibility of a truly world market. Ecology of Innovation What these examples have in common, according to Goldstein et al. (2010), is that they occur in organizations wherein complex systems leadership has managed to position the organization within an “ecology of innovation.” This means that the firm is well situated within its network of suppliers, customers and partnerships and maintains excellent communication across its connections so as to engender knowledge generation, discovery and thus a level of divergence as new opportunities are discovered. Their point is that leadership occurs at the nexus of interactions, where generative human dynamics lead to creativity and innovation (Andriani, 2011; Beck & Chong, 2009; Garud et al. 2011; Garud et al. 2006; Tapsell & Woods, 2009). The key to this is in the quality of interactions, what Goldstein et al. (2010) call interaction resonance, and what Garud et al. (2011) call relational processes. In the Complex Responsive Processes (CRP) perspective, Stacey (1993, 1995) argues that certain conditions are necessary for impactful interactions. These include: trust, the holding of anxiety, power relationships that are both cooperative and competitive, and conversational practices that don’t block explorations (Simpson, 2007, p.475). These interaction-level tensions must be navigated to achieve a high level of interaction resonance. This in turn implies certain leadership activities that are necessary for adaptation (cf. adaptive leadership in complexity
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Complex Systems Leadership Theory leadership theory, Uhl-Bien et al. 2007; Uhl-Bien & Marion, 2009). Complex systems leadership evolves rules of interaction to enable interaction resonance. Goldstein et al. (2010) go on to argue that conditions of highly resonant interactions, bounded in the right way, can lead the system to criticalization in the complexity sense, where the system is poised for a phase transition between two possible dynamic states: one less ordered and thus more symmetric, and one more ordered or organized into specialties and thus less symmetric. The transition from one state to the other can be modeled mathematically if an order parameter can be identified to describe the change (Haken, 2006). Identifying the order parameter for phase transitions in HID remains an open unanswered question in CSLT. More specifically, on one side of the phase transition, the more ordered case, individuals are oriented in certain roles and tasks, and are thus less interchangeable with others. Some are marketers doing marketing things and are only interchangeable with other marketers; some are accountants doing accounting things and can only be replaced by accountants, and so forth. Because fine-grained elements of the system can be differentiated, there is ordering in the system and thus there are fewer ways the system is self-similar. It is thus less symmetric. On the other side of the phase transition, everyone does everything and thus, in a certain sense, everyone is interchangeable with everyone else (ignoring for a moment individual heterogeneity). Such a disordered system is thus more symmetric. This is why qualitative change from one state to the other, called a “phase transition,” represents a discontinuous change in the in the level of order in the system and this change is often referred to as “symmetry breaking” (Haken, 2006; Guastello, 2002). Ecologies of innovation enable symmetry-breaking qualitative change. Generative rules of interaction at the fine-grained level are an enabling prerequisite to innovation reordering of this type (Hazy, 2009).
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Complex Systems Leadership Theory Performance and Efficiency In addition to unifying HID into complex adaptive systems, and the exploration and the generative activities that enable organizing in response to opportunities, the system must also converge to stable operations that effectively and efficiently exploit the resources to which it has access. Thus convergence is the third functional demand placed on the leadership metacapability as the complex adaptive system (as enacted by its agents) seeks to acquire its requisite resources and to conserve the resources it has accumulated as slack (Cyert & March, 1963). Convergence for preservation This functional demand is needed to encourage efficiency and to preserve slack resources (Cyert & March, 1963). In the process, however, potentially productive activities and information about alternative approaches and opportunities are lost (Haken, 2006). The human relations or “consideration” aspects of the process of convergence that brings people on-board, and the “initiating structure” elements that enable action-in-concert have long been associated with leadership (Fleishman, 1953; Stogdill, 1974). Individuals who exhibited either or both of these behaviors are called “leaders” by others even though leadership is actually emerging from within the interactions. The tendency to attribute leadership to individuals is a strong one that has also been observed in the complex system leadership context (MacGillivray, 2010). Complexity ideas and methods have added a perspective on the “how” behind the “what” of these behaviors. Consideration and initiating structure by individual actions enable convergence of a disparate group toward a single, common objective. Convergence of action satisfies a functional demand of the complex system on the leadership meta-capability as defined by Hazy (2011a). More specifically, Phelps and Hubler (2007) showed how groups could set and choose direction when a single individual was sufficiently motivated to move in a particular
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Complex Systems Leadership Theory direction, essentially shutting out and forgoing other possibilities, including preferences of others. In several experimental settings, the role of individuals in catalyzing convergence toward a particular outcome has also been shown to follow distinctively nonlinear patterns of behavior by Guastello and his colleagues (Guastello, 2002; Guastello, 2007; Guastello & Bond, 2004, 2007a; 2007b; Guastello, Craven, Zygowicz, & Bock, 2005; Guastello & Guastello, 1998). Complexity researchers have also studied the impact of leadership on group member selfselection across groups. Dal Forno and Merlone (2007) demonstrated both experimentally and computationally that the complex dynamics associated with the distribution of rewards and punishment by individuals on teams had a significant effect on which teams individuals chose to join, and this in turn impacted the projects that were ultimately completed. Information flow is a critical enabler of project selection and execution. Schreiber and Carley (2006) used data from field observations and dynamic network analysis to study how the flow of information within teams impacted performance. They found that multiple network hubs in the flow of information, rather than a single one, that is, a single “leader,” led to better performance when complex functioning was required. Similarly, Solow and Leenawong (2003) used Kauffman’s (1995) NK model to show that too much complexity within teams can lead to situations of overload that greatly reduced performance. Insight on the efficacy of a centralized control model versus more distributed decision-making was also shown using complexity modeling (Solow & Szmerekovsky, 2006). Hazy (2007a; 2008b) summarized many of these studies into the theory of complex systems leadership. Synthesizing the studies above as well as others completed at the time, he observed that five distinct aspects of convergent leadership had been identified in these complexity inspired studies. These five mechanisms comprise the leadership response to the
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Complex Systems Leadership Theory requisite system demand for collective convergence within HID toward action in concert. These distinct mechanisms include actions or communications by individual agents which: 1. Espouse an approach or cooperation strategy for working towards a common objective, a “program of action,” such that choosing to participate in the program is an attractor for the individual choices of two or more agents (Phelps & Hubler, 2007). 2. Catalyze social influence conditions such that at least one other agent chooses to participate in the program being espoused rather than continuing to act for its own account or according to an alternative program (Phelps & Hubler, 2007). 3. Catalyze choices and action in other agents intended to navigate complexity and overcome the limits to cognitive capacity in an effort to avoid an interaction catastrophe. This is when there is too much interaction and confusion causing performance to drop precipitously (Solow & Leenawong, 2003) 4. Form a distinct output layer (the Executive Office) that expresses learning and action for the system as a unity in the environment; to do so, the agents disambiguate learning and enable the unambiguous expression of action by the system in the environment (Hazy, 2007b). 5. Process feedback information regarding success or failure of enactments in the environment or internal to the system, and translate this information into structural changes in the influence network among agents. This is done by changing the reputation and status of participating individuals and thus changing their relative influence (Hazy, 2007b). Hazy argues that all of these aspects of leadership are facilitated either directly or indirectly by changing the rules of interaction. A theoretical framework for how these leadership mechanisms are actualized within a group of individuals in an organizational setting is discussed next. Microenactments within a CAS By analogy with insect swarming behavior, an emergent process that has been studied intensely (Seeley, 2010), Hazy and Silberstang (2009a) suggest that individual interaction events in groups likewise can be understood as signaling behavior among individuals that culminates in a specific collective action - programs of action (PoAs) - independent of the specific content of the action being considered. Whereas bees swarm in search of a new nest (Seeley, 2010), humans “swarm” in an effort to act in concert with regards to any particular project being considered.
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Complex Systems Leadership Theory Examples of PoAs around which people might “swarm” include the decision to disband a meeting or any social gathering, to initiate a project, or just to meet again the following week. Or they might involve taking a single step in a larger program: to launch as new product development effort, for example. When the relative status and thus influence of the various individuals involved is taken into account the authors posit that this dance of interaction is actually how decisions are taken when the authority to make a decision is “in the room.” To explore this proposition, the authors go on to describe individual signaling behaviors, called “microenactments” (Hazy & Silberstang, 2009a, 2009b; Silberstang & Hazy, 2008). These include signals that initiate a PoA, reject it, accept/imitate it, negotiate to modify it, or synthesize it with others to form a qualitatively new project. Together these microenactments constitute a language of interaction that can enable action in concert. For efficiency, this language unfolds as separate enactments made by individuals, but they are experienced by others in the context of a shared grammar that enables action-in-concert. Aspects of the grammar might include such rules as when and how to propose new ideas (Beck & Chong, 2009), what constitutes a quorum that enables decisions that are binding on the group (Phelps & Hubler, 2006), and when to accept the decision of a quorum (Guastello, 2007; Goldstein et al., 2010). Detailed research on the precise nature of the microenactments that individuals display as well as the grammars that enable shared meaning within this communication system might lead to a deeper understanding of human collective behavior. Although the palette might be distinct for each class of problem, there may also be commonalities, and these might shine additional light on the precise nature of leadership in daily practice. In the spirit of the interdisciplinary nature of complexity thinking, this same problem has also been addressed using an agent-based modeling framework by Panzar, Hazy, McKelvey and Schwandt (2007).
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Complex Systems Leadership Theory Developing fields, like the leadership-as-practice research where the focus is on the dynamic activities of leadership rather than heroic individuals (Raelin, 2011), are linked to the complexity way of thinking. Here we see mutual influence among individuals with common objectives forming into collective action. Research into the precise nature of this process for different classes of problems might lead to a deeper understanding of human collective behavior. Independently, Mangiofico and Feyerherm (2011) have qualitatively identified many of the activities described by Hazy and Silberstang in a non-profit organization. Likewise, research in Shared Leadership can be viewed in this way (Lord et al., 2011). A Contrarian Challenge to Systems Thinking - Complex Responsive Processes The focus of the complex responsive processes approach to complexity is in understanding the interpretive experience of the individual as human beings interact within complex human organizing activity (Stacey, Griffin & Shaw, 2000; Griffin, 2001). This approach distinguishes human complexity from the “systems approach” (von Bertalanffy, 1950; Katz & Kahn, 1966) arguing, in effect, that human organizing is not appropriately studied using systems models (Stacey, 1995). Instead, as Johannessen (2009) states: Taking a complexity approach means that the focus of research attention is drawn towards the exploration of the phenomenon of human interaction and emergence. Human interaction is the cause of emergence, and human interaction only creates further interaction and emergence. This is what is meant by a radical process view of reality (p. 217). The implication of this framing is that the focus of research is on the unfolding of experience, on the narratives themselves, rather than on structures or artifacts that can be modeled and studied using systems approaches.
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Complex Systems Leadership Theory Although coming from a different theoretical framing, the implications of this research stream are not that different from the system-based approaches described in previous sections. For example, in a case study Mangiofico and Feyerherm (2011) have integrated the notions of complex response processes with the systems perspective of Goldstein et al. (2010) to identify the four leadership skills that are implied by complexity thinking: i) perpetually scanning of the ecology to identify flows of information and resources, ii) weaving webs of interaction among actors within and across boundaries, iii) creating coherence among the signals that flow through these networks, what Goldstein, Hazy and Lichtenstein call “interaction resonance”, and iv) support for expanding innovation by offering stabilizing feedback to converge activity toward a kind of dynamic stability that represents a new way of doing things. In a certain sense, these four principles frame the practical implications of the new perspective that is offered by complexity science. The Emerging Complexity Paradigm Figure 1 shows a new paradigm that is emerging. Complexity science provides conceptual tools for thinking about organizing (left box in the figure) and identifies key system demands that must be met if a CAS is to be effective at both performance and adaptation (right box). Three organizing mechanisms and their relationship to the leadership process were described in this chapter (center box). These can be used by managers to drive organizational outcomes. At the bottom of the figure we identify the challenges that all of this complexity brings forward for individuals who are asked to manage or to lead. These include complexity within a given situation such as during a large-scale project, as well as complexity that results from changes over time, as might be the case as technology advances more rapidly than ever. Each of these areas has implications for practice and begs further research.
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Complex Systems Leadership Theory This new paradigm is a significant contribution to leadership research because it begins to connect individual behaviors and actions to system processes, functions and outcomes. To do so it explores the complexity dynamics within fine-grained HID in areas such as criticalization, and through the study of emergence, it also sheds light on how these might result in beneficial changes to the organization’s coarse-grained properties. This perspective is new to leadership research, and it represents a significant advance in understanding which is only beginning to show its promise. A summary of representative empirical studies is shown in Table 1.
Organizing Mechanisms
Complexity Tool-kit
Scale-Crossing Criticalization, Fluctuation, Amplifying Feedback, Divergence, Recombination, Self-Similarity/Fractals, Networks, Dissipative Structures
Fine-Graining Autonomous agents Heterogeneity Interdependence Boundaries & Tagging
Entrainment Leadership Reinforces Structures for Day-to-Day Effectiveness
Emergence Leadership Promotes High-Bandwidth Information Sharing, Experimentation & Synthesis
Identity Tension Leadership Orchestrates Individual, Group & Intergroup Connections & Synthesizes Overlapping Models & Identities
Changing Rules of Interaction
Attractors, Statistical Properties, Stabilizing Feedback, Phase Transitions, Order Parameters
Enacting Complexity Mechanisms
Coarse-Graining
Functional Demands On System Convergence Stability & Predictability Enables Effective Performance
Generative Innovation Enables Variety & Provides Future Options for Adaptive Opportunities
Unifying Common Models, Ethics, & Identities Engender Unity within Boundaries & Enable Collective Action
Individual Requisite Complexity Static Complexity Dynamic Complexity Cognitive & emotional traits
Situational awareness, action, & feedback
Figure 1 - A 2012 view of the emerging Complex Systems Leadership Paradigm includes a complexity tool-kit of ideas and the organizing mechanisms that can be used to satisfy the functional demands of a complex adaptive system. THE ROAD AHEAD In 2007, Jennings and Dooley used textual analysis to identify the emergence of a new paradigm in complex systems leadership research. Five years later the synthetic analysis
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Complex Systems Leadership Theory described herein has brought this paradigm into clearer focus. A review of the literature shows that a new theory has evolved in what can best be described as the abductive theorizing approach advocated in recent years by Max Boisot (2010). The new paradigm that has emerged both transcends and challenges prior research approaches. It transcends prior approaches in that it represents a general theory of human interaction dynamics (HID) consistent with analytical approaches used in the natural sciences. It challenges them in that its generality implies additional criteria and analytical techniques through which prior results may be evaluated. Implications for Research As this theory comes into focus, additional empirical research is needed to inform future iterations of CSLT. In this next phase of abductive theory development, it is increasingly important that quantitative methods be added to the mix so that constructs can be validated and relationships between them identified and tested with statistical methods. However, these methods must be implemented while cognizant of the limitations inherent in traditional methods when events are not independent and where individuals have different preferences, histories and values. To do this, a new way of thinking, new methods, and a new set of skills are needed. Tools like agent-based modeling, the mathematical treatment of dynamical systems, dynamic network analysis, and power-law analysis can all inform these new techniques. However, because the HID approach is qualitatively different from the interaction dynamics typically modeled in the natural sciences, many new technological advances are also needed (Prietula, 2011). As a result, quantitative research in CSLT will require advances on many levels, and many of these will need to be built fresh, from the ground up. It will involve changing the rules of interaction among all of those who are engaged in leadership research and practice. This is
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Complex Systems Leadership Theory perhaps the greatest challenge of all: The new paradigm is not just another way of thinking about leadership; it is also a new way of thinking about social science more generally. The magnitude of this challenge is daunting, certainly. But the potential benefits of action—particularly given the many challenges that face the world in the coming decades—make a focused effort toward a new and better way forward not merely a choice to be taken. It is an ethical imperative. Implications for Practice These developments also have significant implications for practice and thus for leadership development. One of these is the realization that leadership development must go far beyond the current focus on individual self-understanding and communications skills. In the fastmoving economy of the 21st century, individuals will need tools to help them better understand the nonlinear effects in their ecosystems. Increasingly, these are being enabled by social media and socio-technical networks, for example. It would be beneficial to be able to anticipate how various possible interventions might influence emergent outcomes, and then learn to respond quickly and thoughtfully to unfolding events in real-time. We expect that leadership development programs will increasingly be characterized by computer assisted simulations which express real life organizations as complex adaptive systems in a manner analogous to flight simulators in the airline industry, or battlefield simulations in the military. One of the advantages that CSLT provides is a theoretical framework within which one could identify opportunities for management interventions. The potential exists that in the not too distant future, computer simulations could be used to evaluate actions of individuals and groups and then present to the user the likely outcomes at the coarse-grained levels under various scenarios. Not only would this be useful in training, it could also be used to pretest actions to
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Complex Systems Leadership Theory explore possible unintended consequences. With better information, more informed action could be contemplated, and possible contingencies could be better evaluated. Table 1. Empirical studies using various methods Author(s)
Description
Method
Complexity Paradigm
Aasen & Johannessen (2007) Aasen,& Berg (2008). Backström, 2009
Innovation in the subsea technology development Resource generation in pharmacies Integration of employees in the company culture of a bank Training of first line managers
Longitudinal industrial case ethnographic Case study
Complex Responsive Processes CSLT/Directing leadership CSLT/Directing leadership CSLT/Directing leadership
Backström, Hagström, & Göransson, 2011 Backström, Wilhelmson, Olsson, Åteg, & Åberg, 2011 Baker, Onyx & Edwards (2011)
Community service projects
Beck & Chong (2009)
Community groups solving local problems Self-organized patterns in the workplace Development Entrepreneurial business model Project tem formation and success Innovation process at NCR
Buckle Henning & Dugan (2007) Butterfield, Shepherd & Woods (2011) Dal Forno & Merlone (2007) Garud, Gehman, & Kumaraswamy, (2011). Groot (2009)
Network analysis & survey Action learning network, survey and interview Network analysis & qualitative case study Action learning &participant observer Grounded Theory Case study Laboratory study & Agent-model Case study
CSLT/Generative Leadership CSLT/Leadership of emergence CSLT CSLT/Generative leadership CSLT/Convergent Leadership Complexity and innovation
Performance improvement at Dutch Railways Emergence of individuals as team leaders in simulation games Leadership practices in project-based organizations 18 month study of 50 person, technology firm Organizational Transformations: NCR & Intel Leadership in community group Leadership emergence in recreational groups Emergent leadership in youth groups Transformation of a mission church Workgroups at NASA
Case Study/ personal reflection Laboratory Study
Complex Responsive Processes Nonlinear dynamical systems/ Game theory
Qualitative/Interviews
Complexity Leadership Theory Leadership Metacapability Leadership Metacapability
Case studies
Tapsell & Woods, (2009)
Indian Manufacturing Companies Maori of New Zealand
Tobin, J. H. (2009)
US Hospital merger
Case Study/ personal reflection
Guastello et al. (2004, 2005, 2007a,b) Havermans, Den Hartog, Keegan & Uhl-Bien (2010) Hazy (2008a) Hazy (2004, 2008a) MacGillivray (2010) Moerschell (2010) Phelps & Hubler (2007) Plowman et al (2007) Schreiber & Carley (2006) Surie & Hazy (2006)
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Survey/case study System dynamics modeling of case study Phenomenographic study Grounded theory Multi-Case study and agent-based model Case study Network Analysis
Case Study
Complexity Leadership Theory Complexity and punctuated equilibria Dynamical Systems & Bifurcation Theory Leadership of emergence Dynamic Network Analysis CSLT/Generative Leadership CSLT/Generative Leadership Complex esponsive Processes
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Complex Systems Leadership Theory The CSLT approach is a useful and important advance in any case. By making managers aware of the conditions that imply different types of leadership action, and by clarifying what actions lead to which outcomes in a given situation, the process of enacting leadership becomes more understandable as a capability to be learned. This is distinct from more cultish approaches to leadership development that treat “leadership” as a “mysterious” or “authentic” attribute of certain special individuals, one that is hidden deep within a person’s soul and can never be fully understood. Rather than leaving us to trust that certain special people will reach inside themselves to lead us where they believe we should go, CSLT exposes the human interaction dynamics that each of us can influence to construct the world in which we choose to live. FUTURE DIRECTIONS The advancement of complex systems leadership theory has brought to the fore several important research questions: 1. How should the ubiquity of interdependent heterogeneity in HID be treated rigorously when modeling complex systems leadership events and when analyzing empirical data? New statistical techniques are needed that take into account individual learning and memory and path dependence with regards human interactions which limit the validity of many traditional methods (Hazy & Ashley, 2010). 2. What are the precise mechanisms of emergence in HID? What is the role of leadership in this process? Can the number and duration of experiments be quantified to determine if potential success is sustained through reinforcing feedback? 3. By what mechanisms do constraints on human interaction dynamics imply the particulars of emergent coarse-grained properties? How are constraints and their impacts measured? For example, how are constraints to resources, such as financial, human, temporal, and
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Complex Systems Leadership Theory technological, linked to leadership actions and outcomes? How do changes to the constraints translate into qualitatively different properties? What is the role of leadership in this process? 4. How do individuals who are seeking to have an impact recognize coarse-grain properties, determine the need to change them, and then translate this into complex systems leadership actions that locally change the rules of interaction in ways that alter these emergent properties as intended? 5. By what mechanisms do individual agents influence the local rules of interactions of others? What is the role of identity? Of ethics? 6. By what mechanisms do fine-grained interactions imply specific coarse-grained properties? How do changes in local rules become manifest in qualitative changes in the emergent properties? Is the analogy with phase transitions informative for this? 7. By what mechanisms do coarse-grained properties entrain fine-grained rules of interaction in HID? How is this related to leadership as well as to cultural norms, institutional effects, etc.? 8. When focusing on the rules that govern local interactions, how are these rules recognized, developed, shared, remembered, adapted, and replicated? What role do identities play in storing, sharing and evolving rules of interaction? How do ethics play into this question? 9. Can examples of collective agency with regard coarse-grained organizing forms in HID be identified and shown to be ontologically distinct from individual intention and action? What would this mean for leadership research? 10. What are the implications of this new paradigm for leadership development programs going forward?
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Complex Systems Leadership Theory REFERENCES Aasen, T. & Berg, M. (2008). A complexity perspective on innovation processes for subsea technology development International Journal of Learning and Change, 3(3), pp. 294307. Aasen, T.M.B. & Johannessen, S. (2007). Exploring Innovation Processes from a Complexity Perspective. Part II: Experiences from the SIOR case. International Journal of Learning and Change, 2 (4), 434–446. Allen, P. (2001). What is complexity science? Knowledge of the limits to knowledge. Emergence: A Journal of Complexity Issues in Organizations and Management, 3(1), 2444. Anderson, P. (1999). Complexity theory and organization science. Organization Science, 10(3), 216-232. Andriani, P. (2011). Complexity and Innovation. In P. Allen. S. Maguire, & B McKelvey (Eds.), The Sage Handbook of Complexity and Management, pp 454-470. Los Angeles: SAGE. Anneloes, M.L. Raes, Heijltjes, M.G., Glunk, U, Roe, R.A. (2011). The interface of the top management team and middle managers: A Process Model. Academy of Management Review, 36(1), 102-126. Ashby, W. R. (1956). An Introduction to Cybernetics. London: Chapman and Hall; Axelrod, R. (1984) The evolution of cooperation. New York: Basic books Backström, T. (2009). How to organize for local resource generation. The Learning Organization, 16(3).
Hazy & Uhl-Bien
2/11/2012
Page 48 of 64
Complex Systems Leadership Theory Backström, T., Hagström, T., & Göransson, S. (2011). Communication as a mechanism for culture integration. Paper presented at the 55th annual meeting of the international society for the system sciences, Hull. Backström, T., Wilhelmson, L., Olsson, B. K., Åteg, M., & Åberg, M. M. (2011). The Role of Manager in the Post-Industrial Work System. In E. Seglod, E. Berglund, E. Bjurström, E. Dahlquist, L. Hallén & E. Johansson (Eds.), Studies in industrial renewal (pp. 215-227). Västerås: Mälardalen University Press. Bak, P. & Paczuski, M. (1995). Complexity, contingency, and criticality". Proceedings of the National Academy of Sciences of the USA, 92 (15), 6689–6696. Baker, E., Onyx, J., & Edwards, M. (2011). Emergence, social capital and entrepreneurship: Understanding networks from the inside. Emergence: Complexity and Organization, 13(3), 31-45. Barnard, C. I. (1938). The functions of the executive. Cambridge, MA: Harvard University Press. Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Baumann, O. & Siggelkow, N. (2011). Complexity and Competitive Advantage. In P. Allen, S. Maguire, & B McKelvey (Eds.), The Sage Handbook of Complexity and Management (pp 494-505). Los Angeles: SAGE. Beck, D. & Chong, L.C. (2009). Creative Interaction in culturally diverse groups. In The emergence of Collective Identity as a Means for creating and Sustaining Social Value. In J. Goldstein, J.K. Hazy & j. Silberstang (Eds.), Complexity Science and Social Entrepreneurship ) pp.487-506). Litchfield Park, AZ: ISCE Publishing.
Hazy & Uhl-Bien
2/11/2012
Page 49 of 64
Complex Systems Leadership Theory Boal, K.B. & Schultz, P.L. (2007). Storytelling, time and evolution: The role of strategic leadership in complex adaptive systems. The Leadership Quarterly, 18, 411-428. Boisot, M., & Child, J. (1999). Organizations as adaptive systems in complex environments: The case of china. Organization Science, 10(3), 237-252. Boisot, M. & McKelvey, B. (2007). Extreme events, power laws, and adaptation: Towards an econphysics of organization. Academy of Management Conference Best Papers Proceedings, OMT. Boisot, M. & McKelvey, B. (2010). Integrating Modernist and Postmodernist Perspectives on Organizations: A Complexity Science Bridge. Academy of Management Review, 35(3), 415-433. Boisot, M. (2010). Connecting the dots before the world does. Paper presented at the annual meeting of the Academy of Management, Montreal. Boyatzis, R. E. (2008). Leadership development from complexity perspective. Consulting Psychology Journal: Practice and Research 60(4), 298-313. Brown, S., & Eisenhardt, K. (1997). The art of continuous change: Linking complexity theory and time-based evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42, 1-34. Brown, S. & Eisenhardt, K. (1998). Competing on the edge: Strategy as structured chaos. Boston: Harvard Business School Press. Buckle-Henning, P. & Dugan, S. (2007). Leader’s detection of Problematic Self-Organized Patterns in the Workplace. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 386-412). Mansfield, MA: ISCE Publishing Company.
Hazy & Uhl-Bien
2/11/2012
Page 50 of 64
Complex Systems Leadership Theory Butterfield, L., Shepherd, D. & Woods, C (2011). Developing digital citizenship for digital tots: Hector’s World Limited. Emergence: Complexity and Organization 13(3), 16-30. Cilliers, P. (1998). Complexity and postmodernism: Understanding complex systems. London: Routledge. Cyert, R., & March, J. (1963). A behavioral theory of the firm. Englewood Cliffs, NJ: PrenticeHall. Dal Forno A. & Merlone, U. (2007). The emergence of effective leaders: and experimental and computational approach. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 205-226). Mansfield, MA: ISCE Publishing Company. Davis, J. P., Eisenhardt, K. M., & Bingham, C. (2009). Optimal structure, market dynamism, and the stategy of simple rules. Administrative Science Quarterly, 54, 413-452. Denis, J-L., Langley, A., & Pineault, M. (2000). Becoming a leader in complex organizations, Journal of Management Studies, 37(8), 1063-1099. Dooley, K. J. (1997). A complex adaptive systems model of organization change. Nonlinear Dynamics, Psychology and Life Sciences, 1(1), 69-97. Dooley, K. J. (2007). Leadership and a computational model of organizations. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 327322). Mansfield, MA: ISCE Publishing Company. Dosi, G., Nelson, R. R., & Winter, S. G. (2000). The nature and dynamics of organizational capabilities. Oxford: Oxford University Press. Fleishman, E.A. (1953). The description of supervisory behavior. Personnel Psychology, 37, 1-6. Galunic, D. C., & Eisenhardt, K. M. (2001). Architectural innovation and modular corporate forms. Academy of Management Journal, 44(6), 1229-1249.
Hazy & Uhl-Bien
2/11/2012
Page 51 of 64
Complex Systems Leadership Theory Garud, R., Kumaraswamy, A., & Sambamurthy, V. (2006). Emergent by design: Performance and transformation at Infosys Technologies. Organization Science, 17, 277-286. Garud, R., Gehman, J., & Kumaraswamy, A. (2011). Complexity Arrangements For Sustained Innovation: Lessons From 3M Corporation. Organization Studies, 32, 737-767. Gell-Mann, M. (2002). What is complexity? In A. Q. Curzio & M. Fortis (eds.), Complexity and industrial clusters: Dynamics and models in theory and practice (pp.13-24). Berlin: Physica-Verlag. Goldstein, J. (1989). A Far-From-Equilibrium Systems Approach to Resistance to Change. Organizational Dynamics, 17,16-26. Goldstein, J. A. (2007). A new model of emergence and its leadership implication. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 61-92). Mansfield, MA: ISCE Publishing Company. Goldstein, J. A. (2011). Emergence in Complex Systems. In P. Allen, S. Maguire, & B McKelvey (Eds.), The Sage Handbook of Complexity and Management, (pp 65-78). Thousand Oaks: SAGE. 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. Griffin, D. (2001). The emergence of leadership: Linking self-organization and ethics. London: Routledge. Groot, N. (2009). Senior executives and the emergence of local responsibilities: A complexity approach to identity development and performance improvement. International Journal of Learning and Change, 3 (3), 264–280.
Hazy & Uhl-Bien
2/11/2012
Page 52 of 64
Complex Systems Leadership Theory Guastello, S. J. (2002). Managing emergent phenomena: Nonlinear dynamics in work organizations. Mahwah, New Jersey: Lawrence Erlbaum Associates. Guastello, S. J. (2007). Nonlinear dynamics and leadership emergence. The Leadership Quarterly, 18(4), 357-369. Guastello, S. J., & Bond, R. W. J. (2004). Coordination learning in Stag Hunt games with application to emergency management. Nonlinear Dynamics, Psychology, and Life Sciences, 8, 345-374. Guastello, S. J., & Bond, R. W. J. (2007a). The emergence of leadership in coordination intensive games. Nonlinear Dynamics, Psychology, and Life Sciences, 11, 91-117. Guastello, S. J., & Bond, R. W. J. (2007b). A swallowtail catastrophe model of leadership in coordination-intensive games. Nonlinear Dynamics, Psychology, and Life Sciences, 11, 235-351. Guastello, S. J., Craven, J., Zygowicz, K. M., & Bock, B. R. (2005). A rugged landscape model for self-organization and emergent leadership in creative problem solving and production groups. Nonlinear Dynamics, Psychology and Life Sciences, 9(3), 297-233. Guastello, S. J., & Guastello, D. D. (1998). Origins of coordination and team effectiveness: A perspective from game theory and non-linear dynamics. Journal of applied psychology, 83(3), 423-437. Haken, H. (2006). Information and self-organization: A macroscopic approach to complex systems (3rd ed.). Berlin: Springer. Hannan, M. T. & Freeman, J. (1989). Organizational Ecology. Cambridge, MA: Harvard University Press.
Hazy & Uhl-Bien
2/11/2012
Page 53 of 64
Complex Systems Leadership Theory Hannah, S.T., Eggers, J.T., & Jennings, P. L. (2008). Complex adaptive leadership: Defining what constitutes effective leadership for complex organizational contexts. In G. B. Graen & J. A. Graen (Eds.), Knowledge-driven corporation: Complex creative destruction (pp. 79-124). Charlotte, NC: Information Age Publishing. Hannah. S. T., Jennings, P. L., & Nobel, O. B-Y. (2010). Tactical Military Leader Requisite Complexity: Toward a referent Structure. Military Psychology, 22(4), 412-449. Hannah. S. T., Woolfolk, R. L., & Lord, R. G. (2009) Leader self-structure: A framework for positive leadership. Journal of Organizational Behavior, 30, 269-290. Havermans, L., Den Hartog, D., Keegan, A., & Uhl-Bien, M. Leadership in project-based organizations: Applying and extending complexity leadership theory through qualitative exploration. Working Paper. Hazy, J. K. (2004). A Leadership and Capabilities Framework for Organizational Change: Simulating the Emergence of Leadership as an Organizational Meta-Capability, doctoral dissertation, The George Washington University, Washington, DC. Hazy, J. K. (2006). Measuring leadership effectiveness in complex socio-technical systems. Emergence: Complexity and Organization (E:CO), 8(3), 58-77. Hazy, J. K. (2007a). Computer models of leadership: Foundation for a new discipline or meaningless diversion? The Leadership Quarterly, 18(4), 391-410. Hazy, J. K. (2007b). Leading Large: How disambiguation and changing reputations enable back-propagation learning in complex organizations. Paper presented at the Leadership Quarterly FestSchift in Honor of Dr. Jerry Hunt, Lubbock, TX )Oct 12-15, 2007). Hazy, J. K. (2008a). Leadership or luck? The system dynamics of Intel's shift to microprocessors in the 1970s and 1980s. In M. Uhl-Bien, R. Marion & P. Hanges (Eds.), Complexity
Hazy & Uhl-Bien
2/11/2012
Page 54 of 64
Complex Systems Leadership Theory Leadership, Part I: Conceptual foundations (pp. 347-378). Charlotte, NC: Information Age Publishing. Hazy, J. K. (2008b) Toward a theory of leadership in complex systems: Computational modeling explorations. Nonlinear Dynamics, Psychology, and Life Sciences, 12(3) 281-310. Hazy, J. K. (2008c). Patterns of Leadership. The System Dynamics of Intel's Shift to Microprocessors in the 1970s and 1980s. In M. Uhl-Bien, R. Marion & P. Hanges (Eds.) Complexity Leadership, Part I: Conceptual foundations (pp. 379-390). Charlotte, NC: Information Age Publishing. Hazy, J. K. (2009). Innovation Reordering: Five principles for leading continuous renewal. In Schlomer, S. & Tomaschek, N. (Eds.), Leading in Complexity: New Ways of Management (pp. 300). Seiten: Verlag fur Systemische Forschung. Hazy, J. K. (2011a). Parsing the Influential Increment he Language of Complexity: Uncovering the Systemic Mechanisms of Leadership Influence. International Journal of Complexity in Leadership and Management, 1(2), 164-192. Hazy, J. K. (2011b). Leadership as Process: A Theory of Formal and Informal Organizing in Complex Adaptive Systems. Adelphi University School of Business Working Paper: SBWP-2011-02. Hazy, J.K. (in press-a). Unifying leadership: Shaping identity, ethics and the rules of interaction. International Journal of Society Systems and Science. Hazy, J. K. (in press-b). Leading large organizations. International Journal of Complexity in Leadership and Management. Hazy, J.K. & Ashley, A. (2011). Unfolding the future: Bifurcation in Organizing Form and Emergence in Social Systems. Emergence: Complexity and Organization 13(3), 77-91.
Hazy & Uhl-Bien
2/11/2012
Page 55 of 64
Complex Systems Leadership Theory Hazy, J. K., Goldstein, J. A., & Lichtenstein, B. B. (Eds.). (2007a) Complex Systems Leadership Theory. Mansfield, MA: ISCE Publishers. Hazy, J. K., Goldstein, J., & Lichtenstein, B. B. (2007b). Complex systems leadership theory: An introduction. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 1-17). Mansfield, MA: ISCE Publishing Company. Hazy, J. K., Millhiser, W. P., & Solow, D. (2007). Mathematical and computational models of leadership: Past and Future. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 386-412). Mansfield, MA: ISCE Publishing Company. Hazy, J. K., Moskalev, S., & Torras, M. (2009). Toward a theory of social value creation: Individual agency and the use of information within nested dynamical systems. In J. A. Goldstein, Hazy, J. K. & Silberstang, J. (Eds.), Complexity Science and Social Entrepreneurship (pp. 257-281). Litchfield Park, AZ: ISCE Publishing. Hazy, J. K., Moskalev, S, & Torras, M. (2010). Mechanisms of Social Value Creation: Extending Financial Modeling to Social Entrepreneurship and Social Innovation. International Journal of Society Systems Science, 2(2), 134-157. Hazy, J. K. & Silberstang, J. (2009a). Leadership within emergent events in complex systems: micro-enactments and the mechanisms of organisational learning and change. International Journal of learning and Change, 3(3), 230-247. Hazy, J. K. & Silberstang, J. (2009b). The emergence of Collective Identity as a Means for creating and Sustsaining Social Value. In J. A. Goldstein, J. K. Hazy and J. Silberstang (Eds.), Complexity Science and Social Entrepreneurship,( pp.447-470). Litchfield Park, AZ: ISCE Publishing.
Hazy & Uhl-Bien
2/11/2012
Page 56 of 64
Complex Systems Leadership Theory Heifetz, R. A., & Laurie, D. L. (2001). The work of leadership. Harvard Business Review, 79(11), 131-141. Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M. A., Singh, H., Teece, D. J., & Winter, S. G. (2007). Dynamic Capabilities: Understanding strategic change in organizations. Malden, Mass: Blackwell Publishing. Hogue, M., & Lord, R. G. (2007). A multilevel, complexity theory approch to understanding gender bias in leadership. The Leadership Quarterly, 18 (4), 370-390. Holland, J. H. (1975). Adaptation in natural and artificial systems. Cambridge, MA: The MIT Press. Hooijberg, R. (1996). A multidirectional approach to leadership: An extension of the concept of behavioral complexity. Human Relations, 49, 917-946. Hunt, J, G., Osborne, R. N., & Boal, K. .B (2009). The architecture of managerial leadership: Stimulation and channeling of organizational emergence. The Leadership Quarterly, 20, 503-516. Jaques, E. (1989). Requisite organization. Arlington, VA: Cason Hall. Jennings, P. L. & Dooley, K. J. (2007). An emerging complexity paradigm in leadership research. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 17-34). Mansfield, MA: ISCE Publishing Company. Johannessen, S. (2009). The complexity turn in studies of organisations and leadership: relevance and implications. International Journal of Learning and Change, 3(3), 214229.
Hazy & Uhl-Bien
2/11/2012
Page 57 of 64
Complex Systems Leadership Theory Johannessen, S. & Aasen, T.M. B. (2007). Exploring Innovation Processes from a Complexity Perspective, Part I: Theoretical and Methodological Approach. International Journal of Learning and Change, 2 (4), 420–433. Katz, D., & Kahn, R. L. (1966). The social psychology of organizations (2nd ed.). New York: John Wiley & Sons. Kauffman, S. (1995). At home in the universe. Oxford: Oxford University Press. Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago: University of Chicago Press. Levick, D. & Kuhn, L. (2007). Fractality, organizational management and creative change. World Futures, 63(3-4), 265-274. Levinthal, D. A. (1997). Adaptation on Rugged Landscapes. Management Science, 43 (7), 934950. Lichtenstein, B. & McKelvey, B. (2007). Leadership in the four stages of emergence. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 93-108). Mansfield, MA: ISCE Publishing Company. Lichtenstein, B. & Plowman, D.A., (2009). The Leadership of emergence: A complex systems leadership theory of emergence at successive organizational levels. The Leadership Quarterly, 20, 651–661. Lichtenstein, B. B., Uhl-Bien, M., Marion, R., Seers, A., Orton, J. D., & Schreiber, C. (2006). Complexity leadership theory: An interactive process on leading in complex adaptive systems. Emergence: Complexity and Organization (E:CO), 8(4), 2-12. Lord, R. G., Hannah, S. T., & Jennings, P.L. (2011). A framework for understanding leadership and individual complexity. Organizational Psychology Review, 1(2), 104-127.
Hazy & Uhl-Bien
2/11/2012
Page 58 of 64
Complex Systems Leadership Theory Lord, R. G., Hannah. S. T., & Pearce, C. (2011). A framework for understanding leadership and individual complexity. Organizational Psychology Review, 1(2), 104-127. MacGillivray, A. (2010). Leadership in a network of communities: A phenomenographic study, The Learning Organization, 17 (1), 24-40. MacIntosh, R., & MacLean, D. (1999). Conditioned emergence: A dissipative structures approach to transformation. Strategic Management Journal, 20, 297-316. Mangiofico, G., & Feyerherm, A. E. (2011). The case for using a Complexity Perspective as applied to Leadership. Working Paper. March, J. G. (1991) Exploration and Exploitation in Organizational Learning. Organization Science, 2, 71-87. Marion, R., & Uhl-Bien, M. (2001). Leadership in complex organizations. Leadership Quarterly, 12(4), 389. Marion, R., & Uhl-Bien, M. (2001). Leadership in complex organizations. The Leadership Quarterly, 12(4), 389-418. McKelvey, B. (2010). Complexity leadership: The secret of Jack Welch’s success. International Journal of Complexity in Leadership and Management, 1(1), 4-36. McKelvey, B. (2004). Toward a complexity science of entrepreneurship. Journal of Business Venturing, 19, 313-342. McKelvey, B. (1997). Quasi-natural organization science. Organization Science, 8, 352-380. Meyer, A.D., Gaba, V., & Colwell, K.A. (2005). Organizing Far from Equilibrium: Nonlinear Change in Organizational Fields. Organization Science, 16(5), 456-473. Mitchell, M., Hraber, P., & Crutchfield, J.P. (1993). Revisiting the edge of chaos: Evolving cellular automata to perform computations. Complex Systems, 7, 89-130.
Hazy & Uhl-Bien
2/11/2012
Page 59 of 64
Complex Systems Leadership Theory Moerschell, L. (2010). The intersection of punctuated equilibrium and leadership emergence within the framework of Naturalistic Decision Making. Journal of Outdoor Recreation, Education and Leadership, 2(2), 1-4. Morrison, K. (2010). Complexity Theory, School Leadership and Management: Questions for Theory and Practice. Educational Management Administration & Leadership, 38(3), 374393. Nelson, R. R., & Winter, S. G. (1982). An evolutionary theory of economic change. Cambridge, MA: The Belknap Press of Harvard University Press. Nowak, M., Tarnita C.E., & Wilson, E.O. (2010). The evolution of eusociality. Nature 466, August 26, 2010, p.1057. doi: 10.1038/nature0920. Panzar, C., Hazy, J. K., McKelvey, B., & Schwandt, D. R. (2007). The paradox of complex organizations: Leadership as integrative influence. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 305-326). Mansfield, MA: ISCE Publishing Company. Pascale, R., Sternin, J. & Sternin, M. (2010). Power of Positive Deviance: How Unlikely Innovators Solve the World's Toughest Problems. Cambridge, MA: Harvard University Press. Peterson, M. F., & Meckler, M. R. (2001). Cuban-American entrepreneurs: Chance, complexity and chaos. Organization Studies, 22(1), 31-57. Phelps, K.C. & Hubler, A. (2007). Toward an Understanding on Membership and Leadership in Youth Organizations: Sudden changes in average participation due to the behavior of one individual. In J. K. Hazy, J. Goldstein & B. B. Lichtenstein (Eds.), Complex Systems Leadership Theory (pp. 195-204). Mansfield, MA: ISCE Publishing Company.
Hazy & Uhl-Bien
2/11/2012
Page 60 of 64
Complex Systems Leadership Theory Plowman, D., Baker, L. T., Beck, T., Kulkarni, M., Solansky, S., & Travis, D. (2007a). Radical change accidentally: The emergence and amplification of small change. Academy of Management Journal, 50(3), 515-543. Plowman, D., Baker, L. T., Beck, T., Kulkarni, M., Solansky, S., & Travis, D. (2007). The role of leadership in emergent, self-organization. The Leadership Quarterly. Prigogine, I. (1995). The end of certainty: Time, chaos, and the new laws of nature. New York: The Free Press. Prigogine, I. & Stengers, I. (1984). Order out of Chaos. New York: Heinemann. Prietula, M. J. (2011) Thoughts on Complexity and Computational Models. In P. Allen, S. Maguire, & B McKelvey (Eds.), The Sage Handbook of Complexity and Management (pp 93-100). Thousand Oaks: SAGE. Prokopenko, M., Boschetti, F. & Ryan, A. J. (2009). An information-theoretic primer on complexity, self-organization and emergence. Complexity, ISSN 1099-0526, 15(1), 1128. Raelin, J. (2011). From leadership-as-practice to leaderful practice, Leadership, 7(2), 195-211 Richardson, K. (2010). Thinking about Complexity. Lichfield Park, AZ: Emergent Publishing. Schneider, M., & Somers, M. (2006). Organizations as complex adaptive systems: Implications of complexity theory for leadership research. The Leadership Quarterly, 17(4), 351-365. Schreiber, C. & Carley, K. M. (2006). Leadership Style as an Enabler of Organizational Complex Functioning. Emergence: Complexity and Organization, 8(4). Seeley, T. (2010). Honeybee Democracy. Princeton: Princeton University press. Selznick, P. (1948). Foundations of the theory of organizations. American Sociological Review, 13, 25−35.
Hazy & Uhl-Bien
2/11/2012
Page 61 of 64
Complex Systems Leadership Theory Shoup, J.R. & Studer, S. C. (2010). Leveraging Choas: The mysteries of leadership and policy revealed. Lanham, MD: Rowman & Littlefield Education. Siggelkow, N. & Rivkin, J. (2005). Speed and search: Designing organizations for turbulence and complexity. Organization Science, 16, 101-122. Silberstang, J. & Hazy, J. K. (2008). Toward a micro-enactment theory of leadership and the emergence of innovation. The Innovation Journal: The Public Sector Innovation Journal, 13(3), Article 5. Simpson, P. (2007). Organizing in the mist: A case study of leadership and complexity. Leadership and Organization Development Journal, 5, 465-482. Simon, H. A. (1997). Administrative behavior: A study of decision-making processes in administrative organizations (4th ed.). New York: The Free Press. Solow D., & Leenawong, C. (2003). Mathematical models for studying the value of cooperative leadership in team replacement. Computational and Mathematical Organization Theory, 9(1), 61-81. Solow, D., & Szmerekovsky, J. G. (2006). The role of leadership: What management science can give back to the study of complex systems. Emergence: Complexity and Organization, 8(4), 52-60. Stacey, R. D. (1993). Strategic Management and Organization Dynamics. London: Prentice Hall. Stacey, R. D. (1995). The science of complexity: An alternative perspective for strategic change processes. Strategic Management Journal, 16, 477-495. Stacey, R. D., Griffin, D., & Shaw, P. (2000). Complexity and management: fad or radical challenge to system thinking? London: Routledge.
Hazy & Uhl-Bien
2/11/2012
Page 62 of 64
Complex Systems Leadership Theory Stogdill, R. M. (1974). Handbook of Leadership: A survey of the Literature. New York: Free Press Streatfield, P. J. (2001). The paradox of control in organizations. London: Routledge. Surie, G., & Hazy, J. K. (2006). Generative leadership: Nurturing innovation in complex systems. Emergence: Complexity and Organization (E:CO), 8(4), 13-26. Tapsell, P. & Woods, C. (2009).A spiral of innovation framework for social entrepreneurship: Social innovation at the generational dividein an indigenous context. In The emergence of Collective Identity as a Means for creating and Sustaining Social Value. In J. A. Goldstein, J. K. Hazy & J. Silberstang (Eds.), Complexity Science and Social Entrepreneurship( pp.471-486). Litchfield Park, AZ: ISCE Publishing. Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509-533. Thietart, R-A. & Forgues, B. (1995). Chaos Theory and Organization. Organization Science, 6, 19-31. Tobin, J.H. (2009). The myth of rational objectivity and leadership: The realities of a hospital merger from a CEO’s perspective. International Journal of Learning and Change, 3 (3), 248–263. Tsoukas, H. (2005). Complex Knowledge: Studies in Organizational Epistemology. Oxford: Oxford University Press. Uhl-Bien, M., & Marion, R. (2008). Complexity leadership, part 1: Conceptual foundations. Charlotte: Information Age Publishing. Uhl-Bien, M., & Marion, R. (2009). Complexity leadership in bureaucratic forms of organizing: A meso model. The Leadership Quarterly, 20, 631–650.
Hazy & Uhl-Bien
2/11/2012
Page 63 of 64
Complex Systems Leadership Theory Uhl-Bien, M., & Marion, R. (2011). Complexity leadership theory. In A. Bryman, D. Collinson, K. Grint, B. Jackson, & M. Uhl-Bien (Eds.), The Sage Handbook of Leadership (pp. 468482). London: Sage. Uhl-Bien, M., Marion, R., & McKelvey, B. (2007). Complexity leadership theory: Shifting leadership from the industrial age to the knowledge era. The Leadership Quarterly, 18, 298-318. von Bertalanffy, L. (1950). The theory of open systems in physics and biology. Science, 3, 2329. Wheatley, M. J. (1999). Leadership and the new science: discovering order in a chaotic world. San Francisco: Berrett-Koehler. Zaccaro, S.J. (1999). Social complexity and the competencies required for effective military leadership. In J. G. Hunt, G. E. Dodge, & L. Wong (Eds.), Out-of-the-box leadership: Transforming the twenty-first century Army and other top performing organizations (pp. 131-151). Stamford, CT: JAI Press.
i
In a later section we describe a competing approach, Complex Responsive Processes (CRP) put forth by Stacey (1993), which challenges the systems approach entirely. ii Constructive deviations are ad hoc experiments performed with the intention of achieving some purpose; this idea is distinct from the notion of “positive deviance” which is a post hoc analysis and intervention technique used to identify positively performing subgroups (outliers) in populations facing many of the same challenges. The positively deviant solutions are then analyzed and understood before being replicated more broadly across the population (Pascale, Sternin, & Sternin, 2010). This technique could presumably be applied with positive affect to evaluate the relative success of the constructive deviations described herein as they are occurring within organizations that are experiencing criticalization.
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