Complexity Leadership Theory

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Complexity leadership theory: An interactive perspectiveon leading in complex adaptive systemsBenyamin B. Lichtenstein1, Mary Uhl-Bien2, Russ Marion3, Anson Seers4, James DouglasOrton5, and Craig Schreiber61 University of Massachusetts; 2 University of Nebraska-Lincoln; 3 Clemson University; 4 Virginia Commonwealth University; 5 Te

George Washington University; 6 Carnegie Mellon University, USA

raditional, hierarchical views of leadership areless and less useful given the complexities of ourmodern world. Leadership theory must transi-tion to new perspectives that account for thecomplex adaptive needs of organizations. In thispaper, we propose that leadership (as opposedto leaders) can be seen as a complex dynamicprocess that emerges in the interactive spacesbetween people and ideas. Tat is, leadershipis a dynamic that transcends the capabilities of

individuals alone; it is the product of interaction,tension, and exchange rules governing changesin perceptions and understanding. We label thisa dynamic of adaptive leadership, and we showhow this dynamic provides important insightsabout the nature of leadership and its outcomesin organizational fields. We define a leadershipevent as a perceived segment of action whosemeaning is created by the interactions of actorsinvolved in producing it, and we present a set ofinnovative methods for capturing and analyzing

these contextually driven processes. We providetheoretical and practical implications of theseideas for organizational behavior and organiza-

tion and management theory.

Introduction

As twenty-first-century management contin-ues to emphasize decentralized organizingstructures and co-evolutionary ecologies

of firms, institutions, and markets, there is a grow-ing recognition that traditional top-down theories

of leadership are at best overly simplistic (Osbornet al., 2002). Tat is, leading-edge theorists and theleaders they inform are questioning the assump-tion that the essence of leadership rests within thecharacter or the characteristic behaviors of effec-tive supervisors (Seers, 2004). Worse, the notionthat a leader exogenously acts on organizationsin order to achieve the leaders objectives may bemisguided in the presence of the insight that orga-nizations are highly complex and nonlinear (Meyer

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et al., 2005). Tere is also a growing realization thateffective leadership does not necessarily residewithin the leaders symbolic, motivational, or char-ismatic actions. If leadership is not in a leader or doneby a leader, however, how are we to insightfullyconceive exactly what constitutes leadership andfrom where it originates? A novel approach foranswering these questions is grounded in com-plexity science, namely the notion that leader-

ship is an emergent event, an outcome ofrelationalinteractions among agents. In this view, lead-ership is more than a skill, an exchange, or asymbol leadership emerges through dynamicinteractions (Bradbury and Lichtenstein, 2000).Complexity leadership theory investigates therole of leadership in expediting those processesin organizations through which interdependentactions among many individuals combine intoa collective venture (Drath, 2001; Meyer et al.,2005).

Founding the approach of this paper oncomplexity theory per se moves us to a whole-systems view and thus away from the more tra-ditional approaches that focus on variables andcomponent parts. Instead, we will focus on:

Expanding the locus of leadership from theisolated, role-based actions of individuals tothe innovative, contextual interactions thatoccur across an entire social system;

Extending current theory and practice by

focusing on micro-strategic leadership actionsacross all organizational levels and across orga-nizational boundaries;

Increasing the relevance and accuracy ofleadership theory by exploring how leadershipoutcomes are based on complex interactions,rather than independent variables;

Highlighting the relational foundations ofchange in emerging organizational fields,

Practitioner


2/123Lichtenstein, Uhl-Bien, Marion, Seers, Orton, & Schreiber

through the idea that leadership occurs in thespaces between agents;

Providing a new and rich oundation orexplaining the constructive process o collec-tive action as well as the influential behaviorso collective actors;

Connecting to innovative methodologies thatcan enrich our understanding o how leader-ship gets enacted and received in complexenvironments.

Toward a new era in leadership: Complexity

leadership theory

Leadership study, indeed society in general, isinatuated with leaders people who occupysome elevated status or position and to whom

we ofen ascribe some orm o greatness (Gronn,

2002). Te Western mindset about leaders seemsruled by assumptions that leaders have some innatecapacity to plan utures, arrive at rational and cor-rect decisions (Bluedorn, 2002), and control socialoutcomes (Meindl et al., 1985). A new mindset is beginning to emerge,however, which recognizes that social processesare too complex and messy to be attributed to asingle individual or pre-planned streams o events(Finkelstein, 2002; Marion and Uhl-Bien, 2001). AsFinkelstein (2002: 77) put it:

I understand that as researchers we need to simpliyvery complex processes to study them careully, butwhat are we lef with when we remove the messiness,the back-and-orth, the reality?

Although the complexity leadershipapproach redirects emphasis away rom the indi-vidual as leader, it does not in any way diminishthe importance o leadership as an organizationalphenomenon; rather, it recognizes that leadershiptranscends the individual by being undamentally a

system phenomenon (Marion and Uhl-Bien, 2001,2003; Uhl-Bien et al., 2004; Hazy, 2006). Drawingrom complexity science (Marion, 1999), complexityleadership theory offers a new perspective or leader-ship research by considering leadership within theramework o the idea o a complex adaptive system(CAS). In such systems, relationships are not pri-marily defined hierarchically, as they are in bureau-cratic systems, but rather by interactions amongheterogeneous agents and across agent networks.

A CAS is comprised o agents, individu-als as well as groups o individuals, who resonatethrough sharing common interests, knowledgeand/or goals due to their history o interactionand sharing o worldviews. Agents respond toboth external pressures (rom environment orrom other CAS or agents, e.g., leaders) and inter-

nal pressures that are generated as the agentsstruggle with interdependency and resulting con-flicting constraints (e.g., when the needs o oneagent conflict with those o another). Tese ten-sions, when spread across a network o interactiveand interdependent agents, generate system-wideemergent learnings, capabilities, innovations, andadaptability. Importantly, such elaborations areproducts o interactions among agents, rather thanbeing caused by the specific acts o individualsdescribed as leaders.

A complex systems perspective introducesa new leadership logic to leadership theory andresearch by understanding leadership in terms oan emergent event rather than a person. A com-plexity view suggests a orm o distributed lead-ership (Brown and Gioia, 2002; Gronn, 2002) thatdoes not lie in a person but rather in an interactivedynamic, within which any particular person willparticipate as leader or a ollower at different timesand or different purposes. It is not limited to a or-mal managerial role, but rather emerges in the sys-

temic interactions between heterogeneous agents(Marion and Uhl-Bien, 2001, 2003). Tereore,complexity leadership includes a descriptiveanalysis examining the conditions and dynamicprocesses o these interactions and the emergentphenomena that they call orth:

Tere is a growing sense that effective organizationchange has its own dynamic, a process that cannotsimply ollow strategic shifs and that is longer andsubtler than can be managed by any single leader. Itis generated by the insights o many people trying toimprove the whole, and it accumulates, as it were, overlong periods. (Heckscher, 1994: 24)

In other words, leaders in the ormal sense canenable the conditions within which the processoccurs, but they are not the direct source o change.

A key contribution o a complexity leader-ship theory is that it provides an integrativetheoretical ramework or explaining interactive


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dynamics that have been acknowledged by a vari-ety of emerging leadership theories, e.g., sharedleadership (Pearce and Conger, 2003), collectiveleadership (Weick and Roberts, 1993), distributedleadership (Gronn, 2002), relational leadership(Drath, 2001; Uhl-Bien, in press), adaptive leader-ship (Linsky and Heifetz, 2002; Uhl-Bien et al.,

2004), and leadership as an emergent organiza-tional meta-capability (Hazy, 2004, 2006).

Specifying the interactive nature of leadership

in events

Adaptive leadership is defined for this paper as aninteractive event in which knowledge, action pref-erences, and behaviors change, thereby provokingan organization to become more adaptive. Tisdefinition focuses on change, as many definitionsof leadership already do (Bryman, 1996), but also

distinguishes between leadership (as a product ofinteractive dynamics) and leaders (people whoinfluence this process). As such, adaptive leader-ship does not mean getting followers to follow theleaders wishes; rather, leadership occurs wheninteracting agents generate adaptive outcomes.According to this definition, leadership can occuranywhere within a social system. It need not beauthority or position based, but is instead a com-plex interactive dynamic sparked by adaptive chal-lenges. Individuals act as leaders in this dynamic

when they mobilize people to seize new opportu-nities and tackle tough problems. As the situationchanges, different people may act as leaders byleveraging their differing skills and experience.

An excellent starting place for develop-ing a model of adaptive leadership in events canbe found in the work of Mead (1932, 1934, 1938),who brought to the fore the neglected dimensionof inter-subjectivity in the establishment of bothindividual and collective behavior. For Mead, thevery notion of self (identity) becomes intimatelyconnected to the identity of agents (objects andindividuals) with which one interacts in a socialstructure. Allport (1954, 1962, 1967) builds onthis idea by conceptualizing social structure as anongoing cycleof events. Events are the observablenodes in these cycles; multiple cycles may interactdirectly or they may be tangential. Allports theoryprovides a powerful precedent to complexity sci-ence in affirming that longitudinal analyses ofinteraction events should replace cross-sectional

frameworks that purport to examine how singlevariables cause some dependent (pre-assigned)outcome.

Weicks (1979) social psychology of orga-nizing modernizes Allports analysis. Weick arguesthat the basic unit of organization is the doubleinteract of interdependent behaviors between

individuals. He also emphasized that events inorganizations are held together and regulated bydense, circular, lengthy strands of causality per-ceived by members (Weick, 1979: 13). Recently, Cilliers (1998) applied a com-plexity, postmodern lens by connecting these ear-lier ideas on intersubjectivity to Giddenss (1984)partly cognitive model of structuration. An event isthus a bracketing of ongoing interactions to createmeaning. Following this reasoning, we propose anew definition for an event, namely a perceived

segment of action for which meaning relates tointeractions among actors. All of the actors neednot play equivalent roles in the action, but all ofthe roles are interrelated. Another way to say thisis that meaning emerges in the spaces betweenpeople rather than in the acts of individualsper se(Buber, 1970). In essence [Bubers work] pointsto the relational perspective that self and othersare not separable but are, rather, coevolving(Bradbury and Lichtenstein, 2000: 551). In a simi-lar way, Drath (2001: 136) proposed that:

people construct reality through their interactionswithin worldviews... [Tey do it] when they explainthings to one another, tell each other stories, createmodels and theories and in general when theyinteract through thought, word, and action.

Accordingly, leadership events are not constructedby the actions of single individuals; rather, theyemerge through the interactions between agentsover time.

Drivers of adaptive leadership

Collective identity formation as a driver of

adaptive leadership

According to most complexity researchers,agent interactions are governed by rulesand mechanisms for changing rules. One

fundamental form of rule change occurs wheninteractions in leadership events produce a newidentity (e.g., Gioia et al., 2000). According to the



adaptive leadership perspective, this identiy or-mation occurs over time, as participants togetherdefine who we are and what we are doing throughour interactions. In this way, the emergence o asocial object occurs through the in-orming o ajoint social identity. Importantly, such social objectsarise jointly, through the mutual interactions o

its participant creators. Tis driver o collectiveidentity ormation can be orgotten as soon as theparticipants create a common-sense conception oa ormal leader out there, with themselves hold-ing complementary ollower roles (Kahneman andversky, 1972). By this account, complexity lead-ership theory suggests that participants need to bemade aware o this dual process o identity creationand projection, in order to take back ownership otheir role in the identity-ormation process.

Complexity leadership theorys conception

o interactive events offers the potential or speci-ying the construction process o collective action,and thus collective actors (Seers and Wilkerson,2005). Note how different this conception is romtraditional models o leadership, and rom mostcomplexity models o agent rule ollowing. Mostsimulation researchers suggest that agents are gov-erned by a selfish rule (Bonabeau and Meyer, 2001).For example, Nowak et al., (1995) show cellularautomata simulations in which selfish behaviors oagents may, under certain circumstances, generate

cooperative behaviors across an interactive system.In contrast, complexity leadership theory developsa more nuanced view o how rules are used and howthey can change through interactions over time.

Tension as a driver of adaptive leadership

A second driver o innovation in adaptive leader-ship events occurs when the interactions betweenagents spark tension that leads to adaptive change.According to complexity leadership theory, whenagents interact they may experience tension in theorm o pressures on and challenges to their per-sonal knowledge base (Carley and Hill, 2001). Suchchallenges to agent schema can, under the rightenabling conditions, oster realignment o agentscognitive maps to resonate better with the newinormation. Tat is, agents realign their schema inorder to accommodate and thus mitigate disagree-ment (Kauffman, 1993; Marion and Uhl-Bien,2001). Tese tension-related accommodationsofen generate completely new inormation; that

is, ideas, innovations, and rameworks emergethat are unanticipated given the inormation cur-rently available (Uhl-Bien et al., in press). Tereinlay the seeds o adaptive leadership: Agent inter-actions can generate tension through which novelinormation can emerge; when those new ideaslead to positive change, adaptive leadership has

occurred. In this case, the tension that arises inagent interactions can unction as a core driveror change in adaptive leadership. Adaptive lead-ership then may take advantage o such tension asa driver through which interacting agents (people,ideas, etc.) address complex challenges in ways thatproduce new patterns o cognition and behavior.But how do we measure these dynamics, and howcan we expand our understanding o leadership inevents such that ormal leaders can help create theconditions or adaptive leadership and complexity

leadership?

Measuring the space between: Methods for

exploring and analyzing leadership events

Given our interest in exploring the eventsthat generate leadership, we have identi-fied several methods that can be used to

measure and analyze specific leadership eventsover time, as well as the interrelationships thatenact them. Specifically we are interested in epi-sodes o leadership, and on the interactions that

are bracketed into those events. Since interactivedynamics are processes that take place over time,we need methods that attend to the longitudinaland dynamic nature o interactive events and therelationships that construct them.

Focusing on events as the prime unit oanalysis means more than applying new methodsin order to analyze cross-sectional data on individ-ual characteristics. Instead, measuring the spacebetween involves:

Identiying and bracketing the events, episodes,and interactions o interest;

Capturing these events or interactions as datain a systematic way;

Gathering individual/agent level data thatdescribe interaction cues received over time;

Modeling these data in ways that highlighttheir longitudinal and relational qualities;

Analyzing these data in terms o their relational


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qualities and longitudinal dynamics.Identifying and bracketing eventsneed not be com-plicated, depending on the nature o the organiz-ing processes one is examining. A paradigmaticcase is Barleys (1986) examination o interactionsbetween radiologists and technicians during aperiod o dramatic technological change. In that

case, the context o these interactions was defined(bracketed) by a radiological procedure, which inour case would be the event within its nexus o rela-tionships. Less common, but no less interesting, isthe research on organizational meetings or specialevents, in which the crucial episodes are defineda priori by the research interest, and the bracket-ing o these processes is structurally producedand distinguished by the organizational membersthemselves.

Capturing events and interactions system-

atically may result rom the in-depth explorationo organizing processes. For example, managementresearchers have recognized the important role thattemporal events play in making progress (Brownand Eisenhardt, 1997) and catalyzing changes(Gersick, 1994) in dynamic contexts. In those twostudies, the researchers were able to identiy tempo-ral and event-based transitions that structured thedevelopment o the project/venture being studied.A more ormal approach was taken by Lichtensteinet al. (2006) in their discovery o an emergence

event within a nascent entrepreneurial venture.Using grounded theory (Strauss and Corbin, 1993),they coded bi-weekly interview data into our cat-egories, then transormed these codes into a quan-titative ormat (Van de Ven and Poole, 1990). Next,they analyzed each o the time series using qual-ity control methods, which highlighted a dramaticchange in one variable (Dooley and Van de Ven,1999). Post-hocheuristic tests confirmed the pres-ence o two distinct epochs (events) within thesedata.Te interview corresponding to the specificchange point was more deeply examined; it becamethe nexus o a series o changes that were explainedas interdependent aspects o an emergence event.

Gathering individual/agent level dataaboutthe members interdependencies and the interactioncues that they receive over time (traditionally, thecues that lead them) is necessary or exploringhow leadership events diffuse through the spacebetween the participants to influence a popula-tion. Tese data can be gathered through observa-

tion and surveys in the laboratory (Guastello et al.,2005) or in the field (Schreiber and Carley, 2005).o ully understand leadership events, however,it is also necessary to know how these leadershipcues or triggers are perceived by the individualagents who must make particular choices or takespecific actions (Hazy, 2006). Because events

unold over time, the data set must be longitudinal,to capture how these qualities change over time, aswell as cross-sectional, to understand agents per-ceptions and qualities at specific moments in time.Accessing and gathering this type o data is challeng-ing; ortunately, sofware tools and other techniquesenable detailed data gathering at regular intervals inorganizations (www.leadershipscience.com; Amabileet al., 2005). Once gathered, the data can be used asinputs to computational models as described belowor or other quantitative, qualitative, or mixed

method analytic techniques. Modeling data in ways that highlight theirlongitudinal and relational qualitiesenables explo-ration o the complex and interrelated dynam-ics inherent in leadership events. A recent surveyo computer modeling approaches in leadershipresearch (Hazy, in press) identified several differ-ent techniques that have been used or this, includ-ing system dynamics modeling (Davis, 2005; Hazy,2004; Jacobsen and House, 2001), discrete eventsimulation (Jiang and Burton, 2002), agent-based

modeling (Black and Oliver, 2004; Black et al., 2006;Carley and Ren, 2001), network modeling such asthe NK Model (Solow and Leenawong, 2003), anddynamical network analysis (Schreiber and Carley,2004a, 2005a). Tese techniques can be used toexplore the nonlinear relationships resident in thedata and to better understand the analytical impli-cations o theory. Based on these synthetic results,computational analysis can pose research questionsand identiy hypotheses or empirical studies thatmight have otherwise gone unnoticed. In addition, computational modeling canbe used to answer questions that are normativeor plausible. Plausible questions ask what mightbe and explore or go beyond what has trans-pired (Burton, 2003). Computational models areparticularly useul in respect to research on orga-nizational complexity, as real-world complex adap-tive systems do not lend themselves to controlledexperimentation. Trough simulation, we canexplore the complex effects o explanatory vari-



ables in a systematic way. Analyzing data with a focus on theirdynamics and interdependenceis also a critical ele-ment of research that explores a complexity scienceperspective on leadership. Nonlinear dynamicalrelationships inherent in the data create new chal-lenges in data analysis. In addition to the variables

that have been measured in traditional research,such as individual traits or behaviors, new met-rics must be identified that more fully capture thesystem dynamics. Tis is a work in progress andoffers opportunities for methodological research.In addition, new analytical techniques must bedeveloped.

One such technique for rigorously under-standing these relational dynamics is dynamic net-work analysis. Te new dynamic network analysismethodology combines techniques of social net-

work analysis with multi-agent simulations (Carley,2003). Dynamic network analysis represents socio-technical systems in terms of the complex relationalqualities that characterize the interdependencies ofthe system (Krackhardt and Carley, 1998). Also,dynamic network analysis models dynamic changesresulting from natural evolutionary processes suchas learning (Carley and Hill, 2001) and strategicintervention processes such as altering the set ofindividuals within a group (Schreiber and Carley,2004b). Trough the use of dynamic network

analysis, the contextual nature of the network andemergent structure and behavior, including leader-ship events, can be analyzed as well as the effectsof emergence on outcomes such as performance,innovation, and adaptability.

In addition, nonsimulation methods arebeing perfected for developing rigorous longitu-dinal analysis of critical events in emergence overtime. An exemplar is the study of events leading tothe emergence of the Branson, Missouri commu-nity (Chiles et al., 2004). Teir data analysis meth-ods (see pp. 504506) include grounded theory,pattern matching, visual mapping, narrative tech-niques, temporal bracketing, and quantificationusing an event count model analyzed through aPoisson regression. Tis approach resulted in theidentification of four specific eras of emergencepunctuated by a carefully defined series of events;moreover, the researchers were able to generalizefrom these events four drivers of organizationalemergence fluctuation dynamics, positive feed-

back dynamics, stabilization dynamics, and recom-bination dynamics which may be applicable aselements of adaptive leadership and complexityleadership.

Conclusions: Implications for organization

science

By looking for leadership as emerging endog-enously within interactions while beingembedded within organizations, so-called

leaders are not assumed to be directing collectiveaction. Tere is no linear cause-and-effect relation-ship to discover. Instead, leadership becomes aterm that is descriptive of certain social forces atplay among actors, which may include a formalleader. Tis view is consistent with Giddenss (1984)duality of structure in that social structures produceand in some sense lead collective action, while at

the same time being reproduced by those actionsover time. By considering leadership action froman endogenous, time-dependent perspective, weare better able to integrate the time dimension ofsocial systems into organization theory, revealinga unique method for addressing Radcliffe-Browns(1952) challenge to sociological theory: How donew types of social structure come into existence?(cited in Burrell and Morgan, 1979: 56).

Complexity leadership theory begins toaddress this issue by arguing that certain inter-

actions in a social network will have a nonlinearinfluence on future interactions within the net-work. As such, leadership actions may be seen asfield-level effects that potentially catalyze theemergence of new firms (Uhl-Bien et al., in press),proto-institutions (Maguire et al., 2004) or organi-zational fields (Chiles et al., 2004). Field is beingused here in a cognate sense to that found in phys-ics; that is, a matrix underlying a social groupingwhose influence reaches to all the actors withinthat field.

Another application for complexity lead-ership theory focuses on how leadership eventsmay occur within and/or give rise to emergentnodes in a social network. Such an approach pres-ents a unique addition to research on networks,by exploring how and when certain nodes may behighly leveraged within a collective social system.Moreover, by exploring influential nodes in termsof leadership outcomes rather than in terms ofthe individualized roles these nodes might repre-


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sent complexity leadership theory may offer anew way to explain the role of individual actionin the enactment of structures of constraint andopportunity (Ibarra et al., 2005: 359).

Complexity leadership theory also reflectsa new approach to understanding dynamic organi-zational capabilities, including innovation, strategic

alliance making, and merger and acquisition capa-bilities (eeceet al., 1997; Eisenhardt and Martin,2000). eece (2005) has argued that the next hori-zon of management research is how to manage andlead an organizations dynamic capabilities. In ourview, leadership is the emergent result of interactingindividuals such that behavior and resource ele-ments of the organization come together in usefulways a frame that can be formalized in terms ofdynamic organizational capabilities and routines.Such a link between leadership and organizational

capabilities has recently been explored throughcomputational modeling (Hazy, 2006). Such framing reflects the growing use ofcomputational modeling in organization theory(Carley and Prietula, 1994; Carley and Svoboda,1996; Levinthal and Warglien, 1999; March, 1991;March and Olsen, 1976) and the use of comple-mentary modeling techniques in leadershipresearch (Hazy, 2006). Of particular note is the useof Kaufmanns (1993) NK model in organizationalcontexts (Levinthal, 2001; Levinthal and Warglien,

1999) to explore strategic choices and top manage-ment team dynamics. Although that approach hasbeen focused around strategic search, innovation,and learning (e.g., Rivkin, 2000, 2001; Siggelkow,2001, 2002), Siggelkow and Rivkins (2005) approachcomes close to modeling the microdynamics ofleadership.

Moreover, complexity leadership theoryaccepts the juxtaposition of order and apparent cha-otic change as an essential characteristic of social envi-ronments; in this way a complexity framework forleadership is fully integrated within the social psychol-ogy of organizing (Weick, 1979; Weick et al., 2005).Similarly, by framing leadership as emergent and thusendogenous, it can be usefully explored from both theinterpretivist and the functionalist traditions of orga-nizational analysis (Burrell and Morgan, 1979). Complexity leadership theory also offersan important middle ground between computa-tional analyses of individual agents, and the struc-tures that emerge through their interactions. It

explores the actions and events that catalyze emer-gent structures, and by reducing dependence onthe individual the new theory expands our expla-nations about the origin and directionality of trans-formative change.

Te practical and managerial implicationsof complexity leadership theory are legion; we offer

here just a few initial suggestions. By focusing onhow leadership may occur in any interaction, thisnew perspective dramatically expands the poten-tial for creativity, influence, and positive changein an organization. More than simplistic notionsof empowerment, this approach encourages allmembers to be leaders to own their leader-ship within each interaction, potentially evokinga much broader array of responses from everyonein an organization. Complexity leadership theoryprovides a clear and unambiguous pathway for

driving responsibility downward, sparking self-organization and innovation, and making the firmmuch more responsive and adaptive at the bound-aries. In turn, significant pressure is taken off for-mal leaders, allowing them to attend more directlyto identifying strategic opportunities, develop-ing unique alliances, and bridging gaps across theorganizational hierarchy.

Complexity leadership theory generatesnew managerial strategies, including the use oftension to create adaptive change; that is, when

lower-level tensions are induced in the organiza-tion to produce adaptive change that addresses thecomplex challenges facing the organization (Uhl-Bien et al., in press). Goldstein (1994) first showedhow internal tension, carefully introduced, couldhelp spark transformative change; Uhl-Bien et al.(in press) convincingly argue that Jack Welch wasa consistent user of management by tension duringhis tenure at GE. Many more practical suggestionsmay be garnered through this approach.

Making interactions and relationships pri-mary creates a new avenue for improving ethicaland behavioral standards in an organization, for itis much easier to identify a set of appropriate rulesfor interactions between individuals than it is forsomeone (who?) to distinguish between appro-priate and inappropriate leadership behaviors.Complexity leadership theory also provides a path-way for respecting diversity, not only through itsformal emphasis on heterogeneity, but also becausecultural respect is much easier to cultivate through



one-on-one interactions than it is to consistentlyenact through one-to-many leadership exchanges.

In conclusion, Scotts (2004) reflectionson the nature o emerging organizational trendsargue or increased attention to the relationshipsthrough which organizational activity is con-ducted. Whereas leadership research has been

ocused on durable, distinctive properties o enti-ties, a complexity-inspired model o leadership inevents presents an alternative conceptual rame-work, based in relationships, complex interactions,and influences that occur in the space betweenindividuals. As such, it reflects the complexity othe real world, increases the relevance o our leader-ship theories, and provides new insights or stu-dents, researchers, and managers in the complexworld o business.

ReferencesAllport, F.H. (1954). Te structuring o events: Outline

o a general theory with applications to psychology,Psychological Review, ISSN 0033295X, 61: 281303.

Allport, F.H. (1962). A structuronomic conception obehavior: Individual and collective,Journal of Abnor-mal and Social Psychology, ISSN 0096851X, 64: 330.

Allport, F.H. (1967). A theory o enestruence (event-structure theory): Report o progress, AmericanPsychologist, ISSN 0003066X, 22: 124.

Amabile, ., Barsade, S., Mueller, J., and B. Staw (2005).Affect and creativity at work,Administrative Science

Quarterly, ISSN 00018392, 50(3): 367403.Barley, S.R. (1986). echnology as an occasion or struc-turing: Evidence rom observations o C scanners andthe social order o radiology departments,Administra-tion Science Quarterly, ISSN 00018392, 31(1): 78109.

Black, J. A. and Oliver, R. (2004). Proactive versus passiveleader behavior and style influences on the group levelcontext-or-learning, paper presented at the Proceed-ing or the Irish Academy o Management.

Black, J.A., Oliver, R.L., Howell, J.P., and King J.P. (2006).A dynamic system simulation o leader and group e-ects on context or learning, Te Leadership Quarterly,ISSN 10489843, 17(1): 39.

Bluedorn, A. (2002). Images o planning, perormance,and other theory, in F. Yammarino and F. Dansereau(eds)Multi-level Issues in Organizational Behavior andProcesses, Greenwich, C: JAI Press, ISBN 0762311061,6772.

Bonabeau, E. and Meyer, C. (2001). Swarm intelligence:A whole new way to think about business, HarvardBusiness Review,ISSN 00178012, 5: 107114.

Bradbury, H. and Lichtenstein, B. (2000). Relation-ality in organizational research: Exploring the space

between, Organization Science, ISSN 10477039, 11:551564.

Brown, S.L., and Eisenhardt, K.M. (1997). Te art ocontinuous change: Linking complexity theory andtime-paced evolution in relentlessly shifing orga-nizations, Administration Science Quarterly, ISSN00018392, 42(1): 134.

Brown, M.E. and Gioia, D.A. (2002). Making thingsclick: Distributive leadership in an online division oan offline organization,Leadership Quarterly, ISSN10489843, 13(4): 397420.

Bryman, A. (1996). Leadership in organizations, inS.R. Clegg, C. Hardy and W. Nord (eds) Handbook ofOrganization Studies, London: Sage, ISBN 0585323321,pp. 276292.

Buber, M. (1970). I and Tou, New York: Scribners Sons,ISBN 0684717255.

Burrell, G. and Morgan, G. (1979). Sociological Paradigmsin Organizational Analysis, Aldershot: Ashgate, ISBN0566051486.

Burton, R. (2003). Computational laboratories ororganization science: Questions, validity and docking,Computational and Mathematical Organization Teory,ISSN1381298X, 9(2): 91108.

Carley, K.M. (2003). Dynamic network analysis, inP. Pattison (ed.) Dynamic Social Network Analysis:Workshop Summary and Papers, Washington D.C.:Te National Academies Press, ISBN 0309519160,133145.

Carley, K.M. and Hill, V. (2001). Structural change andlearning within organizations, in E.R. Larsen (ed.)Dynamics of Organizations: Computational Modeling

and Organization Teories, Menlo Park, CA: MIPress/AAAI, ISBN 0262621525, pp. 6392.

Carley, K.M. and Prietula, M.J. (eds) (1994), Computa-tional Organization Teory, Hillsdale, NJ: LawrenceErlbaum Associates, ISBN 080581406.

Carley, K.M. and Ren, Y. (2001). radeoffs between per-ormance and adaptability or C3I architectures, paperpresented at the Command and Control Research andechnology Symposium, Annapolis, MD.

Carley, K.M. and Svoboda, D.M. (1996) Modelingorganizational adaptation as a simulated annealingprocess, Sociological Methods and Research, ISSN00491241, 25(1): 138168.

Chiles, ., Meyer, A., and Hench, . (2004). Organiza-tional emergence: Te origin and transormation oBranson, Missouris musical theaters, OrganizationScience, ISSN 10477039, 15: 499520.

Cilliers, P. (1998).Complexity and Postmodernism: Under-standing Complex Systems, New York, NY: Routledge,ISBN 0415152879.

Davis, J.N. (2005). How is charisma routinized? A newlook at an old question, unpublished dissertation,Lubbock, X: exas ech University.


9/1210 E:CO Vol. 8 No. 4 2006 pp. 2-12

Dooley, K.J. and Van de Ven, A.H. (1999). Explainingcomplex organizational dynamics, Organization Sci-ence, ISSN 10477039, 10(3): 358372.

Drath, W. (2001). Te Deep Blue Sea: Rethinking the Sourceof Leadership, San Francisco: Jossey-Bass & Center forCreative Leadership, ISBN 0787949329.

Eisenhardt, K.M. and Martin, J.A. (2000). Dynamiccapabilities: What are they?, Strategic ManagementJournal, ISSN 01432095, 21: 11051121.

Finkelstein, S. (2002). Planning in organizations: Onevote for complexity, in F. Yammarino and F. Dansereua(eds.),Multi-level Issues in Organizational Behavior andProcesses, ISBN 0762311061, pp. 7380.

Gersick, C. (1994). Pacing strategic change: Te case ofa new venture,Academy of Management Journal, ISSN00014273, 37(1): 945.

Giddens, A. (1984). Te Constitution of Society: Outlineof the Teory of Structuration, Berkeley, CA: Universityof California Press, ISBN: 0520052927.

Gioia, D., Schultz, M., and Corley, K. (2000). Orga-

nizational identity, image, and adaptive instability,Academy of Management Review, ISSN 03637425, 25:6381.

Goldstein, J. (1994). Te Unshackled Organization, Port-land, OR: Productivity Press, ISBN 156327048X.

Gronn, P. (2002). Distributed leadership as a unit ofanalysis, Leadership Quarterly, ISSN 10489843, 13:423451.

Guastello, S.J., Craven, J., Zygowicz, K.M., and Bock, B.R.(2005). A rugged landscape model for self-organizationand emergent leadership in creative problem solvingand production groups, Nonlinear Dynamics, Psychol-

ogy and Life Sciences, ISSN 10900578, 9(3): 297233.Hazy, J.K. (2004). A leadership and capabilities frame-

work for organizational change: Simulating the emer-gence of leadership as an organizational meta-capabil-ity, unpublished dissertation, Washington, D.C.: TeGeorge Washington University.

Hazy, J.K. (2006). Measuring leadership effectivenessin complex socio-technical systems, Emergence:Complexity and Organization, ISSN 15213250, 8(3):58-77.

Hazy, J.K. (in press). Computer models of leadership:Foundation for a new discipline or meaningless diver-sion? Te Leadership Quarterly, ISSN 10489843.

Heckscher, C. (1994). Defining the post-bureaucratictype, in A. Donnellon and C. Heckscher (eds) TePost-Bureaucratic Organization: New Perspectives onOrganizational Change, Newbury Park, CA: Sage, 14ISBN 0803957173, pp. 1463.

Ibarra, H., Kilduff, M., and sai, W. (2005). Zoomingin and out: Connecting individuals and collectivitiesat the frontiers of organizational network research,Organization Science, ISSN 10477039, 16: 359371.

Jacobsen, C. and House, R.J. (2001). Dynamics of charismatic

leadership: A process theory, simulation model, and tests,Te Leadership Quarterly, ISSN 10489843, 12(1): 75112.

Jiang, L. and Burton, R. (2002). Internal fit between teamstructure, communication methods and leaders exper-tise, paper presented at the Computational Analysisof Social and Organizational Systems 2002, CarnegieMellon University.

Kahneman, D. and versky, A. (1972). Subjective prob-ability: A judgment of representativeness, CognitivePsychology, ISSN 00100285, 3: 430454.

Kauffman, S. (1993).Te Origins of Order: Self-Organi-zation and Selection in Evolution, New York: OxfordUniversity Press, ISBN: 0195058119.

Krackhardt, D. and Carley, K.M. (1998). A PCANS modelof structure in organization, paper presented at theInternational Symposium on Command and ControlResearch and echnology, Monterrey, CA.

Levinthal, D.A. (2001). Organizational adaptation and en-vironmental selection: Interrelated processes of change,Organization Science, ISSN 10477039, 2: 140-144.

Levinthal, D.A. and Warglien, M. (1999). Landscapedesign: Designing for local action in complex worlds,Organization Science, ISSN 10477039, 10(3): 342357.

Lichtenstein, B., Dooley, K., and Lumpkin, G.. (2006).Measuring emergence in the dynamics of new venturecreation,Journal of Business Venturing, ISSN 08839026,21: 153-175.

Linsky, M. and Heifetz, R.A. (2002). Leadership on theLine: Staying Alive through the Dangers of Leading,Cambridge: Harvard Business School Press, ISBN1578514371.

Maguire, S., Hardy, C., and Lawrence, . (2004). Institu-

tional entrepreneurship in emerging fields: HIV/AIDStreatment advocacy in Canada,Academy of Manage-ment Journal, ISSN 00014273, 47(5): 657-679.

March, J.G. (1991). Exploration and exploitation inorganizational learning, Organization Science, ISSN10477039, 2(1): 7187.

March, J.G., and Olsen, J.P. (1976).Ambiguity and Choicein Organizations, Bergen, Norway: Universitetsforlaget,ISBN 8200014789.

Marion, R. (1999). Te Edge of Organization: Chaos andComplexity Teories of Formal Social Organization,Newbury Park, CA: Sage, ISBN 0761912657.

Marion, R. and Uhl-Bien, M. (2001). Leadership incomplex organizations, Leadership Quarterly, ISSN10489843, 12: 389418.

Marion, R. and Uhl-Bien, M. (2003). Complexity theoryand Al-Qaeda: Examining complex leadership, Emer-gence: Complexity Issues in Organizations and Manage-ment, ISSN 15213250, 5: 5678.

Mead, G.H. (1932). he Philosophy of the Present,Chicago: Open Court Publishing Company, LCCN3219616.

Mead, G.H. (1934). Mind, Self, and Society, Chicago:



University o Chicago Press, ISBN 0226516679.Mead, G.H. (1938). Te Philosophy of the Act, Chicago:

University o Chicago Press, ISBN 0226516660.Meindl, J.R., Ehrlich, S.B. and Dukerich, J.M. (1985).

Te romance o leadership, Administrative ScienceQuarterly, ISSN 00018392, 30(1): 78.

Meyer, A., Gaba, V., and Colwell, K. (2005). Organizingar rom equilibrium: Nonlinear change in organiza-tional fields, Organization Science, ISSN 10477039,16: 456473.

Nowak, M.A., May, R.M., and Sigmund, K. (1995). Tearithmetics o mutual help,Scientific American, ISSN00368733, 272(6): 76-81.

Osborn, R.N., Hunt, J.G., and Jauch, L.R. (2002). owarda contextual theory o leadership, Leadership Quar-terly, ISSN 1048-9843, 13: 797837.

Pearce, C.L. and Conger, J.A. (2003). Shared Leadership:Reframing the Hows and Whys of Leadership, TousandOaks: Sage, ISBN 0761926232.

Radcliffe-Brown, A. (1952). Structure and Function in

Primitive Society, London: Cohen and West, LCCN:543649.

Rivkin, J.W. (2000). Imitation o complex strategies,Management Science, ISSN 00251909, 46: 824-844.

Rivkin, J.W. (2001). Reproducing knowledge: Replicationwithout imitation at moderate complexity, Organiza-tion Science, ISSN 10477039, 12(3): 274293.

Schreiber, C. and Carley, K.M. (2004a). Going beyond thedata: Empirical validation leading to grounded theory,computational and mathematical organization theory,ISSN 1381298X, 10(2): 155164.

Schreiber, C. and Carley, K.M. (2004b). Key personnel:

Identification and assessment o turnover risk, paperpresented at the NAACSOS Conerence Proceedings,Pittsburgh, PA.

Schreiber, C. and Carley, K.M. (2005). Ineffective organi-zational practices at NASA: A dynamic network analy-sis, Carnegie Mellon University, School o ComputerScience, Institute or Sofware Research, International,echnical Report, CMU-ISRI-05-135.

Scott, W.R. (2004). Reflections on a hal-century oorganizational sociology,Annual Review of Sociology,ISSN 03600572, 30: 121.

Seers, A. (2004). Leadership and flexible organizationalstructures, in G. B. Graen (ed.), New frontiers of lead-ership, LMX Leadership: Te Series, Greenwich, C:Inormation Age Publishing, ISBN 1593112394, 2,131.

Seers, A. and Wilkerson, J.W. (2005). oward a model orelational micro-organizing: Social exchange, identity,and structure, unpublished paper.

Siggelkow, N. (2001). Change in the presence o fit: Terise, the all, and the renascence o Liz Claiborne,Academy of Management Journal, ISSN 00014273, 44:838857.

Siggelkow, N. (2002). Evolution toward fit, Admin-istrative Science Quarterly, ISSN 00018392, 47(1):125159.

Siggelkow, N. and Rivkin, J.W. (2005). Speed andsearch: Designing organizations or turbulence andcomplexity, Organization Science, ISSN 10477039,16(2): 101122.

Solow, D. and Leenawong, C. (2003). Mathematical mod-els or studying the value o cooperational leadership inteam replacement, Computational and MathematicalOrganization Teory, ISSN 1381298X, 9(1): 6181.

Strauss, A. and Corbin, J. (1993). Basics of Qualitative Re-search, Newbury Park, CA: Sage, ISBN 0803959400.

eece, D. (2005). Dynamic capabilities: he causes,consequences and challenges o change, in J. Hazy(ed.), Comment at a Symposium at the Academy ofManagement Annual Conference, uesday, August 8,2005, Honolulu, HI.

eece, D.J., Pisano, G., and Shuen, A. (1997). Dynamiccapabilities and strategic management, Strategic Man-

agement Journal, ISSN 01432095, 18(7): 509533.Uhl-Bien, M. (in press). Relational leadership theory:

Exploring the social processes o leadership andorganizing, Te 2006 Yearly Review of Te LeadershipQuarterly, ISSN 10489843.

Uhl-Bien, M., Marion, R., and McKelvey, B. (in press).Complexity leadership theory: Shifing leadershiprom the industrial age to the knowledge era, TeLeadership Quarterly, ISSN .

Van de Ven, A.H. and Poole, M.S. (1990). Methods orstudying innovation development in the MinnesotaInnovation Research Program, Organization Science,

ISSN 10477039, 1(3): 313335.Weick, K.E. (1979). Te Social Psychology of Organizing,

Reading, MA: Addison Wesley, ISBN 0201085917.Weick, K.E. and Roberts, K.H. (1993). Collective mind

in organizations: Heedul interrelating on flight decks,Administrative Science Quarterly, ISSN 00018392,38(3): 357381.

Weick, K.E., Sutcliffe, K. and Obsteld, D. (2005). Orga-nizing and the process o sensemaking, OrganizationScience, ISSN 10477039, 16: 409-421.

Benyamin B. Lichtenstein, Ph.D. (Boston College,

1998) is Assistant Proessor o Management andEntrepreneurship at the University o Massachusetts,Boston. He has helped grow entrepreneurshipprograms at the University o Hartord, SyracuseUniversity, and most recently at U-Mass Boston.Dr. Lichtensteins research expertise ocuses onapplications o complexity science to leadership,entrepreneurial emergence and transormation,and collaboration, trust, and inter-organizationallearning. Proessor Benyamin, as his students


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call him, has published over 40 papers and chap-ters and presented several dozen more, includ-ing articles in internationally recognized journalssuch as Organization Science, Journal of BusinessVenturing, Entrepreneurship Teory and Practice,Human Relations, and theAcademy of ManagementExecutive, where he received the Article o the

Year award in 2000. He regularly provides con-sulting support or entrepreneurial firms and largecompanies. In addition to his proessional work, hefinds his greatest joy these days connecting with hisbeautiul wie Sasha and their two young children,Simeon and Moriah.

Mary Uhl-Bien, Ph.D. (University o Cincinnati,1991) is the Howard Hawks Chair in BusinessEthics and Leadership and the Associate Directoro the Gallup Leadership Institute at the University

o Nebraska-Lincoln. She has published articleson leadership (e.g., relational leadership theory,leadermember exchange, social exchange, andcomplexity leadership) in leading national andinternational journals, including Academy ofManagement Journal,Journal of Applied Psychology,Journal of Management, Human Relations, andTe Leadership Quarterly. She is Senior Editoro the Leadership Horizons Series published byInormation Age Publishing, and serves on the edi-torial boards o Te Leadership Quarterlyand the

Academy of Management Journal. She has consultedwith organizations including State Farm Insurance,Walt Disney World, the U.S. Fish & Wildlie Service,British Petroleum, and the General AccountingOffice.

Russ Marion (Clemson University) is author oTe Edge of Organization (1999), Leadership inEducation (2001), and Leadership in ComplexOrganizations (Te Leadership Quarterly).Marion is currently co-editor o a special editionon Complexity Leadership or Te LeadershipQuarterly, and is co-editor o a volume oLeadershipHorizons: Te Series. He co-organized workshopson complexity leadership at the Center or CreativeLeadership and at George Washington University.Marion has presented on complexity leadership atthe India Institute o echnology, the Institute orManagement Development in Switzerland, and inworkshops on destructing complex movements atthe US Department o Deense.

Anson Seersis currently a Proessor o Managementat Virginia Commonwealth University School oBusiness, and holds a Ph.D. degree in businessadministration rom the University o Cincinnati.His research publications have ocused on workroles and working relationships, encompassing top-ics such as leadermember exchange relationships,

teammember exchange relationships, emergentleadership, role conflict and role ambiguity, teamand organizational commitment, work team effec-tiveness, and task orce pacing. Dr. Seers is a Fellowand Past President o the Southern ManagementAssociation.

James Douglas Orton (Ph.D., University oMichigan) is an expert on strategy-losing andstrategy-remaking processes in the U.S. nationalsecurity community and other loosely coupled

networks. Dr. Orton is a senior aculty memberat the George Washington Universitys ExecutiveLeadership Doctoral Program. He teaches doc-toral seminars on strategy, leadership, organizationtheory, loosely coupled systems, sensemaking pro-cesses, high-reliability organizations, and the crafo organizational scholarship.

Craig Schreiber recently earned his Ph.D. inComputation, Organizations and Society romCarnegie Mellon University. He was a member o

the Center or Computational Analysis o Social andOrganizational Systems (CASOS) at the Instituteor Sofware Research International in the School oComputer Science. He is currently a research asso-ciate or the National Research Council. Previouslyhe has worked on research projects sponsored bythe National Science Foundation, NASA, the Officeo Naval Research and Army Research Labs. Hisinterests include strategic management, organiza-tion and management theory, leadership, influenceand power, organizational structure, organizationalperormance, organizational risk, organizationallearning, knowledge management, inormationtechnology, computational organization science,social network analysis, dynamic network analysis,and model validation.


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