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The Leadership Quarterly 28 (2017) 261–267
Contents lists available at ScienceDirect
The Leadership Quarterly
journal homepage: www.elsevier.com/locate/leaqua
Dynamic viewpoints on implicit leadership and followership
theories: Approaches, findings, and future directions
It has been more than 40 years since Eden and Leviathan (1975) demonstrated how Implicit Leadership Theories (ILTs) guide
raters’ sense-making processes when completing leadership questionnaires. In the intervening years, interest in implicit theories
has been widespread and considerable research has been generated with significant implications for our understanding of leadership and followership processes in organizational settings (Epitropaki, Sy, Martin, Tram-Quon, & Topakas, 2013). Organizational
members are sense-makers and they use their implicit theories to construct a simplified understanding of events that emphasize
human qualities rather than the more complex effects of organization systems (Meindl, 1995). Such research recognizes the active, constructive role of perceivers in the social influence process that is at the heart of leadership. Recent theoretical developments (e.g., Lord, Brown, & Harvey, 2001; Lord & Shondrick, 2011) have highlighted the dynamic nature of leadership and
followership schemas but empirical research has lagged behind. Thus, our motivation for this special issue was to showcase
new empirical and conceptual work that captures ILTs and IFTs as dynamic, context-sensitive and time-sensitive phenomena.
The early work of Lord, Foti, and De Vader (1984) applied social cognitive theory to understanding implicit theories and developed a theory of leadership that describes how categorization influences perception, memory and interactions with a potential
leader. They proposed that ILTs are cognitive categories with a graded structure similar to other types of person (Canter &
Mischel, 1977) and object categories (Rosch, 1978). Rather than being defined by concrete, specific critical features, that distinguish leaders, such categories develop around an abstract set of attributes and behaviors shared by different types of leaders.
Thus, categories form around prototypes, the most typical examples or the most ideal types (Gabora, Rosch, & Aerts, 2008).
These category structures are thought to be learned through experience, although they may originate early on from experience
with caregivers (Keller, 1999, 2003). Individuals rely on these categories to distinguish leaders from non-leaders and the resulting
categorization process is based on either recognition or inferential processes. Leadership perceptions based on recognition-based
processes are the result of a match between the perceiver’s leadership prototype and the perceived characteristics and behavior of
potential leaders, whereas inferential-based processes rely on information about past performance to infer leadership.
In understanding leadership as a social influence process, follower categorization is equally as important as leader categorization (Uhl-Bien & Pillai, 2007). A similar social cognitive process has been hypothesized in the case of Implicit Followership Theories (IFTs; Sy, 2010). IFTs are cognitive categories individuals hold regarding the traits and behaviors typically associated with
followers (Sy, 2010; van Gils, van Quaquebeke, & van Knippenberg, 2010). Similar to ILTs, categories of IFTs can be based on
the most typical instances or the most ideal; however, current research has focused on the former. Perceptions and identification
of an individual as a follower can be recognition-based processes following from a match between the perceiver’s followership
prototype and perceived follower characteristics and behavior, but followership can also be inferred based on performance information (Sy, 2010).
Match with a leader or follower category serves as an antecedent of organizational outcomes, such as leader-member exchange (Coyle & Foti, 2015; Engle & Lord, 1997; Epitropaki & Martin, 2005; Sy, 2010), as well as bias in behavioral ratings
(Hansbrough, Lord, & Schyns, 2015). Thus, work in the area of implicit theories has advanced our understanding of the cognitive
processes underlying leaders’ and followers’ perceptions, interpretations, and sense-making in response to both leadership and
followership behaviors (DeRue & Ashford, 2010; Shamir, 2007; Shondrick & Lord, 2010), showing perceptions of both leaders
and followers are critical to the leadership process.
More recent perspectives (e.g., Hanges, Lord, & Dickson, 2000; Lord & Shondrick, 2011; Lord et al., 2001) have attempted to
capture the inherently dynamic and complex nature of leadership and followership perceptions using a connectionist framework.
In connectionist models, the process unfolds when top-down constraints such as goals and gender combine with bottom-up inputs such as behaviors of a potential leader or follower to activate multiple nodes in the prototype network. Such perspectives
allow for the possibility that ILTs and IFTs are not static and change may take place at the individual, relational, or organizational
http://dx.doi.org/10.1016/j.leaqua.2017.02.004
1048-9843/© 2017 Elsevier Inc. All rights reserved.
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level of analysis. The connectionist perspective offers one potential explanation of how perceptions of leadership and followership
can be fluid and context sensitive, yet still produce coherence and substantial consistency (Foti, Knee, & Backert, 2008; Sy et al.,
2010). Thus, dynamics begin to play a greater role when it is evident that ILTs and IFTs are not fixed in time and place but, instead, are context sensitive.
Overview of the articles
The goal of this special issue was to capture recent theoretical and empirical developments in Implicit Leadership and Followership Theories that address some of the more dynamic aspects of the leadership process. In the five articles that follow, both theoretical and empirical advances are evident, and represent two major themes. The first two articles advance our understanding of
the dynamic aspects of implicit theories by focusing on the influence process and investigating relational schemas or implicit theory congruence. The remaining three articles enhance our understanding of the dynamic nature of implicit theories by focusing on
either the temporal aspect of implicit theories or the role of emotional expression. Table 1 provides an overview of the focus of
each article in terms of characteristics of the implicit theory and method used.
Theme 1 – relational influence processes
Research can capture the dynamic nature of implicit theories by focusing on the leadership relationship, instead of solely on
leader OR follower implicit theories. The leadership relationship can be conceptualized in different ways and at different levels
of analysis. Relational schemas are cognitive structures that represent regularities in patterns of interpersonal relatedness and consist of expected contingences of how the (significant) other will react in a specific social situation (Baldwin, 1992). Relational
schemas include three elements: an interpersonal script, a self-schema and a schema about the other person. Epitropaki et al.
(2013) considered relational schemas of leadership a promising line of research that can extend ILT and IFT research to the dyadic
level of analysis to help understand the dynamic interplay between ILTs and IFTs.
Tsai, Dionne, Wang, Spain, Yammarino and Cheng (2017) respond to the call for an in-depth understanding of relational leadership schemas. They specifically examined two types of relational schemas, namely expressive relational schemas (ERS) that are
associated with social support and instrumental relational schemas (IRS) that emphasize short-term economic exchanges. They
further investigated the effects of inter-individual relational schemas’ congruence on leader-follower relationships. By using polynomial regression and response surface methodology, they showed that ERS congruence was associated with positive followerrated LMX. Interestingly, both IRS congruence and incongruence were found to have a negative impact on LMX. Their findings
have important implications for ILTs as well as for LMX theory and research. They not only highlight the role of relational schemas
for leader-follower interactions but also point to the need for a closer look into the content of these relational schemas. Their results suggest that individuals (leaders or followers) who hold schemas of relationships as mainly short-term economic exchanges
(versus a deeper affective connection) will be less likely to invest the time and energy to cultivate high quality interactions. One
could even argue that relational schemas may neutralize (in the case of IRS congruence) or accentuate (in the case of ERS congruence) the importance of LMX quality in organizational settings.
The degree of congruence or incongruence in implicit theories held by leaders and followers is at the core of the mutual influence process (Coyle & Foti, 2015; Engle & Lord, 1997). Specifically, interpersonal congruence (the extent to which leaders
and followers hold similar implicit theories) are important influences on how individuals perceive relationship quality with
their partner (Epitropaki et al., 2013). Lord and Maher (1991) provide a theoretical framework for the interpretation of the effects
of both followers’ and leaders’ implicit theories on their dyadic relationship. They move away from the simplistic conceptualizations that assume leaders’ behaviors affect followers’ behaviors and vice versa, to propose that these relationships are affected by,
and filtered through, the implicit theories of both individuals.
Table 1
Overview of articles.
Authors
Recognition or
inference process
ILT/IFT/both
Typical/ideal
prototypes
Implied/explicitly
measured time
Method
Theme 1 – relational influence process
Riggs & Porter (2017)
ILT
Recognition
Typical
Implied
Tsai, Dionne, Wang, Spain,
Yammarino, & Cheng (2017)
ERS and IRS (relational
schemas)
Recognition
Ideal
Implied
Alipour, Mohammed, & Martinez
(2017)
Chiu, Balkunid, & Weinberg
(2017)
Trichas, Schyns, Lord, & Hall
(2017)
Theme 2 – dynamic representation of implicit theories
Temporal ILTs (TILTs)
Recognition
Ideal
Explicitly theorized
and IFTs (TIFTs)
ILT
ILT
Inference
Recognition
Typical
Typical
Polynomial regression and
response surface
Polynomial regression and
response surface
Theory paper
2-Wave study
Social network analysis, HLM
Implied
Experimental study in a banking
context ANOVAs, SEM
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Interpersonal congruence is the focus of the second article of the special issue. Riggs and Porter (2017) examine how congruence between leader and follower implicit leadership theories impacts LMX. The authors contend that congruence in ILTs triggers
automatic categorization processes. Namely, leaders and followers who hold similar mental models of leaders will more inclined
to view each other as “leader-like” therefore, congruence of ILTs serves as a heuristic to differentiate leaders from non-leaders.
Furthermore, based on the similarity hypothesis (i.e., people prefer similar others), ILT congruence fosters a positive evaluation
of the potential relationship partner as well as a willingness to confer leadership status on that individual thereby setting the
stage for the development of high quality leader-follower relationships. Using polynomial regression and response surface methodology to assess congruence, Riggs and Porter found that congruence between leader and follower ILTs was positively associated
with LMX while less congruence was associated with lower quality LMX.
Theme 2 – dynamic representations of implicit theories
Understanding the dynamic nature of implicit theories has been the focus of much theorizing. The remaining three articles
capture the dynamic perspective of ILTs/IFTs by considering how implicit theories may change over time and may vary based
on the context.
The first perspective proposes that components of time should be incorporated directly into ILTs and IFTs. In their paper,
Alipour, Mohammed and Martinez (2017) argue that temporal individual differences are an important factor in the context of
ILTs and IFTs. They specifically focus on four time-based individual differences, namely time patience, time perspective,
polychronicity and pacing style and introduce the concepts of temporal ILTs (TILTs) and IFTs (TIFTs). They specifically propose
that individuals have prototypes about the temporal attributes of ideal leaders and followers. Temporal ILTs are likely to best
be represented by a 3-factor structure that includes a future-time perspective, polychronicity and deadline pacing. Temporal
IFTs are also represented by a 3-factor structure but their content is different. They include present-time perspective, early pacing
and time patience. They further outline the implications of inter-individual TILTs and TIFTs congruence on leader-follower interactions. If, for example, the follower holds a temporal prototype of an ideal leader as future-oriented, polychronic and not a deadline pacer but his/her actual manager is present-oriented, monochronic and deadline pacer, this is likely to create coordination
difficulties and negatively affect the leader-follower interactions. They also highlight the possibility of national cultural differences
of TILTs and TIFTs content. By using connectionist models as their guiding framework, they further present a heuristic example of
a connectionist TILTs and TIFTs network at the subordinate level and illustrate the role of contextual constraints such as organizational culture in the generation of temporal leadership and followership prototypes.
The second perspective broadens the conceptualization of bottom up process in the connectionist model to include when a
leader’s facial expression conveys different emotions. Trichas, Schyns, Lord and Hall (2017), in an experimental study conducted
in an organizational setting, examined the effects of leader’s happy vs. nervous emotions on leadership perceptions and ILTs endorsement. Their results showed that in the condition of a happy emotional display by the leader, participants exhibited higher
endorsement of prototypical ILTs (e.g., sensitivity) and lower endorsement of antiprototypical traits (e.g., tyranny). In general,
the leader’s display of happy facial expressions resulted in higher leadership ratings, higher trait ratings, greater correlations
among trait ratings and greater dependence of trait ratings on leadership perceptions. There are important implications of this
study for the dynamic nature of ILTs (and IFTs). Their study supports the core argument of connectionist models that leadership
categories are context-sensitive and vary both within and between individuals. If a minimal manipulation, such as a facial emotional expression, was enough to generate change in the salience of prototypical vs. antiprototypical traits, the possibility of ILTs
and IFTs malleability in very short time-lags (even to the point of daily fluctuation) needs to be further examined.
As noted previously, a connectionist framework captures the inherently dynamic nature of leadership perceptions. One important implication of a connectionist perspective is that the leader prototype can be activated by characteristics of the culture, leader, follower or context. Chiu, Balkunid, and Weinberg (2017) explore how information about the context- the manager’s position
in a social network- activates followers’ leadership perceptions. According to the network perspective, individuals are embedded
within networks of interconnected relationships that provide opportunities for and constraints on behavior. The authors assert
that these social networks provide followers with information about a manager’s power and influence which, in turn, activates
the leader prototype. Chiu et al. (2017) conducted both a longitudinal and cross-sectional study to test these ideas. Across two
studies they found that managers’ network centrality activated followers’ leadership perceptions. Moreover, the relationship
between managers’ network centrality and followers’ leadership perceptions was mediated by managers’ social power.
Future research and new directions
To begin, we offer some important clarifications for those doing research in this area.
1) ILTs are not synonymous with actual leader behavior. Instead, the literature focuses on perceptions of leaders rather than objective leader behavior. For example, in Lord and Maher’s (1991) reciprocal influence model, social perception is conceptualized as a sense-making process that focuses on the interpretation of behavior rather than leader behavior per se. Moreover,
reliance on ILTs and ILFs may trigger “false alarms” in person perception whereby observers incorrectly report behaviors
that were not observed yet are consistent with the leader prototype (Phillips & Lord, 1982). Therefore, reliance on ILTs may
introduce a bias into leadership ratings. Epitropaki and Martin (2005) showed that employees relied more on their ILTs to
make sense of their relationship with their manager when their intrinsic motivation was low. Their finding was consistent
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with Macrae and Bodenhausen’s (2000) suggestions that individuals resort more to schematic thinking when motivation is
low. The Trichas et al. (2017) study in this special issue further emphasizes the role of emotion and mood as a contributing
factor to individuals’ reliance on prototypical (in conditions of positive emotion) and antiprototypical (in conditions of negative emotion) leadership traits. This is an interesting avenue for future research. Under which conditions are individuals more
likely to resort to categorical thinking and fill in perceptual gaps based on their ILTs and IFTs rather than engage in careful information processing of exhibited leadership behaviors?
2) Notably, implicit leadership theories are not outside an individual’s conscious awareness. Rather the term implicit, as used in
implicit leadership theories, refers to individuals’ preconceptions about traits (e.g., the patterning of leadership variables) that
they bring to the leadership situation (Eden & Leviathan, 1975). Individuals have an internal working model or schema comprised of certain traits and characteristics that are typically associated with the word “leader”. Moreover, as demonstrated by
previous research, individuals are quite aware of the content of these categories; yet, at the same time, individuals may be unaware of the impact of these categories (e.g., false memories) on their decision making and judgments. As shown in the
Trichas et al.’s (2017) study, embodied characteristics and states such as facial expressions and emotion may impact leadership
perceptions outside conscious awareness. Therefore, contrary to early perspectives that imposed a strict dichotomy of implicit
vs. explicit processing, the current consensus is that most schemas may be processed implicitly and explicitly (Epitropaki et al.,
2013).
3) Implicit leadership theories have a clearly defined center but fuzzy boundaries. Therefore, even though there may be wide
spread agreement about certain characteristics such as intelligence associated with the word “leader” (e.g. Lord et al., 1984;
Offermann, Kennedy, & Wirtz, 1994) there is still variation based on individual differences. For example, previous research
has found that some individuals are more likely to endorse antiprototypical leader characteristics (Bray, Foti, Thompson, &
Wills, 2014; Foti, Bray, Thompson, & Allgood, 2012; Keller, 1999). Moreover, the GLOBE studies (Den Hartog, House,
Hanges, & Ruiz-Quintanilla, 1999) found that while leader attributes associated with charismatic/transformational leadership
were universally endorsed, the endorsement of other leader attributes-such as risk taking, ambition, compassion, enthusiasm,
sensitivity, self-sacrifice, and willfulness was culturally contingent.
4) There is an important and meaningful difference between typical leaders and ideal leaders. As noted by Junker and van Dick
(2014), implicit theories are represented on two dimensions: the norm of the prototype and the valence of the prototype. The
norm of the prototype refers to whether the category is represented by the most representative or typical characteristics, or
the most ideal. The valence of the prototype refers to whether the attributes contained in the prototype are positive or negative. For example, Schyns and Shilling (2011) found that ILTs were comprised of both effective and ineffective attributes. Likewise, Epitropaki and Martin (2005) report that the term “leader” is associated with both positive and negative characteristics.
On the other hand, some research (e.g., Foti et al., 2012; Keller, 1999) has focused on ideal leaders in order to capture leadership preferences based on individual differences.
As with any complex area of research, the theory is ahead of the data. This is clearly the case in the study of dynamic approaches to implicit theories. We sought to close this theory-data gap with the inclusion of the empirical studies reported
in this special issue. Beyond the clarifications for conducting research in this area, we offer the following insight and new directions for future empirical research.
Riggs and Porter (2017), Tsai et al. (2017), and the authors of numerous prior studies (Coyle & Foti, 2015; Engle & Lord, 1997;
Topakas, 2011) demonstrate that the extent to which leaders and followers hold congruent ILTs and IFTs impacts both partners’ assessment of relationship quality (e.g. LMX). These variable-oriented investigations, however, assume all characteristics
(e.g. intelligent, hardworking) are equally meaningful. Studying congruence of implicit theories can be meaningfully extended
using a person-oriented approach. The person-oriented approach is so labeled because it takes into account intra-individual
variation within a system of variables (Bergman & Vargha, 2013). That is, the person-approach acknowledges that variables
can combine differently for some types of individuals than they do for others. Thus, rather than focusing on the variables
per se, and how they relate within the population as a whole, person-oriented research identifies and compares subgroups
of individuals sharing similar patterns of variables within a population (Foti & McCusker, 2017). Adopting a pattern-oriented
approach allows researchers to gain a more in-depth examination of the interplay between content and structure of implicit
theories, thus enhancing understanding of the relationship between implicit theories (Foti & Coyle, 2015). Such research
should examine how profiles of ILTs and IFTs are related as well (e.g. whether individuals with a certain pattern of ILTs are
likely to hold a certain pattern of IFTs) as well as whether this correspondence predicts relationship-oriented outcomes.
Furthermore, comparing these correspondence rates for leaders and followers may also be fruitful.
Future research should examine the extent to which congruence on implicit theories of typical vs. ideal leaders differentially
predicts relevant work outcomes (e.g. organizational citizenship behaviors, counterproductive work behaviors, work-family
conflict). Further examination of both types of implicit theories in the context of the same study would provide much needed
clarity regarding the fruitfulness of using ILTs and IFTs in leadership training models and team-building exercises.
Taking a different approach, future research using a person-oriented approach could also focus on examining profiles of congruence at the dyadic level rather than the individual level. This approach differs from examining the correspondence an
individual’s ILTs and IFTs by identifying subgroups (i.e. classes) of dyads with similar multidimensional patterns of implicit theory congruence (Foti et al., 2012). This approach contributes a unique perspective of dyadic congruence to literature in two
important ways: 1) by identifying critical points of congruence between leaders and followers, and 2) by examining congruence on ILTs and IFTs in the context of the same analysis. By assigning dyads to patterns using posterior probabilities, we can
then assess the extent to which sub-group membership is more predictive of relationship-oriented outcomes (e.g. LMX,
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perceived support, contribution to the relationship) (Bray, Lanza, & Collins, 2010). Follow-up studies could then assess the extent to which additional information can be captured using patterns of dyadic congruence on relational schemas to predict relationship-oriented outcomes.
One further avenue for future research is to address the effects of implicit theories on the measurement of behavior (Eden &
Leviathan, 1975; Hansbrough et al., 2015; Rush, Thomas, & Lord, 1977). In particular, leadership perceptions can be subject to
gap filling processes regardless of whether they are the result of recognition-based or inferential-based processes. Individuals
using recognition-based processes may endorse items that seem familiar (because they fit the pattern of behaviors that are
typically associated with leaders) but did not actually occur. Inferential-based processes such as attributions can also be subject
to automatic, gap filling processes. For example, Taylor and Fiske (1978) contend that attributions are a “top-of-the head” phenomenon rather than more of a controlled process. In particular, attributions are highly dependent on where the observer’s
attention is focused as the perceiver may accept the first plausible explanation for an event rather than engage in a more extensive search process (Lord & Shondrick, 2011). Indeed, Phillips and Lord (1981) have demonstrated that because leaders are
salient individuals may attribute the performance of the group to leaders. Such attributions are likely the result of knowledge
connectionist systems. In a connectionist network, when some prototypical leader characteristics are activated, they also activate the entire network of the leader prototype which may promote gap-filling processes. In general, such associative processing is the default processing mode (Fiske & Taylor, 2013). Therefore, as observed by Shondrick, Dinh, and Lord (2010), the use
of categorization-based processes is one of the biggest obstacles to leadership measurement.
Focusing on events may provide a mechanism to increase the accuracy of leadership ratings. Doing so would encourage raters
to move away from the gap-filling processes associated with semantic memory and instead rely on the rich, vivid details associated with episodic memory. Indeed, episodic memory is the only kind of memory system that allows individuals to consciously
re-experience past events (Tulving, 2002). Therefore, tapping into episodic memory by use of prior events may be particularly
helpful to obtain retrospective accounts of leadership. For example, Hansbrough, Lord, and Schyns (2016) report that validity is
increased for scales based on episodic memory compared to scales based on semantic memory. Morgeson (2005) found substantial agreement in leader ratings when raters were focused on a specific event. Thus it may be possible to increase accuracy and
reduce the use of gap filling processes, such as ILTs, by designing leadership ratings to focus on specific events rather than general
impressions.
The role of time needs further attention by ILTs and IFTs researchers. Although Alipour et al. (2017) offer a novel lens on the
temporal dimensions of implicit theories and Trichas et al. (2017) indicate the possibility for high trait fluctuation, some core
questions about change outlined in our call for papers warrant additional empirical evidence. How do ILTs and IFTs change
over time and which patterns of change can we observe in narrow time spans (e.g., diary studies) vs. longer time spans (e.g.,
from youth to late adulthood)? As Lord (2017) notes “leadership science tends to emphasize entities over processes as explanations…. and it under-emphasizes the contextual factors that cause events to occur, particularly the unruly quantum events that
dramatically change system states, and which may ultimately affect the performance outcomes we hope to predict from leadership theory” (p. 18). Despite the dynamic conceptualization of ILTs and IFTs in recent years, the absence of longitudinal studies is
striking. With the exception of Foti et al. (2008) who focused on the process of recreating connectionist leadership representations in terms of attractors and trajectories in two independent studies, limited empirical work has attempted to capture the dynamic nature of ILTs. Epitropaki and Martin (2005) examined the effects of ILTs on LMX using a 12-month time lag and found
evidence for stability. It is however possible that such a long time lag may not capture the dynamic fluctuations of ILTs and IFTs.
As Day (2014) points out, if few measurements are used, then there is the danger of missing the curvilinear nature of change.
Day and Sin (2011) for example, examined the developmental trajectories of individuals participating in team-based leadership
development activities. Using latent growth modeling techniques to analyze leadership development over 4-time points showed
a curvilinear pattern (an overall negative leadership trajectory with a slight upturn in the last measurement). We clearly need
intensive longitudinal data (ILD) with multiple and short measurement intervals in order to capture the dynamic nature of ILTs
and IFTs. Experience sampling methodology (ESM) studies (e.g., Alliger & Williams, 1993) will be particularly relevant in this
context.
Finally, questions regarding the implications of leader and follower identity for ILTs and IFTs outlined in our call for papers remain unanswered. In their recent multilevel review of leader and follower identity, Epitropaki, Kark, Mainemelis, and Lord (2016)
highlighted the role of leadership and followership schemas as central components of leader and follower identities. They further
argued that intra-individual congruence of ILTs and enacted leadership behaviors will increase the salience of a leader identity on
the individual level. It will also increase the chances of leader identity claiming in a relational context and the view of the person
as embodying the group leadership prototype on the collective level. On the other hand, intra-individual ILTs incongruence may
result to difficulties in transitioning into a leadership role.
Conclusion
Overall, this special issue was meant to bring together articles using a variety of theoretical and methodological advancements
to enhance our understanding of the role of implicit theories in the leadership process. A better understanding of ILTs and IFTs is
essential to understanding how the leadership processes develop and unfolds over time. For example, as noted by DeRue and
Ashford (2010), if a would-be leader makes a leadership (influence) attempt but others do not respond in turn with following
behavior(s) then it is not leadership. Future research needs to take a more dynamic and perhaps a more systems oriented
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perspective. Further advancement of knowledge in the area of implicit theories will require a better match between our dynamic
and process oriented conceptualization of the leadership and our research (Dinh, Lord, Gardner, Meuser, Liden, & Hu, 2014).
We would like to thank Leanne Atwater, Senior Editor, and the associate editors of The Leadership Quarterly for supporting a
special issue on implicit leadership and followership theories. Moreover, this special issue would not have been possible without
the contributions of the reviewers listed below. We would like to thank them for their insightful, constructive, and detailed comments that helped to improve these manuscripts. We realize that the production of special issues requires additional time commitments from the LQ editorial board members and ad hoc reviewers, and we greatly appreciate the time and effort they
invested. Thank you again.
Jan Ketil Arnulf
Roya Ayman
Michelle Bligh
Kimberley Breevaart
Douglas Brown
Melissa Carsten
Shane Connelly
Dorothy Carter
Barbara Crosby
Fred Dansereau
Deanne Den Hartog
Tobias Dennerlein
Reinout de Vries
Marion Eberly
Cecile Emery
Jörg Felfe
Rosalie Hall
Paul Hanges
Crystal Hoyt
Ronald Humphrey
Dejun Tony Kong
Robert Liden
Yonghong (Tracy) Liu
Robert Lord
Robin Martin
Adam Meade
Susan Murphy
Austin Lee Nichols
Richard Osborn
James S. Phillips
Raj Pillai
Ronald Riggio
Terri Scandura
Charles Scherbaum
Jan Schilling
Birgit Schyns
Carl