The Leadership Quarterly

The Leadership Quarterly

The Leadership Quarterly 24 (2013) 858–881

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The Leadership Quarterly

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Implicit Leadership and Followership Theories “in the wild”: Taking stock of information-processing approaches to leadership and followership in organizational settings

Olga Epitropaki a,b,⁎, Thomas Sy c, Robin Martin b, Susanna Tram-Quon c, Anna Topakas d

a ALBA Graduate Business School at the American College of Greece, Athens, Greece b Aston Business School, Aston University, UK c University of California, Riverside, United States d University of Sheffield, UK

a r t i c l e i n f o

⁎ Corresponding author at: ALBA Graduate Business E-mail addresses: oepitrop@alba.edu.gr (O. Epitrop

a.topakas@sheffield.ac.uk (A. Topakas).

1048-9843/$ – see front matter © 2013 Elsevier Inc. A http://dx.doi.org/10.1016/j.leaqua.2013.10.005

a b s t r a c t

Article history: Received 17 June 2013 Received in revised form 17 September 2013 Accepted 3 October 2013 Available online 30 October 2013

Editor: Chet Schriesheim highlight their practical utility for the exercise of leadership and followership in applied settings.We

For over 30 years information-processing approaches to leadership and more specifically Implicit Leadership Theories (ILTs) research has contributed a significant body of knowledge on leadership processes in applied settings. A new line of research on Implicit Followership Theories (IFTs) has re-ignited interest in information-processing and socio-cognitive approaches to leadership and followership. In this review,we focus on organizational research on ILTs and IFTs and

clarify commonmisperceptions regarding the implicit nature of ILTs and IFTs, reviewboth direct and indirect measures, synthesize current and ongoing research on ILTs and IFTs in organizational settings, address issues related to different levels of analysis in the context of leadership and follower schemas and, finally, propose future avenues for organizational research.

© 2013 Elsevier Inc. All rights reserved.

Keywords: Information-processing Implicit Leadership Theories (ILTs) Implicit Followership Theories (IFTs) Schemas Leader categorization theory

1. Introduction

Twenty-two years after Lord andMaher (1991) published their seminal book “Leadership and Information processing: Linking perceptions with performance”, socio-cognitive approaches are still at the forefront of leadership research. In addition to Implicit Leadership Theories (ILTs) research that spans over 30 years, a new and exciting field that also adopts an information-processing perspective has emerged, that of Implicit Followership Theories (IFTs, Shondrick & Lord, 2010; Sy, 2010). Since its inception, considerable research has been generated with significant implications for our understanding of leadership and followership processes in organizational settings (Carsten, Uhl-Bien, West, Patera, & McGregor, 2010; Shondrick & Lord, 2010; Sy, 2010; Van Gils, van Quaquebeke, & van Knippenberg, 2010).

Theories of top-down cognition (e.g., Galambos, Abelson, & Black, 1986; Lord & Maher, 1991) suggest that people rely on cognitive simplification mechanisms or schemas to cope with information complexity (e.g., Fiske & Taylor, 1991). These socio-cognitive processes also operate in organizational settings and research has shown that individuals are naturally inclined to classify people as leaders and/or followers (Engle & Lord, 1997; Lord, 1985; Lord, Foti, & Phillips, 1982; Lord & Maher, 1991; Sy, 2010). People are categorized as leaders on the basis of the perceived match between their behavior or character and the attributes of a pre-existing leader category or prototype, i.e., the Implicit Leadership Theories, the follower holds in memory. A similar socio-cognitive process of comparison has also been hypothesized in the case of Implicit Followership Theories (Sy, 2010).

School at the American College of Greece, 6-8 Xenias Str., 115 28, Athens, Greece. Tel.: +30 210 8964531. aki), thomas.sy@ucr.edu (T. Sy), r.martin@aston.ac.uk (R. Martin), stram001@ucr.edu (S. Tram-Quon),

ll rights reserved.

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There have been two (relatively) recent reviews published on Implicit Leadership Theories (Shondrick, Dinh, & Lord, 2010; Shondrick & Lord, 2010). Specifically, Shondrick et al. (2010) reviewed key findings in social categorization theory and applied recent developments in cognitive science to explain how an understanding of symbolic, connectionist and embodied representation of knowledge can benefit leadership measurement. Their review primarily focused on memory processes in relation to leadership measurement and limited emphasis has been placed on the practical utility of ILTs in organizational settings. Similarly, Shondrick and Lord (2010) focused more on the prototype generation process and the perceptual and memory processes underlying ILT and IFT formation, as well as their implications for behavioral leadership measures. Both reviews utilize a cognitive science perspective and present mainly experimental findings whereas limited emphasis is placed on the “real-world” applicability of ILTs and IFTs and their implications for leader–follower relationships, job attitudes, affect and performance in organizational settings. A guiding theme in social cognition is, however, application to real-world settings (Fiske & Taylor, 1991) and socio-cognitive research recognizes both the importance of what goes on inside the mind, as well as the behavior that takes place in the external world.

Our review will adopt a different, but complementary, perspective to the previous two reviews and will take ILTs and IFTs “in the wild” (a term borrowed from Day & Sulsky, 2000). We will specifically attempt to extend previous research on implicit leadership and followership by explicitly focusing on organizational research on ILTs and IFTs and their practical utility for the exercise of leadership and followership in applied settings. Our review will cover both ILTs and IFTs, with the latter being a new and promising line of research. As part of this review, we will also clarify the multiple meanings of the term ‘implicit’ (e.g., the confusion over the various meanings of ‘awareness’). Moreover, we will review both direct and indirect measures of ILTs and IFTs, including projective methods and implicit association tests, amongst others (Uhlmann et al., 2012). We will also extend previous reviews by focusing on newly proposed (and in some cases tested) leadership schemas (such as, Relational Schemas and Leadership Structure Schemas) that highlight the importance of a multi-level view of ILTs and IFTs (individual, dyadic and collective).

2. An overview of Implicit Leadership Theories and Implicit Followership Theories in applied settings

Implicit Leadership Theories (ILTs) are defined as cognitive structures or prototypes specifying the traits and abilities that characterize leaders (Lord, Foti, & De Vader, 1984; Lord & Maher, 1991). Similarly, Implicit Followership Theories (IFTs) are defined as cognitive structures and schemas about the traits and behaviors that characterize followers (Sy, 2010). These schemas are developed on the basis of socialization processes and prior experiences with leaders and followers, are stored in memory and are activated when individuals interact with someone resembling that category, such as actual leaders or followers (e.g., Epitropaki & Martin, 2004; Kenney, Schwartz-Kenney, & Blascovich, 1996). Whereas explicit theories are constructions of scientists that are based on data and scientific observation, implicit theories are constructions by people (laypersons or scientists) that reside in the minds of these individuals (Levy, Chiu, & Hong, 2006; Rosenberg & Jones, 1972; Sternberg, 1985). Thus, they represent subjective reality and perceptions, in contrast to (explicit) scientific theories that strive to approach objective reality (Sternberg, 1985). Understanding implicit theories is important as they set up an interpretative frame within which information is processed (Chiu, Hong, & Dweck, 1997). Regardless of accuracy, individuals use their ILTs and IFTs as a sensemaking function (Weick, 1995) to understand and respond to leaders or followers (Shondrick & Lord, 2010; Sy, 2010). In fact, individuals rely on and make use of their implicit theories even when confronted with overwhelming contradictory scientific evidence (Lewandowsky, Oberauer, & Gignac, 2013).

The importance of ILTs for understanding managerial leadership took a long time to be recognized as early studies mainly viewed them as a potential source of bias in leadership measurement (e.g., Eden & Leviathan, 1975; Gioia & Sims, 1985). It was studies like those of Lord et al. (1984) and Cronshaw and Lord (1987) that moved research away from considering ILTs as a source of measurement error by emphasizing the effect of ILTs on people’s leadership perceptions, and acknowledging their utility as an explanatory framework for organizational leadership. Still, the vast majority of studies on ILTs conducted in the 1970s to early 1990s focused mainly on issues of content and measurement using samples of undergraduate students in laboratory experiments to the neglect of studies in organizational contexts (Lord & Maher, 1991). Lord and Maher (1991) had, however, offered a strong theoretical rationale for the role of ILTs in applied settings. They had specifically argued, for example, that within the context of Leader–Member Exchanges (e.g., Graen & Uhl-Bien, 1995) people can use ILTs as both a basis for interpreting the behavior of their dyad partner (in the case of followers) and as a foundation for generating their own behavior (in the case of leaders). It was only during the late 1990s (Engle & Lord, 1997) and 2000s (Epitropaki & Martin, 2005) that organizational research was conducted to explicitly address the effect of ILTs in the context of real manager-follower dyads.

On the other hand, Implicit Followership Theories (IFTs) research, building on the insights from the ILTs research, was quicker to examine the impact of IFTs in actual organizational settings (e.g., Sy, 2010; Whiteley, Sy, & Johnson, 2012). Still the total number of studies examining ILTs and IFTs in organizational settings is relatively small in comparison to research conducted in laboratory settings or research focusing on other leadership constructs such as, LMX and transformational leadership. One of the reasons could be conceptual confusion over the term ‘implicit’ which may deter organizational researchers from conducting ‘explicit’ field research (e.g., how can implicit theories be assessed via self-reports in field settings if participants lack awareness of such constructs?). It is thus important to clarify the meaning of implicit in this particular context.

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3. What is ‘implicit’ in ILTs and IFTs?

As explained, the term ‘implicit theory’ denotes that ILTs and IFTs reflect lay theories of leadership and followership (vs. ‘explicit’ or formal scientific theories). A common criticism that organizational researchers face when studying ILTs and IFTs is that they are assessing implicit phenomena through an explicit methodology (i.e., a direct assessment, such as, self-reporting). The term ‘implicit’ reflects that ILTs and IFTs tend to operate in implicit (preconscious) fashion, although they may also be processed explicitly (consciously) (Lord & Maher, 1991). In contrast to early perspectives that imposed a strict dichotomy of explicit vs. implicit processing, the current consensus is that most schemas may be processed explicitly and implicitly, with implicit processing as the default mode and explicit processing operating only in situations when sufficient motivation and opportunity (e.g., time and cognitive capacity permitting) are present (Bargh, 2006; Fazio, 1990; Gawronski & Payne, 2010; Smith & DeCoster, 2000; Strack & Deutsch, 2004).

Implicit processing within the leadership domain (i.e., with regards to ILTs and IFTs) means that individuals tend to lack impact awareness, which reflects individuals’ awareness of the influence of an activated schema on action tendencies. Thus, individuals may be unaware that certain schemas have been activated and its processing has impacted their action tendencies. For example, a negative interaction with a follower may activate schemas associated with “bad followers” that may subsequently, without full conscious awareness, have a momentary impact on one’s action tendencies to view and treat followers in a negative manner. Similarly, facial expressions (Schyns & Mohr, 2004; Trichas & Schyns, 2012) and embodied aspects of information processing (Lord & Shondrick, 2011) may impact action tendencies outside conscious awareness. Implicit processing does not necessarily imply a lack of content awareness, which reflect individuals’ awareness of the schema itself (i.e., phenomenon that is accessible to conscious introspection) (Gawronski, Hofmann, & Wilbur, 2006). The notion that lack of content awareness is a necessary precondition for implicit processing is a common misperception (Bargh, 2006; Fazio & Olson, 2003; Gawronski, 2009; Gawronski & Payne, 2010; Gawronski et al., 2006; Greenwald & Banaji, 1995). Reviews of the literature show that there is not strong evidence that individuals possess implicit theories to which they lack introspective access (De Houwer, Teige-Mocigemba, Spruyt, & Moors, 2009; Fazio & Olson, 2003; Gawronski & Bodenhausen, 2006a; Gawronski et al., 2006). Awareness may vary across context and time, and depends on individuals’ motivation, as well as situational constraints (e.g., time constraints and cognitive load) (Fazio & Olson, 2003).

Indeed, research has demonstrated that individuals possess content awareness of their implicit theories in a variety of phenomena, including morality (Chiu et al., 1997), emotions (Izard, 2007), employee voice (Detert & Edmondson, 2011), person malleability (Heslin, Latham, & VandeWalle, 2005), and leadership (Epitropaki & Martin, 2004, 2005; Kenney et al., 1996; Lord et al., 1984; Offermann, Kennedy, & Wirtz, 1994). More germane to the leadership domain, corroborating evidence demonstrates that leaders and followers have introspective access to ILTs and IFTs (Carsten et al., 2010; Epitropaki & Martin, 2004, 2005; Kruse & Sy, 2011; Kruse, Sy, & Tram, 2012; Offermann et al., 1994; Sy, 2010; Sy et al., 2010; Tram-Quon & Sy, 2013; Whiteley et al., 2012). Individuals may have introspective access (content awareness) to many phenomena (e.g., explain their assumptions and beliefs about followers) and yet at any given moment lack impact awareness whereby the activation of such phenomena (e.g., followers should be conformists) may impact their action tendencies (e.g., evaluate dissenting followers negatively because they do not fit the prototypical model of a conformist follower).

4. Theoretical underpinnings of ILTs and IFTs

Prior to reviewing organizational research focusing on ILTs and IFTs we will give a very brief overview of their main theoretical foundations.

4.1. Early approaches

Lord andMaher (1991) proposed four competingmodels of information-processing applicable to leadership (and followership) research: (a) The rational model which assumes that individuals have access to all relevant information and unlimited capacity in processing this information. Although often not representative of the kind of processing that takes place, this model was considered to be valuable when used as a benchmark model of optimal information processing. (b) The expert model which differentiates between experts who rely on elaborate, well-organized knowledge structures on the basis of their extensive experience in a particular context, and novices who need to engage in more demanding and complex cognitive processes. (c) The six-stage circular cybernetic model which is dynamic and assumes simultaneous processing of past information, current behavior and future planning. This model proposes that implicit theories shape expectations and behaviors via self-fulfilling mechanisms (Darley & Fazio, 1980). Recent research has provided empirical evidence for this model (Whiteley et al., 2012).

The fourth and most influential model proposed was the limited-capacity model which relies on the principles of cognitive simplification. According to this model, perceivers are able to effectively respond to limited information situations by using pre-existing schemas and limiting information processing resources to a satisfactory, rather than an optimal level. One example of a limited-capacity model is the leadership categorization approach (Rosch, 1978) that has received the most attention and spurred significant empirical work in the context of ILTs (e.g., Foti & Lord, 1987; Kenney et al., 1996; Larson, 1982; Lord, 1977, 1985; Lord & Alliger, 1985; Lord & Maher, 1991; Lord et al., 1984). It has specifically been suggested that organizational members, through socialization and past experiences with leaders, develop Implicit Leadership Theories (ILTs), i.e., cognitive structures or prototypes specifying the traits and abilities that characterize a leader vs. a non leader. According to the categorization model, people are then

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categorized as leaders though recognition-based processes and on the basis of the perceivedmatchbetween their behavior or character and the attributes of a pre-existing leader category or prototype that the follower holds in memory. In a business context specifically, employees are hypothesized to use ILTs as an uncertainty reduction mechanism and compare their actual manager to their implicit profile in order to form an impression of that manager and subsequently evaluate the quality of the exchanges they develop with the manager.

Furthermore, according to leader categorization theory, people use both category-based representations (a prototype) and target-based representations (an exemplar or specific person) to represent categories (Lord et al., 1982; Schneider, 2005; Smith & Zarate, 1990). According to the prototype approach, perceivers compare stimuli from the comparison-individual to attributes of an abstract leadership or followership prototype. According to the exemplar view, perceivers categorize a target individual based on the extent to which stimuli concerning this person are similar to those of a person most representative of the category.

Lord and Maher (1991) postulated that, even though the various models of information processing have their respective advantages, the leader categorization model is the most applicable in the context of leadership perceptions and has thus been utilized as the main theoretical basis by the bulk of empirical research we will review.

Although beyond the scope of our review, it is important to acknowledge that Lord and Maher (1991) also highlighted the importance of inferential processes of leadership perceptions. Whereas recognition-based processes (reviewed above) emphasize specific traits or features of leadership, inferential processes emphasize functional aspects. Leadership can be, thus, inferred from the outcomes of salient events, such as the leader’s performance. Lord and Maher (1991) further suggested that recognition and inferential processes can be applied differentially to lower and upper levels of the corporate hierarchy. Recognition-based processes are assumed to operate on the lower and middle-manager level, where there is face-to-face manager–employee interaction. In contrast, inference-based processes are likely to function on the remote top-management level where due to employees’ lacking direct personal knowledge of the manager’s behavior, perceptions of leadership are inferred on the basis of salient outcomes. Leader distance (e.g., Antonakis & Atwater, 2002) can thus be an important explanatory variable for these differential perceptual processes.

4.2. Recent theoretical developments

Categorization theory has offered significant insights into the cognitive structure of leadership and followership and the process by which ILTs and IFTs impact leadership and followership perceptions in applied settings. The recently proposed connectionist perspective (Brown & Lord, 2001; Hanges, Lord, Godfrey, & Raver, 2002; Lord, Brown, & Harvey, 2001) attempts to capture the inherently dynamic and complex nature of leadership and followership prototypes and offers one potential explanation of how perceptions of leadership and followership can be fluid and context sensitive, yet still produce consistency and stability over time (Foti, Knee, & Backert, 2008). The connectionist model is an advancement to previous theoretical interpretations of ILTs due to its focus on the schema activation process. Lord et al. (2001) describe connectionist networks as “networks of neuron-like processing units that continuously integrate information from input sources and pass on the resulting activation (or inhibition) to connected (output) units” (p. 314). The core argument is that leadership categories are sensitive to context and they vary both within and between individuals, and are thus generated in real-time as a response to contextual, task-related, and person- and organization-influenced factors. Despite their dynamic nature, connectionist models also allow for ILTs generalizability and stability over time. As Lord et al. (2001) state “this model can be used to understand both the stability and flexibility that is witnessed in the application of leadership prototypes” (p. 311). A generic leadership schema that is generalizable in different contexts can exist but there is also the possibility of different node activation of the generic schema in different contexts. The connectionist model is thus a valuable extension to the leadership categorization theory, as it accounts for the complexity involved in implicit theory activation and utilization. The social identity leadership theory (e.g., Hogg & van Knippenberg, 2003) that we will describe in detail in Section 9.2.2 can be thought of as a special case of a connectionist model as it has emphasized the group context within leadership is exercised and the possibility of prototype change as a result of contextual changes (Lord & Hall, 2003).

Recently, Shondrick and Lord (2010) applied the principles of Adaptive Resonance Theory (Grossberg, 1999) in the context of leadership prototypes. According to this approach when external stimuli are perceived (e.g., the direct manager) they are automatically compared to categories in the long-term memory in a process described as “bidirectional feedback loops”. If a match to a leader category is unsuccessful the perceiver then matches the observed actor to a different category (e.g., non-leader) or creates a new category on the basis of the perceived stimuli. When resonance occurs (i.e., a successful match with a category) in the patterns of observed behavior and a leadership prototype, it becomes difficult to make a distinction between implicit theories and observed behavior. Shondrick and Lord (2010) propose that this process is equivalent to the gap filling processes described in the connectionist network approach, and is more prominent for abstract than for specific features. They further explain that the process of matching stimuli to prototypes will be monitored by the vigilance parameter, which is an individual difference that reflects the degree of strictness in prototype matching. Once resonance is achieved, reliance on ILTs increases and their effect on leadership perceptions become even more prominent. According to the adaptive resonance theory, not only are new categories created by unsuccessful matches, but existing categories are constantly modified and refined on the basis of inputs from the environment and interactions with target actors. It, thus, emphasizes the dynamic interaction of ILTs and context.

Finally, another theory recently utilized in the context of ILTs (in combination with connectionist theory) is Catastrophe Theory (Foti et al., 2008; Lord & Maher, 1991; Thom, 1975). Foti et al. (2008) focused on the process of recreating connectionist leadership representations in terms of attractors (i.e., states into which a dynamical connectionist system settles) and trajectories

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(i.e., time-ordered set of states of the dynamical system). Attractors are strongest when the leadership schemas they represent are usedmore frequently or are easier to access due to congruence with the target. The trajectories model leadership perceptions. The cusp surface that is produced is three-dimensional and depicts changes that may occur in stable regions through trajectories that change over time. As the mathematical representations involved in catastrophe theory are beyond the scope of this review, interested readers are referred to Brown (1995) and Poston and Stewart (2012). The results obtained by Foti et al. (2008) via non-linear modeling analyses showed that leadership perceptions can best be explained through a dyad perspective, as a joint effect of leader and perceiver characteristics.

In the specific context of IFTs, in addition to the categorization and connectionist theories outlined in previous sections, a Predisposition Proposition has also been utilized. Individuals may internalize and endorse certain IFTs over time that predispose them to perceive and treat followers in a certain fashion (Engle & Lord, 1997; Sy, 2010). This proposition reflects the notion that leaders tend to have a stable management style that is a reflection of their assumptions about the fundamental nature of followers (Bass & Bass, 2009; Eden, 1990; McGregor, 1960). Although the number of studies is small, research indeed lends support to this proposition. For example, transformational leaders hold primarily positive IFTs that accounts for their transformational behaviors (Goodwin, Wofford, & Boyd, 2000; Johnson, Sy, & Kedharnath, 2012). The predisposition proposition is explained by the perception–behavior link (Bargh, Chen, & Burrows, 1996; Chartrand & Bargh, 1999) which posits that the perception or activation of a schema (e.g., IFTs) elicits corresponding behaviors consistent with that cognition because both cognitive concepts and corresponding social responses are represented mentally, and the activation of one leads to the activation of the other (Collins & Loftus, 1975; Dijksterhuis & van Knippenberg, 1998). The perceived world consists of highly correlated representations, and the link between perception and behavior is developed on the basis of repeated observations of co-activation (Feldman, 1981; Taylor & Crocker, 1981). Thus, repeated co-activation of perception and behavior overtime develops a strong linkage such that behavioral response eventually becomes a habitual action tendency and is triggered upon the mere presence of the relevant stimuli (Bargh, 1989; Berkowitz, 1984; Carver, Ganellen, Froming, & Chambers, 1983; Mischel, 1973).

Within the leader–follower contexts, individuals develop response tendencies that are triggered without much conscious impact awareness upon activation of their internalized and endorsed IFTs (Engle & Lord, 1997; Sy, 2010). Accordingly, leaders who internalize and endorse the Industry dimension of IFTs (that followers go above and beyond expectations, are hardworking and productive) are more likely to have higher expectations for followers and provide them with more autonomy. Similarly, leaders who internalize and endorse the Incompetence dimension of IFTs (that followers are uneducated, slow, and inexperienced) are more likely to micro manage and set lower expectations for followers. Indeed, the tenets of the perception–behavior link have been demonstrated by research showing the influence of IFTs on the Pygmalion effect (Whiteley et al., 2012).

5. ILT and IFT measurement: Direct vs. indirect measures

A criticism often addressed at applied ILT and IFT research is its reliance on direct (explicit) measures such as self-report scales that may not fully capture implicit processes. Indirect (implicit) measures, on the other hand, aim to capture psychological attributes (e.g., attitudes, schemas and stereotypes) without requiring participants to report a subjective assessment of these attributes. Indirect measures aim to minimize participants’ awareness of what is being measured and/or their ability to control their responses. For example, rather than asking participants to complete a racial attitudes questionnaire (direct measure), such attitudes are inferred from their reaction time performance in a speeded categorization task (indirect measure). As Uhlmann et al. (2012) point out, failure to use indirect (implicit) measures in the case of implicit phenomena might lead to a disconnection between theory and methods. On the other hand, indirect measures are neither a panacea nor a substitute for good direct measures. In our review, we will present both explicit and implicit measures with applicability in ILTs and IFTs research.

5.1. Direct measures

5.1.1. Trait-lists The majority of early studies on ILTs have used vignettes or free-form narratives in combination with the Leader Behavior

Description Questionnaire (LBDQ) (e.g., Ayman & Chemers, 1983; Larson, 1982; Phillips & Lord, 1982b; Rush, Phillips, & Lord, 1981; Rush, Thomas, & Lord, 1977) or the Survey of Organizations (Eden & Leviathan, 1975; Taylor & Bowers, 1970; Weiss & Adler, 1981) in order to measure leadership prototypes and their effect on leader behavior measurements. Lord et al. (1984) were the first to generate a pool of 59 leader attributes, (e.g., intelligent, honest, educated, and dedicated), based on a free-form narrative exercise of undergraduate students writing down as many attributes as they thought applied to a leader. They subsequently found that these traits differed in the level of prototypicality defined as the degree the traits listed matched the image of a leader participants had in mind. Some traits, such as intelligent, honest, understanding were rated high on prototypicality, others such as happy and high achiever were found to be neutral while another category of traits such as authoritarian and dishonest, were rated low in prototypicality. In the same study, Lord et al. (1984) also developed the Akron Leadership Questionnaire (ALQ) that consisted of 25 two-word behavioral statements which varied in prototypicality. Items such as “emphasizes goals,” “proposes solutions,” and “exercises influence” were thought to be prototypical, items such as “withholds rewards,” “criticizes harshly,” and “neglects details” were classified as anti-prototypical and items such as “integrates information” and “emphasizes feelings” were thought as neutral.

Gerstner and Day (1994) used the same list of 59 attributes generated by Lord et al. (1984) and asked participants to assign a prototypicality rating for a “business leader” based on a five-point scale from “does not fit my image [of a business leader] at all”

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(1), to “fits my image [of a business leader] very well” (5). On the basis of item means, they split the attributes in three groups: prototypical (1 SD above the mean), anti-prototypic (1 SD below the mean) and neutral (−1 SD to +1 SD). Attributes such as dedicated, charismatic, intelligent, honest, determined, were found to be prototypic, while traits such as strict, conservative, manipulative, unemotional, were classified as low in prototypicality. Ten items fell into the neutral category (e.g., industrious, well-groomed, well-dressed, likable).

A significant contribution in ILTs measurement was a study by Offermann et al. (1994). They developed a list of 41 items measuring eight dimensions of ILTs, six prototypic, namely, Sensitivity (sensitive, compassionate, etc.), Dedication (dedicated, hard-working, etc.), Charisma (energetic, charismatic, etc.), Attractiveness (well-groomed, attractive, etc.), Intelligence (intellectual, educated, etc.), and Strength (strong, bold), and two anti-prototypic, namely, Tyranny (domineering, pushy, etc.), andMasculinity (male, masculine). Their studywas conducted in five stages and utilized samples of both students andworking professionals. They alsomade a clear distinction between stimulus conditions that described a “business leader”, an “effective leader” and a “supervisor”. Their results provided support for the 8-factor structure across all three stimulus conditions.

Building upon Offermann et al.’s (1994) scale, Epitropaki (2000) and Epitropaki and Martin (2004) developed the most recent explicit measure of ILTs. Following a thorough validation process and utilizing two organizational samples, they asked participants to rate how characteristic each trait was of a “business leader”. They found that in organizational settings, ILTs could be captured by 21 items (out of the 41 proposed by Offermann et al., 1994) and were most accurately reflected by six first-order factors (Sensitivity, Intelligence, Dedication, Dynamism, Tyranny and Masculinity) and two higher-order factors (Leadership Prototype and Leadership Anti-Prototype).

One of the biggest endeavors to study ILTs in a wide context of 62 countries was House et al.’s (1999, 2004) GLOBE study. They introduced the notion of Culturally endorsed Implicit Leadership Theories (CLTs), focusing on characteristics of “effective leaders” across cultures and suggested that there are some global traits that are seen as contributing to effective leadership (positive traits) or being impediments to it (i.e., negative traits). They identified six global dimensions of CLTs, namely, Charismatic/Value-based, Team-oriented, Self Protective, Participative, Humane, and Autonomous. They also listed 21 universal positive leader attributes (e.g., honest, dynamic, intelligent, motive arouser), eight universal negative leader attributes (e.g., loner, ruthless, dictatorial) and 35 specific leader characteristics that are viewed as positive in some cultures and negative in others, i.e., they are culturally contingent (e.g., ambitious, individualistic, compassionate, domineering).

Ling, Chia, and Fang (2000) also developed a Chinese Implicit Leadership Theories scale using a student and a working population sample (from five different occupational groups) and found support for a 4-factor model of ILTs in a Chinese context. Their factors included: Personal morality (e.g., honest, trustworthy, incorruptible), Goal effectiveness (e.g., decisive, competent, insightful), Interpersonal competency (e.g., charming, socially skilled, seasoned) and Versatility (e.g., multitalented, sense of humor, well-read).

In addition to these scales, other measures of ILTs include: the Schein Descriptive Index (SDI) (Schein, 1973); the modification of the Systematic Multiple Level Observation of Groups (SYMLOG; Nye & Forsyth, 1991); the Campbell Leadership Indicator (CLI; Campbell, 1991); and the Leaders described as Worthy of Influence (Kenney et al., 1996). However, these scales – with the exception of the Schein Descriptive Index – have only been used sporadically and in some cases information regarding their psychometric properties is limited.

When assessing commonalities among all existing ILTs trait-lists, we must highlight the striking similarities among the traits identified by different studies. For example, attributes such as intelligent, honest, dynamic, motivated, etc. seem to exist in all the above lists and also a distinction between positive (prototypic) and negative (anti-prototypic) traits has been made by most researchers.

When it comes to IFTs, only two empirical studies have examined the content of IFTs (Carsten et al., 2010; Sy, 2010). Although IFTs may reflect a wide range of attributes (e.g., Sy, 2010, initially identified 1030 descriptors), there seems to be consensus regarding their representative core dimensions. Sy (2010) conducted five validation studies involving 1362 participants regarding the content of IFTs. Results support the psychometric properties of the IFTs instrument, providing evidence for content, convergent, discriminant, criterion, and incremental validity, internal and temporal consistency, as well as generalizability acrossmultiple industries and independent samples. The IFTs instrument consists of 18 items that represent six factors: Industry, Enthusiasm, Good Citizenship, Conformity, Insubordination, and Incompetence. The first three and latter three also represent a second-order factor of Prototypic (positive) and Anti-prototypic (negative) IFTs, respectively. Beyond Sy’s (2010) series of validation studies, the factor structure and validity of IFTs (e.g., criterion validity, predictive validity, convergent validity, anddivergent validity) have beendemonstrated inmultiple independent studies (Kruse & Sy, 2011; Kruse et al., 2012; Sy, 2010; Tram-Quon & Sy, 2013;Whiteley et al., 2012), including dissertation research (Duong, 2012; Whiteley, 2012).

Moreover, Carsten et al.’s (2010) qualitative research provides corroborating evidence for the content, factor structure, and validity of IFTs. Carsten et al.’s results show that the traits and behaviors of followers are represented on a continuum of passive to proactive characteristics. Passive Followership is characterized by obedience, deference, flexibility and low levels of responsibility (similar to the Conformity factor that consists of the characteristics “Soft Spoken,” “Follows Trends,” and “Easily Influenced”). Reflecting the midpoint of the continuum, Active Followership is characterized by taking ownership, expressing one’s voice, and being a team player (similar to the Good Citizen factor that consists of the characteristics “Loyal,” “Reliable,” and “Team Player”). Proactive Followership is characterized by initiative taking and advancing the goals of the organization (similar to the factors of Enthusiasm and Industry that consists of the characteristics “Excited,” “Hardworking,” “Productive,” and “Goes Above and Beyond”). Along these lines, a potential proxy measure of IFTs is Carsten and Uhl-Bien’s (2009, 2012) 5-item belief in the co-production of leadership scale, which assesses beliefs about the degree followers should be proactive in the leadership process (e.g., “Followers should be on the lookout for

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suggestions they can offer to superiors” and “As part of their role, followers must be willing to challenge superiors’ assumptions”). The co-production of leadership construct is akin to the construct of Implicit Performance Theories (Engle & Lord, 1997;Wernimont, 1971), which captures performance expectations for followers (e.g., “Find outwhat supervisor expects,” “Accept some control from supervisor,” “Take and give suggestions,” etc.). Thus, the latter measures, which capture expectations about what followers should do or perform, are related to and complement IFTs, which capture schemas of who followers are.

5.1.2. Congruence scores The use of difference scores to capture the leader–follower or prototype–actual matching process (that has been a core

proposition of leader categorization theory) is of interest. In reality, only one type of congruence scores has been utilized in published ILTs research, i.e., absolute difference scores (utilized by Engle & Lord, 1997 and Epitropaki & Martin, 2005). Engle and Lord used absolute difference scores to measure inter-personal (leader–follower) ILT congruence whereas Epitropaki and Martin used them to examine followers’ intra-personal (Implicit–Explicit ILTs) congruence.

The use of congruence scores in organizational research has been a heavily debated topic (Edwards, 1994) and both of the above mentioned studies followed Edwards (1994) suggestions and tested whether the proposed constraints on the composite measure were appropriate. However, in recent years other approaches of testing congruence have become popular, such as polynomial regression (Edwards & Cable, 2009) and Latent Congruence Modeling (Cheung, 2009) that alleviate many of the problems associated with congruence scores. Topakas (2011a) compared four types of difference scores capturing Implicit– Explicit ILT congruence, namely algebraic difference, absolute difference, square difference and profile similarity indices (Q) and further utilized Latent Congruence Modeling. Her comparison consistently showed a significant effect of Implicit–Explicit ILT congruence on LMX (no matter which methodology was used) and further supported the mediating role of LMX in the relation between ILT congruence and outcomes. Tram-Quon (2013) also employed Latent Congruence Modeling and found congruence between leaders’ and followers’ positive IFTs predicted leader–follower congruence on LMX ratings. We recommend that researchers interested in capturing prototype matching processes carefully consider all available methods of assessing intra-personal and inter-personal congruence prior to making their final choice. Additional research is clearly needed in order for more solid conclusions to be drawn regarding the utility of congruence scores in this particular context.

5.1.3. Variable- vs. person-oriented approaches Recent research on ILTs has mainly utilized the (category-based) prototype approach (e.g., Engle & Lord, 1997; Epitropaki &

Martin, 2004, 2005; Gerstner & Day, 1994). Nevertheless, more recent empirical and theoretical developments suggest that the (target-based) exemplar categorization also needs to be considered in ILT and IFT research (Shondrick & Lord, 2010; Smith & Zarate, 1990). To that direction, Ho (2012) and Ho and Michael (2013) distinguished between variable-oriented (prototype-based) vs. person-oriented (exemplar-based) approaches to ILTs and examined them simultaneously in a study of 581 employed individuals. Their results showed different patterns of relationships of variable-oriented vs. person-oriented ILTs with perceptions of charismatic leadership and specifically variable-oriented approaches were shown to have higher predictive validity in the particular context. However, as Ho and Michael (2013) point out, these findings should not discourage researchers from employing person-oriented approaches to ILTs and IFTs.

5.2. Indirect measures

Complementing direct methods of assessing implicit theories, indirect methods assess individuals’ implicit theories whereby they are largely unaware of the assessment. The need for utilization of indirect measures in order to fully understand ILTs and IFTs has been previously acknowledged (e.g., Ho, 2012; Medvedeff & Lord, 2007; Sy, 2011). Like other implicit cognitions, ILTs and IFTs involve spontaneous information processing especially under high cognitive load conditions such as managerial and organizational contexts (Brewer, 1988; Fazio & Olson, 2003; Ho, 2012; Sy, 2011). Indirect measures are expected to avert high levels of conscious processing and collect information on intuitive and/or unconscious processes that influence judgments and behavior (Barsade, Ramarajan, &Westen, 2009; Fazio, Sanbonmatsu, Powell, & Kardes, 1986; James, 1998; James & LeBreton, 2011). They are still however hypothesized to be – similarly to direct measures – constrained by both implicit and explicit processes, ruling out “process pure” measures (Conrey, Sherman, Gawronski, Hugenberg, &Groom, 2005; Uhlmann et al., 2012).Moreover, both indirect anddirectmeasures are valid assessments of unique aspects of phenomena, and neithermeasure is inherentlymore accurate in capturing the “true”nature of a phenomenon (Conrey & Smith, 2007; Evans, 2008; Smith & DeCoster, 2000; Strack & Deutsch, 2004). Accordingly, neither measure is inherently more predictive of behavioral outcomes. The predictive superiority of either measure varies across domains (e.g., direct measures are better predictors of consumer behavior and political preferences, and indirect measures are better predictors of group and racial behaviors) (Nosek, Hawkins, & Frazier, 2011).

Uhlmann et al. (2012) have recently developed a functional taxonomy that clusters available indirect (implicit) measures into three categories: accessibility-based, association-based and interpretation-based measures. We follow the same taxonomy in our presentation of indirect measures of ILTs and IFTs.

5.2.1. Accessibility-based measures Such methodologies assess the extent to which a target concept is spontaneously activated in a person’s mind. Examples

include lexical decision tasks (Kunda, Davies, Adams, & Spencer, 2002; Meyer & Schvaneveldt, 1971), word fragment completion tasks (Gilbert & Hixon, 1991; Johnson et al., 2012), and Stroop tasks (Mathews & MacLeod, 1985; Stroop, 1935). In the context of

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ILTs, recently Dinh and Lord (2013) used a word-fragment exercise to indicate ILTs accessibility in a scenario study that described the performance of an effective or ineffective manager. They found that implicit measures of Dedication, Sensitivity, Strength, Dynamism and Attractiveness formed a pattern that was significantly more likely to occur in the effective rather than the ineffective leader condition. Similarly Snead, Coyle, Diana, and Foti (2013) have developed a semantic priming approach for measuring of ILTs. Their research provided evidence for a connectionist model of ILTs, demonstrating ILTs may be dynamically accessed as a function of contextual cues.

Beyond assessment, research has manipulated the accessibility of implicit constructs. Focusing on IFTs, Sy (2011) utilized a supraliminal priming methodology (Bargh, Chartrand, Reis, & Judd, 2000; Bargh et al., 1996; Dijksterhuis & Bargh, 2001) to elicit positive IFTs to examine its salutary influence on corresponding action tendencies. Participants’ positive IFTs were activated with a word search puzzle. The word search puzzle consisted of a 15 × 20 matrix of letters with a list of the words representing positive IFTs (Sy, 2010) imbedded in the puzzle. Compared with the neutral prime condition (consisting of word search puzzles imbedded with a list of neutral words representing colors, hobbies, and animals), participants in the activated positive IFTs condition evaluated an employee described in a neutrally-worded vignette (e.g., no performance information was provided) more positively on relationship quality and performance. These experimental effects were corroborated with a field study of leader–follower dyads demonstrating the positive associations of positive IFTs with high relationship quality and follower performance. Utilizing the same priming methodology, Whiteley (2012) demonstrated that participants in the activated positive IFTs condition reported higher levels of performance expectations, liking, LMX quality, affect, and effort for an employee described in a neutrally-worded vignette, than participants in the activated neutral or negative IFTs conditions.

5.2.2. Association-based measures Such tests typically rely on reaction times when categorizing rapidly presented stimuli to determine the extent to which

multiple concepts are linked as part of a cognitive schema. Examples include priming tasks (Fazio, Jackson, Dunton, & Williams, 1995; Fazio et al., 1986) and the IAT (Greenwald, McGhee, & Schwartz, 1998), among others.

Recently, Ho (2012) developed an indirect measure of ILTs using the Go/No Go Association Task (GNAT). GNAT is an absolute association measure that requires subjects to distinguish target category terms (in this case, leadership traits) from distracter terms rapidly and accurately. She used a diverse sample of 417 professionals contacted through Amazon-Mechanical Turk to increase ecological validity of the results. Her results suggested that based on the accuracy index of association only Sensitivity, Dedication, and Intelligence traits were used to distinguish leaders from non-leaders, whereas on the basis of the latency index Dedication, Intelligence, Charisma, and Tyranny were critical traits for leader identification.

Tram-Quon (2013) has developed an indirect measure of IFTs based on the Single-target IAT (Karpinski & Steinman, 2006) and items from the IFTs scale (Sy, 2010). This Single-target IAT IFT measure assesses individuals’ evaluative association with followers. In the Single-target IAT IFTs measure there is one target category, which is “follower”, and two attribute categories, which are “positive” and “negative.” Using a computer, participants are presented with words representing one of the three categories (e.g., subordinate, worker, productive, reliable, rude, arrogant), one word at a time. In the first stage, participants are asked to press a response key when follower words or positive words (i.e., follower + positive) appear, and to press a different response key when negative words appear (i.e., negative). In the second stage, participants press a response key when positive words (i.e., positive) appear, and press a different response key when follower words or negative words (i.e., follower + negative) appear. Participants are asked to respond quickly while making as few mistakes as possible. The timed performance difference between the two stages represents the direction and strength of the association to followers (Greenwald et al., 1998). A large discrepancy indicates a strong, positive or negative attitude towards followers, whereas a small discrepancy indicates a slight, positive or negative attitude towards followers. Because the Single-target IAT IFTs measures response latencies in milliseconds, individuals are less able to deliberately control their responses and fake their endorsement of followers.

5.2.3. Interpretation-based measures Such measures assess reactions to and inferences drawn from complex and ambiguous information. Examples are the

Rorschach inkblot test (Rorschach, 1927), the Thematic Apperception Test (Morgan & Murray, 1935), the Conditional Reasoning Test (CRT; James, 1998) and the linguistic intergroup bias (LIB; Maass, Salvi, Acuri, & Semin, 1989).

Focusing on IFTs, Sy (2013) employed a projective approach, paralleling the approach used to indirectly assess Psychological Capital (Harms & Luthans, 2012). Participants were given scenarios depicting followers at work (e.g., “group member talks to supervisor”) and asked to invent stories for the scenarios. Subsequently, participants were asked to assess the followers in the scenarios using items from the IFTs scale (Sy, 2010). The assessment is indirect in that it is based on participants’ projections that were made previously. That is, the projective method does not directly ask participants to self-report their personal responses, rather, participants believe they are merely reporting the characteristics of the followers in the stories. Accordingly, participants are less susceptible to social desirability and self-presentation issues.

In addition to the implicit measures presented here, future research on ILTs and IFTs could benefit by incorporating recent insights from neuroscience (e.g., Balthazard, Waldman, Thatcher, & Hannah, 2012; Lee, Senior, & Butler, 2012; Waldman, Balthazard, & Peterson, 2011). Neuroimaging techniques (such as MRI and EEG devices) may help provide a better understanding of implicit schemas of leadership and followership.

Like others scholars in this field (e.g., James & LeBreton, 2011; Uhlmann et al., 2012), we believe indirect (implicit) measures hold great promise for ILT and IFT research in organizations. Because direct and indirect measures have distinct advantages and

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disadvantages, development of both measures would allow for a holistic assessment of individuals’ ILTs and IFTs. Direct, self-report measuresmaybe short in length, thus not time consuming to administer, can easily be administered by organizational personnel, and are easy to score and interpret. Indirect measures may complement direct measures of ILTs and IFTs because direct measures may be more susceptible to social desirability and self presentation issues (although implicit measures are not completely immune) (Gawronski, 2009). Altogether, development of both indirect and directmeasures can advance our understanding of how controlled anduncontrolled processing shapes leader–follower processes and outcomes.

6. ILT and IFT research in organizational settings

Two main lines of research on Implicit Leadership and Followership Theories in organizational settings can be identified: (a) research on the content, structure, and generalizability of ILTs and IFTs, and (b) research on outcomes and to a lesser degree on antecedents, moderators and mediators. We have already discussed research on ILTs and IFTs content and factor structure in Section 5, thus, in this section we will discuss empirical work focusing on generalizability, antecedents, outcomes and moderators/mediators.

6.1. Generalizability

When assessing ILTs and IFTs generalizability across different perceiver groups, existing research has focused on three main areas: (a) gender (Deal & Stevenson, 1998; Epitropaki &Martin, 2004; Nye& Forsyth, 1991; Offermann et al., 1994; Sy, 2010); (b) culture (Bryman, 1987; Den Hartog, House, Hanges, Ruiz-Quintanilla, & Dorfman, 1999; Gerstner & Day, 1994; House et al., 1999) and (c) different employee groups (Epitropaki & Martin, 2004).

When assessing ILTs and IFTs generalizability across female and male perceivers, research has generally provided support (e.g., Nye & Forsyth, 1991; Offermann et al., 1994). Despite the observed similarity on ILTs and IFTs factor structure, some differences have, however, been found on certain dimensions between women and men. Deal and Stevenson (1998) found that although both male and female subjects had similar perceptions of a prototypic leader (i.e., no content differences), males rated traits such as aggressive, competitive and feelings not easily hurt, higher than females, while females rated traits such as being aware of others’ feelings, helpful and self-confident higher thanmales. Similarly Johnson, Murphy, Zewdie, and Reichard (2008) found that masculine (vs. feminine) individuals expect from their leaders more masculinity, strength, tyranny, and less sensitivity. Epitropaki and Martin (2004) also found women to expect a leader to be more understanding, sincere and honest and less domineering, pushy andmanipulative thanmen. Recently,Weidner (2012) applied generalizability analysis to examine the sources of variance in ILTs. Results showed that rater characteristics (i.e., gender, agency-communality and political ideology), target characteristics (i.e., authority level, gender and basic level category of the leader) and interactions between them, were all significant sources of variance in ILTs.

Although not reported, Sy (2010) found differences in endorsement (but not content) for IFTs across gender, age, and education groups. However, the differences between the effect sizes were small and the groups only differed on a limited number of dimensions. For example, male leaders rated the dimensions of Insubordination and Enthusiasm higher than female leaders; younger leaders rated the dimensions of Conformity and Follower Anti-prototype higher than older leaders; more-educated leaders rated the dimensions of Follower Prototype higher than did less-educated leaders.

Although beyond the scope of this review, we need to acknowledge the long line of research on gender stereotypes and leadership (e.g., Ayman & Korabik, 2010; Chung-Herrera & Lankau, 2005; Duehr & Bono, 2006; Heilman, Block, Martell, & Simon, 1989; Schein, 1973; Schein & Mueller, 1992). Drawing from role incongruity theory (Eagly & Karau, 2002) and the lack of fit model (Heilman, 2001) prior research has consistently documented the incongruity between construals of women and leaders and the biased evaluations that women receive as leaders due to this lack of fit. Koenig, Eagly, Mitchell, and Ristikari (2011), in a recent meta-analysis, distinguished among three main paradigms utilized in gender and leadership stereotypes research: the “think manager–think male” (e.g., Schein, 1973, 1975; Schein & Mueller, 1992; Schein, Mueller, Lituchy, & Liu, 1996) the agency– communion (Powell & Butterfield, 1979) and the masculinity–femininity paradigm (Shinar, 1975). Schein’s studies have generally provided support for the similarity of stereotypes of men and successful leaders across multiple cultural contexts. Studies of the agency–communion paradigm (e.g., Powell & Butterfield, 1979) further supported a gender-stereotypical content of the leader stereotype whereas studies of the masculinity–femininity paradigm (Shinar, 1975) tested masculine vs. feminine content of occupational stereotypes. Koenig et al.’s (2011) meta-analysis provided support for the masculinity of leader stereotypes across all three paradigms but also indicated that this masculine construal of leadership has decreased over time and was greater for male rather than female research participants.

Second, research has extensively focused on cultural differences on ILTs. Bryman (1987) tested whether the leadership prototypes in the UK were similar to the ones previously identified and found support for generalizability. Gerstner and Day (1994) examined ILTs in eight different countries (France, Germany, Honduras, India, Taiwan, China, Japan and USA) and their results showed significant differences. For example, Western countries were found to rate the trait determined as highly prototypical, whereas Eastern countries rated the trait intelligent highly. A milestone study for the role of national culture on leadership prototypes was the GLOBE study that examined Culturally Endorsed ILTs (CLTs) in 62 countries (Den Hartog et al., 1999; House, Hanges, Javidan, Dorfman, & Gupta, 2004; Javidan, Dorfman, De Luque, & House, 2006). The study’s findings indicated that some leadership prototypes are universal while other are culture specific. Of the six leadership dimensions identified in the study, two showed to be universal, namely Charismatic/Value-Based and Team-Oriented leadership, and four were found to differ between cultures, namely Self-Protective, Participative, Autonomous, and Humane-Oriented leadership.

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Sy and colleagues (Festekjian, Tram, Murray, Sy, & Huynh, in press; Sy et al., 2010) also found cultural differences among different groups within the same national culture. Leadership perceptions of Asian Americans were based on a competent leader prototype (i.e., Intelligence and Dedication), whereas leadership perceptions of Caucasian Americans were based on an agentic leader prototype (i.e., Dynamism, Masculinity, and Tyranny). Lankau and Chung (2009) also assessed similarities and differences of successful managers across four cultural groups: American, European, Asian and Latin American using the Schein Descriptive Index. Despite some observed differences on specific traits, their overall results suggested high levels of cross-cultural consistency. As a possible explanation for their finding, they proposed that globalization and widespread management education programs teaching Western theories of leadership have gradually contributed to the cultural convergence of ILTs. Other cross-cultural studies have also indicated that the observed ILT differences are likely reflections of levels of endorsement for a given dimension (e.g., charisma) rather than differences in dimension content (Ensari & Murphy, 2003; Johnson et al., 2008). In contrast, we are not aware of any existing research on cultural differences in IFTs. Paralleling the ILTs literature, much can be gained by investigating cultural differences in IFTs.

Third, the generalizability of ILTs across different work groups and settings has been examined. Specifically, Epitropaki and Martin’s (2004) results of factorial invariance analyses, provided support for a similar factor structure across different employee groups of age, organizational position and tenure. As the authors argued such findings suggest that employees in different work positions or in different stages of their working life hold similar perceptions of leadership (no content differences). They did, however, find differences in factor covariances and means between different employee groups. For example, managerial employees rated traits such as dynamic, energetic and strong higher than employees in a non-managerial role. Also manufacturing employees rated traits such as domineering, pushy and manipulative higher than service employees while the opposite was true for traits such as sensitive and helpful.

Thus, although the content and factor structure of ILTs was the same across different employee groups, the strength of interrelationships between factors as well as the degree of certain traits differed, suggesting that certain combinations of ILTs factors or certain ILTs traits were likely to be more salient in one context than the other. Their findings, thus, offered support to the connectionist model (Lord et al., 2001) that allows for both stability and flexibility of ILTs as a function of context influences. Although not reported, Sy (2010) found similar outcomes for IFTs. The content and endorsement of IFTs did not differ for employee groups of different managerial levels, job functions, and spans of control.

6.2. Antecedents

Very few studies have explicitly addressed the question “Where do leadership and followership prototypes come from?”. Studies have shown that implicit leadership theories are established early in childhood (e.g., Antonakis & Dalgas, 2009; Ayman-Nolley & Ayman, 2005). Thus, most organizational studies have taken for granted the assumptions of categorization theory regarding prototype development through early socialization experiences, and consequently, research on ILTs and IFTs antecedents is scarce. Only Keller (1999) examined personality characteristics and parental traits as antecedents of ILTs. She found personality traits, such as agreeableness, conscientiousness, extroversion, openness, neuroticism, and self-monitoring, to influence implicit leadership theories. Specifically, individuals characterize as prototypical a leader that was similar to one self. She also found idealized leadership images to mirror descriptions of parental traits. Keller (2003) subsequently provided theoretical interpretations of the effect of caregivers and early childhood experiences based on attachment theory. She proposed that follower attachment styles (secure, anxious-ambivalent and avoidant) would significantly influence their Implicit Leadership Theories.

Recently, Ehrahrt (2012) examined the effect of followers’ self-concepts (specifically their self-esteem and self-construal) on three dimensions of ILTs (charisma, sensitivity and dedication) and subsequent implications for follower preference of specific leadership styles. His results showed significant correlations between self-construal and all three ILTs dimensions as well as between self-esteem and Sensitivity. They further indicated that the effects of independent self-construal on charismatic leader preference were partially mediated by the ILT dimension of Dedication, and the effects of interdependent self-construal were fully mediated by the ILT dimension of Sensitivity. No significant effects were found for self-esteem. With regards to IFTs, preliminary evidence also suggested that Extraversion might be an antecedent of positive IFTs (Duong, 2012; Kruse et al., 2012).

Furthermore, empirical evidence suggests that trait and state affect may be antecedents of IFTs and ILTs. Affect and IFTs possess structural similarities in that both are positively and negatively valenced. Given their structural similarities, Kruse and Sy (2011) proposed that affect and IFTs may be connected through their shared valence within the structure of associative networks (Fiske & Taylor, 1991) that reflect interconnections of related constructs. Across four experiments incorporating multiple affect (sadness, anger, and happiness) and samples (students, working adults, and leaders), Kruse and Sy (2011) demonstrated that affect activated corresponding IFTs such that sadness and anger activated negative IFTs (but not positive IFTs), and happiness activated positive IFTs (but not negative IFTs). Similarly, Johnson et al. (2012) found in a field sample of leaders a positive association between negative IFTs and negative affect but not positive affect. These results demonstrate the associative nature of IFTs and affect, and indicate that the action of one (e.g., affect) results in the activation of the other (e.g., IFTs). Similarly, emerging research in ILTs show parallel results whereby, ILTs have also been linked to affect (Johnson, Walczak, & Sy, 2013; Kruse & Sy, 2011). For example, Johnson et al. (2013) using neural networking found stress to lead to an increased activation of anti-prototypical leadership schema dimensions such as Tyranny and Masculinity and deactivation of the schema dimension of Sensitivity. Extending the finding on the associative nature of ILTs and affect, Kruse and Sy (2013) found that angry followers are more likely to endorse the leader when leader power is salient than when leader power is not salient. Although anger normally

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activates negative information about others, power inhibits access to negative information, which leads to a more positive view and endorsement of the leader. The role of affect in the context of both ILTs and IFTs is a new line of research that holds great promise for the future. In general, given the paucity of research, investigating the antecedents of IFTs and ILTs can be a fruitful direction for future research.

6.3. Outcomes

A criticism of ILTs research is that much is focused on the classification and identification of leaders, with fewer demonstrations of the link between ILTs and workplace outcomes. In contrast, the research on IFTs is focused on its impact on work related outcomes, although this literature is small given its novelty as an emerging area of research. Herein we review existing research on ILTs as well as the emerging research on IFTs and workplace outcomes. Given the relatively small number of studies (with regard to ILTs) and the novelty (in the case of IFTs), we review both published as well as unpublished results.

Existing studies examining the role of ILTs and IFTs in organizational settings havemainly focused on three outcomes: (a) leadership variables and specifically, Leader–Member Exchanges (LMX) and transformational leadership, (b) job attitudes (such as job satisfaction and commitment), and (c) job performance.

6.3.1. Leader-Member Exchanges (LMX) One of the first studies to examine the role of Implicit Leadership Theories in an organizational setting was Engle and Lord’s

(1997). They proposed that similarity in leaders’ and followers’ ILTs would provide a solid ground for mutual understanding, identification, adjustment of behavior to expectations and enhanced quality of leader–follower relationships. They thus studied the effects of supervisor–subordinate ILT congruence on LMX and found that ILT congruence between supervisor and subordinate was not an important predictor of LMX, but both supervisor and subordinate ILTs separately had a significant effect on LMX quality. They also examined Implicit Performance Theories (IPTs) and found leader–follower IPTs congruence to be related to LMX.

Epitropaki (2000) and Epitropaki and Martin (2005), building upon leader categorization theory, proposed that it is the match between one’s ILTs and the recognition of those attributes in the actual leader (implicit–explicit ILTs intra-individual congruence) that will affect Leader–Member Exchanges rather than inter-individual congruence. In a longitudinal organizational study, they found intra-individual congruence between employees’ Prototype and actual manager characteristics to positively affect Leader– Member Exchanges whereas Implicit–Explicit Anti-prototype congruence had a negative effect on LMX. Implicit–Explicit ILT congruence was also found to indirectly predict employee outcomes such job satisfaction, commitment, well-being and performance. Multi-group analysis revealed that the relationships between Implicit–Explicit ILT congruence, LMX and outcomes did not differ across followers on the basis of differences in job demands and relationship tenure with the manager. Their cross-lagged analyses further provided support for a direct causal effect of Implicit–Explicit ILT congruence on LMX and did not render support for a possible reciprocal effect between the two as Lord and Maher (1991) had indicated. More recently, Topakas (2011b) using Latent Congruence Modeling tested the above relationship in the context of three studies (two student samples and one organizational sample). Her results provided strong support for the effect of Implicit–Explicit ILT congruence on Leader– Member Exchanges.

To date, a number of studies have examined the relationship between IFTs and LMX. Sy (2010) found that leaders’ Followership Prototype and Anti-prototype were (respectively) positively and negatively related to follower outcomes on liking for leaders, relationship quality with leaders, and trust in leaders. Similarly, leaders’ Followership Prototype and Anti-prototype respectively has positive and negative consequences for leader outcomes such as liking for followers, and relationship quality with followers. In another study on Pygmalion leadership, Whiteley et al. (2012) found that Leaders’ positive IFTs shaped positive relationship quality in leader–follower dyads. Moreover, Sy (2013) found that leaders and followers (positive) IFTs interacted to influence relationship quality. Specifically, relationship quality is highest when both leaders and followers holdmore positive IFTs. Furthermore, Duong (2012) found that leaders’ IFTsmeasured at the individual level (i.e., a general perceptual representation of a target follower) was significantly related to relationship quality. These preliminary results indicate a moderate relationship between IFTs and relationship quality, suggesting that perceptual representations of followers are related to the quality of interactions between leaders and followers. Finally, Coyle, Foti, Giles, Langford, andHolup (2013) examined the congruence between leaders and followers on ILTs and IFTs in a laboratory setting. They found inter-individual congruence on leader prototypes to be related to LMXquality as assessed by followers and congruence on follower prototypes to be related to LMX as assessed by leaders.

6.3.2. Transformational leadership One of the early studies examining ILTs and transformational leadership was Bass and Avolio’s (1989) who in a survey on a

sample of 87 participants asked them to describe their immediate superior using MLQ-5R. They also measured respondents’ ILTs using 23 prototypical attributes identified by Lord et al. (1984). Their results indicated that prototypical traits were more highly correlated with transformational leadership than transactional leadership. In other words, “…participants saw transformational leaders as being closer to their image (rated prototypicality) of a leader as compared to transactional leaders fitting that image” (Bass & Avolio, 1989, p. 525). Based on this finding, Bass (1997) suggested that “…when people think about leadership, their prototypes and ideals are transformational” (p. 135). Den Hartog et al. (1999), using the GLOBE data, further supported Bass’ (1997) proposition, as their results indicated that CLT attributes associated with charismatic/transformational leadership were universally endorsed as contributing to outstanding leadership. Epitropaki (2000) examined the impact of Implicit–Explicit

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ILT congruence on employees’ transformational leadership perceptions. Results showed significant positive effects of Implicit– Explicit Prototype congruence and negative effects of Implicit–Explicit Anti-Prototype congruence on transformational leadership.

With regard to IFTs, researchers have long proposed that leaders’ style is a function of their perceptions of followers (Eden, 1990; McGregor, 1960). Specifically, transformational leaders’ behavioral style that elicits high follower performance is a function of leaders’ positive IFTs (Goodwin et al., 2000; Johnson et al., 2012). Johnson et al. (2012) found that leaders’ positive IFTs influenced attributions of charismatic leadership and this relationship was mediated through follower liking of the leader. Similarly, Duong (2012) found a significant relationship between leaders’ positive IFTs and transformational leadership. Specifically, leaders’ positive IFTs mediated the relationship between Extraversion and Transformational leadership. Duong found that leaders’ positive IFTs (but not negative IFTs) measured at the individual level were positively related with transformational leadership, suggesting that leaders who have more positive views of their own followers exhibit more transformational leadership. In sum, these results indicate that IFTs are determinants of leadership style, and positive IFTs activate action tendencies that are germane to transformational leadership.

6.3.3. Job attitudes The first study that explicitly addressed the role of ILTs for job attitudes was that of Epitropaki and Martin (2005). They

highlighted the fact that Lord and Maher’s (1991) theory focused solely on the effects of leadership schemas on perceptions of leadership behaviors and had made no explicit reference to the role of ILTs for employee attitudes. However, based on the literature on the effects of trait-based evaluations of oneself and others on job satisfaction and well-being (e.g., Bono & Judge, 2003; Judge, Locke, Durham & Kluger, 1998) they hypothesized that the evaluations employees make of their manager on the basis of how distant or close he/she is to their implicit leadership profile, could potentially affect more global evaluations of their work. Their results showed Implicit–Explicit ILT congruence impacted job satisfaction, organizational commitment and well-being via LMX. Topakas (2011a) recent studies also showed that LMX fully mediated the effects of ILT congruence on job satisfaction, task satisfaction, group satisfaction and well-being.

Furthermore, the existing IFT research has found significant effects for the prototypical (positive) IFTs on employee outcomes such as job satisfaction andwell-being (E. Kruse, 2010; E.T. Kruse, 2010; Johnson&Kedharnath, 2010; Sy, 2010) but results on the effects of antiprotoypical (negative) IFTs on outcomes are rathermixed. Additionally, Kedharnath (2011) did not find support for themediating effect of LMX in the relationship between supervisor IFTs and employee outcomes.

6.3.4. Job performance Although there are several studies that have adopted an inferential processes lens and examined the impact of leader

performance cues on leadership perceptions (e.g., Kollée, Giessner, & van Knippenberg, 2013; Lord & Maher, 1991; Meindl, 1995; Meindl, Ehrlich, & Dukerich, 1985; Phillips & Lord, 1982a; Rush et al., 1981), there is limited emphasis on the role of ILTs for employee job performance. Only one study (Topakas, 2011a) has shown a positive association between ILT congruence and task performance via LMX. In contrast, IFT research has been more prolific with regards to studies examining performance as an outcome. Whiteley et al. (2012) found that leaders’ positive IFTs influenced follower performance by shaping leaders’ performance expectations for their followers. This research demonstrated that IFTs serve as antecedents to naturally occurring Pygmalion effects that shape performance (vs. the body of research on Pygmalion effects involve artificial experimental manipulation of leaders’ performance expectations for their followers). Complementing Whiteley et al.’s focus on dyadic level effects, Tram-Quon and Sy (2013) also found an effect of leaders’ positive IFTs on follower performance at the group level. This group level finding suggests that IFTs may shape leader performance expectations across all followers rather than being limited to a subset of followers.

Paralleling these results, Johnson et al. (2012) found that leaders’ positive IFTs influenced follower performance because IFTs shape leaders’ enactment of transformational behaviors. Moreover, Duong (2012) found that leaders’ negative (anti-prototypical) IFTs were negatively related to follower performance. In addition, leaders’ positive and negative IFTs (measured at the individual level) were positively and negatively related to follower performance, respectively. Whereas these studies focused on the effect of Leaders’ IFTs on follower performance, Sy (2011) found that leaders’ and followers’ IFTs may interact such that leaders’ IFTs influenced follower performance more positively when followers conceived of their roles in less positive terms, suggesting that leaders’ IFTs activate salutary action tendencies (e.g., set high goals and expectations) that compensate for a lack of self-generated actions on the part of followers. In sum, research has focused on the relationship of IFTs and follower performance, suggesting that IFTs shape performance via Pygmalion processes.

6.4. Mediators and moderators

As it became evident from our previous discussion on ILTs, IFTs and Leader–Member Exchanges, LMX has probably been the most researched mediating variable in this context. The majority of reported studies (e.g., Epitropaki & Martin, 2005; Sy, 2010; Topakas, 2011a) provide strong support for the mediating role of LMX in the relationship between ILTs, IFTs and employee outcomes. Research also provides some support for the mediating role of transformational leadership as discussed above (e.g., Duong, 2012; Epitropaki, 2000; Goodwin et al., 2000).

An individual characteristic that has been found to act as a significant moderator and differentiate the extent to which employees used ILTs to form an impression of their manager is intrinsic motivation. Based on Macrae and Bodenhausen’s (2000)

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proposition that schematic thinking is more likely to be used when motivation is low, Epitropaki and Martin (2005) found that employees with low levels of intrinsic motivation were more inclined to use a categorical mode and rely on ILTs in order to evaluate their LMX quality than employees with high levels of intrinsic motivation. This finding was further corroborated by Foti et al. (2008) who in an experimental study found that personal relevance of the leader’s behavior and participant engagement affected variance in the leader networks. When participants were less engaged, they exhibited more stable cognitive representations of leadership. Another important moderator is affect. Affect influences access to ILTs, and has been shown to change the degree to which followers endorse their leaders (Johnson et al., 2013; Kruse & Sy, 2013)

With regards to IFTs, Whiteley et al. (2012) found that supervisory experience moderated the relationship between leaders’ IFTs and their performance expectations for followers. Specifically, leaders with less supervisory experience relied more on their IFTs in regards to performance expectations for followers. Kruse and Sy (2011) found that affect changes the accessibility of different follower prototypes.

7. Levels of analysis in leadership and followership schemas

As Foti et al. (2008) point out “…an impressive 70% of conceptual publications included in the domain of information-processing and implicit leadership domain explicitly stated the level of analysis regarding theoretical development” (p. 193). Implicit Leadership Theories (ILTs), for example, have been conceptualized as cognitive categories organized hierarchically into three levels: Superordinate, basic, and subordinate (Lord et al., 1982, 1984). The most abstract level, the superordinate level, contains traits and characteristics that distinguish leaders from non-leaders. In the level below (i.e., the basic level) are contextualized prototypes that distinguish among different types of leaders, such as business, military, religious. Finally, subordinate level representations capture the traits and characteristics describing different types of leaders in the specific context. For example, under ‘business leader’ we can distinguish between CEO leadership,middle levelmanagers, front-line supervisors and so forth. An excellent graphic representation of the hierarchy of leadership categories can be found in Lord et al. (1984).

Three different levels of cognitive categories are also hypothesized with regard to IFTs (Sy, 2010). At the superordinate level, target individuals are classified as followers or non-followers. Theoretically, there should be few attributes that apply to all followers and very little overlap between followers and non-followers. At the basic level (middle level), contextual information is taken into account that results in different, contextually defined followership categories. For example, different followership categories may exist for military, religious, or business followers. At the subordinate level (lowest and least inclusive level), different types of followers within a particular context are differentiated. For example, the subordinate categories for the basic level category of business follower may be mechanical engineers in the automotive manufacturing industry or software engineers in the information technology industry. A simplified graphic representation of the followership categorization theory (modeled after a figure in Lord et al., 1984, p. 347) is shown in Fig. 1.

In addition to the levels of abstracted representation discussed above, IFTs may be further represented at different levels within the context of an organization (i.e., within the hierarchy of a company). IFTs may be hierarchically distinguished at the company, group, and individual levels. IFTs may range from higher order levels capturing broader abstracted representations (i.e., company and group level IFTs) to lower order levels capturing more personalized abstracted representations (i.e., a generalized impression of a particular follower). A simplified graphic representation of IFTs within an organizational context is provided in Fig. 2.

Continuing with our business example, differences on IFTs may exist at the company level within the information technology sector because organizational culture likely shapes IFTs (Sy, 2010). For example, research on differences in organizational culture and identity (Fitzsimons, Chartrand, & Fitzsimons, 2008) suggest that the Conformity dimension of IFTs may be more heightened at IBM than at Apple. Moreover, differences in IFTs may exist at the group level within the same company. For example, IFTs may differ between engineering andmarketing groups because of differences in group-level culture. Sub-group differences in IFTs may

Fig. 1. A hierarchy model of followership categories.

Fig. 2. An organizationally based hierarchy model of followership categories.

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also exist within the same group. As an example, researchers have found differences in IFTs across different management groups within the same engineering function of a federal agency (Wofford, Goodwin, & Whittington, 1998).

In addition to forming category-based abstracted representations (impressions across individuals), people also form target-based abstracted representations for single individuals (impressions of a target follower across situations and time) (Schneider, 2005). Research indicates that leaders do form individual-level IFTs for specific followers (Duong, 2012). Individual-level IFTs reflect a general impression or summary ofwho the follower represents (i.e., a reflection of a follower prototype), and the performance evaluation reflect how well a follower has performed which may be tied to a specific task or time period (e.g., performance on a given project). Indeed, research shows that individual-level IFTs and evaluations of individual performance are related (correlations range from − .43 for the Anti-prototype factor to .65 for the Prototype factor) (Duong, 2012) but distinct constructs because none of the correlations exceed the recommended cut-off point of .85 for establishing parallel constructs (Kline, 1998).

8. Change of ILTs and IFTs over time

It is also important to address issues related to how leadership and followership schemas change over time. Shondrick et al. (2010) have mainly focused on the process of early development of ILTs and highlighted the role of social factors such as past relationships and interactions with close others (e.g., Keller, 2003). Although they do mention that “…rather than envisioning an ILT as a stable and uniform construct, ILTs may be better conceptualized as dynamic structures that can change across one’s life span” (p. 964), they do not explicitly address ILTs and IFTs schema change in organizational settings.

Epitropaki and Martin (2004) in an analysis of ILTs alpha, beta and gamma change (Golembiewski, Billingsley, & Yeager, 1976) provided support for ILTs stability over a 12-month period. There was no evidence of respondents’ re-conceptualizing the construct (gamma change), re-calibrating the ILTs measurement instrument (beta change) or of level change on the latent variable of ILTs (alpha change). Moreover, Lord and Maher (1991) as well as Engle and Lord (1997) had proposed that ILTs can change as a result of Leader–Member Exchanges (LMX) and a feedback loop possibly exists between employees’ categorization of a manager as congruent to the implicit leadership profile and their perceptions of the manager’s behavior and the quality of their dyadic relationship. Epitropaki and Martin (2005) tested this hypothesis with a cross-lagged model that examined the possibility of reciprocal effect between ILTs and LMX utilizing a 1-year time lag. Their results found support for the originally hypothesized direction of effects (ILTs to LMX rather than vice versa) and for stability of ILTs over time. Consistent with the above literature, Sy (2010) found that IFTs also remained stable across time (over 3 weeks).

If leadership and followership schemas are indeed stable and resistant to change what are the implications for leader behavioral flexibility? Prior research on complexity (e.g., Lord, Hannah, & Jennings, 2011) and innovation (e.g., Rosing, Frese, & Bausch, 2011) has highlighted the need for leaders to quickly adjust to environmental changes and to switch between opening and closing behaviors if they want to foster innovation. Such flexibility could be possibly limited by strong leadership and followership schemas. Hogg and van Knippenberg (2003) have commented on a ‘prototypicality paradox’ resulting from a stable and highly consensual group prototype of a leader. Whereas in the beginning prototypicality imbues leaders with status, charisma and influence, over time all these elements might set them apart. The leader may gradually be perceived as “other” rather than “one of us”. Furthermore, leaders might become reluctant to initiate changes and take unpleasant decisions out of fear of loss of prototypicality. There is, thus, a “dark side” of schema stability.

Although generally resistant to change, there is empirical evidence indicating that implicit theories can be malleable. Prior research on schema change (e.g., Jelinek, Smircich, & Hirsch, 1983; Labianca, Gray, & Brass, 2000; Taylor & Crocker, 1981) has proposed that once schemas are established, they tend to endure and are resistant to change, however, it is possible for them to change over time if the information environment is dramatically altered (Isenberg, 1987). Schema change can occur through a

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dialectic process of conflict between old and new schemas after experiences or disconfirming information that make people question the validity or utility of existing schemas (Labianca et al., 2000; Poole, Gioia, & Gray, 1989).

Thus, one pathway to ILT and IFT change is to challenge existing schemas with counter factual evidence (Dasgupta & Greenwald, 2001). For example, exposure to counter-exemplars (e.g., successful women CEOs such as Meg Whitman of Ebay and Indra Nooyi of PepsiCo) may weaken the link between leadership and being male (Dasgupta & Asgari, 2004). Although counterfactuals may weaken existing schemas, new associations may need to be formed for change to take hold. Research points to several possible intervention strategies, such as awareness development and prototype activation (Gawronski & Bodenhausen, 2006b) that we will present in detail in the section on leadership development implications.

We can also draw some insights on changing implicit theories from the close relationships literature (e.g., Fletcher, Simpson, & Thomas, 2000). Specifically, the flexibility of ideal standards (i.e., to what extent a partner can fall below the ideal but still be considered acceptable) is of interest in this context (Fletcher et al., 2000). Although ideal standards are generally conceptualized as relatively stable (e.g., Campbell, Simpson, Kashy, & Fletcher, 2001) the model allows for some flexibility. Flexibility or “range of acceptance” increases on the basis of individual self-assessments and situational feedback. If for example, “I don’t consider myself that attractive because of weight gain or hair loss” (self-assessment) or after a series of rejections of prospective partners (situational feedback), I might be willing to settle for less and increase the “range of acceptance”. In the context of leadership and followership, such flexibility might also be possible. For example, after several interactions with a series of bad leaders, a follower might be willing to increase his/her “acceptance range” of a less than ideal leader with possible implications for prototype readjustment and ILT change.

9. Implications and agenda for future research

Throughout this review we have identified several directions for future research. We will not repeat them all here but instead try to offer some general observations, research ideas that have not been explicitly addressed in our previous discussion, as well as practical suggestions for leadership development.

9.1. Organizational research implications

Given the limited number of organizational studies on ILTs and that research on IFTs has just started, the potential for organizational research that addresses real-world implications of information-processing approaches to leadership and followership is significant.

First, it became evident from our previous discussion that a promising line of research for both ILTs and IFTs is on antecedents. The importance of self-perceptions for ILTs has also been acknowledged by Müller and Schyns (2005) as well as Van Quaquebeke, van Knippenberg, and Brodbeck (2011). Future research could examine leader and follower core self evaluations (e.g., Judge & Bono, 2001), personality traits (Judge, Bono, Ilies, & Gerhardt, 2002) and self-construal (e.g., Cross, Hardin, & Gercek-Swing, 2012) as possible antecedents of Implicit Leadership and Followership Theories. Research could also empirically examine Keller’s (2003) propositions for the impact of attachment styles on ILTs. The role of trait and state affect for ILTs and IFTs could also be an exciting new line of research as we discussed in Section 6.2.

Second, in addition to further examining the impact on ILTs and IFTs on Leader–Member Exchanges and transformational leadership, other leadership variables such as authentic leadership (e.g., Avolio &Gardner, 2005;Walumbwa, Avolio, Gardner,Wernsing, & Peterson, 2008) and ethical leadership (e.g., Brown & Treviño, 2006) could be investigated in the particular context. One question worthy of attention is the possible overlap of authentic leadership with leadership prototypes: “Are authentic leaders prototypical leaders?”. Research could thus examine the effects of follower implicit–explicit ILT congruence on their authentic leadership perceptions but also leader self-schemas can be of special interest in the specific context. Congruence of leaders’ ILTs with their own perceptions of the leadership traits they exhibit could potentially affect follower perceptions of authentic leadership. Leaders whose perception of their leadership behavior is closer to their implicit prototype might be also seen by followers as more authentic and genuine (true to themselves).

In addition to their documented impact on LMX, ILTs and IFTs could be important predictors of LMX Differentiation processes. LMX Differentiation is defined as the degree of within-group variation that exists when a leader forms different quality relationships with different members (e.g., Erdogan & Bauer, 2010; Liden, Erdogan, Wayne, & Sparrowe, 2006; Martin, Epitropaki, Thomas, & Topakas, 2010). A high degree of variability might create conditions that promote competition and antagonism among team members, whereas low levels of variability might enhance cooperation and social harmony in the group (Hooper & Martin, 2008). An obvious implication for IFT research could be that low levels of congruence of leader’s IFTs and explicit IFTs traits observed in the majority of his/her followers leads to high levels of LMX differentiation. The leader is likely to form excellent relations with only a few followers that fit the follower prototype and bad relations with the majority of followers who don’t. Furthermore, LMX Differentiation research has generally adopted a leader-centric approach, that is, the observed variability in relationships is seen as the outcome of leader’s choices and preferences. If we, however, adopt a more follower-centric perspective, ILTs can also affect LMX Differentiation. Followers who perceive low levels of match between their ILTs and observed leader characteristics are also likely to make less effort to cultivate a good relationship with the leader. If many followers experience such incongruence and very few see a prototype-actual match, high levels of variability in leader–follower relationships are likely to exist.

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Furthermore, ethical leadership (e.g., Mayer, Aquino, Greenbaum, & Kuenzi, 2012; Mayer, Kuenzi, Greenbaum, Bardes, & Salvador, 2009) implications can be addressed. Interestingly, the leader or follower being ethical is not part of current conceptualizations of implicit leadership and followership. The only related traits that can be identified in existing ILTs lists (e.g. Lord et al., 1984; Offermann et al., 1994) are ‘honest’ and ‘trustworthy’ and in the IFTs literature is the Good Citizenship dimension (e.g., reliable, loyal) of IFTs (Sy, 2010) (Sy’s initial itemgeneration of 161 attributes in Study 1did identify the related traits such as “truthful,” “sneaky,” “integrity,” “fair,” but these did not survive subsequent rounds of construct validation). The specific trait ‘ethical’ cannot be found in either ILTs or IFTs lists. Even in the Chinese Implicit Leadership Theories scale (Ling et al., 2000) that identified a separate Personal Morality factor, the ‘ethical’ trait is not present. Their list includes similar traits to the ones we mentioned before (e.g., honest, trustworthy, self-disciplined) and they further identify one trait more clearly related to ethical decision-making, i.e., incorruptible. What are the implications of such an absence? If being ‘ethical’ is not part of people’s cognitive structures and ‘lay theories’ of leadership and followership, is ethical leadership a counter-intuitive notion, a form of transcendence and we thus shouldn’t be surprised by the several instances of leader (and follower) violations and misconduct? Or via adopting a connectionist perspective, could we argue that ethical leadership or followership is relevant in particular contexts only and an ‘ethical’ node might be activated in such contexts (e.g., religious leaders and followers) but not in others (e.g. business)? This is a research area of considerable potential.

We can also identify implications for creativity research. Similar to the absence of ‘ethical’, also striking is the absence of the trait ‘creative’ from existing lists of ILTs and IFTs (e.g., Offermann et al., 1994; Sy, 2010) (Sy’s Study 1 did initially identify “not innovative”, “uncreative,” and “cannot think for oneself” but these items did not survive subsequent rounds of construct validation). As a matter of fact, in Lord et al.’s (1984) list, the trait ‘creative’ was included in the non-leader attributes list which clearly indicates that creativity is not viewed as a core characteristic of leadership (Epitropaki, 2012). On the contrary, creativity is associated with non-leadership. Mueller, Goncalo, and Kamdar (2011) take this idea further and report a negative association between expressing creative ideas and assessment of leadership potential. Their studies, however, showed that when the charismatic leader prototypewas activated in observers’ minds they tended to view the idea espoused by the “charismatic” leader as more creative. Mueller et al. (2011) further suggested that it is possible that people under-estimate the leadership potential of creative individuals, but over-estimate the creative potential of charismatic leaders. It would be therefore of interest for future research to examine the effects of ILTs on creative leadership (e.g., Sternberg, Kaufman, & Pretz, 2003) and of IFTs on employee creativity processes (e.g., Amabile, Schatzel, Moneta, & Kramer, 2004).

Another area of organizational research that could benefit by taking into account ILTs and IFTs issues is that of newcomer socialization (e.g., Bauer, Bodner, Erdogan, Truxillo, & Tucker, 2007; Van Maanen & Schein, 1979). The organizational socialization theory assumes that newcomers will try to reduce uncertainty. Uncertainty reduction theory (Berger, 1979) suggests that people seek information during their organizational entry period in an attempt to create a predictable environment. Several authors have noted the importance of the initial period of employment in an organization in shaping employees’ subsequent attitudes and behaviors and particular attention has been drawn to the socialization experiences that organizations provide to newcomers (e.g., Allen & Meyer, 1990; Wanous, 1980). Within this context, the role of pre-existing knowledge structures and past experiences in the socialization process has been generally acknowledged. Jones (1983) described individuals as developing “cognitive maps” on the basis of previous experiences and stated that these cognitive structures would moderate newcomers’ definitions of events and generally affect the way socialization experiences are learned and interpreted. ILTs and IFTs as pre-existing cognitive structures on leadership and followership can potentially have a significant impact on the development of interpersonal relationships during the organizational socialization process.

9.2. Implications for levels-of-analysis

As indicated in Section 7, theoretical work on ILTs and IFTs has clearly addressed the level of analysis issue and has incorporated individual, group, task, organizational and cultural constraints (e.g., Hanges, Lord, & Dickson, 2000; Lord et al., 2001). When we, however, focus on empirical work conducted on ILTs and IFTs in organizational settings, a different pattern emerges. ILTs and IFTs have mainly been viewed as intrapersonal-level constructs that reside within the person and affect perceptions of leadership and/or followership. Research adopting the social identity leadership perceptive (e.g. De Cremer, van Dijke, & Mayer, 2010; van Knippenberg & van Knippenberg, 2005) – that we will cover later – can be viewed as an exception as it explicitly focuses on the group-level. Most studies employ single-source design examining either followers’ ILTs or leaders’ IFTs (e.g., Den Hartog et al., 1999; Duong, 2012; Epitropaki & Martin, 2004, 2005; Johnson et al., 2012; Sy, 2010) and few studies have utilized a two-source methodology (e.g., Engle & Lord, 1997; Sy, 2011; Tram-Quon & Sy, 2013). Furthermore, current conceptualizations and research on ILTs and IFTs, despite acknowledging group and organizational constraints, basically focus on one single leader or follower and in a sense adopt a traditional, individualistic and hierarchical view of leadership. Individuals are categorized as leaders or non-leaders (or followers or non-followers) on the basis of their match to an individual prototype. Shondrick et al. (2010) highlighted the challenge that the shared leadership concept poses for implicit leadership theory. They also suggested two alternative possibilities, that “in shared, complex leadership situations paymore attention to momentary goals than the person-focused construct of leadership” (p. 973) and that “people focus more on affectively-based structures to gain an understanding of micro-level processes” (p. 973). None of the empirical studies has explicitly addressed the multi-level nature of ILTs and IFTs and implications for shared leadership conceptualizations (e.g., Contractor, DeChurch, Carson, Carter, & Keegan, 2012; Schriesheim, Castro, Zhou, & Yammarino, 2001; Yammarino & Dansereau, 2008). Thus, the potential for research (and

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theoretical advancements) in that direction is vast. We will specifically offer some suggestions on the dyadic and collective level of analysis.

9.2.1. Dyadic level The dynamic interplay between ILTs and IFTs has not been extensively addressed with the exception of two theoretical papers,

by Shondrick and Lord (2010) and Van Gils et al. (2010). Shondrick and Lord (2010) stress that both types of implicit theories are important as leadership and followership are socially constructed processes. They further highlight the dynamic nature of ILTs and IFTs and the impact of contextual influences and constraints (Lord et al., 2001). Van Gils et al. (2010) further attempted to explain current asymmetries and disagreements observed in leader- and follower-assessments of LMX via differences in both parties’ implicit theories. Examining ILTs and IFTs on the dyadic level can offer us important insights on leader–follower processes. There has been one published study that has specifically looked at relational schemas of leadership (Huang, Wright, Chiu, & Wang, 2008). 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. Huang et al. (2008) found leaders and members formed different relational schemas. Specifically, leaders developed schemas focused on work-related issues whereas members were focusingmore on interpersonal concerns.We consider relational schemas of leadership a promising line of research that can extend ILT and IFT research to the dyadic level of analysis. Based on Baldwin’s (1992) three-element conceptualization of relational schemas (self-schema, other-schema and interpersonal script) we offer a graphical representation of relational schemas in leader– follower relationships in Fig. 3.

Leadership and followership research can generally benefit from incorporating insights from relationship science and close relationships research (for a review see, Thomas, Martin, Epitropaki, Guillaume, & Lee, 2013). Information processing is fundamental to interaction in close relationships and the importance of determining the cognitive mechanisms that govern relational exchanges has been widely acknowledged (e.g., Arias & Beach, 1987; Eberly, Holley, Johnson, & Mitchell, 2011; Scott, Fuhrman, & Wyer, 1991). In the context of close relationships, in addition to relational schemas (Baldwin, 1992), it has further been suggested that individuals hold Implicit Theories of Relationships, i.e., schemas about what makes for a good relationship which in part, determine one’s goals and motivations in relationships (Knee, 1998; Knee, Patrick, & Lonsbary, 2003). Implicit Theories of Relationships, ITRs (e.g., Knee, 1998) focus on beliefs about whether relational partners are “meant to be” (i.e., destiny beliefs) or if the relationship must be nurtured and cultivated (i.e., growth beliefs). Individuals who hold destiny IRTs, base the success of their romantic relationships on whether the partner was the person with whom they were “meant to be” (Knee et al., 2003) and are susceptible to high disillusionment or false glee due to their “all or nothing” mentality. Relatedly, Knee (1998) showed that destiny theorists’ relational satisfaction depends upon their ability to perceive their partner as the ideal partner. Once a relational partner is no longer considered to be “ideal,” destiny theorists often terminate the relationship. In contrast, people with growth IRTs consider such difficulties as the impetus for positive change and growth in the relationship (Knee et al., 2003).

Fletcher, Simpson and colleagues (e.g., Fletcher, Simpson, Thomas, & Giles, 1999; Fletcher et al., 2000) also utilized a socio-cognitive approach and focused on ideal standards in close relationships. Ideal standards combine elements of the actual self, the ideal partner but also the ideal relationship. The consistency (congruence) between one’s ideal standard and a partner

Fig. 3. Relational leader–follower schemas.

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affects relationship perceptions and it can explain evaluation, explanation and regulation in close relationships. The more closely a person’s ideal standard matches their perceptions of their current partner, the more positively they evaluate the relationship. Furthermore, both greater ideal–partner congruence and positive assessment of the relationship quality have been found to be negatively related to the likelihood of relationship dissolution over time (Fletcher et al., 2000). Building on this, research on the dyadic-level could, for example, examine Implicit Theories of Leader–Follower Relationships. People might hold implicit theories of not only an ‘ideal’ leader or an ‘ideal’ follower but also of an ‘ideal’ LMX relationship and issues related to the content and stability of Implicit Theories of Leader–Follower Relationships (ITLFRs) could be examined.

9.2.2. Collective level On the collective level, there are three lines of research of relevance to ILTs and IFTs. First, on the group level, the social identity

theory of leadershipwhich has been developed principally by Hogg, van Knippenberg and colleagues (e.g., Hogg, 2001; Hogg & van Knippenberg, 2003; Hogg, van Knippenberg, & Rast, 2012) is of interest. This is a social cognitive approach that, in short, proposes that effective leaders are highly group-prototypical, i.e., they embody the desirable characteristics and behaviors of group members and therefore are in a position to influence group members. Prototypes in this approach are not alien to the concept of Implicit Leadership Theories (ILTs, Lord et al., 1984) discussed earlier. Whereas ILTs refer to a representation of a leader in general (that might apply across many organizational contexts), leader group prototypicality refers to what group members believe are the desirable ways to think, feel and behave in their group. Prototypical leaders are more central and important to self-definition than non-prototypical leaders because they embody group norms and are more likely to favor the in-group and promote the well-being of their group. Numerous studies, across different occupations and cultures, have shown that prototypical leaders are perceived as more desirable and effective than non-prototypical leaders (see Hogg et al., 2012, for a recent review).

Second, an interesting (and new) line of research focuses on Leadership Structure Schemas (LSS) defined by DeRue and Ashford (2010) as cognitive schemas of how leadership should be structured (hierarchical vs. shared leadership). Hierarchical LSS portray leadership as best initiated by a single leader whereas shared LSS portray leadership as most effective when shared by all group members. Although published empirical work on LSS is still limited given its recent proposal, this is an active line of research (especially by De Rue and his colleagues) that is worth attention in relation to future directions for ILTs and IFTs research.

A third line of research that is of potential interest is that on network schemas of leadership (e.g., Janicik & Larrick, 2005). For example, Balkundi and Kilduff (2006) focused on network schemas and discussed the idea that a leader’s cognitive representations of social networks determine both the choices leaders make as well as leadership effectiveness. They build on the idea that networks are both cognitive structures that reside in the mind of organizational actors as well as actual structures of relationships among them and specifically stated that the “network approach locates leadership not in the attributes of individuals but in the relationships connecting individuals” (p.942). Although Balkundi and Kilduff (2006) have not offered a graphical representation of network leadership– followership schemas, Fig. 4 attempts to capture such a notion. We specifically suggest that in a network of shared leadership and followership roles, each organizational actorwill utilize both ILTs and IFTs as part of their self-schema aswell as of their other-schema for each of the actors they interact with. We also assume that a network leadership–followership script (similar to the interpersonal script proposed by Baldwin regarding relational schemas)will emerge and subsequently determine the pattern of leader–follower interactions among network actors.

Fig. 4. Network schemas in shared leadership–followership interactions.

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9.3. Implications for leadership development

In light of continued calls for research on leader development (e.g., Day, 2011), it is important to highlight the application of Implicit Leadership and Followership Theories for developing leaders and followers.

First, leaders and followers may need to develop awareness about the expectations for their leadership context (i.e., the ILTs and IFTs that are operating) and how implicit theories shape action tendencies. This is particularly important given that much of daily behaviors operate without full conscious awareness (Wood, Quinn, & Kashy, 2002) and individuals may not be fully aware of how their implicit theories shape action tendencies without such training. One effective training intervention for raising self- and social-awareness regarding the expectations for leaders and followers is the drawing exercise developed by Schyns, Kiefer, Kerschreiter, and Tymon (2011) that can be used as a vehicle for understanding how leader (and follower) prototypes are developed and shaped. Although raising awareness and developing an understanding of implicit theories is important, such interventions may be limited to contexts where individuals are consciously aware of their behaviors and have sufficient motivation and opportunities (e.g., time and cognitive capacity permitting) to control their behaviors (Bargh, 2006; Gawronski & Payne, 2010; Smith & DeCoster, 2000; Strack & Deutsch, 2004). Two other interventions show promise for changing implicit processes: Conditioning and Selective Prototype Activation (Gawronski & Bodenhausen, 2006b). Conditioning involves pairing a concept (e.g., follower) with a new association (e.g., productive). Such conditioning may require several hundred trials (Olson & Fazio, 2001), although this process may be facilitated via readily available software training programs that have shown positive results for changing implicit associations (e.g., IAT) (Kemps, Tiggemann, Martin, & Elliott, 2013). Selective Prototype Activation assumes that individuals hold multiple (positive and negative) IFTs, and any given prototype may be activated in a given instance (Hanges et al., 2000; Lord & Shondrick, 2011; Sy, 2010; Sy et al., 2010). Accordingly, this intervention involves repeated cueing of positive prototypes (of leadership and followership) such that they become chronically accessible. Selective Prototype Activation can be implemented via games and by eliciting emotions (Kruse & Sy, 2011; Sy, 2013), as described earlier. In turn, the activated prototypes shape action tendencies because individuals use schemas that are most readily accessible in responding to others (Chen & Bargh, 1997; Devine, 1989; Srull & Wyer, 1979). In addition to proximal effects, selective prototype activation may have distal effects in that over time it may shift individuals’ implicit theories toward a permanent positive change.

10. Summary and conclusions

Our review has highlighted the positive contributions that socio-cognitive approaches have made to understanding leadership and followership in applied settings. We clarified common misperceptions regarding the implicit nature of ILTs and IFTs and further explained their theoretical foundations and causal mechanisms. We reviewed both direct and indirect measures and also synthesized current and ongoing research (e.g., in relation to LMX and performance). We further highlighted a series of yet to be published new developments (e.g., in relation to transformational leadership, affect, indirect assessment methods, and selective activation of IFTs) and different levels of analysis that should be addressed in the context of leader and follower schemas. Together, these results demonstrate that ILTs and IFTs have significant practical implications for leadership and workplace outcomes. We accordingly provided perspectives on practical interventions for using ILTs and IFTs for the development of leaders and followers. In sum, ILTs remain a strong line of leadership research, while IFTs have infused a new perspective and excitement in our understanding of leadership and followership.

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  • Implicit Leadership and Followership Theories “in the wild”: Taking stock of information-processing approaches to leadershi…
    • 1. Introduction
    • 2. An overview of Implicit Leadership Theories and Implicit Followership Theories in applied settings
    • 3. What is ‘implicit’ in ILTs and IFTs?
    • 4. Theoretical underpinnings of ILTs and IFTs
      • 4.1. Early approaches
      • 4.2. Recent theoretical developments
    • 5. ILT and IFT measurement: Direct vs. indirect measures
      • 5.1. Direct measures
        • 5.1.1. Trait-lists
        • 5.1.2. Congruence scores
        • 5.1.3. Variable- vs. person-oriented approaches
      • 5.2. Indirect measures
        • 5.2.1. Accessibility-based measures
        • 5.2.2. Association-based measures
        • 5.2.3. Interpretation-based measures
    • 6. ILT and IFT research in organizational settings
      • 6.1. Generalizability
      • 6.2. Antecedents
      • 6.3. Outcomes
        • 6.3.1. Leader-Member Exchanges (LMX)
        • 6.3.2. Transformational leadership
        • 6.3.3. Job attitudes
        • 6.3.4. Job performance
      • 6.4. Mediators and moderators
    • 7. Levels of analysis in leadership and followership schemas
    • 8. Change of ILTs and IFTs over time
    • 9. Implications and agenda for future research
      • 9.1. Organizational research implications
      • 9.2. Implications for levels-of-analysis
        • 9.2.1. Dyadic level
        • 9.2.2. Collective level
      • 9.3. Implications for leadership development
    • 10. Summary and conclusions
    • References

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