what do you think of followers? examining the content, structure, and consequences of implicit...

Organizational Behavior and Human Decision Processes 113 (2010) 73–84

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Organizational Behavior and Human Decision Processes

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What do you think of followers? Examining the content, structure,and consequences of implicit followership theories

Thomas SyDepartment of Psychology, University of California, 900 University Ave., Riverside, CA 92521, United States

a r t i c l e i n f o a b s t r a c t

Article history:Received 21 October 2009Accepted 28 June 2010Available online 23 July 2010

Accepted by Daan van Knippenberg

Keywords:Implicit theoryFollowershipPrototypesLeadershipCategorization theory

0749-5978/$ - see front matter � 2010 Elsevier Inc. Adoi:10.1016/j.obhdp.2010.06.001

E-mail address: [email protected]

Implicit followership theories (IFTs) are defined as individuals’ personal assumptions about the traits andbehaviors that characterize followers. Goals of this research were to: (1) Identify the content and struc-ture of IFTs, (2) examine the relationship between IFTs and extant implicit theories in the leadership lit-erature, and (3) establish a preliminary nomological network of leaders’ implicit followership theories byexamining its consequences for leader–follower interpersonal outcomes. This study included 1362 par-ticipants across five separate studies and seven samples. Results provide evidence for content, conver-gent, discriminant, criterion, and incremental validity, as well as internal and temporal consistency ofthe IFTs instrument. IFTs are represented by a first-order structure (Industry, Enthusiasm, Good Citizen,Conformity, Insubordination, and Incompetence), and a second-order structure (Followership Prototypeand Antiprototype). Leaders’ IFTs predicted interpersonal outcomes: liking, relationship quality, trust,and job satisfaction. Future research and practical implications are discussed for this understudiedbranch of leadership research.

� 2010 Elsevier Inc. All rights reserved.

Introduction

What are the perceptions that individuals have about follow-ers? A fundamental task of all organisms is to classify and catego-rize stimuli in their environment (Rosch, 1978). In particular,research from the social cognition literature indicates that individ-uals have a natural propensity to classify others (Fiske & Taylor,1991). In organizational settings, researchers have posited thatindividuals are naturally inclined to classify people as leadersand followers (Engle & Lord, 1997; Lord, Foti, & Phillips, 1982; Lord& Maher, 1993). While a rich body of research on implicit leader-ship theories (ILTs) has been established in the past 30 years, thereis noticeably little research on the corresponding notion of implicitfollowership theories (IFTs) despite evidence in support of IFTs. Forexample, McGregor (1960) posited that Theory X leaders have dif-ferent assumptions about the personal attributes of followers thando Theory Y leaders. Likewise, Eden (1990) proposed that leaders’performance expectations are influenced by their implicit theoriesabout workers. In addition, research has demonstrated that trans-formational and transactional leaders have different follower-sche-mas (Goodwin, Wofford, & Boyd, 2000; Wofford & Goodwin, 1994).Likewise, followers possess different follower-schemas that areinfluenced by context (Carsten, Uhl-Bien, West, Patera, & McGre-gor, 2010). Thus, leadership theories and empirical evidence indi-

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cate that individuals have preconceived notions or implicittheories about followers.

Individuals’ cognitions shape their judgment of and response toothers (Fiske & Taylor, 1991). Indeed, research has established thatindividuals utilize ILTs to judge and respond to leaders (Lord & Ma-her, 1993). Like ILTs, individuals’ IFTs may shape how they judgeand respond to followers, which has implications for outcomes inleader–follower contexts. Research on IFTs addresses a major gapin the leadership literature on how leaders and followers ‘‘perceive,decide, behave, and take action” (Avolio, Walumbwa, & Weber,2009). Furthermore, insights generated from research integratingboth ILTs and IFTs may provide a more complete understandingof leadership (van Gils, van Quaquebeke, & van Knippenberg,2010). As such, the goal of the present research is to examine im-plicit followership theories (IFTs). Specifically, three key researchquestions are addressed in the present research: (1) What is thecontent and structure of IFTs, (2) How are IFTs related to implicittheories in the extant leadership literature (i.e., implicit leadershiptheories and implicit performance theories), and (3) What are theconsequences of IFTs for leader–follower interpersonal outcomes?

Theoretical foundation and construct definition of IFTs

Research indicates that individuals are cognitive misers whonaturally categorize others to streamline cognition because cate-gories serve the function of simplifying the external world (cogni-tive economy), permitting abstract and symbolic thinking, and

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74 T. Sy / Organizational Behavior and Human Decision Processes 113 (2010) 73–84

providing a shared system of labels that facilitate communication(Fiske & Taylor, 1991). This process of categorizing others is sofundamental that it operates automatically and spontaneously(within milliseconds) by the mere presence of a stimulus target(Boldenhausen & McCrae, 1998). Individuals categorize otherson the basis of visually salient cues (e.g., race, gender, age, etc.)and social roles (Operario & Fiske, 2004) such as leader and fol-lower. Research on the categorization of leaders in the organiza-tional literature has been examined within the context of ILTs.Surprisingly, research on the corresponding notion of IFTs isnoticeably absent despite its appearance in the literature nearlytwo decades ago (e.g., Eden, 1990; Lord & Maher, 1993).

IFTs are defined as individuals’ personal assumptions about thetraits and behaviors that characterize followers. Consistent withthe literature on implicit theories, IFTs represent individuals’ ‘‘lay”or ‘‘naïve” theories (vs. formal theories) (Rosenberg & Jones, 1972).IFTs likely form at an early age (Hunt, Boal, & Sorenson, 1990) viasocialization, and further develop as individuals gain experienceswith followers (Lord & Maher, 1993). Central components of IFTsare prototypes, defined as abstract composites of the most repre-sentative member or the most commonly shared attributes of aparticular category (Lord et al., 1982; Rosch, 1978). Prototypesmay be based on common taxonomy (central tendency prototypes,i.e., ‘‘how followers are”) or goal-derived (ideal prototypes, i.e.,‘‘how followers should-be”) (Barsalou, 1985; Schyns & Meindl,2005). Goal-derived follower prototypes have received some atten-tion in the literature. For example, followers’ perceptions of effec-tive followers include the attributes of ‘‘integrity,” ‘‘dependable,”‘‘communication skills,” etc. (Carsten et al., 2010). Goal-derived fol-lower prototypes also have been examined under the framework ofimplicit performance theories (IPTs), defined as performance expec-tations for employees, and include the parallel attributes of ‘‘hon-est,” ‘‘reliable,” ‘‘communicates effectively,” etc. (Engle & Lord,1997; Wernimont, 1971). As such, IPTs conceptually overlap withgoal-derived follower prototypes in that both reflect expectationsfor effective followers, thereby consisting of only positive attri-butes. In comparison, common taxonomic follower prototypesare broader based, consisting of both positive and negative attri-butes (Eden, 1990; Goodwin et al., 2000; McGregor, 1960; Pillai& Uhl-Bien, 2007; Wofford & Goodwin, 1994) that provide a morecomprehensive representation of followers. Indeed, scholars haveasserted that perceptions of followers may be more negative thanpositive (Pillai & Uhl-Bien, 2007). The focus of the current researchis common taxonomic follower prototypes.

IFTs may consist of both universal dimensions that are pertinentacross contexts and idiosyncratic dimensions that are context spe-cific (van Gils et al., 2010). Consistent with the trajectory of re-search on ILTs, it may be more relevant to examine first theuniversal dimensions of IFTs (Epitropaki & Martin, 2004), with sub-sequent stages focusing on context-specific dimensions (Ensari &Murphy, 2003; House et al., 2004; Johnson, Murphy, Zewdie, & Rei-chard, 2008). Furthermore, while context may influence individu-als’ implicit theories (Foti, Knee, & Backert, 2008; Hanges, Lord, &Dickson, 2000), contextual effects likely reflect differences inendorsement for the same set of core attributes rather than actualdifferences in attribute content (Epitropaki & Martin, 2004). In-deed, differences in ILTs as a function of gender (Ensari & Murphy,2003; Johnson et al., 2008), culture (Gerstner & Day, 1994), andrace and occupation (Sy et al., in press) primarily reflect differencesin endorsement for the same set of core leadership attributes. Like-wise, contextual differences in perceptions of effective followersprimarily reflect differences in endorsement for the same set ofcore follower attributes (e.g., differences in endorsement for obedi-ence as an effective follower attribute) (Carsten et al., 2010). Thus,identifying the core content and structure of IFTs in the currentresearch affords cross-context comparisons, thereby facilitating

future research on contextual effects on IFTs (Epitropaki & Martin,2004; House et al., 2004).

Theoretical relevance of IFTs

Research on IFTs answers the call to address two key challengesto advance the field of leadership (Avolio et al., 2009): (1) The needto be more holistic in the examination of leadership by integratingfollowers as a focal element, and (2) the emerging trend of exam-ining leaders’ cognitions, and how they process information, par-ticularly, leaders’ perception of followers. As such, IFTs may helpadvance our understanding of leadership.

IFTs serve as ‘‘sensemaking” functions (Weick, 1995) fromwhich individuals interpret, understand, and respond to followerbehaviors (Poole, Gioia, & Gray, 1989). IFTs may influence individ-uals’ behaviors because they use IFTs as a benchmark to formimpressions of followers (Lord & Maher, 1993). Individuals engagein a matching process of comparing their IFTs with a target person(e.g., a follower) and based on the degree of congruence, individu-als form an impression of followers that subsequently shapes theirbehaviors towards followers. Furthermore, inference-based pro-cesses (Lord & Maher, 1993) posit that IFTs can be inferred fromfollowers’ performance. Inference-based processing involves mak-ing attributions of follower characteristics based on outcomes ofsalient events. For example, followers are perceived as industriouswhen business goals are successfully accomplished.

Individuals also may internalize and endorse certain IFTs overtime, which may predispose them to judge and respond to followersin a certain fashion (Engle & Lord, 1997; Lord & Maher, 1993) be-cause implicit theories may operate spontaneously and automati-cally (Boldenhausen & McCrae, 1998). For example, theoristshave argued that leaders’ management style is a function of theirpredisposed assumptions of followers (McGregor, 1960). Indeed,research demonstrates that leaders have different follower-sche-mas that predispose them to interpret events differently, which re-sults in correspondingly different behaviors toward followers(Goodwin et al., 2000). In sum, IFTs may influence outcomes in lea-der–follower contexts because IFTs (1) serve as benchmarks fromwhich individuals judge and respond to followers, and (2) predis-pose individuals to judge and respond to followers in a certainfashion. The benchmark and predisposition propositions are con-sistent with theorists’ propositions that implicit theories affectjudgments and behaviors via their impact on controlled anduncontrolled information processing (van Gils et al., 2010).

Because IFTs may be antecedents of leaders’ and followers’ af-fect, behaviors, and cognitions (Lord & Maher, 1993), IFTs may haveparticular relevance on leader–follower interpersonal outcomes(Graen & Uhl-Bien, 1995). Thus, leaders who have more positiveIFTs may behave differently towards followers than leaders whohave more negative IFTs (McGregor, 1960). Differences in leaders’behaviors towards followers, as a function of their IFTs, should im-pact leader–follower interpersonal outcomes such as liking forleaders and followers, relationship quality, etc. (The impact of lead-ers’ IFTs on interpersonal outcome variables are examined in Study5). It may be that the effect of leaders on followers is explainedpartly by IFTs. Indeed, existing evidence shows that performancedifferences between followers may largely result from leaders’ per-ceptions of and subsequent interactions with their followers(Goodwin et al., 2000; Wofford & Goodwin, 1994). Much can begained by understanding how leaders utilize implicit theories tointerpret their environment and subsequently guide leadership ac-tions (Avolio et al., 2009; Lord & Brown, 2004). Much can also begained by understanding how leaders’ IFTs impact followers’ affect,behaviors, cognitions (i.e., subsequent information processing),and outcomes. Research has demonstrated that followers tend to

T. Sy / Organizational Behavior and Human Decision Processes 113 (2010) 73–84 75

fulfill the perceptions leaders have of them (Eden, 1992). In fact,the role of leaders in shaping followers is so central that scholarshave recently reconceptualized leadership as the process by whichleaders transform followers (Lord & Brown, 2004).

Furthermore, the utility of IFTs is that it may augment extantmodels of leadership. For example, whereas ILTs have explainedhow followers use their implicit theories of leaders to guide theiractions toward leaders (e.g., determining who is a good leaderand whether to follow their directives), IFTs may explain how lead-ers use their implicit theories of followers to guide their actions to-ward followers (e.g., determining whether to reward or punish)(Engle & Lord, 1997), as well as explain how followers use their im-plicit theories of followers to guide their own actions (Carstenet al., 2010). In a similar vein, IFTs may advance our understandingof Leader Member Exchange (LMX) theory by illuminating howcongruence in leaders’ and followers’ ILTs and IFTs may accountfor relationship quality, i.e., leaders and followers both have ILTsand IFTs that function as interpretation frameworks from whichrelationship quality is judged (van Gils et al., 2010). Furthermore,IFTs may further our understanding of Pygmalion effects. A missinglink in Pygmalion research is the lack of explanation for the ante-cedents of leaders’ performance expectation. Indeed, Eden (1990)has identified IFTs as potential antecedents of leaders’ performanceexpectations.

Overview of studies

The methods utilized by Offermann, Kennedy, and Wirtz (1994)and Epitropaki and Martin (2004) were consulted in the develop-ment and validation of the IFTs instrument because their proce-dures followed extensive and rigorous validation processes.Furthermore, this approach results in the development of a shortmeasure of IFTs, which has practical value for organizational re-search by minimizing respondents’ workload, fatigue, and bias,while improving response rates (Epitropaki & Martin, 2004). Thisstudy also follows established scale development procedures (Hin-kin, 1998). Accordingly, the current research consists of fivephases, each corresponding to Studies 1–5. The goal of Study 1was to generate a comprehensive and representative pool of itemsfor the IFTs instrument. The goals of Study 2 were to identify theunderlying structure of IFTs, and examine internal consistenciesof the identified factors. The goals of Study 3 were to cross validatethe factor structure, and evaluate convergent and discriminantvalidity. The goal of Study 4 was to assess temporal consistency,with the secondary purpose of providing additional cross valida-tion evidence for the factor structure of IFTs. The goal of Study 5was to examine the theoretical relevance and consequence of IFTs,and in doing so, provide evidence of criterion and incrementalvalidity.

1 The list of items is available from the author upon request.

Study 1: Item generation

Study 1 utilized an inductive methodology. An inductive meth-od is appropriate when novel constructs lack substantial researchto guide content development (Hinkin, 1995). Furthermore, thesingle adjectival approach (e.g., ‘‘productive”) was employed in-stead of the statement-based approach (e.g., ‘‘In general, followersare productive”) because accumulating evidence indicates that theformer is methodologically superior (Gill & Hodgkinson, 2007).

Method

ParticipantsStudy 1 consisted of 149 workplace leaders from a variety of

industries (e.g., professional services, transportation, telecommu-

nication, retail, manufacturing, etc.). Participant demographicsincluded: 73 (49%) males, average age of 35.85 years (SD = 11.54),16.16 (SD = 10.33) average years of work experience, 32.9% AsianAmerican, 23.5% Caucasian, 19.5% Hispanic, 6% African American,7.4% ‘‘other,” and 10.7% who did not indicate their race.

ProcedureWorkplace leaders were recruited by a team of trained under-

graduates. Participants responded to one of four surveys that askedthem to list up to 20 traits or characteristics of either a ‘‘follower,”‘‘effective follower,” ‘‘ineffective follower,” or ‘‘subordinate.” Theseterms were included as stimulus cues in order to capture a widedomain of characteristics representing IFTs. Because there maybe distinctions for perceived effectiveness of a target person, stim-ulus cues for effective and ineffective followers were included. Inaddition, the possibilities that distinctions exist as a function ofthe hierarchical structure of cognitive categories were considered.That is, cognitive categories may be organized hierarchically (e.g.,superordinate, basic, etc.) with each level reflecting the degree ofinclusiveness for the cognitive categories (for a review, see Lordet al., 1982). Consistent with past theorizing (Offermann et al.,1994), ‘‘follower” and ‘‘subordinate” reflect superordinate-leveland basic-level terms, respectively. In addition, consistent withthe literature on implicit theories as ‘‘lay” theories, no definitionsof the stimulus cues were provided (Offermann et al., 1994).

Results

Once a set of items was generated, three faculty members fromthe leadership field reviewed them to establish preliminary faceand content validity. The various follower cues (i.e., ‘‘follower,”‘‘effective follower,” and ‘‘ineffective follower”) generated 1030 un-ique items. The typical items generated from the ‘‘subordinate” cuewere well reflected in the pool of 1030 items, either in exact terms(e.g., shy), by synonym (e.g., timid), or by its exact opposite (e.g.,outgoing). The frequency with which each item was nominatedwas then calculated. Items that were nominated only once or twice(e.g., skeptical) were deleted. Items that were obvious synonyms(e.g., smart and intelligent) were combined in order to reducethe number of items to a manageable size. This procedure yieldeda pool of 161 items.1

Study 2: Exploratory factor analysis

The goal of Study 2 was to identify the underlying structure ofIFTs utilizing exploratory factor analysis.

Method

ParticipantsData were collected from 428 workplace leaders representing a

wide range of industries (e.g., professional services, education,healthcare, telecommunication, retail, etc.). Participant demograph-ics included: 257 (60%) females, average age of 35.63 (SD = 12.02),average of 7 years of leadership experience (SD = 7.05), averagework week of 42 h (SD = 13.11), 65% Caucasian, 13% Asian American,9% Hispanic, 8% African American, and 5% ‘‘other.” Participantsrepresented a wide range of leadership levels: Entry-level (39%),middle-level (23%), senior-level (16%), upper-middle-level (11%),and non-leader (i.e., had prior leadership experience but were notin leadership positions at the time of the study) (11%).

Table 1Study 2: factor matrix, communalities, item means, and standard deviation.

Factors Variables Factor loading Communalities M SD

Industry (.86) Hardworking .87 .91 6.30 2.09Productive .63 .72 6.14 2.08Goes above and beyond .46 .50 5.37 2.36

Incompetence (.74) Uneducated .81 .63 4.37 2.33Slow .57 .52 4.40 2.23Inexperienced .56 .43 5.26 2.43

Conformity (.71) Easily influenced .82 .74 7.07 2.32Follows trends .64 .42 7.15 2.26Soft spoken .51 .42 6.01 2.42

Enthusiasm (.83) Excited .87 .75 5.29 2.12Outgoing .81 .66 5.09 2.12Happy .58 .55 5.71 2.04

Insubordination (.82) Arrogant �.83 .63 3.39 1.99Rude �.76 .68 3.34 1.90Bad temper �.68 .61 3.47 1.97

Good citizen (.81) Loyal .75 .64 7.07 2.14Reliable .74 .62 6.73 2.12Team player .73 .54 7.52 2.01

Note. Numbers in parentheses represent the scale reliabilities for each factor. N = 428. IFTs scale � 2008 Thomas Sy. Use of this scale for scholarly researchpurposes is granted without further permission to academic researchers at public or non-profit colleges or universities. All other rights reserved by ThomasSy.


ProcedureWorkplace leaders were recruited via a community networking

website to complete a survey on perceptions of followers. Datawere collected from two diverse samples. Sample 1 consisted of262 leaders who were compensated with a $10 gift certificate foran online retailer, and Sample 2 consisted of 166 leaders who werenot compensated. The 161 items were combined in random orderto form a single measure of follower perceptions. Using a 10 pointscale, participants were asked to indicate how characteristic eachof the items was for followers (1 = not at all characteristic; 10 = ex-tremely characteristic).2 As in Study 1, no explicit definition of theterms was provided. Responses from both samples were compared,and they were determined to be similar (t-tests indicated that re-sponses to the 161 IFTs items did not differ significantly betweensamples). As such, responses from both samples were combinedfor further analyses.

Results

The 428 participants reflected a good sample size for factoranalysis (Tabachnick & Fidell, 2001). Exploratory factor analysiswith oblique factor rotation was performed to determine the num-ber of factors. Multiple rounds of analyses were conducted, inwhich items with loadings below .30 were eliminated from subse-quent analyses. The number of factors to be extracted was guidedby Cattell’s (1966) scree test and eigenvalues above 1. On this ba-sis, a six factor solution was chosen for three reasons: (1) It was themost conceptually interpretable, (2) it resulted in sound factorstructures with strong internal consistency, and (3) it accountedfor a substantial amount of total variance explained (60%). For par-simony, the top three items for each factor were retained, resulting

2 A potential issue with the scale anchor is that it could have been construed asprototypicality (as is intended) or the unintended meaning of atypicality (i.e., not atall relevant). However, the atypicality construal is less likely because (1) the contentvalidity of the IFTs attributes were previously established with leadership scholarsand industry executives, (2) the results provided evidence for the family resemblancestructure for the attributes (Lord et al., 1982; Lord and Maher, 1993), (3) the identifiedattributes are corroborated by those of Carsten et al. (2010), and (4) none of the 1362participants indicated that they were confused by the scale anchor. Furthermore, thescale anchor is identical to those utilized in validated ILTs measures (e.g., Epitropakiand Martin, 2004; Offermann et al., 1994).

in an 18-item measure of implicit followership theories. Whilethere are no strict rules for the number of items per factor, threeitems are considered acceptable (Hinkin, 1998). Furthermore, threeitems per factor are consistent with those for ILTs, which rangefrom two to six (Epitropaki & Martin, 2004). Table 1 presents thefactor names, reliabilities, item variables, factor loadings, commu-nalities, means, and standard deviations. All items had factor load-ings above .40 and loaded on only one factor. The communalitiesranged from .42 to .91. The reliabilities ranged from .71 to .86. Con-tent analysis of the items for each of the six factors yielded thedimensions of Industry, Enthusiasm, Good Citizen, Conformity,Insubordination, and Incompetence.3

Study 3: Confirmatory factor analysis

The goal of Study 3 was to cross validate the factor structure ob-tained in Study 2. A secondary goal was to examine convergent anddiscriminant validity. Particularly, the association of IFTs to thetheoretically relevant constructs of IPTs and ILTs were of interest.

Method

ParticipantsAs in Study 2, data were collected from 397 workplace leaders

representing a wide range of industries (e.g., Professional services,leisure, retail, healthcare, telecommunication, etc.) Participantdemographics included: 214 (54%) females, average age of 34.70(SD = 11.28), average of 6 years of leadership experience (SD =6.30), average work week of 39 h (SD = 12.65), 69% Caucasian,14% Asian American, 8% Hispanic, 5% African American, and 4%‘‘other.” Participants represented a wide range of leadership levels:Entry-level (33%), middle-level (27%), upper-middle-level (14%),senior-level (13%), and non-leader (i.e., had prior leadership

3 Content validation was conducted with 25 senior level executives utilizingAnderson and Gerbing’s (1991) measures of Proportion of substantive agreement, Psa

and Substantive-validity coefficient, Csv. Psa values for the IFTs items ranged from .76to 1, with an average of .87. Csv values were all statistically significant (p < .01), with aranged from .56 to 1, and an average of .77. Results provide support for the contentvalidity of IFTs.

Table 3Study 3: intercorrelations, reliabilities, means, and standard deviations of IFTs factors.

Factors 1 2 3 4 5 6

1. Industry (.88)2. Enthusiasm .67*** (.87)3. Good citizen .63*** .63*** (.78)4. Conformity �.23*** �.17** .01 (.75)5. Insubordination �.09 �.01 �.23*** .02 (.91)6. Incompetence �.25*** �.22*** �.27*** .30*** .37*** (.85)

M 5.98 5.77 7.12 7.20 2.95 4.56SD 2.29 2.13 1.86 1.99 1.84 2.11

Note. Numbers in parentheses represent reliabilities. N = 397.** p < .01.

*** p < .001.


experience but were not in leadership positions at the time of thestudy) (13%).

MaterialsIFTs were assessed with the scale derived from Study 2. IPTs

were assessed with the shortened version of Wernimont’s (1971)scale adapted by Engle and Lord (1997). Cronbach’s alpha for all17 items was .97. ILTs were assessed with the shortened versionof Offermann et al.’s (1994) scale adapted by Epitropaki and Martin(2004). Cronbach’s alpha for the six ILTs dimensions ranged from.88 to .94.

ProcedureSurveys were administered to two diverse samples. Sample 1

consisted of 308 leaders recruited online (identical to Study 2 pro-cedures), and Sample 2 consisted of 89 leaders recruited from threelocations of a coffee house franchise (the 89 leaders were patronsof the coffee house). Sample 1 leaders completed the surveys on-line and were compensated with a $5 gift certificate for an onlineretailer. Sample 2 leaders completed a paper version of the surveyand were compensated with a $5 gift certificate for the coffeehouse franchise. Results for Sample 1 were no different from thecombined samples. Thus, the results of the combined samples werereported.

Results and discussion

The combined sample of 397 participants was considered agood sample size (Tabachnick & Fidell, 2001). Maximum likelihoodconfirmatory factor analysis was used with AMOS 16.0 to examinethe validity of the six factors of IFTs. In line with Kline’s (1998) rec-ommendation, four statistics for assessing model fit were reported:Normed chi-square measure (v2/df), comparative fit index (CFI),Tucker-Lewis index (TLI), and root–mean–square error of approxi-mation (RMSEA).

First-order six-factor modelIt was hypothesized a priori that (1) responses to the IFTs scale

would be explained by six factors, (2) each item would have a non-zero loading on its designated factor and zero loadings on all otherfactors, (3) the six factors would be correlated, and (4) measurementerror terms would be uncorrelated. The hypothesized model of sixfactors was further tested with competing models: (1) A null modelspecifying that the IFTs items have no existing relationship, (2) a onefactor model with all items loading onto a single factor because theIFTs scale may simply measure a general construct, and (3) atwo-factor model with items loading on one prototypic and oneantiprototypic factor that reflect two general dimensions of IFTs.Table 2 presents the results of these analyses. Results indicated thatthe six correlated factor model provided the most parsimonious fitto the data, v2(120) = 271.75, p < .001, (v2/df = 2.27, CFI = .96,TLI = .95, RMSEA = .06). Table 3 presents the intercorrelations, reli-abilities, means, and standard deviations of the IFTs factors.

Table 2Overall fit indices for alternative factorial models of the IFTs scale.

Model v2 df v2/df

Null 4232.34 171 24.75One factor 2295.63 135 17.01Two correlated factors 1625.33 134 12.13Six correlated factors 271.75 120 2.27Second order CFA model 348.89 128 2.73

Note. Numbers in bold indicate acceptable fit indices. CFI = comparative fit index. TLI = Tucfactor analysis.*** p < .001. N = 397.

Second-order two-factor modelFirst-order factors that are correlated suggest the possibility of a

hierarchical model (Noar, 2003). Accordingly, on the basis of theILTs literature demonstrating that implicit theories may be repre-sented by higher-order factor structures, it was hypothesized thatthe six first-order factors would be explained by a second-orderfactor structure. A second-order two-factor model is also consis-tent with research positing that individuals have two broad per-spectives of followers (McGregor, 1960). A second-order, twocorrelated factor confirmatory factor analysis was tested, wherebythe three dimensions of Industry, Enthusiasm, and Good Citizenmeasured the higher latent construct of a Followership Prototype,and the three dimensions of Conformity, Incompetence, and Insub-ordination measured the higher latent construct of FollowershipAntiprototype. The prototype and antiprototype terms reflect dif-ferent notions in the literature. These terms have been utilized toreflect representativeness and distinctiveness of attributes. Forexample, prototypic (e.g., ‘‘coordinates groups” and ‘‘exercisesinfluence”) and antiprototypic (e.g., ‘‘requests approval” and‘‘agrees readily”) characteristics reflect leader and non-leader attri-butes, respectively (Lord, Foti, & De Vader, 1984). These terms alsohave been utilized to reflect the positive and negative valence ofattributes. For example, prototypic (e.g., ‘‘Intelligence” and ‘‘Dedi-cation”) and antiprototypic (e.g., ‘‘Tyranny” and ‘‘Masculinity”)characteristics reflect positively and negatively valenced leaderattributes, respectively (Epitropaki & Martin, 2004; Offermannet al., 1994). In the current research, Followership Prototype andAntiprototype reflect positively and negatively valenced dimen-sions of IFTs, respectively.

Results in Table 2 indicated that although the IFTs items werenot best represented by two first-order factors (i.e., first-order pro-totypic and antiprototypic followership), the six first-order factorswere well represented by two second-order factors. Results of thesecond-order confirmatory factor analysis model indicated a rea-sonable fit to the data, v2(128) = 348.89, p < .001, (v2/df = 2.73,CFI = .95, TLI = .93, RMSEA = .07). The significantly different chi-square values between the first-order six-factor model and the sec-ond-order two-factor model, Dv2(8) = 77.14, p < .001, suggested

Dv2 Ddf CFI TLI RMSEA

.251936.71*** 36 .47 .33 .20

670.30*** 1 .63 .53 .171353.58*** 14 .96 .95 .06

77.14*** 8 .95 .93 .07

ker-Lewis index. RMSEA = root–mean–square of approximation. CFA = confirmatory

Loyal

Reliable

Team player

Excited

Outgoing

Happy

Hardworking

Productive

Goes above and beyond

Easily influenced

Follows trends

Soft spoken

Uneducated

Slow

Inexperienced

Good Citizen

Enthusiasm

Industry

Conformity

Incompetence

Followership Antiprototype

Followership Prototype

.70

.79

.73

.85

.80

.83

.91

.85

.78

.86

.89

.42

.86

.72

.84

.98

.39

.35

.87

.88

.87

-.31

Arrogant

Rude

Bad tempered

Insubordination.81.92.89

Fig. 1. Second-order factor model of implicit followership theories. All factor loadings and the correlation between follower prototype and antiprototype are significant atp < .001. v2 (128, N = 397) = 348.89, v2/df = 2.73, comparative fit index = .95, root–mean–square error of approximation = .07.


the first-order model best represented the data. However, all fitindices indicated that the second-order model was plausible, thusproviding support for the existence of two higher factors of Follow-ership Prototype and Antiprototype. Thus, results supported boththe two second-order factor model and the six first-order factormodel. A graphic representation of this model is provided in Fig. 1.

Convergent and discriminant validityTwo aspects of convergent and discriminant validity were

examined: (1) Convergent and discriminant validity among thesix IFTs factors, and (2) convergent and discriminant validity ofthe six IFTs factors with theoretically relevant constructs (i.e., ILTsand IPTs). Regarding the former, convergent validity was examinedby assessing whether each item had a statistically significant factorloading on its specified factor (Anderson & Gerbing, 1988). Conver-gent validity was supported as all factor loadings were significantwith critical ratios ranging from 8.00 to 24.62 (p < .001), and stan-dardized loadings ranging from .42 to .92. Likewise, results of theIFTs latent factor correlations in Table 3 provided initial supportfor discriminant validity as none of the correlations exceeded therecommended cut-off point of .85 (Kline, 1998). Furthermore, dis-criminant validity was examined with a test suggested by Ander-son and Gerbing (1988). The test assessed whether theconfidence intervals (two standard errors) around the correlationestimates between two factors included 1.0. None of the confi-dence intervals for the correlation estimates between two factorsincluded 1.0, providing support for the discriminant validity ofthe six subscales.4

Convergent and discriminant validity were examined next byassessing the association of IFTs with theoretically relevant con-

4 A detailed presentation of all discriminant validity analyses is available uponrequest.

structs (i.e., ILTs and IPTs). It was expected that (1) IFTs would beassociated with ILTs and IPTs (convergent validity) and (2) theirassociation would not be high given that they are not measuresof the same construct (discriminant validity). As reported in Ta-ble 4, the moderate associations between IFTs with ILTs and IPTsprovided evidence for both convergent and discriminant validity(Campbell & Fiske, 1959; Hinkin, 1998). Although the results forFollowership Antiprototype were less than perfect, further validityevidence was provided in Study 5. As a whole, the pattern of resultsprovided preliminary evidence of convergent and discriminantvalidity.

Study 4: Temporal consistency and replication of factorstructure

The primary goal of Study 4 was to examine temporal consis-tency. In addition, providing further cross validation evidence forthe factor structure of IFTs beyond the initial confirmatory factoranalysis is highly desirable (Hinkin, 1998). Data were collectedfrom a sample of students. Students are likely to have developedIFTs because implicit theories are developed at an early age (Huntet al., 1990), and students are likely to have had various experi-ences in leader–follower contexts. Thus, it would be informativeto cross validate the factor structure of IFTs with a different popu-lation of participants.

Method

Participants and proceduresTest-retest reliability was assessed with a sample of 228 under-

graduates. Participant demographics included: 135 (59%) females,average age of 21.81 years (SD = 3.53), 33% Asian American, 25%Hispanic, 19% Caucasian, 7% African American, 9% ‘‘other,” and 7%

Table 4Study 3: correlations between IFTs, IPTs, and ILTs.

IFTs Subscales IPT Sens Intel Dedi Dyna Tyra Masc L-Proto L-Anti

1. Industry .14* .20*** .14* .11 .12* .16** .16** .17** .18**

2. Enthusiasm .14* .23*** .19** .12* .21*** .25*** .27*** .23*** .29***

3. Good Citizen .28*** .33*** .30*** .26*** .30*** .15** .17** .35*** .18**

4. Conformity .24*** .13* .21*** .17** .21*** .19** .09 .22*** .15*

5. Insubordination �.23*** �.22*** �.18** �.23*** �.26*** .27*** .23*** �.24*** .28***

6. Incompetence �.05 �.05 .01 �.04 �.03 .24*** .20** �.01 .24***

7. F-Proto .20** .28*** .23*** .18** .23*** .22*** .23*** .28*** .25***

8. F-Anti-Proto �.01 �.06 .02 �.04 �.03 .34*** .25*** �.01 .32***

Note. F-Proto = Followership Prototype. F-Anti-Proto = Followership Antiprototype. IPT = Implicit performance theories. Sens = Sensitivity. Intel = Intelligence. Dedi = Dedi-cation. Dyna = Dynamic. Tyra = Tyranny. Masc = Masculinity. L-Proto = Leadership Prototype. L-Anti = Leadership Antiprototype. N = 397.

* p < .05.** p < .01.

*** p < .001.


who did not indicate their race. The time lag between administra-tions (i.e., Time 1 and Time 2) of the IFTs scale was 4 weeks.

Results

The 4-week test-retest reliability estimates for the IFTs dimen-sions of Conformity, Insubordination, Incompetence, Industry,Enthusiasm, and Good Citizen were .83, .85, .82, .87, .85, and .89,respectively. As such, test-retest reliabilities for the IFTs dimen-sions were acceptably stable over time. Furthermore, internal con-sistency estimates for all IFTs dimensions were acceptable at Time1 (.79–.89) and Time 2 (.82–.90).

Confirmatory factor analyses provided further support for thesix first-order factor structure at Time 1, v2(120) = 261.81,p < .001, (v2/df = 2.23, CFI = .94, TLI = .91, RMSEA = .07) and Time2, v2(120) = 262.29, p < .001, (v2/df = 2.19, CFI = .94, TLI = .92,RMSEA = .07). Furthermore, confirmatory factor analyses providedsupport for the two second-order factor structure at Time 1,v2(128) = 322.47, p < .001, (v2/df = 2.52, CFI = .92, TLI = .89,RMSEA = .08) and Time 2, v2(128) = 317.39, p < .001, (v2/df = 2.48,CFI = .92, TLI = .90, RMSEA = .08).

Study 5: Consequences of IFTs

The goal of Study 5 was to establish a preliminary nomologicalnetwork of IFTs by examining the theoretical relevance and conse-quences of IFTs for leader–follower outcomes. As a preliminaryinvestigation, Study 5 focused specifically on leaders’ IFTs. More-over, while results provided support for both first- and second-or-der factor models, Study 5 focused on the second-order factors ofFollowership Prototype and Antiprototype because (1) the notionof bandwidth-fidelity (Cronbach & Gleser, 1965) suggests the nat-ure of the criterion should dictate the choice of predictors in orderto enhance validity (Hogan & Roberts, 1996; Ones & Viswesvaran,1996), and the second-order model would be more appropriate inthe current study context as the criterion variables (e.g., satisfac-tion, relationship quality, etc.) and research context (i.e., a widerange of companies, industries, locations, etc.) were broad in scope,and (2) theories suggest consequences of leaders’ IFTs could be ex-plained best by two broad perspectives of followers (e.g., Eden,1990; McGregor, 1960).

A second goal of Study 5 was to provide additional validity esti-mates. Criterion validity is an important facet of construct validityand represents the extent to which a construct is related to othervariables on the basis of theory (Cronbach & Meehl, 1955; Hinkin,1998). In addition to criterion validity, it is important to demon-strate the incremental validity of IFTs over related implicit theoryconstructs, i.e., ILTs and IPTs. The variables of (1) liking, (2) rela-tionship quality, (3) trust, and (4) job satisfaction were of interest

because research has established their relevance and linkage to im-plicit theories (Engle & Lord, 1997; Giessner & van Knippenberg,2008). Furthermore, examining the relationships between thesevariables and IFTs extend our understanding of the nomologicalnetwork of IFTs, in comparison with other implicit theories (i.e.,ILTs and IPTs). Criterion validity was examined by relating leaders’IFTs to followers’ outcomes (Sample 1): (1) Liking for leaders, (2)relationship quality with leaders, (3) trust in leaders, and (4) jobsatisfaction. Also, incremental validity was examined by relatingleaders’ IFTs to followers’ outcomes while controlling for IPTs. Like-wise, criterion validity was examined by relating leaders’ IFTs toleaders’ outcomes (Sample 2): (1) Liking for followers, and (2) rela-tionship quality with followers. Furthermore, incremental validitywas examined by relating leaders’ IFTs to leaders’ outcomes whilecontrolling for IPTs and ILTs. As discussed, leaders’ IFTs may shapehow leaders judge and respond to followers, which influence lea-der–follower interactions that impacts leader–follower outcomes.

Liking and relationship quality

Liking and relationship quality are strongly linked such that lik-ing can be regarded as one facet of relationship quality (Wayne,Shore, & Liden, 1997). Leaders’ IFTs may impact liking and relation-ship quality because leaders’ IFTs may serve as sensemaking func-tions (Weick, 1995) that act as antecedents of leaders’ affect,behaviors, and cognitions toward followers. Thus, leaders’ IFTsmay shape the pattern of interactions between leaders and follow-ers because many aspects of dyadic relationships are based on theautomatic use of implicit theories in perceiving and interpretingthe behaviors of one’s dyadic partner (Engle & Lord, 1997). Becauseevaluations often correspond with perceivers’ implicit theories(Johnson et al., 2008; Lord & Maher, 1993), leaders’ prototypicand antiprototypic perceptions of followers may influence leadersto evaluate and treat followers positively and negatively, respec-tively (Goodwin et al., 2000; Wofford & Goodwin, 1994), whichin turn may have a corresponding positive and negative impacton liking and relationship quality. For example, leaders who per-ceive that followers are loyal may evaluate followers’ behaviorspositively (e.g., followers are working late because they are teamplayers who want to see our team succeed), which may positivelyinfluence leader–follower interactions (e.g., empowering followersand affording them wide discretion in managing their work andtime) that impact interpersonal outcomes (i.e., liking and relation-ship quality). Conversely, leaders who perceive that followers areincompetent may evaluate followers’ behaviors negatively (e.g.,followers are working late because they are slow), which may neg-atively influence leader–follower interactions (e.g., micro-manag-ing followers) that impact interpersonal outcomes. Accordingly, itwas hypothesized:


Hypothesis 1a: Leaders’ Followership Prototype will be positivelyrelated to followers’ liking for and relationship quality with leaders.Hypothesis 1b: Leaders’ Followership Antiprototype will be nega-tively related to followers’ liking for and relationship quality withleaders.Hypothesis 2a: Leaders’ Followership Prototype will be positivelyrelated to leaders’ liking for and relationship quality with followers.Hypothesis 2b: Leaders’ Followership Antiprototype will be nega-tively related to leaders’ liking for and relationship quality withfollowers.

Trust

Leadership and trust are inherently intertwined (Dirks, 2000).Leaders’ perceptions of followers may affect the level of trust be-tween leaders and followers. As posited above, leaders’ prototypicand antiprototypic perceptions of followers may influence leadersto evaluate followers positively and negatively, respectively. Inturn, leaders’ positive and negative evaluations of followers mayaffect leaders’ trust in followers positively and negatively, respec-tively. Consequently, leaders will exhibit more or less trustingbehaviors, and in accordance with Social Exchange Theory (Blau,1964), followers will reciprocate in kind to leaders’ display of trust.Thus, it was hypothesized:

Hypothesis 3a: Leaders’ Followership Prototype will be positivelyrelated to followers’ trust in leaders.Hypothesis 3b: Leaders’ Followership Antiprototype will be nega-tively related to followers’ trust in leaders.

Job satisfaction

Leaders account for a significant portion of followers’ job satis-faction (Locke, 1976). In fact, leaders can buffer or be a source ofstress that influences followers’ job satisfaction, depending onleaders’ treatment of followers and the nature of leader–followerinteractions (Bono, Foldes, Vinson, & Muros, 2007) that may be afunction of leaders’ IFTs (Goodwin et al., 2000; Wofford & Good-win, 1994). In line with previous rationale, leaders’ prototypicand antiprototypic perceptions of followers may influence leaders’positive and negative treatment of followers, respectively. Leaders’positive treatment of followers satisfies their interpersonal needs,and meeting these needs increases followers’ job satisfaction(Mayer, Bardes, & Piccolo, 2008). Conversely, followers who receivenegative treatment from leaders may not have their interpersonalneeds satisfied, which may negatively impact followers’ job satis-faction. Accordingly, it was hypothesized:

Hypothesis 4a: Leaders’ Followership Prototype will be positivelyrelated to followers’ job satisfaction.Hypothesis 4b: Leaders’ Followership Antiprototype will be nega-tively related to followers’ job satisfaction.

Method

Sample 1 participantsData were collected from 80 dyadic pairs (160 participants) of

workplace leaders and their followers from various industries lo-cated in a large metropolitan area in the Western United States(e.g., Education, professional services, healthcare, food service, re-tail, etc.). Ethnicity of participants was diverse: Caucasian (32%),Asian American (27%), Hispanic (21%), African American (14%),and other (6%). Leaders and followers worked an average of 46(SD = 12.83) and 32 (SD = 15.58) hours per week, respectively.Regarding followers, 42 (53%) were female and their age rangedfrom 18 to 70, averaging 29.34 years (SD = 11.03). Regarding lead-

ers, 44 (56%) were male and their age ranged from 20 to 66, aver-aging 38.81 years (SD = 11.10). Leaders had an average of 11 yearsof leadership experience (SD = 7.89) and represented a wide rangeof leadership levels: Senior-level (38%), upper-middle-level (21%),middle-level (18%), and entry-level (23%).

Sample 1 proceduresA team of trained undergraduates received approximately 1 h of

training on study protocols, ethical guidelines, and were providedwith detailed written protocol instructions, including standardizedrecruitment scripts, to recruited working adults from their existingnetwork of contacts. Leaders completed an online survey consist-ing of the IFTs and IPTs scales. Followers completed an online sur-vey reporting their liking for leader, relationship quality withleader, trust in leader, and job satisfaction.

Sample 2 participants and proceduresParticipants and procedures were the same as those in Study 3

for the sample of 308 leaders who completed an online survey con-sisting of measures of IFTs, IPTs, liking for followers, and quality ofrelationship with followers.

Materials for Samples 1 and 2IFTs were assessed with the same scale described in Study 3. As

control variables, IPTs (Engle & Lord, 1997) and ILTs (Epitropaki &Martin, 2004) were assessed with the same scales described inStudy 3.

Liking for leader was measured with a four item scale (e.g., ‘‘Ilike my work group supervisor very much”) (Wayne et al., 1997).Followers rated these items using a 7-point Likert-type scale(1 = strong disagree; 7 = strongly agree).

Relationship quality was measured with the Dual-PerspectiveLMX7 scale that was developed specifically to assess both leaderand follower perspectives (Paglis & Green, 2002). Each subscaleconsisted of 7 items and sample items included, ‘‘My supervisorunderstands my problems and needs” (follower perspective), and‘‘I think I understand my subordinate’s problems and needs” (lea-der perspective). Leaders and followers rated these items using a5-point Likert-type scale (1 = strong disagree; 5 = strongly agree).

Trust was measured with a seven item scale (e.g., ‘‘I believe mysupervisor has high integrity”) (Gabarro & Athos, 1976). Followersrated these items using a 5-point Likert-type scale (1 = strong dis-agree; 5 = strongly agree).

Job satisfaction was measured with a four item scale (e.g., ‘‘Allin all, I am very satisfied with my current job”) (Quinn & Shepard,1974). Followers rated these items using a 7-point Likert-type scale(1 = strong disagree; 7 = strongly agree).

Results

Table 5 presents the means, standard deviations, reliabilities,and correlations. Leaders’ Followership Prototype was positivelyrelated to all follower outcomes (i.e., liking for leaders, relationshipquality with leaders, trust in leaders, and job satisfaction). Like-wise, leaders’ Followership Antiprototype was negatively relatedto all follower outcomes. Similarly, leaders’ Followership Prototypewas positively related to all leader outcomes (i.e., liking for follow-ers, and relationship quality with followers). Likewise, leaders’Followership Antiprototype was negatively related to leaders’ re-port of relationship quality with followers, but not with leaders’liking for followers. The results suggested that while FollowershipPrototype consistently predicted both leader and follower out-comes, Followership Antiprototype was less consistent (i.e., didnot predict leader liking for follower). Overall, the results providedsupport for the criterion validity of IFTs and all hypotheses, excepthypothesis 2b.

Table 7Study 5: partial correlations for IPTs and ILTs controlling for Leaders’ IFTs.

L.Liking L.LMX

IPTs .13* .21**

ILTs – Leadership Prototype .10 .08ILTs – Leadership Antiprototype .05 .05

Table 5Study 5: correlations, means, standard deviations, and reliabilities for leaders’ IFTs, IPTs, ILTs and criterion variables.

Sample 1 Sample 2

Variables 1 2 3 4 5 6 7 5 6 7 8 9 10 11

1. F.Liking (.94)2. F.LMX .66*** (.87)3. F.Trust .50*** .50*** (.82)4. F.Satisf .53*** .57*** .61*** (.87)5. L.Proto .42*** .40*** .23* .29* (.90) (.91)6. L.Antiproto �.36** �.49*** �.32** �.33** �.34** (.80) �.27*** (.78)7. L.IPTs .20 .05 .26* .14 .24* �.04 (.96) .20** �.01 (.97)8. L.Liking .39*** �.10 .26*** (.87)9. L.LMX .41*** �.18** .37*** .64*** (.88)10. L.ILTs-P .28*** �.01 .68*** .28*** .35*** (.94)11. L.ILTs-A .25*** .32*** �.03 .12* .08 .04 (.94)

M 5.66 4.08 4.15 5.39 6.41 4.40 8.15 6.31 4.91 8.69 5.14 3.70 8.43 4.56SD 1.33 .70 .69 1.39 1.67 1.27 1.37 1.81 1.38 1.39 1.24 .75 1.33 2.36

Note. ‘‘L” indicates leaders’ ratings. ‘‘F” indicates followers’ ratings. Liking = Liking for dyadic partner. LMX = Relationship quality. Satisf = Job satisfaction. Proto = FollowershipPrototype. Antiproto = Followership Anti-prototype. IPTs = Implicit Performance Theories. ILTs-P = Implicit Leadership Theories – Leadership Prototype. ILTs-A = ImplicitLeadership Theories – Leadership Anti-prototype. Sample 1 N = 160. Sample 2 N = 308.

* p < .05.** p < .01.

*** p < .001.

Table 6Study 5: partial correlations for leaders’ IFTs and criterion variables.

Criterion Controlling for IPTs Controlling for IPTs and ILTsSample 1 Sample 2

L.Proto L.Antiproto L.Proto L.Antiproto

1. F.Liking .37*** �.36**

2. F.LMX .37*** �.51***

3. F.Trust .17 �.32***

4. F.Satisf .29** �.35**

5. L.Liking .29*** �.14*

6. L.LMX .31*** �.22***

Note. ‘‘L” indicates leaders’ ratings. ‘‘F” indicates followers’ ratings. Liking = likingfor dyadic partner. LMX = relationship quality. Satisf = job satisfaction. Proto = Fol-lowership Prototype. Antiproto = Followership Anti-prototype. IPTs = implicit per-formance theories. ILTs = implicit leadership theories. Sample 1 N = 160. Sample 2N = 308.

* p < .05.** p < .01.

*** p < .001.


To examine the incremental validity of IFTs, partial correlationswere conducted to examine the association between leaders’ Fol-lowership Prototype and Antiprototype with follower and leaderoutcomes, while controlling for related implicit theory constructs(i.e., IPTs, and ILTs). Table 6 presents the partial correlation results.Consistent with the pattern of results for criterion validity, Follow-ership Prototype and Antiprototype accounted for additional vari-ance, above and beyond IPTs and ILTs, for all leader and followeroutcomes, with the exception of followers’ trust in leaders. Overall,after controlling for IPTs and ILTs, the results provided support forthe incremental validity of IFTs and all hypotheses, with the excep-tion of hypothesis 3a. An analysis also was conducted on Sample 2examining the relationships between IPTs and ILTs with the out-come variables while controlling for leaders’ IFTs. Results in Table 7indicated that just as leaders’ IFTs accounted for additional

variance above and beyond IPTs, IPTs also accounted for additionalvariance beyond that of leaders’ IFTs. Thus, while the two con-structs may be related, they are distinct in accounting for uniquevariances in the outcome variables (i.e., Liking and LMX). In addi-tion, the results provided evidence indicating that leaders’ IFTsare broader constructs that encompasses IPTs, given that leaders’IFTs accounted for more variance than IPTs.

General discussion

Results suggest that IFTs are most accurately represented by afirst-order six-factor structure that includes Industry, Enthusiasm,Good Citizen, Conformity, Insubordination, and Incompetence. IFTsalso are accurately represented by a second-order two-factorstructure: Followership Prototype (Industry, Enthusiasm, and GoodCitizen) and Followership Antiprototype (Conformity, Insubordina-tion, and Incompetence). In addition to identifying the content andstructure of IFTs, an assessment instrument was developed andvalidated to facilitate research. Results support the psychometricproperties of the IFTs instrument, providing preliminary evidencefor content, convergent, discriminant, criterion, and incrementalvalidity, as well as internal and temporal consistency. In turn, theseprovide evidence for construct validity (Hinkin, 1995). Further-more, the theoretical relevance and consequences of IFTs weredemonstrated. Specifically, leaders’ IFTs have consequences forthe interpersonal aspects of leader and follower outcomes. As dis-cussed below, IFTs may also have consequences beyond interper-sonal outcomes, i.e., performance outcomes.

Future research

IFTs may further augment our understanding of well-substanti-ated theories in the organizational science literature. Future re-search could extend the examination of IFTs beyond leaders tofollowers. While Study 5 examined leaders’ IFTs, followers also haveIFTs (Carsten et al., 2010; Engle & Lord, 1997; van Gils et al., 2010).Indeed, Study 4 demonstrated that the structure and content ofIFTs for undergraduate students (befitting the label of followers)were similar to leaders. It may be fruitful to examine the congru-ence between leaders’ and followers’ IFTs and ILTs on leader–fol-lower outcomes (Engle & Lord, 1997; van Gils et al., 2010), thus


answering calls for leadership research to be more integrative(Avolio et al., 2009).

In addition to interpersonal outcomes, IFTs may be particularlyapplicable to theories positing the role of leaders in shaping fol-lower performance outcomes. Specifically, Eden’s Pygmalion the-ory (e.g., 1990, 1992) has established that leaders’ performanceexpectations may significantly impact follower performance out-comes. However, Pygmalion theory is incomplete (McNatt, 2000)because it does not explain the antecedents of leaders’ perfor-mance expectations. In classic Pygmalion studies, expectationsare artificially manipulated by the researchers (i.e., researchers cre-ate the expectations for participants). One potential mechanismmay be leaders’ perceptions of followers (Eden, 1990). That is, lead-ers’ IFTs may be antecedents of leaders’ performance expectationsfor followers that lead to Pygmalion effects whereby followers ful-fill leaders’ positive perceptions of followers (i.e., Followership Pro-totype), or Golem effects whereby followers fulfill leaders’ negativeperceptions of followers (i.e., Followership Antiprototype) (Eden,1990, 1992). In sum, leaders’ IFTs may determine leaders’ perfor-mance expectations for followers, which then shape followers’ per-formance outcomes. Furthermore, consistent with inference-basedprocessing (Lord & Maher, 1993), this process may be cyclical suchthat the corresponding follower performance outcomes may serveas feedback that reinforces leaders’ IFTs (Goodwin et al., 2000;Wofford & Goodwin, 1994).

In addition to Pygmalion effects, future research should exam-ine the relationship between leaders’ IFTs and followers’ self-con-cept, an emerging area of research (Avolio et al., 2009; Lord &Brown, 2004; van Knippenberg & Hogg, 2003). Scholars have pos-ited that leadership is the process by which leaders transformthe way followers envision themselves (Lord & Brown, 2004). Con-sistent with research positing that leaders’ treatment of followersis determined by their assumptions of followers (McGregor,1960), it could be that Theory X leaders who endorse more antipro-totypic perceptions of followers may treat followers differentlyfrom Theory Y leaders who endorse more prototypic perceptionsof followers. In turn, their leadership style and treatment of follow-ers impact followers’ conceptualization of themselves (Lord &Brown, 2004).

IFTs also may be antecedents for individuals’ affective experi-ences. For example, leaders’ IFTs may account for leaders’ affectand the transference of affect from leaders to followers (Bonoet al., 2007; Sy, Cote, & Saavedra, 2005). Leaders’ IFTs may predis-pose leaders to certain affective experiences. That is, leaders’ posi-tive or negative perception of followers (i.e., leaders’ IFTs) mayelicit corresponding affective experiences in leaders (e.g., percep-tions of insubordination in followers may elicit anger). Further-more, leaders are key sources of uplifts and hassles for followers(Dasborough, 2006), which may be a result of leaders’ behaviorsand interactions with followers that are shaped by leaders’ IFTs.Leaders who endorse more prototypic perceptions of followersmay be more likely to engender positive group affective tone,and leaders who endorse more antiprototypic perceptions of fol-lowers may be more likely to engender negative group affectivetone (Sy et al., 2005). Thus, future research could examine theinteraction of IFTs with leadership and emotions.

Study limitations

This study has several limitations. First, the majority of the par-ticipants in the different samples were primarily Caucasian and fe-male. Thus, it is possible that the results may be skewed to theperspective of these participants. However, the major minoritygroups were represented in the study samples and the racial com-position reflects those of the US population. Likewise, the propor-tion of female to male participants in the samples is consistent

with studies in the ILTs field (e.g., Epitropaki & Martin, 2004; John-son et al., 2008; Offermann et al., 1994) and the broader social sci-ence literature.

Second, this study included individuals from a variety of differ-ent companies, industries, and job functions. As such, it was notpossible to control for extraneous factors that may confound thestudy results. However, the diversity of respondents, particularlythe multiple samples utilizing multiple methodologies, may alsoincrease the generalizability of the results. Nevertheless, the gener-alizability of the results may be limited to Western perspectives ofIFTs as implicit theories may vary as a function of context (Fotiet al., 2008; Hanges et al., 2000).

Third, the type of follower was not specified. Theorists arguethat implicit theories may be examined at three hierarchical levels(for a review, see Lord et al., 1982). This study primarily focused onIFTs at the superordinate level (i.e., followers in general). This ap-proach is consistent with researchers’ recommendations (Lord &Maher, 1993) to examine perceptions beyond the basic level (i.e.,specific types of followers, e.g., military, business, minority, reli-gious, etc.). However, given that the majority of the participantswere from the business sector, it is also likely that they were refer-ring to business followers in their responses. On the other hand,unlike individuals’ romance with leaders, which may lead individ-uals to pay more attention to and make distinctions between dif-ferent leaders, it may be that followers are less likely to bedifferentiated because individuals do not afford the same level ofattention and fascination with followers (Pillai & Uhl-Bien, 2007).Thus, followers are often viewed and treated as an undifferentiatedmass or collective (Collins, 2006). As such, the results of this studymay be generalized to a broader category of followers. That is, theconceptualization of IFTs may be most relevant at the superordi-nate level.

Practical implications

IFTs have implications for evaluations of followers. Personneldecisions are often based on individuals’ perceptions of followers,which are often systematically biased (Heslin & VandeWalle,2008). Individuals who endorse more antiprototypic followershiptheories may be prone to providing punitive evaluations of follow-ers (e.g., severity errors). Conversely, individuals who endorsemore prototypic followership theories may be prone to providingpositive evaluations of followers (e.g., leniency errors).

Furthermore, because evaluations often correspond with per-ceivers’ implicit theories (Johnson et al., 2008; Lord & Maher,1993), leaders may more easily recognize potential in followersthat fit their implicit theories of Followership Prototype and maynot recognize potential in equally capable followers who exhibitless congruence. This is particularly relevant in multicultural envi-ronments. For example, among other traits, Western leaders mayrecognize the potential of followers who show Enthusiasm, and la-bel and treat these individuals as ‘‘high potentials.” However, Wes-tern leaders may overlook the same potential in equally capablefollowers who may not exhibit Enthusiasm because their culturalvalues may inhibit expressions of emotions (e.g., Eastern culturessuch as Japan and China). This bias may also occur for gender(Johnson et al., 2008). As such, an important practical implicationis that leaders should develop awareness of their IFTs profile, andhow these perceptions may bias their cognitions and behaviors to-ward followers.

In sum, IFTs are an understudied branch of leadership researchthat complements ILTs and IPTs. IFTs address the historical gap inleadership research that has focused primary on leaders, and an-swer recent calls for leadership research to be more integrativeby incorporating followers as a focal element, as well as calls formuch needed research on leaders’ cognitions (Avolio et al., 2009).


Thus, an integrative examination of implicit theories of leaders andfollowers may provide more holistic understanding of leadership,as well as inform leadership practice because IFTs are applicationoriented. As demonstrated in Study 5 and consistent with the Pyg-malion literature, leaders’ IFTs may have consequences for leaders’and followers’ cognitions, affect, behaviors, and outcomes. Consis-tent with this line of reasoning, it is possible that the performanceof leaders, followers, and organizations can be elevated throughIFTs.

Acknowledgments

I thank Daan van Knippenberg and his team for valuable edito-rial guidance. I extend my gratitude to Paul Adelman, Uma Kedhar-nath, Tina Kim, Sharon Rogala, Susanna Tram, and Paul Whiteleyfor assistance with data collection and support. I also thank JinNam Choi, Dov Eden, Howard Friedman, Stefanie Johnson, BobLord, Bob Rosenthal, and Susan Sy for helpful comments.

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