For the past 40 years, there has been a growing interest in understanding how employees manage impressions in order to shape how they are seen by others at work (for a review, see Bolino et al., 2016). During this time, a number of studies have shown that impression management (IM) affects who is hired in organizations (Barrick et al., 2009; Peck & Levashina, 2017), how in-role and extra-role performance are evaluated (Bolino et al., 2006; Brouer et al., 2015; Wayne & Liden, 1995), and how IM affects employee resource depletion and deviance (Klotz et al., 2018a, 2018b). Studies have also shown that employees who experience job insecurity use IM to impress their supervisors (Huang et al., 2013), and that employees who experience shame use the IM tactic of exemplification to appear more dedicated and worthy (Bonner et al., 2017). In short, research provides ample evidence that IM plays a ubiquitous role in organizational life.

Previous research has contributed to our understanding of the nature, antecedents, and consequences of IM, but this work has most often investigated the effects of ingratiation and self-promotion (two specific positive IM tactics) on interview decisions and performance evaluations (Peck & Levashina, 2017). Although these outcomes are important, communication professionals and executive coaches emphasize that managing impressions is critical for career success (e.g., Kramer & Harris, 2020). Career success has been termed the “ultimate outcome of a career” (e.g., Spurk et al., 2019, p. 37) and describes the “accumulated positive work and psychological outcomes resulting from one’s work experiences” (Ng et al., 2005, p. 368). Despite the potential importance of IM to advance one’s career, there has been surprisingly little research exploring this topic. Judge and Bretz (1994) found that supervisor-focused ingratiation was positively related to career success, while job-focused self-promotion was negatively related to career success. However, there has been even less research dedicated to understanding the tactics of exemplification, intimidation, and supplication, whereby people seek to be seen as dedicated, threatening, and needy, respectively, and how these tactics may also affect career success, particularly when used in combination with ingratiation and self-promotion. In other words, although prior research indicates that people use various IM tactics to shape their image (Bolino & Turnley, 1999; Bolino et al., 2008), most studies tend to focus on the individual use of certain tactics (see studies below for exceptions on IM on the job, and Moon et al., 2023, for IM in selection), rather than investigating their joint effects, despite evidence suggesting that there is considerable value in understanding how people use IM tactics in combination.

Three different studies have examined the use of IM tactics at work in combination, and all have hinted towards similarities in identified profiles of IM use. In the first study, Bolino and Turnley (2003) used cluster analysis to identify three patterns of ingratiation, self-promotion, exemplification, intimidation, and supplication used by students. They labeled those who tended to use only the positive IM tactics of ingratiation, self-promotion, and exemplification as the positives; those who used relatively high levels of all of the tactics as aggressives; and those who used relatively few of the tactics as passives. They also found that positives and passives were viewed as more desirable team members compared to the aggressives. Building on this research, Maher et al. (2018) used cluster analysis to replicate the IM profiles identified by Bolino and Turnley (2003). Results converged in three out of four different samples of respondents. More recently, Chawla et al. (2021) used latent profile analysis (LPA) to identify profiles of IM. Across three studies, they again identified passive, aggressive, and positive profiles (as well as three additional profiles). Further, they found that profiles of IM were related to employees’ feelings of inauthenticity and coworker assessments of employee job performance, withdrawal, absenteeism, and sincerity.

These studies demonstrate the insight gained from exploring how employees manage impressions using a “person-centered” perspective (e.g., Wang et al., 2013; Woo et al., 2024). Person-centered research (as opposed to variable-centered research) acknowledges the fact that there may be sub-groups of individuals who differ in their configurations or patterns of certain characteristics and behaviors, such as IM in the present case. Relatedly, such an approach also offers a new opportunity to shed light on the mixed meta-analytic effects of the use of single IM tactics on career outcomes (Higgins et al., 2003). For example, the 95% credibility interval for the relationship between self-promotion and objective career success (e.g., promotion and salary recommendation) ranges from negative to positive values. In fact, these varying results may be explained by the differential impact of distinct patterns of IM. Yet, person-centered IM research so far (Bolino & Turnley, 2003; Chawla et al., 2021; Maher et al., 2018) has not yet provided insights on the effects of a combinatory use of IM on career outcomes. Given that career success, as highlighted above, is a key outcome from both a theoretical and a practical perspective, this is a critical limitation. Thus, the purpose of this paper is to build upon previous IM research by using LPA to identify different patterns of IM use and to examine their impact on subjective and objective indicators of career success. In doing so, we contribute to the IM literature in three ways.

First, we examine the relationship between IM profiles and multiple indicators of career success (e.g., Ng et al., 2005; Spurk et al., 2019): salaries, promotions, and reward recommendations as objective indicators of career success, and perceived career success (i.e., the degree to which employees feel their careers have been successful) as an indicator of subjective career success. As such, we provide knowledge on how effective different combinations of IM tactics are with a focus on employees’ career. This is especially relevant because IM aims at presenting oneself in a certain light, and different combinations of IM could exert a differential influence on employees’ careers and the perception of their career. We thereby extend prior research because, as previously noted, Maher et al. (2018) did not examine any outcomes of IM profiles, and Bolino and Turnley (2003) only looked at whether peers perceived students using certain IM profiles as more favorable group members. Further, whereas prior research has frequently investigated the effects of IM on interviewing decisions and performance appraisals (Bolino et al., 2016), few studies have examined the career implications of IM tactics (e.g., Judge & Bretz, 1994), and no study has investigated how the use of IM tactics in combination may affect employees’ career success.

Second, we extend the career literature by offering a more nuanced understanding of IM effectiveness in the context of both objective and subjective career success. On the one hand, objective and subjective career success are moderately correlated. Yet, on the other hand, research also indicates that both types of career success are fundamentally different and often have different antecedents and implications (Ng & Feldman, 2014). Thus, it is important to distinguish effects for each outcome. Therefore, we examine differential effects of IM profiles on objective and subjective career success to allow for specific conclusions regarding each indicator. Notably, we do this in an exploratory manner for subjective career success. This is because, theoretically, opposing effects of how certain IM profiles may affect subjective career success are possible, and the lack of variable-centered research on this relationship means there is little empirical guidance for determining a direction. Altogether, studying effects on both objective and subjective career success provides a more comprehensive and complete understanding of how profiles of IM are related to career success. This can also lead to theory-driven research on IM and subjective career success.

Third and finally, as noted earlier, Bolino and Turnley (2003) conducted their studies with two samples of undergraduate students. Maher et al. (2018) used multiple samples in their research, including full-time employees recruited by students in management courses (Samples 1 and 4); employees working for an automotive organization (Sample 2); and HR professionals, working for organizations in a variety of industries (Sample 3). Chawla et al. (2021) also used multiple samples of full-time employees, recruited via Amazon Mechanical Turk (Study 2) or undergraduate students (Study 1 and 3), with an additional sample of study participants’ coworkers (Study 3). Whereas the data collected by Maher et al. (2018) were all self-reported, Bolino and Turnley (2003) collected multi-source data from students, and Chawla et al. (2021) included multi-source data from employees and their coworkers (Study 3). We collect both employee self-report data as well as data from employee-supervisor dyads. In doing so, we extend prior research by avoiding same-source bias (Podsakoff et al., 2012), and acknowledge supervisors as one of the most important gatekeepers/decision-makers for career progression (e.g., King, 2004).

Identifying IM Profiles

The first aim of our research is to identify IM profiles using LPA. Following the idea of constructive replication (e.g., Köhler & Cortina, 2019), we expect to find profiles that differ both quantitatively (i.e., in their frequency, such as people demonstrating a high versus low amount of all five tactics) and qualitatively (i.e., in their shape, such as people demonstrating a high amount of only positive tactics versus a high amount of all five tactics; e.g., Gabriel et al., 2015; Marsh et al., 2009). Despite some inconsistencies in the number of profiles across studies (i.e., from three to five, Bolino & Turnley, 2003; Chawla et al., 2021; Maher et al., 2018), in each previous study, across multiple samples, three profiles differed quantitatively and qualitatively: the positive profile, encompassing those employees who mainly use the positive IM tactics of ingratiation, self-promotion, and exemplification; the aggressive profile, including those employees who make use of all tactics at relatively high levels; and the passive profile, including employees who make less use of all IM tactics. Thus, in Study 1 we examine the following hypothesis:

  • Hypothesis 1: Using LPA, there will be qualitatively and quantitatively distinct profiles of IM in Study 1, including an aggressive, passive, and positive profile.

Then, in Study 2, we aim to assess whether the profile structure of Study 1 could be replicated in a second sample. Hence, our second hypothesis predicts that we will find the same profiles as in Study 1.

  • Hypothesis 2: In Study 2, the same profiles of IM identified in Study 1 will be found.

IM Profiles and Their Relation to Objective and Subjective Career Success

The second aim of our research is to further contribute to our understanding of how IM profiles relate to career success. IM theory posits that people use IM to achieve desired outcomes (Leary & Kowalski, 1990; Schlenker, 1980), and this has been an important area of organizational research for decades (Bolino et al., 2016). In the career context, this pertains to career success, which has been conceptualized as the “ultimate outcome of a career” (Spurk et al., 2019, p. 37). In support of such theorizing, research on individual positive IM tactics has illustrated that IM can influence career success. For instance, supervisor-focused ingratiation was found to relate positively to career success, while job-focused self-promotion negatively relates to career success (Judge & Bretz, 1994). While career success has been defined as the “positive psychological or work-related outcomes or achievements one accumulates as a result of work experiences” (Seibert et al., 1999, p. 417; Seibert & Kraimer, 2001), research has often included only one of two operationalizations of career success, that is, either objective career success or subjective career success (e.g., Ng et al., 2005). Objective career success can be directly observed by others and can be measured in a standardized way (e.g., salary or number of promotions, Spurk et al., 2019, see also Boudreau & Boswell, 2001; Judiesch & Lyness, 1999; Ng et al., 2005; Seibert et al., 2001). Subjective career success refers to “the focal actor’s evaluation and experience of achieving personally meaningful career outcomes” (Spurk et al., 2019, p. 36), and it can be measured as perceived career success (e.g., Abele & Spurk, 2009; Heslin, 2003; Turban & Dougherty, 1994).

Based on findings from variable-centered research, IM profiles may also predict career success, and LPA allows us to examine whether career success differs between profiles. To obtain a better understanding of how IM profiles predict career success comprehensively, we examine the relationship of different IM profiles with important indicators of objective and subjective career success. For objective career success, we focus on salary, number of promotions, and reward recommendations. Reward recommendation is a more forward-looking indicator of career success and one that would be rated by the employee’s supervisor (Allen & Rush, 1998; Spurk et al., 2019). More precisely, reward recommendations capture the supervisor’s willingness to recommend their subordinates for salary increases, promotions, high profile projects, public recognition, and opportunities for professional development (e.g., Allen & Rush, 1998). Reward recommendations can be categorized as an objective career success indicator because they are evaluated objectively by someone who has important influence over the employee’s career (i.e., immediate supervisors). Building on the notion that IM can influence career success, the differential effects of the combined use of IM (i.e., IM profiles) on the supervisor-rated outcome of reward recommendations, an indicator of the effectiveness of individuals’ IM use, may be especially relevant (Bozeman & Kacmar, 1997; Ferris & Judge, 1991; Gardner & Martinko, 1988). Supervisors are typically the ones who recommend their subordinates for rewards (e.g., Allen & Rush, 1998), and there is empirical evidence that employees’ use of IM relates to the reward recommendations they receive (Deng et al., 2020).

For subjective career success, we focus on perceived career success (Ng et al., 2005; Spurk et al., 2019), whereby employees subjectively evaluate how successful their career has been. Our approach to consider both objective and subjective career success indicators is especially relevant in light of a recent review highlighting the necessity of adopting a holistic approach to career success, including both objective and subjective indicators given that they represent nomologically-distinct facets of career success (Spurk et al., 2019).

Predicting Objective Career Success

An established tenet of IM theory as well as social influence theory is that IM is employed to maximize one’s reward-cost ratio when interacting with others (Ferris et al., 2002; Leary & Kowalski, 1990; Schlenker, 1980). In the work context, rewards typically include salaries, promotions, and reward recommendations. We assume that a clear emphasis on positive IM tactics such as self-promotion, ingratiation, and exemplification (consistent with the positive profile from prior research) would be beneficial for achieving these objective outcomes in comparison to a lower use of IM tactics (i.e., the passive profile that is characterized by a lower use of IM). The underlying mechanism is that the positive profile should better convey the image of a competent, dedicated, and likeable employee (Bolino & Turnley, 2003) who is to be rewarded in organizations. More specifically, self-promotion and ingratiation aim to increase how employees are perceived on competence and likeability/warmth, which are recognized as the two key dimensions of person evaluations (Fiske et al., 2007). In addition, perceiving someone as dedicated, as intended through the use of exemplification, should result in seeing the employee as more committed and inclined to engage in organizational citizenship behaviors – a behavior that is highly valued by organizations because it contributes to organizational success (e.g., Podsakoff et al., 2009).

  • Hypothesis 3: Employees with a positive IM profile will have (a) higher salaries, (b) higher promotions, and (c) higher reward recommendations than employees belonging to the passive profile.

Second, we propose that a profile with an undifferentiated high use of IM (consistent with the aggressive profile from prior research, Bolino & Turnley, 2003; Maher et al., 2018) will be associated with less objective career success than a profile with a focus on positive tactics (consistent with the positive profile from prior research) or a profile characterized by low levels of IM usage (consistent with the passive profile from prior research). In particular, it has been argued in the IM literature that such a “shotgun” approach, in which relatively high levels of IM are used indiscriminately, may backfire for employees (Bolino et al., 2016), and that using too much IM increases the risk of being perceived as too obviously or transparently managing impressions or even manipulating others (Gordon, 1996; Jones, 1964).

The mechanism underlying this career-undermining effect of the aggressive profile might relate to the images that can be elicited when employing negative tactics. Specifically, the use of supplication and intimidation can come at the high cost of appearing less dedicated and lazier (supplication), and of appearing more superior and bossier (intimidation) (see Turnley & Bolino, 2001, for this variable-centered research). Such images might result in unfavorable reactions from supervisors and colleagues, as they undermine the image of a likeable and dedicated employee, thereby reducing supervisors’ willingness to promote the employee’s career and colleagues’ willingness to cooperate with the employee, which may likewise undermine the employee’s career success (Bolino & Turnley, 2003). This effect might be particularly high for employees belonging to the aggressives profile who simultaneously use high levels of negative tactics, and high levels of positive tactics. This is because it might be perceived as more manipulative when used in combination (as described above) as they try to convey conflicting images (Chawla et al., 2021). In comparison, both positives and passives focus on positive tactics (albeit at different levels), and avoid displaying high levels of negative tactics. In support of this argument, in prior research, aggressives felt more inauthentic than passives and positives (Chawla et al., 2021, Study 1 and Study 2) and were less likely to be perceived favorably (Bolino & Turnley, 2003), in comparison to both passives and positives. Accordingly, we expect employees in the aggressive profile to exhibit the lowest career success.

  • Hypothesis 4: Employees with an aggressive IM profile will have (a) lower salaries, (b) fewer promotions, and (c) lower reward recommendations than employees belonging to the positiveFootnote 1 and passive profiles.

Exploring the Prediction of Subjective Career Success

With regard to subjective career success, we examine the direction of the relationship of the very active IM users (i.e., the positive and the aggressive profile) in comparison to the passive profile. We pose this as a research question (RQ) because theory suggests that opposing effects may come into play here, and it is difficult to determine the direction of effects a priori. On the one hand, it appears possible that these active IM users (positives and aggressives) employ IM in order to enhance their self-image, as self-enhancement is an important IM motive (Leary, 1995; Schlenker, 1985). As such, when these individuals actively manage their career-related image by using IM, and they perceive their behaviors as effective, it could enhance the positivity of their career-related self-image, hence their subjective career perceptions. On the other hand, in light of ego-depletion theory (e.g., Baumeister et al., 1998), it is possible that a more active use of IM (i.e., the positive and the aggressive profile) and constant monitoring might consume resources that can lead to higher levels of exhaustion, subjective fatigue, and negative affect (Baumeister et al., 1998; Hagger et al., 2010; Trougakos et al., 2015). This resource consumption, in turn, could lower employees’ subjective perceptions of their career in comparison to passive IM users (i.e., the passive profile) who would have conserved the resources necessary to deploy this very active form of IM. Therefore, we examine the following RQ:

  • Research Question 1: How does the subjective career success of employees with a very active use of IM (i.e., an aggressive or positive profile) compare to the subjective career success of the passive profile?

We conducted two studies to investigate our hypotheses and RQ1. Study 1 sought to identify IM profiles that differ both quantitatively and qualitatively, thereby aiming to replicate IM profile solutions found in earlier research (Bolino & Turnley, 2003; Chawla et al., 2021; Maher et al., 2018) and testing Hypothesis 1. Moreover, Study 1 examined relationships between IM profiles and salaries and promotions as objective career success indicators (Hypotheses 3 a-b and 4 a-b), as well as explored relationships with subjective career success (RQ1). Hypotheses were tested among employees working in a diverse range of occupations and industries. Study 2 set out to replicate the profiles found in Study 1 (i.e., testing Hypothesis 2) and to examine the relationship between IM profiles and supervisor ratings of reward recommendations as a further, more forward-looking indicator of objective career success (i.e., Hypotheses 3c and 4c). To do so, Study 2 used data from employee-supervisor dyads who were again employed in various different occupations and industries.

Study 1

In Study 1, we identify IM profiles (Hypothesis 1) and test Hypotheses 3 a-b and 4 a-b with regard to their relationship with objective career success (e.g., salary, promotions) and RQ1 with regard to subjective career success (i.e., perceived career success).

Method

Sample and Procedure

We collected data from Swiss employees via an online survey with the help of a market research companyFootnote 2 (for a similar approach see Batinic et al., 2010; Debus et al., 2020). As part of the informed consent, we informed employees that they could withdraw from the study at any point without consequence and we also assured anonymity. Participants were compensated with bonus points worth 0.50 EUR, which they were later able to exchange for donations to a charitable organization, cash, or shopping vouchers.

In total, 401 individuals agreed to participate. We excluded 142 participants who were not working for pay, were students, were self-employed, or did not complete the survey. Moreover, we excluded 17 participants who provided nonsensical answers to questions about their salary or their job title, which suggests that these respondents were responding carelessly to the survey. Finally, we excluded five participants who demonstrated no variation when answering the impression management items. As such, our final sample included 237 participants (59.1% of the full sample). Of these, 51.9% were male, and mean age was 42.47 years (SD = 11.13). On average, participants had been employed at their current company for 7.76 years (SD = 7.75). A total of 63.7% of participants had vocational training, 22.8% had a bachelor’s degree or a degree from a university of applied sciences, 13% had a university or a doctoral degree, and 0.4% had no formal degree. The majority of participants worked full-time (64.1%) versus part-time. Participants worked in a variety of industries (e.g., health and social services, real estate/IT/research and development, construction, commerce, agriculture, credit and insurance, education, communications and information transmission) as well as in a variety of different occupations (e.g., teacher, flight attendant, process manager, cashiers, IT specialists, trucker, customer relations manager).

Measures

We administered all measures in German. For measures for which a German version of the scale was unavailable, we followed Brislin’s (1980) translation/back-translation procedure.

Impression Management Tactics

Impression management tactics were assessed using Bolino and Turnley’s (1999) measure, in which each of the five tactics is measured with four or five items. Sample items are “I talk proudly about my experience or education” (self-promotion), “I compliment my colleagues so they will see me as likeable” (ingratiation), “I stay at work late so people know I am hard working” (exemplification), “I am intimidating with coworkers when it will help me get my job done” (intimidation), and “I act like I know less than I do so people will help me out” (supplication). Respondents were asked to indicate how often they engage in each of these behaviors at work, ranging from 1 = never behave this way to 5 = often behave this way. Cronbach’s alphas were 0.83 for self-promotion, 0.86 for ingratiation, 0.68 for exemplification, 0.83 for intimidation, and 0.91 for supplication. We also followed the recommendation by Cheung et al. (2023) and examined the average variance extracted (AVE). AVE indicates the amount of variance that is captured by a construct in relation to the amount of variance due to measurement error and serves as a criterion of convergent validity. The results show that AVEs were greater than the 0.50 threshold proposed by Fornell and Larcker (1981) for self-promotion (0.60), ingratiation (0.61), intimidation (0.51), and supplication (0.69), yet that for exemplification it was below this threshold (0.36).

Objective Career Success

Objective career success was assessed via salary and number of promotions.

Salary was assessed by asking respondents to report their monthly salary (in Swiss francs). To account for differences in respondents’ contractual workload, we calculated the full-time equivalent monthly salary for each respondent. Respondents’ mean salary was 6,925.54 CHF/month (SD = 2,897.91, range: 1,000 to 19,500 CHF).

Number of promotions was assessed by asking respondents about the number of promotions that they had received during their entire career (mean number of promotions = 1.87, SD = 1.82, range: 0.00—12.00).

Subjective Career Success

Subjective career success was assessed as perceived career success using the four-item measure by Turban and Dougherty (1994), adapted to the statement format. A sample item was “My career has been successful.” Responses were given on a seven-point rating scale, ranging from 1 = fully disagree to 7 = fully agree. Cronbach’s alpha was 0.87 and AVE was 0.63.

Controls

We controlled for several variables that might influence career success outcomes, specifically age, tenure, workload, and whether individuals were in a leadership position (Ng & Feldman, 2014; Ng et al., 2005).

Analytic Approach

We tested our hypotheses using LPA in Mplus 8 (Muthén & Muthén, 1998–2017). As alluded to in the introduction, LPA is a relatively novel analytic strategy in the work and organizational behavior literature that allows us to identify groups of individuals (i.e., latent subpopulations or profiles) that share similar patterns of variables (here: profiles with regard to the use of the five IM tactics, e.g., Spurk et al., 2020; Wang et al., 2013). As compared to more traditional clustering methods (e.g., k-means clustering, hierarchical clustering) that are non-latent in nature, group membership is treated as an unobserved, categorical variable by LPA. The value of this variable indicates the degree of probability to which an individual belongs to a certain profile. Further advantages of LPA over traditional clustering methods are that variables within LPA may be continuous, categorical, counts, or a combination of these, and that further covariates can be used for profile description – which is what we will do when examining whether the identified profiles differentially relate to outcomes in the form of career success indicators in the present study (Spurk et al., 2020).

Following best practices (e.g., Spurk et al., 2020; Wang et al., 2013), we started by identifying the optimal number of profiles in our sample; this provided an answer to Hypothesis 1. To do so, we followed the recommendations by Nylund et al. (2007) and first specified two latent profiles and then increased the number of profiles. In doing so, we assessed the increase in model fit and theoretical interpretability of the model in each step. We selected the best-fitting profile solution by relying on three types of statistical fit indicators (see Gabriel et al., 2015; Klotz et al., 2018a, 2018b; Nylund et al., 2007; Tofighi & Enders, 2007). First, we compared our models using four relative fit information criteria: log likelihood (LL), Akaike information criterion (AIC), Bayesian information criterion (BIC), and sample-size-adjusted BIC (SSA–BIC). There are no cutoff scores for LPA fit statistics, but lower LL, AIC, BIC, and SSA–BIC values in comparison to other profile solutions indicate better model fit. Second, we compared different likelihood ratio tests (i.e., the Lo-Mendell-Rubin likelihood ratio test [LMR] and the bootstrap likelihood ratio test [BLRT]) “that quantify specific comparisons between the model of interest and a model with one fewer class” (Spurk et al., 2020, p. 10). Both the LMR (Lo et al., 2001) and the BLRT (Nylund et al., 2007) should be significant (p < .05). Third, we inspected entropy as an indicator of classification quality, which reflects the “confidence with which individuals have been classified as belonging to one group or another” (Spurk et al., 2020, p. 10). An entropy value should be above the recommended threshold level of 0.80, and larger entropy values compared to other profile solutions indicate better model fit (Clark & Muthén, 2009). In the next step, we examined whether the identified profiles relate differently to the two objective career success indicators (i.e., salary and number of promotions, as proposed in Hypotheses 3a-b and 4a-b) and subjective career success (i.e., perceived career success as proposed in RQ1). Statistically, this implies that we test mean differences across the different profiles in relation to the three aforementioned career success indicators. Further, to account for the influence of the control variables, we deployed McLarnon and O’Neill’s (2018) proposed manual 3-step approach of the DU3STEP procedure in Mplus 8. DU3STEP allows for unequal profile-specific variance and has been recommended to use for continuous outcome variables (Asparouhov & Muthén, 2014), which is the case in our study (see also Hirschi et al., 2020; Zhu et al., 2017).

Results

Means, standard deviations, and correlations of Study 1 variables are shown in Table 1. Table 2 displays the fit statistics for possible latent profile structures. As shown here, the four-profile solution exhibited better fit compared to the two- and three-profile solutions because it had lower LL, AIC, BIC, SSA–BIC values, and significant LMR and BLRT values. Although the five-profile solution had slightly lower LL, AIC, and SSA–BIC statistics and a slightly higher entropy value in comparison to the four-profile solution, the LMR fit statistic was not significant for the five-profile solution. Given that both LMR and BLRT should be significant (Gabriel et al., 2015), we retained the four-profile structure (see Fig. 1).

Table 1 Means, standard deviations, and correlations of Study 1 variables
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Table 2 Fit statistics for profile structures for Study 1 and Study 2
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Fig. 1
figure 1

Latent profiles for different IM tactics in Study 1

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Figure 1 presents the estimated means of all five impression management strategies for each profile. In line with Bolino and Turnley (2003) and Maher et al. (2018), we found a “positive” profile, in which 85 individuals (i.e., 35.9%) reported using relatively high levels of those tactics that generally seek to elicit a positive impression (i.e., ingratiation, self-promotion, and exemplification) and relatively low levels of those tactics that tend to evoke an unfavorable impression (i.e., supplication and intimidation). The second profile comprised 69 respondents (i.e., 29.1%) who used relatively low levels of all five IM tactics. Following Bolino and Turnley (2003) and Maher et al. (2018), we labelled this profile the “passives.” The third profile was characterized by 20 individuals (i.e., 8.4%) who exhibited high levels of all five IM tactics. Following Bolino and Turnley (2003) and Maher et al. (2018), we labelled this profile the “aggressives.” Finally, the fourth profile, which has not been found in prior research, was characterized by 63 respondents (i.e., 26.6%) who showed moderate levels of all five IM tactics; we termed this profile the “moderates.” In sum, we identified different profiles that differed quantitatively and qualitatively and that included three profiles which were similar to earlier research (Bolino & Turnley, 2003; Chawla et al., 2021; Maher et al., 2018) – thus supporting Hypothesis 1.

Table 3 (see also Fig. 2) displays results from the 3-step procedure used to test differences in outcomes among the different profiles as conditional upon the influence of the control variables. The table displays z-standardized values for the three outcomes across the four-profile solution. First, concerning salary, we should first note that, overall, employees in the passive profile had the highest salary, and those in the moderate profile had the lowest salary. For Hypothesis 3a, we found that positives’ salary was significantly lower than passives’ salary. Because results were in the opposite direction of what we had hypothesized, Hypothesis 3a was not supported. For Hypothesis 4a we found that aggressives’ salary was significantly lower than the salary of passives (but there was no difference between aggressives and positives). Thus, Hypothesis 4a, positing that aggressives’ salaries would be lower than positives’ and passives’ salaries, was partially supported. Moreover, as salary levels are well known to differ considerably by industry type (e.g., Krueger & Summers, 1988) and gender (e.g., OECD, 2023), we examined whether our results remained consistent when controlling for these two variables. The pattern of results was the same as in the earlier analyses, in that passives had the highest, and aggressives had the lowest salary. The only change was that we no longer found a significant difference between the passive and the moderate profile.Footnote 3

Table 3 Results with the manual DU3STEP approach for outcomes of IM profiles (Study 1)
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Fig. 2
figure 2

Standardized means of outcomes by latent IM profiles in Study 1

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Second, concerning promotions, we found that, overall, employees in the passive profile had the highest number of promotions, and employees in the moderate profile had the lowest number of promotions. For Hypothesis 3b, we found that positives’ promotions were significantly lower than passives’ promotions. Because results were in the opposite direction of what we expected, Hypothesis 3b was not supported. Similarly, for Hypothesis 4b, we found that aggressives’ promotions were significantly lower than passives’ promotions (but there was no difference between aggressives and positives). Thus, Hypothesis 4b, positing that aggressives’ promotions would be lower than positives’ and passives’ promotions, was partially supported.

Finally, we found that perceived career success was highest among positives and lowest among passives. Positives scored significantly higher on perceived career success than passives. Results thus provide an answer to RQ 1, indicating that positives’ levels of subjective career success were significantly higher than those of passives.

Taken together, using LPA, we identified four profiles in Study 1. Three of these profiles (i.e., positive, aggressive, passive) were consistent with prior research, and we also identified an additional profile – namely, the moderate profile, in which respondents used moderate levels of all five IM tactics. Further, we demonstrated the relevance of these profiles for indicators of objective career success (i.e., salary, number of promotions) and, in a more exploratory way, for perceived career success. Generally speaking, employees with a passive profile had the highest salaries and promotions, whereas moderates scored lowest. Perceived career success was highest among positives and lowest among passives (with positives scoring significantly higher than passives).

Study 2

Study 2 sought to replicate the IM profiles found in Study 1 (i.e., Hypothesis 2) and to examine the relationship between IM profiles and supervisor-ratings of reward recommendations (Hypotheses 3c and 4c).

Method

Sample and Procedure

Data were collected among employee-supervisor dyads from various companies in Switzerland. We used an official, publicly accessible database to search for companies and their contact information. When organizations agreed to participate, we asked them to distribute a study invitation letter to either their supervisors or their employees (depending on the company’s preferences). In cases where supervisors were the first to receive our invitation, we asked them to register for study participation with one of their subordinates; in cases where employees were the first to receive our invitation, we asked them to register with their respective supervisor. To avoid selection effects when supervisors had multiple subordinates who fulfilled the study criteria, we asked supervisors to register the subordinate whose surname appeared first alphabetically. Every supervisor and every employee could only register once for the study, such that there was no nesting with regard to employees and their supervisors. After the employee-supervisor dyads had registered for study participation and had provided consent, we sent each of them an individualized link to an online survey whereby we could later match supervisors and subordinates who belonged to the same dyad. In return for their participation, participants received a summary of the study findings and took part in a lottery to win one out of ten shopping vouchers worth 30 CHF each. These vouchers could be redeemed at grocery stores, restaurants, public transportation, or cultural institutions and events.

In total, 338 employee-supervisor dyads registered for the study. Upon merging employee and supervisor surveys that had been fully completed, we obtained a dataset of 277 employee-supervisor dyads. From these, we excluded one dyad because the response time of the employee survey was unrealistically short as determined from pretests. In addition, we excluded eight dyads for which either employees or supervisors had provided nonsensical answers or comments (e.g., concerning non-existing jobs), which indicated that these respondents had responded carelessly. The final sample consisted of 268 dyads (79.3% response rate based on the number of employee-supervisor dyads who had initially registered for the study). Employees’ average age was 38.70 years (SD = 11.82), and 38.8% were male. On average, employees had been employed at their current company for 7.09 years (SD = 7.79). A total of 64.4% of employees had vocational training, 10.4% had a bachelor’s degree or a degree from a university of applied sciences, 19.8% had a university or a doctoral degree, and 5.3% did not have any formal degree. Supervisors’ average age was 46.27 years (SD = 9.79), and 63.1% were male. On average, supervisors had been employed at their current company for 11.38 years (SD = 9.83). A total of 48.8% of supervisors had vocational training, 12.3% had a bachelor’s degree or a degree from a university of applied sciences, 38.4% had a university or a doctoral degree, and 0.4% did not have any formal degree. Employee-supervisor dyads were employed in a variety of different industries (e.g., health and social services, real estate/IT/research and development, construction, commerce, agriculture, credit and insurance, education, communications and information transmission) and occupations (e.g., dentist, researcher, clerical assistants, CEO/CIO/COO, head physician).

Measures

Impression Management Tactics

Impression management tactics were measured using the same items as in Study 1. Cronbach’s alphas were 0.85 for self-promotion, 0.90 for ingratiation, 0.78 for exemplification, 0.79 for intimidation, and 0.88 for supplication. AVE was 0.61 for self-promotion, 0.69 for ingratiation, 0.50 for exemplification, 0.46 for intimidation, and 0.61 for supplication.

Objective Career Success

Objective career success was operationalized via reward recommendation ratings provided by the respective supervisors, using the five-item scale by Allen and Rush (1998). Each item asked supervisors to report the extent to which they would recommend the respective employee for five common organizational rewards: salary increase, promotion, high profile project, public recognition, and opportunities for professional development. Responses were made on a five-point rating scale, ranging from 1 = would definitely not recommend to 5 = would recommend with confidence and without reservation. Cronbach’s alpha was 0.76 and AVE was 0.39.

Analytic Approach

We again tested our assumptions by applying LPA. To model outcomes (testing Hypotheses 3c and 4c), while accounting for the influence of the control variables, we again used the manual 3-step procedure in Mplus (Asparouhov & Muthén, 2013; McLarnon & O'Neill, 2018).

Results

Means, standard deviations, and correlations of Study 2 variables are shown in Table 4. To test Hypothesis 2 (i.e., whether we can replicate the profile structure from Study 1), we again examined the fit statistics for possible latent profile structures. As shown in Table 2, the four-profile solution again exhibited the best fit to the data. It had lower LL, AIC, BIC, and SSA–BIC values, as well as significant LMR and BLRT values, in comparison to the two- and three-profile solutions. Although the five-profile solution had slightly lower LL, AIC, BIC, and SSA–BIC statistics and a slightly higher entropy value in comparison to the four-profile solution, the LMR statistic was not significant for the five-profile solution. We thus retained the four-profile structure (see Fig. 3), thereby replicating the same set of profiles that we obtained in Study 1. More specifically, we again found two relatively large profiles of “positive” impression managers (72 individuals, i.e., 26.9% of the sample) and “passive” impression managers (146 individuals, i.e., 54.5% of the sample), and two further profiles of “moderate” impression managers (44 individuals, i.e., 16.4% of the sample) and “aggressive” impression managers (six individuals, i.e., 2.2% of the sample).Footnote 4 Thus, Hypothesis 2 was supported.

Table 4 Means, standard deviations, and correlations of Study 2 variables
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Fig. 3
figure 3

Latent profiles for different IM tactics in Study 2

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To examine profile similarity across Studies 1 and 2 in more detail, we followed the four-step procedure outlined by Morin et al. (2016). In a first step, we examined whether the number of latent profiles identified in both samples were the same (i.e., configural similarity). As the class enumeration procedure was conducted separately across both samples, this test reflected the analysis that we have reported already – finding that the optimal number of profiles was four in both studies. We can thus conclude that configural equivalence is given in our case. Based on these two separate analyses, we then estimated a baseline comparison model to be used for the next step (see Table 5). Second, we examined whether the within-profile means of the five different IM tactics (i.e., the indicators) are the same across our two samples (i.e., structural similarity). As can be seen in Table 5, AIC, BIC and SSA-BIC decreased in this model, which implies an improved fit to the data; therefore, the profile solutions in both samples are structurally similar. Third, we examined whether the indicators’ (i.e., IM tactics’) within-profile variability is the same across both samples (i.e., dispersion similarity). As can be seen in Table 5, fit indices did not improve compared to the previous model, such that dispersion similarity was not evident across our two samples. Finally, we examined distributional similarity – referring to “whether the relative size of the profiles is similar across groups” (Morin et al., 2016, p. 234). Fit indices did not improve in contrast to the previous model (see Table 5), such that we cannot demonstrate distributional similarity across our samples. In sum, based on our analyses, we can conclude that the profile solutions across our two samples are configurally and structurally similar (i.e., both samples yielded the same number of profiles with similar levels on the underlying indicators), yet we could not confirm dispersion and distributional similarity.

Table 5 Fit statistics from the profile similarity analysis for Study 1 and Study 2
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Next, we examined differences in reward recommendations across the different profiles, thus testing for Hypothesis 3c and 4c. Our analyses (see Table 6 and Fig. 4) revealed that, overall, employees in the passive profile received the highest level of reward recommendations, and those in the aggressive profile scored lowest. For Hypothesis 3c, we found that passives’ reward recommendations were significantly higher than positives’ reward recommendations. Because results were in the opposite direction of what we expected, Hypothesis 3c was not supported. For Hypothesis 4c, we found that aggressives’ promotions were significantly lower than passives’ promotions (but there was no difference between aggressives and positives). Thus, Hypothesis 4c, positing that aggressives’ promotions would be lower than positives’ and passives’ promotions, was partially supported.

Table 6 Results with the manual DU3STEP approach for reward recommendation as outcome of IM profiles (Study 2)
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Fig. 4
figure 4

Standardized means of reward recommendation by latent IM profiles in Study 2

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In sum, we again found the four IM profiles: positive, passive, aggressive, and moderate. Further, using multi-source data, we found that employees emphasizing a passive use of IM tactics received significantly higher reward recommendations than those who emphasized the positive or aggressive use of IM tactics.

Discussion

Despite the fact that employees engage in IM in order to manage their careers, the current literature provides relatively little insight concerning the link between IM and career success (for an overview see Bolino et al., 2016), and notably, even fewer insights when it comes to explaining the career success implications of using IM tactics in combination. In the present research, we utilized a person-centered approach to examine the predictive validity of IM profiles on different indicators of career success as the “ultimate outcome of a career” (e.g., Spurk et al., 2019, p. 37). Our study provides several relevant findings.

First, across two studies, we replicated three IM profiles that were likewise identified in previous research (Bolino & Turnley, 2003; Chawla et al., 2021; Maher et al., 2018), including a positive, a passive, and an aggressive profile. This finding was also in line with our theorizing. The fourth profile that emerged in our research was a pattern we labeled “moderate” because it consisted of employees who used relatively moderate levels of all five IM tactics. Second, across both studies, the combined use of IM had relatively consistent effects on objective career success indicators. In particular, in contrast to our hypotheses, passives consistently scored highest on all three objective career success indicators, and employees in the moderate profile exhibited low levels of objective career success, which were similar to the aggressive profile. We discuss this unexpected pattern further below. Third, we provided partial empirical evidence for the theoretically proposed backfire effect when IM is used in an aggressive way (Bolino et al., 2016; Crant, 1996), implying that such a pattern may be risky for objective career success indicators (i.e., salary, number of promotions, and reward recommendations). More precisely, aggressives scored significantly lower as compared to passives on all three objective career success indicators. Finally, for subjective career success, we found that positives scored highest, and passives scored lowest. Concerning the passives, this study thereby found an opposing pattern regarding their objective and subjective career success. While the passives scored highest on the objective indicators, they scored lowest on the subjective career success indicator – thus pointing to the qualitatively different nature of objective and subjective career success. Below, we discuss the theoretical implications of these findings in more detail.

Theoretical Implications

Our study yields several theoretical implications. First, and partly in line with our predictions, the aggressive use of IM was consistently associated with lower levels of all three objective career success indicators, specifically in contrast to the passive profile. These findings align with our initial proposition about potential backfire effects when using aggressive IM. Moreover, it may be difficult for aggressive IM users to advance career-wise while trying to project inconsistent images (i.e., eliciting favorable images due to self-promotion, ingratiation, and exemplification, as well as unfavorable images due to supplication and intimidation). One possible reason is that such behavior (i.e., displaying inconsistent IM behavior) could be draining and lead to feelings of inauthenticity (Chawla et al., 2021), which could in turn negatively affect task performance. Indeed, Chawla et al. (2021) found that passives obtained higher coworker ratings of job performance than positives and supplicating aggressives. In sum, our findings extend prior theorizing by indicating that using very low levels of IM in combination (i.e., a passive IM use) can be more effective than using very high levels of IM – an idea that has largely been neglected in the literature.

Second, our contrasting findings for subjective and objective career success can inform theories on IM, including its motivation and effectiveness in career contexts. In particular, for subjective career success, we found that positives were significantly more satisfied with their career as compared to passives, whereas the difference between aggressives and passives was not significant. This suggests there is a need to refine our theorizing such that we avoid from automatically interpreting all active IM use as an effective self-enhancement strategy (Schlenker, 1985), specifically as it pertains to one’s career (i.e., employees’ subjective perceptions of their career). Instead, it appears that a potential self-enhancement effect tends to only be present for the active use of IM centering on positive tactics in comparison to a passive use. Indeed, it is conceivable that this active use of positive IM can enhance employees’ subjective career perceptions by perceiving their own behaviors as likeable, competent, and dedicated. In contrast, employees who use IM passively may not perceive themselves to be successful in their careers because they do not engage in behaviors to make themselves appear more likeable, competent, and dedicated. Hence, our research suggests that IM may not just be externally directed, but may also play to employees themselves (i.e., the self as an audience, Bolino et al., 2016) and potentially explain part of the fluctuation of subjective career success (Zacher, 2015). We thus encourage future research to elucidate the underlying mechanisms that explain why positives enjoy high levels of subjective career success.

Concerning the findings for objective career success (i.e., consistently highest among the passive IM profile), this might be explained by the motive of self-verification that has, besides self-enhancement, been put forward as another major motive for managing impressions (Leary, 1995) and used as a theoretical approach to understand IM (e.g., Crawford et al., 2019). When individuals use IM as a means for self-verification, they aim for a confirmation of their own self-images by others; that is, they desire to be seen by others as they see themselves (see also Bozeman & Kacmar, 1997; Swann et al., 1992, 2003). We suggest that the rather limited use of IM by individuals in the passive profile might reflect self-verification (Cable & Kay, 2012) and may be perceived as particularly authentic by observers (e.g., Moore et al., 2017), thereby contributing to superior objective career success in comparison to other IM users (i.e., aggressives, positives, moderates). This possibility is aligned with recent career-related findings on the relevance of self-verification in the context of job search, which finds that applicants with higher self-verification motives are perceived as more authentic by others and receive more job offers (Moore et al., 2017). At the same time, as passives may keep to themselves, they do not actively strive towards increasing their subjective career perceptions, which distinguishes them from the positives (as discussed above). However, given that this is a post-hoc interpretation of our findings, and we did not include a measure of IM motives, we encourage future research to systematically investigate how IM motives may influence IM profiles and career-related outcomes.

Finally, our research highlights the value of taking a person-centered approach (e.g., Wang et al., 2013) because it shows that the implications of using multiple IM tactics in combination are different than using specific IM tactics in isolation. For instance, in Study 1, according to the correlation matrix (see Table 1), there were only a few correlations between the five IM tactics and the three career success indicators. Relatedly, in Study 2, none of the five IM tactics, individually, were significantly correlated with reward recommendations (see Table 4). Yet, using LPA, our analyses revealed that profiles of IM, reflecting the combined use of IM tactics, predicted multiple indicators of career success. As such, our research generally highlights the value added by adopting a profile perspective in IM research, thereby adding to the body of recent research (Chawla et al., 2021; Maher et al., 2018) and contributing to a more comprehensive theoretical perspective on IM that complements prior variable-centered research.

Limitations and Directions for Future Research

Our study has limitations that need to be acknowledged. First, despite our theoretical assumptions about the link between IM profiles and career success, we cannot determine the direction of causality with this data. In addition, our research is more descriptive than variable-centered research on IM, but this is often true when using LPA, as it is an inductive approach with the aim of theory development rather than result confirmation (see Woo et al., 2024, for a discussion of this in a recent review on person-centered approaches). As such, we see our results as one valuable step towards developing a theory of the combinatory use of the five IM tactics identified by Jones and Pittman (1982). In this way, our study provides a foundation for future theory testing, using complementary deductive approaches that should ultimately facilitate a deeper understanding of IM.

Second, obtaining data from both supervisors and employees is especially demanding, expensive, and time-consuming and has restricted our upper limit of sampling. Against this backdrop, we acknowledge that the size of our samples (i.e., 237 in Study 1 and 268 in Study 2) was comparatively small for LPA, given that sample sizes of 500 are usually recommended (see Nylund et al., 2007, for a simulation study with different sample sizes and indices). To account for this limitation, we chose to base our decision on the number of profiles on those indicators that have been found to be least affected by sample size, that is LMR and the BLRT, as indicated by negligible change in the Type I error rates across different sample sizes for the type of analysis that we conducted (Nylund et al., 2007). Put differently, whereas AIC and the SSA-BIC (and the BIC in Study 2) were slightly lower for the five-profile solution, we based our final decision on the significance of the LMR and the BLRT and thus chose the four-profile solution. Indeed, this decision is further supported by the additional profile similarity analysis that we conducted, which lends further confidence to the determined number of profiles. In a related vein, we need to acknowledge that some of our measures displayed reliabilities that were lower than the recommended level of 0.80 for research purposes (e.g., exemplification in Studies 1 and 2 [0.68. and 0.78], and intimidation in Study 2 [0.79], Nunnally, 1978, see also Carmines & Zeller, 1979; Lance et al., 2006). Notably, in the original scale validation study (Bolino & Turnley, 1999), the reliabilities for two scales were below the 0.80 threshold (i.e., 0.75 for exemplification, and 0.78 for self-promotion). Thus, even though we see stability in our results based on the replication of the profiles across two samples, we would like to raise the possibility that the low reliability of these measures likely introduced measurement error and to some degree, might have lowered the stability of results.

Third, similar to earlier research conducted in the U.S. and Brazil, we identified a positive, an aggressive, and a passive profile in the Swiss data (Bolino & Turnley, 2003; Chawla et al., 2021; Maher et al., 2018). Theoretically, one may conclude that the aggressive, positive, and passive profiles, which emerged in this and previous studies as well as ours, utilizing data from three different countries, are somewhat “culturally universal” profiles. Complementing this perspective, our finding of an additional moderate profile provides potential support for theorizing on how cultural contexts may influence the use of IM. Previously, against the backdrop of the individual-collective dimension of culture, Maher et al. (2018) discussed differences between the uses of exemplification in the profiles of respondents from U.S. samples in comparison to a sample of Brazilian employees. Specifically, they suggest that the lower use of exemplification in the Brazil sample as opposed to the higher use of it in the three U.S. samples, might be explained by a potentially more negative view of exemplification as a self-focused tactic in the more collectivistic culture of Brazil in comparison to the individualistic one of the USA. In our research, we identified a moderate profile, in which respondents used moderate levels of all five IM tactics. It might be the case that cultural differences have likewise contributed to the emergence of this moderate profile. More precisely, Switzerland and the U.S. differ in terms of the cultural characteristic of modesty, referring to “the underrepresentation of one’s positive traits, contributions, expectations or accomplishments” (Wosinska et al., 1996, p. 230). Whereas the Swiss culture places great importance on the values of modesty and diplomacy, Anglo countries, such as the U.S., highly value being unique, outstanding, and forceful (e.g., Schmid Mast et al., 2011). Thus, given their tendency to be more modest and diplomatic, it is understandable that Swiss respondents who use all five IM tactics would more clearly differentiate in using them at either moderate or truly aggressive levels. This, again, might have contributed to the fact that we identified both a moderate and an aggressive IM profile. The moderate profile might be representative of culturally-bound profiles, thereby suggesting that IM theory may have to acknowledge the role of culture to a greater extent. To facilitate a better understanding of how IM use is affected by culture, we call for systematic cross-cultural research on IM that investigates the use of IM and its perceived effectiveness across various countries with comparable samples concerning jobs and industries.

Relatedly, it would be useful to further delve into the nature, meaning, and size of the moderate profile. In contrast to cultural values taxonomies in cross-cultural research (such as the taxonomy by Hofstede, 2001), modesty is a value that has received much less research attention and that can be indirectly inferred from cross-cultural research on honesty-humility [a trait defined by the adjectives of honest, sincere, fair, and modest or their opposites (Ashton et al., 2014)]. Concerning honesty-humility, Swiss respondents appear to obtain descriptively higher scores on honesty-humility than U.S. respondents (García et al., 2022), supporting the notion that the Swiss culture may reinforce the importance of modesty and greed avoidance, thereby contributing to the appearance of a modest IM profile in comparison to cultures that place less value on modesty (e.g., the U.S.). Support for this assumption stems from variable-centered research on IM showing negative correlations between individuals’ honesty-humility scores and their IM scores (Bourdage et al., 2015). As such, it would be worthwhile to explore how levels of honesty-humility in a country influence the emergence of a moderate IM profile.

Fourth, additional research is needed to more systematically consider how profiles and their effectiveness are impacted by industries, organizations and jobs. So far, prior studies with employees (Chawla et al., 2021; Maher et al., 2018), as well as our study, included samples that were very heterogeneous in terms of industries, organizations, and jobs. Importantly, we cannot determine to what extent these factors contribute to the variation and effectiveness of these profiles. For instance, IM might be more strongly associated with objective career success in competitive environments and/or jobs (e.g., in consultancy businesses) than in less competitive public organizations. Accordingly, we recommend surveying more homogeneous samples that include people working in similar jobs and organizations across different cultures (as described in the prior paragraph). By controlling for these factors, it would be easier to determine whether differences in profiles are due more to industry/organization/job factors than to cultural factors. Relatedly, our profile similarity analysis demonstrated that the profile solutions across the two samples were configurally and structurally similar, meaning that the nature of the profiles (i.e., the number of profiles and the levels of the indicators) were generalizable. Morin et al. (2016) acknowledge that differences are more likely to emerge for dispersion and distribution similarity, which is reflected in our findings. Indeed, the authors highlight that “differences do not represent an inherent limitation in the data but rather indicate limits to the generalizability of profile solution that may deserve further exploration” (Morin et al., 2016, p. 235). We thus encourage future research to identify variables that may contribute to differences regarding the variability of IM tactics across profiles as well as differences in the relative size of the profiles across different samples.

Fifth, to better understand the differential effects of IM profiles on career success, we recommend examining more proximal outcomes of IM profiles in the future, particularly the desired images associated with IM. Image outcomes, such as competence, dedication, and neediness, have not been investigated in profile-centered research (for one exception on the effects of likeability see Bolino & Turnley, 2003). Further, given that IM profiles can convey a more comprehensive image (e.g., that of a competent, likeable and dedicated employee for the positive profile), the effects found using a person-centered approach might be more pronounced than those found using variable-centered research emphasizing the link between individual tactics and desired/undesired images (Turnley & Bolino, 2001). Indeed, such investigations may find that these broader images mediate the relationship between IM profiles and career success.

Finally, our findings support the argument that career success is a complex construct. Although scholars generally differentiate between objective and subjective career success (e.g., Spurk et al., 2019), our nuanced findings regarding IM profiles and career success suggest that even within the category of objective career success, the typical indicators may capture something slightly different. In Study 1, for example, the correlation between salary and promotions was only 0.39, which was negligibly higher than the correlation between perceived career success and each objective career success indicator (e.g., Seibert et al., 2001). Therefore, we encourage future studies on career success to take a more in-depth look at the multiple types of career success indicators as well as differential effects of predictors and potentially underlying mechanisms.

Practical Implications

As we note above, our research design prevents conclusions about causality. Nonetheless, the practical implications of our study are relevant for employees who seek to effectively manage their image in the workplace for career purposes, for career counsellors and executive coaches who support employees’ efforts to be successful at work, and for managers who decide upon promotions and other organizational rewards that thereby shape employees’ careers. In that regard, first, our findings suggest that employees should be aware that how they combine different IM tactics can have an impact on their career and that those effects may also differ in their implications for objective and subjective career success. Specifically, employees who want their supervisors to recommend them for promotions and other organizational rewards should restrict themselves to use relatively little IM (i.e., the passive profile) or to a combination of the positive IM tactics of ingratiation, self-promotion, and exemplification to shape their image at work (i.e., the positive profile). At the same time, however, our findings indicate that employees who also seek to view their career more positively should aim to use positive tactics rather than passive ones, given that the former increases chances of perceiving their career success more positively in comparison to the latter. Yet, given that the passive profile was most consistently related to the highest objective career outcomes, employees might have to consider a trade-off between being vs. feeling most successful. Second, career counsellors and executive coaches should warn those they advise that the aggressive use of IM tactics could also, to some degree, undermine their career success. Finally, from the perspective of the organization, managers may wish to reflect upon the extent that decisions that concern their subordinates are influenced by the subordinates’ combined use of IM tactics. This will help ensure that their subordinates’ careers are not adversely influenced by factors that are unrelated to job performance.

Conclusion

Using two studies and a person-centered approach, we identified different profiles of IM use and found that they are differentially related to indicators of career success. In particular, our findings suggest that when employees engage in passive IM use, it is consistently related to the highest levels of objective career success; in contrast, engaging in an aggressive and/or moderate use of IM is related to significantly lower levels of objective career success. Interestingly, we found a somewhat reversed pattern for subjective career success, whereby positives scored highest, and passives scored lowest – a finding that may be due to self-affirmation processes and/or different temporal dynamics. These results not only have important practical implications for employees who seek to get ahead in organizations, but they also increase our broader understanding of IM and how managing impressions at work can be a complicated and potentially risky endeavor. At the same time, our findings call for an even more fine-grained conceptualization of career success, above and beyond the objective-subjective career success distinction.