DO BIRDS OF A FEATHER FLOCK TOGETHER? A FIT THEORY PERSPECTIVE ON LMX QUALITY AND RATEE FEEDBACK REACTIONS

Rater–Ratee H-Factor (In)congruence and LMX

We separate an effectance motive (Figure 1, quadrants 1 and 2) from a repulsion hypothesis (Figure 1, quadrants 3 and 4). This helps us understand the difference between the two parts of the similarity-attraction theory (Byrne, 1971) that apply to PA. We maintain that rater–ratee H-factor congruence shows an effectance motive no matter how high or low the H-factor is. This is based on the similarity-attraction theory. People with a high H-factor neither exploit nor deceive others nor do they consider themselves entitled to more material things. Despite possessing the power or ability to control the entire pie, individuals with a high H-factor distribute their fair share to others. This is because such people prioritize ethics over profit and treat others fairly. Thus, individuals with a high H-factor gain the trust of others and are likely to receive reciprocation in the form of cooperation (Lee & Ashton, 2013; Paul et al., 2022).

Building on the above, it stands to reason that the interaction between people with high H-factor may attract each other and reap the benefits of cooperation. On the contrary, people with a low H-factor may have a common tendency to exploit, deceive, and manipulate others for their personal gains. Such people often consider themselves entitled to material things. Therefore, they are prone to depriving others of their due share of the pie. Nevertheless, we expect that, because of their common quest for personal gains, the interaction between people with low H-factor might make them allies, albeit with little trust in each other. Contrary to the above, we assume that the rater–ratee H-factor incongruence predicts repulsion between them. Whether the rater has a high H-factor and the ratee has a low one or vice versa, they are likely to repel each other due to different motives. These discrepancies in personality traits may cause the rater–ratee dyad to limit their interactions with each other. Such a situation can make it difficult for them to have a high-quality relationship.

The rater–ratee H-factor congruence determines high LMX quality. Enhancing the effectiveness of the exchange process, specifically through role-taking and role routinization (Yuan et al., 2023), leads to the generation of goal congruence. Goal congruence occurs when a leader defines and communicates organizational or departmental goals to the follower and then aligns the follower’s efforts with the defined goals and tasks (Colbert et al., 2008; Man Tang et al., 2022). So we think it is likely that, no matter the level (high or low H-factor), a rise in rater–ratee H-factor congruence could mean that the effectance motive will rise as well. So, when both raters and ratees are high in H-factor, they tend to find each other similar in their world, developing an effectance motive for each other. Such a state, in which both rater and ratee are high in H-factor, is considered to increase LMX quality, characterized by socioemotional exchanges (quadrant 1, Figure 1). According to Korman’s (1970) balance theoretical hypothesis, individuals gravitate toward roles and situations that align with their worldview. This provides us a basis for offering the assumption that, when both raters and ratees are low in the H-factor, they may generate an effectance motive for each other. Primarily, this is due to their shared worldview, but they also act as allies to satisfy their individual interests, which may include a desire for money, status, or power. A low H-factor means that the person has a tendency to be manipulative, so rater–ratee congruence at a low H-factor is likely to lead to transactional LMX (quadrant 2, Figure 1) (Cogliser et al., 2009).

The rater–ratee H-factor incongruence leads to low LMX quality. Usually, this occurs due to an ineffective exchange process in which the rater and ratee’s worldviews differ from each other, leading them to pursue uncommon individual goals, which, in turn, generates goal incongruence. The similarity-attraction theory’s reinforcement model suggests that dyad members experience increased repulsion due to low LMX quality. For instance, when levels of rater–ratee H-factor diverge, inconsistencies in role expectations and requirements between them prevail (Graen, 1976). Inconsistencies in a person’s worldview stimulate feelings of anxiety and confusion. Similarly, discrepancies in expectations create tension, confusion, and indecision (Kahn et al., 1964). If the rater has a low H-factor and the ratee has a high H-factor (quadrant 3, Figure 1), or if the rater has a high H-factor and the ratee has a low H-factor (quadrant 4, Figure 1), we still believe that the LMX quality will be low. In sum, we hypothesize the following.

Hypothesis 1: Rater–ratee H-factor congruence (both at high and low levels of H-factor) predict higher LMX than rater–ratee H-factor incongruence (either rater H-factor is higher than ratee H-factor or ratee H-factor is higher than rater H-factor).

Rater–Ratee H-Factor Congruence and LMX

We have already said that rater–ratee H-factor congruence is more likely to predict higher LMX quality than their incongruence. Now, we want to show how two different levels of H-factor affect LMX quality (Figure 1: quadrant 1 vs. quadrant 2). We maintain that H-factor congruence will have a bigger impact on LMX quality when raters and ratees have high H-factors compared with low H-factors. This is because the similar-to-me premise says that congruence is better than incongruence. That is, a dyad congruent at a high H-factor is more likely to agree on working together based on both members’ preferences for ethics over profits. Such congruence generates socioemotional exchanges, resulting in high LMX quality. In fact, such a consensus incites both rater and ratee to advance their relationship by employing collaboration, positivity, and support. As a result, ratees perceive themselves as trusted partners rather than just hired hands (Dansereau et al., 1975; Uhl-Bien et al., 2022), whereas raters view ratees as trusted assistants, thereby feeling obligated to respond to them with favorable and constructive work resources (Graen & Scandura, 1987).

With a low H-factor, a rater–ratee dyad can exhibit mutual understanding and goal congruence, albeit solely for the purpose of pursuing personal profits, disregarding ethics and fairness. This could potentially develop into a mutual alliance and an objectively good dyadic relationship, but due to their manipulative tendencies, they are less likely to trust each other, resulting in a need to maintain a closed relationship (Lee & Ashton, 2013). So, under these circumstances, their relationship would remain transactional. Thus, we hypothesize the following.

Hypothesis 2: Rater–ratee H-factor congruence predicts high LMX; however, LMX is higher when rater–ratee H-factor is high (socioemotional relationship), than when rater–ratee H-factor is low (transactional relationship).

Rater–Ratee H-Factor Incongruence and LMX

Based on the ideas behind LIFT, we make the case for how two types of rater–ratee H-factor incongruence affect LMX quality in different ways. The effect of rater–ratee H-factor incongruence on LMX quality is likely to be asymmetrically low. That is, rater–ratee H-factor incongruence will predict even lower LMX quality when rater H-factor is high and ratee H-factor is low (quadrant 4) compared with when rater H-factor is low and ratee H-factor is high (quadrant 3).

A rater with a lower H-factor than the ratee may view the ratee’s H-factor as incompatible with the rater’s own motives; however, this incompatibility is considered to mitigate the undesirable consequences of incongruence. Earlier research on employee behavior at work has shown that honesty is a good indicator of how well they will do their job (Ete et al., 2020; Johnson et al., 2011) and a bad indicator of psychopathy, Machiavellianism, sexual quid pro quos, and other bad behaviors (Ashton & Lee, 2008; Lee et al., 2005; Marcus et al., 2007; Pletzer, 2021). These positive outcomes (high employee performance and low undesirable work behaviors) help leaders pursue their work-related targets and, as a result, lower the likelihood of rater–ratee H-factor incongruence. Thus, it can be expected that despite a rater’s low H-factor, when employing active cooperation in the stages of role taking and role making, the ratee with a high H-factor can slightly lessen the negative effects of rater–ratee H-factor incongruence on LMX quality.

Alternatively, a ratee with a lower H-factor than the rater is prone to constantly looking for ways to undermine others’ goodwill and remain involved in counterproductive work behaviors (Marcus et al., 2007) and ingratiation (Lee & Ashton, 2013; Paul et al., 2022). Furthermore, such a ratee is likely to evade active cooperation and, thus, provoke the rater’s reprisal. These circumstances can be unsupportive for the ratee, particularly in the role-taking and role-making stages of LMX development. This is because the ratee’s counterproductive work behavior and exploitive tendencies will make the rater with a high H-factor reluctant and cautious to send more roles to the ratee with a low H-factor. As a result, a ratee with a low H-factor can slightly increase the negative effects of rater–ratee H-factor incongruence on LMX quality. Together with this, a rater with a high H-factor may also employ negative reinforcement for the dishonest ratee, causing a lower LMX.

Thus, we anticipate that, when a ratee has higher levels of honesty than the rater, the incongruence effect (quadrant 3) is less damaging to LMX quality than when the incongruence effect is such that a ratee has lower honesty than the rater (quadrant 4).

Hypothesis 3: Rater–ratee H-factor incongruence predicts low LMX; however, LMX is lower when rater H-factor is higher than ratee H-factor compared with when ratee H-factor is higher than rater H-factor.

Rater–Ratee H-Factor (In)Congruence and Ratee Feedback Reactions via LMX

Honesty has various facets, such as sincerity, fairness, greed avoidance, and modesty, and they all have implications for how people relate to others. For instance, a high H-factor is associated with altruistic tendencies (manipulation avoidance, scrupulous fairness, and humbleness), whereas a low H-factor is associated with antagonistic tendencies (instrumental ingratiation, exploitation, and self-entitlement) (Lee & Ashton, 2013; Paul et al., 2022).

In the PA context, feedback-seeking behavior and feedback acceptance are considered valuable stakeholder reactions. Feedback-seeking behavior fits the description of proactive behavior: “anticipatory action that employees take to impact themselves and/or their environments” (Grant & Ashford, 2008, p. 4). Feedback acceptance is defined as “the recipient’s belief that the feedback is an accurate portrayal of his or her performance” (Ilgen et al., 1979, p. 356). Specifically, we expect rater–ratee H-factor (in)congruence through LMX to affect ratee feedback reactions, such as ratee feedback-seeking behavior and feedback acceptance.

Leaders form differential relationships with members that appear to be of high or low quality (Uhl-Bien et al., 2022). Particularly in the PA context, these relationships are believed to predict outcome variables. Some studies back this up by showing that raters and ratees who have good interactions are more likely to have positive responses to the PA process (Elicker et al., 2006; Khan & Iqbal, 2022). Ratee feedback reactions are no different. Empirical research supports the above argument. For instance, Huang (2012) and Chuang et al. (2014) suggest that employees who have a positive attitude toward their supervisors are more inclined to seek negative feedback from the supervisor. Similarly, Katz et al. (2021) suggest that affect-based trust substantially increases the feedback frequency due to the perceived cost reduction in feedback seeking.

Feedback acceptance as one of the ratee reactions has also received notable research attention (e.g., Atwater & Brett, 2005; Kinicki et al., 2004; London et al., 2023). Research generally finds that ratees respond more positively to favorable feedback than unfavorable feedback (Anseel & Lievens, 2006; Brett & Atwater, 2001; London et al., 2023; Nease et al., 1999; Tonidandel et al., 2002). Hence, people tend to have positive self-views and self-affirmations and uphold their self-esteem in the finest possible light in the eyes of others, that is, a self-enhancement tendency (London et al., 2023; Sedikides & Gregg, 2003). Because of this self-enhancement tendency, we expect that rater–ratee H-factor congruence is likely to result in more positive feedback reactions than incongruence per se.

Whereas we have argued for the mediating role of LMX quality in rater–ratee H-factor congruence and ratee feedback reactions, we also acknowledge the possibility of other mechanisms underlying the relationship between H-factor congruence and feedback reactions. Simply put, in the context of rater–ratee congruence at low levels of H-factor, a ratee may seek feedback, not necessarily due to LMX quality, but potentially due to preconceived opportunity costs such as failing to gain an undue share or employing image-enhancing motives (i.e., instrumental ingratiation). Likewise, it is possible that the ratee accepts feedback despite being congruent with the rater at a low H-factor, again not because of LMX quality, but because accepting feedback would fulfill the ratee’s desire to bend rules for personal gain. Besides this, rater–ratee H-factor congruence may rightly be beneficial for ratee performance as the cognitive load on such a ratee in working with the counterpart rater is low (Mayer & Gavin, 2005). As a result, we hypothesize that LMX quality is partially mediated.

Hypothesis 4: LMX mediates the relationship between rater–ratee H-factor (in)congruence and (a) ratee feedback-seeking behavior and (b) ratee feedback acceptance.

According to Ashford and Black (1996), feedback reactions are more relevant to two specific work contexts. The first pertains to newcomers entering the organization (Parker & Collins, 2010). The second pertains to the uncertainty inherent in middle management roles. Middle managers frequently address this uncertainty with continuous information and feedback seeking (Ashford & Tsui, 1991), also known as the feedback-as-an-aid-to-learning argument (Ashford et al., 2016; De Stobbeleir et al., 2020). We pursued the aim of understanding ratee feedback reactions due to varying levels of a personality trait (honesty) through an underlying mechanism (LMX), focusing on the feedback as a tool for learning. We conducted a field study to investigate the impact of rater–ratee personality configurations on outcome variables in a natural environment. The contextual landscape that embodies an organization’s social system allows personality traits to interplay among rater–ratee dyads to influence performance, ratings, and behavior (Brown et al., 2019; Harari et al., 2015).

Data and Sample

The study focused on two types of organizations in Pakistan: multinational beverage companies and telecom companies. We selected these organizations due to their established performance management systems for their engineering staff. In the beverage industry, production engineers work closely with machine operators and foremen. Their job involves developing, installing, and maintaining equipment on nonstop production lines. They need to be technically skilled, flexible, and able to manage stressful situations. Performance appraisal for these engineers relies on continuous feedback and key performance indicators (KPIs).

Telecommunication engineers in Pakistan’s telecom sector provide various communication and engineering solutions, including radio and satellite communications, internet, banking, and broadband technologies. Their work is often project-based with tight deadlines and involves tasks such as service delivery, feasibility studies, and documentation. With quarterly and annual appraisals based on KPIs, feedback is critical to their job.

We used purposive sampling to select participants based on their relevance to the research questions. We selected ratees (employees) based on their continuous contact with their direct raters (managers) and their proximity to them in the workplace. We selected the rater participants in a similar manner, considering their direct role as raters for the ratee participants, using data gathered from the human resources (HR) departments of their respective organizations. With the support of management in the respective organizations, we distributed 340 questionnaires among randomly selected employees (ratees) from a population of 1,460 and to all 120 managers who were their direct reports. Out of the matched pairs, we received usable responses from 310 ratees and 100 raters. The response rates were high with 91% from ratees and 83% from raters. The criteria established by Krejcie and Morgan (1970) deemed the sample sizes acceptable based on the response rates and the size of the rater and ratee populations.

We accessed the data through a systematic process. Initially, we sought approval from the HR departments of the respective organizations, ensuring compliance with established procedures for protecting organizational confidentiality (Babbie, 2020). Second, we communicated the purpose and requirements of participation through a cover letter, assuring respondents that their responses would be kept confidential. Third, we specified to the organizations the type of research participants required (leader–member dyads) and the estimated time for completing the questionnaire. Fourth, we obtained voluntary participation and explained the questionnaire’s structure, prioritizing participant privacy and informed consent. To maintain anonymity, we assigned a code to each leader and member questionnaire and placed them in separate envelopes. Subsequently, participants returned the filled-out questionnaires anonymously in the designated envelopes.

As our study relied on self-reports, it was important to address potential common method bias (CMB). To achieve this, we utilized both ex ante and ex post approaches (Podsakoff et al., 2024). At the design stage, we ensured that the questionnaire was clear and free of jargon, providing participants with ample time to respond. We also included a cover letter emphasizing the anonymity of their responses and reassuring them that there were no right or wrong answers. We conducted the survey in English, and all participants were proficient in the language. At the analysis stage, we employed Harman’s one-factor test to identify the presence of CMB. The results indicated that only 28.46% of the total variance was attributable to a single factor, which is far below the threshold of 50%, suggesting that CMB was not an issue in our data.

Furthermore, we assessed the potential for nonresponse bias by comparing early and late respondents (Armstrong & Overton, 1977; Vogel & Jacobsen, 2021). Through t-tests on the main study variables, we found no statistical differences between the two groups, indicating that nonresponse bias was not a significant concern in our study.

We employed polynomial regression and response surface methodology (as discussed by Edwards, 2002) to examine our hypotheses. This technique is superior because previous studies investigating the impact of personality (Big Five) congruence on LMX quality have often relied on difference scores (Bernerth et al., 2008; Liao et al., 2013). According to Edwards (2002), these methods have limitations, such as low reliability, information loss, and ambiguous interpretation. Polynomial regression addresses these drawbacks and avoids restricting a three-dimensional relationship (i.e., leader H-factor, member H-factor, relational and work outcomes) to a two-dimensional one. This means that polynomial regression looks at the differences and similarities between (in)congruence at different levels of the H-factor. This includes congruence at high and low levels of honesty and humility as well as cases of incongruence in which the leader is higher on honesty and humility than the member and vice versa (Edwards, 2002).

Measures

Data Analysis Approach

We used response surface analysis and the following polynomial regression equation (Edwards & Cable, 2009; Matta et al., 2015) to find out how the (in)congruence between the ratee–rater H-factor affected the LMX and ratee feedback reactions. Notably, to keep things simple, we didn’t include control variables in the equation.

$$\mathit{LMX}=b_0+b_1{H}_{\mathit{ratee}}+b_2{H}_{\mathit{rater}}+b_3{\left(H_{\mathit{ratee}}\right)}^2+b_4\left(H_{\mathit{ratee}}\times H_{\mathit{rater}}\right)+b_5{\left(H_{\mathit{rater}}\right)}^2+e_{\mathit{LMX}}.$$

Before we estimated the three second order polynomial terms, that is, ($b_3{\left(H_{\mathit{ratee}}\right)}^2+b_4\left(H_{\mathit{ratee}}\times H_{\mathit{rater}}\right)+b_5{\left(H_{\mathit{rater}}\right)}^2)$ (Aiken et al., 1991), we median-centered rater honesty (H_rater) and ratee honesty (H_ratee) to avoid multicollinearity. Subsequently, we used the regression coefficients to generate a three-dimensional response surface. We plotted this surface with rater honesty (H_rater) and ratee honesty (H_ratee) on perpendicular horizontal axes and ratee-reported LMX quality on the vertical axis (as discussed in Edwards & Cable, 2009; Matta et al., 2015; Zhang et al., 2012). The floor of the graph represents two important lines for interpretation: (1) the congruence line, along which ratee and rater H-factors are congruent, and (2) the incongruence line, along which ratee and rater H-factors are incongruent. We tested the first two hypotheses according to the three important attributes of these response surfaces as outlined by Edwards and Cable (2009). The first requirement is that the curvature along the incongruence line be negative, indicating a downward slope in which the dependent variable (LMX) decreases as the rater and ratee H-factors differ in either direction. To test the first feature, we examined whether the curvature along the incongruence line (R = −r), calculated as b₃ – b₄ + b₅, is significantly negative using techniques employed for testing linear combinations of regression coefficients (Edwards & Cable, 2009).

The second feature that supports the congruence effect necessitates an examination of the ridge, which represents the peak of the response surface. Along the congruence line, the ridge marks the surface’s highest point. This means that the dependent variable (LMX) is at its highest point of rater–ratee H-factor congruence (Edwards & Cable, 2009). This condition is satisfied when the surface ridge (the first principal axis) has a slope (P¹¹) of one and an intercept (P¹⁰) of zero, representing the congruence line (Edwards, 2002; Edwards & Parry, 1993). It necessitates a nonlinear combination of regression coefficients derived from polynomial regression. We used 10,000 bootstrapped samples to find 95% confidence intervals for both the slope (P¹¹) and the intercept (P¹⁰), following the method described by Edwards and Cable (2009).

The final feature concerns the slope of the congruence line, determining whether the surface along this line is flat or not. This slope, denoted by r = R, must be primarily positive. This means that the dependent variable (LMX) is higher for congruence (at higher H-factor levels) compared with incongruence. We assessed this characteristic by analyzing the slope along the congruence line (where, for instance, r = R, and calculated as b₁ + b₂) to be both positive and significant. This process involved using methods for testing the linear combinations of regression coefficients as used in previous studies within the field of congruence research (Edwards & Cable, 2009; Edwards & Parry, 1993).

Additionally, we examined the asymmetrical incongruence effect, wherein LMX is of higher quality when the ratee’s H-factor is higher than the rater’s H-factor as opposed to when the rater’s H-factor is higher than the ratee’s H-factor. To assess this, we estimated the slope of the incongruence line (b₁ – b₂), which needed to be negative and significant to validate this feature (Matta et al., 2015). We performed an additional test to examine the asymmetric incongruence effect stated in Hypothesis 3. To illustrate that the dependent variable (LMX) is higher when the ratee H-factor is greater than the rater H-factor compared with when the rater H-factor is greater than the ratee H-factor, we computed the lateral shift quantity (Matta et al., 2015; Zhang et al., 2012). This quantity represents the magnitude and direction of a lateral shift along the incongruence line in the response surface and is calculated as [b₂ – b₁] ÷ [2 × (b₃ – b₄ + b₅)]. Hypothesis 3’s support is based on a negative lateral shift quantity. To evaluate the significance of the lateral shift quantity, we used 10,000 bootstrapped samples to construct a 95% confidence interval (Matta et al., 2015).

Mediation Test

We used the block variable method (Edwards & Cable, 2009) to look at how (in)congruence between honesty and humility affects ratee reactions, specifically behavior seeking feedback and behavior accepting feedback, through the mediating mechanism of LMX. The study took the five polynomial terms (H_ratee, H_rater, H_ratee², (H_ratee × H_rater), and H_rater²) and put them all into one block variable. This made a weighted linear composite that showed the effect of both congruence and incongruence as a single coefficient. Thereafter, we conducted a regression analysis, using the block variable as the independent variable and LMX as the dependent variable. We utilized the resulting regression coefficient as the path coefficient, which connected the congruence of the H-factor to the mediator (LMX). The path coefficient served as a basis for assessing the direct, indirect, and total effects of the mediator within the model. This study looked at how the H-factor between raters and ratees affected the outcome variables, specifically the ratees’ behavior when seeking feedback and their willingness to accept it. We computed the direct and indirect effects by multiplying the path coefficients. To test the indirect effects and bias-corrected confidence intervals, we used 10,000 samples by bootstrapping as outlined by Efron and Tibshirani (1994) and MacKinnon et al. (2004).

Interpretation of Key Findings

The following are our study’s key findings.

First, the results of Hypothesis 1 show that rater–ratee congruence in the H-factor was a strong predictor of LMX quality and feedback reactions, including behavior seeking and accepting feedback. We built on the similarity-attraction paradigm for finding supplementary fit. This approach helped to observe the ways in which dyadic congruence in the H-factor affects LMX quality and subsequent ratee reactions (feedback-seeking behavior and feedback acceptance). The results of this study support the similarity attraction theory (Byrne, 1962). However, the approach to evaluating similarity was different in terms of the theory’s applicability and generalizability beyond attitudinal similarity.

Second, this study shows how important it is to separate the different levels of H-factor because each level has important effects on relationship building (LMX) and how ratees react to performance feedback. The answer to Hypothesis 2 is that, yes, high–high H-factor congruence from the altruistic plane of HEXACO does produce higher quality LMX than low–low H-factor from the antagonistic plane of personality traits. This indicates that the rater–ratee dyads have been working together for years and have known each other well. As one can get to know someone’s honesty after long interactions, the rater–ratee dyads were able to differentiate between high– and low–H-factor partners.

Third, response surface analysis showed contrasts in cases in which rater–ratee pairs had different H-factor levels. Based on the LIFT theory (Sy, 2010) and the fact that the ratee is below the leader in the vertical dyad linkage of LMX (meaning that the ratee tries to improve the relationship with the leader), we came up with Hypothesis 3: LMX quality is lower when the rater H-factor is higher than the ratee H-factor. The results of our study support the view posited in Hypothesis 3. Specifically, it advocates that differences in the levels of H-factor are more detrimental to the formation of LMX when ratee honesty is lower than rater honesty than its reverse.

The study contributes to the fit literature by exploring the impact of rater–ratee honesty incongruence from LIFT’s perspective. The results indicate that leaders form preconceived traits about their followers and deliver high-quality sent roles to the followers who happen to possess such traits, sending low-quality sent roles to those who do not possess those preconceived traits. As LMX is initiated by leaders in the form of sent roles, a ratee who is high in honesty performs the ratee’s received roles honestly and fairly, which, in turn, forms a higher LMX. This study also suggests that, when rater honesty is greater than ratee honesty, the former is reluctant to extend high-quality sent roles to such a ratee, which is again attributable to LIFT (Sy, 2010). These results suggest that, when ratees adapt to the organization, they likely develop LMX based on role episodes (role taking, role making, and role routinization) rather than developing LMX to avoid uncertainty as may be the case in the context of newcomers.

Theoretical Implications

Our study’s findings are likely to add theoretical value to the current knowledge base in the following ways.

First, our study gives a way forward toward rater–ratee personality configurations for eliciting desired ratee feedback reactions. The usefulness of performance feedback is contingent upon its recipient’s reactions. Feedback reactions allow the feedback recipient to internalize the feedback. Therefore, understanding the underlying mechanism behind rater–ratee personality configurations and ratee feedback reactions is still under investigation. One of the major factors that generate positive feedback reactions is the ratee’s perception of the feedback source (De Stobbeleir et al., 2020; Katz et al., 2021; Son & Kim, 2016). As personality traits are associated with social interactions and perceptions (Dust et al., 2021; Zaccaro et al., 2018), they can affect organizational behavior and its outcomes.

Only a handful of previous studies focused on exploring the effects of ratee personality traits (the Big Five) on ratee feedback seeking (Krasman, 2010; Parker & Collins, 2010) and feedback acceptance (Bell & Arthur, 2008). Moreover, these studies ignored the rater’s personality and, therefore, precluded the possibility of observing rater–ratee personality configurations as contextual factors that influence the ratee feedback reactions. We suggest that the real picture of ratee feedback reactions is far more complex and depends on various levels of personality fit between the rater–ratee dyads. The findings of our study suggest that depending on the rater’s level of H-factor, a ratee’s high level of H-factor may not always engender positive ratee feedback reactions. Although counterintuitive, interestingly, when raters themselves were low in H-factor, ratees who had a compatible low level of H-factor still engendered positive reactions to feedback as compared with when they were incongruent in their H-factor. These findings highlight the importance of incorporating the personality configuration of rater–ratee dyads into the theoretical framework for a complete understanding of ratee feedback reactions.

Second, this study adds to the relevant body of scholarship by looking at how different personality types interact within the LIFT similarity-attraction paradigm and how these interactions affect the quality of LMX. It shows that the interactions between raters and ratees can have different effects on the role-taking and role-making stages of LMX. Even when rater and ratee are not compatible in a normatively positive way (for example, when rater and ratee have a low H-factor), high-quality LMX can still develop. This goes against what one might think. We highlighted that rater–ratee personality interplay leads to differing levels of LMX quality.

The study also shows an asymmetrical incongruence effect when LIFT and LMX formation are combined in the rater–ratee H-factor. This shows how important it is to have a high H-factor rater to lessen the possible negative effects of incongruence in the rater–ratee H-factor. Our findings demonstrate that the incongruence between a high H-factor rater and a low H-factor rater is more detrimental to LMX quality than between a low H-factor rater and a high H-factor rater. This complex pattern of effects suggests that the dyadic congruence of personality traits is predictive of LMX. This is important because the ratees receiving work support from their raters based on their LMX quality are likely to demonstrate superior task-related and extra-role behaviors (Gkorezis, 2015).

Third, we show that dyadic relationship quality (LMX) plays a part in linking (in)congruence between raters and ratees in the H-factor of personality to ratee reactions. This way, we propose dyadic exchange quality (aka LMX, derived from role theory) as one of the explanatory mechanisms for gaining the benefits proposed by person–supervisor fit. By combining the person–supervisor fit (in relation to the similarity-attraction paradigm and LIFT) with LMX, we can improve our understanding of how various poles of congruence and incongruence configurations influence ratee feedback reactions.

In plain words, it shows a variety of situations in which the supplementary fit and/or complementary fit in the rater–ratee dyad’s H-factor may help and/or hinder the two people from achieving a better exchange relationship, leading to varying levels of ratee feedback reactions. Not only did this study add to the body of research on the person–supervisor fit, but it also showed that comparing the effects of rater–ratee congruence and incongruence might not give a full picture of the subtle effects of high versus low congruence levels as well as the effects of asymmetrical incongruence. This suggests that a more complex and in-depth look at different levels of (in)congruence can give us more theoretical information about what causes LMX and person–supervisor fit.

Practical Implications

Recognizing the causes of extraneous variance in PAs and mitigating their effects can enhance the validity of performance ratings (Murphy & DeNisi, 2008). Rater–ratee personality configuration is one source of extraneous variance, and it has a strong influence on the rater–ratee dyadic relationship as well as ratee reactions to PA. Of most practical value is the finding that LMX quality enhances both ratee feedback seeking and feedback acceptance. Rater–ratee H-factor and the motives pertinent to their personalities have differential effects on LMX quality. Interestingly, our findings reveal that ratees low in H-factor may not always develop lower quality relationships with their raters or not generate shoddier feedback reactions as compared with their more honest peers.

In this study, the effects of congruence suggest that, in such situations in which both rater–ratee dyads have low levels of H-factor, a relatively high-quality LMX relationship may still be formed, and it may still engender positive feedback reactions provided the levels of H-factor in the dyad are compatible. Therefore, when the rater–ratee dyad has a low H-factor, organizations may not be able to improve ratee performance or elicit positive ratee reactions. Thus, organizations could mitigate the effects of personality configuration to some extent by holding the rater accountable for the ratings or the pervasive control mechanism (i.e., the rater’s justification of the ratings documented by the rater for the rater’s ratees as a portion of the rater’s performance evaluation).

Indeed, in work units, raters typically lack the opportunity to select individuals with similar personalities. Typically, the task of leading a work unit or team falls on raters. When relatively honest leaders are leading less honest followers (i.e., the most undesirable situation for LMX quality in the present study), we suggest regular interactions as well as mutual goal-setting techniques. Providing feedback in addition to developmental opportunities can mitigate the effects of incongruence to some extent and improve LMX quality.

Managerial efficacy can also have a significant impact on LMX quality. An environment of open communication, accountability, clear guidance, constructive feedback, and professional development platforms can significantly affect LMX and ratee feedback reactions (Eisenberger et al., 2019). Leadership development programs and mentorship opportunities play a significant role in mitigating the negative effects of personality traits, such as low H-factor on LMX development and ratee feedback reactions. Such initiatives serve as a means for leaders and members to enhance their self-awareness, interpersonal skills, and emotional intelligence, which, in turn, will generate high-quality LMX (Schyns, 2015) and positive feedback reactions. Similarly, by improving communication, conflict resolution, and empathy skills, management can create a more supportive environment, which can mitigate the negative effects of personality traits on LMX development (Eisenberger et al., 2019). Likewise, mentorship programs can provide support and guidance from experienced individuals, which can mitigate the negative effects of personality traits on relationship quality and feedback reactions.

Limitations and Future Research Directions

The current research design involves some strengths and data collected from different sources (e.g., raters and ratees reported their own levels of H-factor; ratees reported LMX and feedback reactions). However, we should consider the present study’s contribution in light of a few limitations.

First, we were interested in ratee reactions to PA feedback; that is why our interest was in ratee perceptions of LMX quality. The ratee reported measures of LMX quality may still suffer from the effects of common method variance. Rater-reported LMX quality relates closely to a lot of benefits that a ratee might enjoy (e.g., developmental opportunities, resources, protection, etc.). Both rater and ratee perceptions of LMX quality can have an influence on ratee feedback reactions because of their inherent dyadic relationship. Additionally, both raters and ratees reported the quality of LMX, which may lead to more solid conclusions about the role of LMX agreement in ratee feedback reactions.

Second, our research model solely focuses on ratee reactions. Because we only used ratee reaction as the ultimate criterion, it is still necessary to examine other PA outcomes. In other words, ratee reactions depend on individual differences in configuration and have a strong correlation with performance. On the other hand, we can also use personality (in)congruence and LMX formation to predict aspects of raters, such as their job performance (Deluga, 1998) and their perceived job performance (Bauer & Green, 1996).

Finally, we operationalized personality congruence from an external observer’s perspective (i.e., objective or actual congruence). However, the amount of subjective congruence in personality perceived by both members of the dyad could also impact LMX. Our results support our main claim that personality similarity is linked to LMX and the ratees’ responses to it. However, measuring personality similarity (perceived similarity) could add to our study’s findings. For example, such research could determine if subjective perceptions (perceived similarity) cause lower quality LMX in situations in which rater–ratee dyads diverge in honesty.

In countries such as Pakistan, the adoption of 360° performance appraisals remains limited, predominantly confined to selected private-sector organizations. The prevailing norm still leans heavily toward traditional performance evaluation systems within numerous organizations. Furthermore, the bureaucratic structures inherent in many high-context societies often mitigate the impact of complaints or whistleblowing, particularly when directed at leaders exhibiting low levels of honesty and humility. Additionally, antagonistic tendencies are a universal trait present in every individual, operating along a continuum. Significant violations often trigger formal complaints, but minor transgressions often escape scrutiny, allowing individuals with similar antagonistic traits to potentially exploit the system even in the developed world.

Future research directions could extend our study in a variety of ways. Future research can test the relationships by looking at LMX quality from both the rater’s and the ratee’s points of view. In addition, we can incorporate additional outcome variables, such as rater–ratee performance. It would be interesting to find out if personality (in)congruence between raters and ratees leads to LMX (dis)agreement between raters and ratees over time. This is because raters have the power to use socioemotional or transactional resources. Future research can also identify the boundary conditions for this relationship. One example is dyadic performance (Matta et al., 2015), which can lessen the impact of personality (in)congruence on LMX and ratee reactions. This is because personality differences may not be as important if dyadic performance is high. Also, it is likely that a combination of personality traits from the altruistic plane of HEXACO determines the quality of LMX relationships (for example, raters high in honesty and high in agreeableness vs. ratee low in honesty and high in agreeableness, etc.).