Commitment profiles for employee voice: dual target and dominant commitment mindsets

Every day, employees experience different problems at work. From organizational behavior research, the way an employee deals with problems at work is subject to their level of job satisfaction or organizational commitment (Grima & Glaymann, 2012; Withey & Cooper, 1989). Understanding employees’ reactions and/or intentions in problematic situations is vital since such understanding provides a chance to solve the problem and avoid damage in the long run (i.e., turnover rates), restoring the well-being of the organization (Hsiung, 2012; Lee & Varon, 2020; Li et al., 2018). For instance, employees’ responses to company practices that are perceived as wrong or problematic might differ because the employees have different concerns. One employee might be interested in the problem and try to find ways to solve it; another might ignore it and keep a silent or low profile. Company practices that are perceived as problematic, and dissatisfying working situations like unethical managerial behavior, are called malpractices. Various concepts explain the possible reactions to malpractices: voice behavior, exit, whistleblowing, and counterproductive behavior. The EVLN (exit, voice, loyalty, and neglect) model, which was originally developed from Hirschman’s (1970) model, provides information to explain employees’ different responses to problematic events in the workplace caused by unpleasant conditions (Hsiung & Yang, 2012; Lee & Varon, 2020).

The EVLN model proposes that employees’ belief that a situation cannot be improved might be an underlying reason for exit behavior. On the other hand, if the exit is not an option for some reason, employees might show loyalty and, instead of expressing their dissatisfaction, might wait for action from the company or their manager to improve the situation. Furthermore, some employees express voice behavior, which includes individual attempts to improve a negative situation rather than waiting for a solution from someone else (Farrell, 1983). Because employees have various motivations for their responses (Dyne et al., 2003), it is important that multiple underlying factors are investigated to improve the voice literature.

In this regard, organizational commitment, as one of the most crucial factors in terms of an employee’s response to unpleasant situations, has been well investigated using the variable-centered approach. This approach takes employees as people with a single averaged commitment, which makes them have a varying degree of each commitment type. The person-centered approach, on the other hand, is a more exploratory method of gaining an understanding of employee behavior. It takes each person as a unique case, which helps managers and organizations to understand differentiated responses as well as commitment types. The approach considers the possibility of multiple commitment levels for each person by using a tailor-made attitude, which allows researchers to gain detailed information on the variables. Along these lines, this paper is interesting as it will enable readers to understand the effect of dominant commitment profiles on voicing behavior. With the help of this approach, differentiated configurations for employee commitment might be observed (Meyer & Morin, 2016). Although the relationship between EVLN and commitment is well understood (Beatty et al., 2012; Burris et al., 2008; Johnson et al., 2009; Luchak, 2003), there is a gap in our knowledge of how individuals’ diverse commitment profiles are linked to different EVLN responses. Meyer and Herscovitch (2001) proposed theoretical “profiles of commitment”, which predict different behavioral outcomes. They also assert that employees are likely to develop different targets for their commitment, such as their organization, team, or supervisor. Based on the person-centered approach, this study unfolds the change in commitment profiles in response to malpractices according to the EVLN model.

There are two main gaps in the literature regarding the relationship between commitment and the EVLN responses. Different behavioral outcomes are found across different cultures. According to Hofstede’s cultural dimensions, high power distance cultures care less about accountability than individualistic cultures (Onyango, 2017). Even though diverse “person-centered” commitment profiles based on those of Meyer and Herscovitch (2001) were found in a high power distance culture (i.e., Turkey) when looking at turnover intentions and organizational citizenship behaviors (OCB) (i.e., altruism) (Wasti, 2005), differentiation among EVLN responses, as a form of OCB (Morrison, 2014), has not been studied in diverse contexts, and this is the first gap in the literature. Regarding cultural context, it is known that not only organizational commitment levels but also team commitment levels are crucial to understanding EVLN responses, especially when we consider high power distance cultures (Alang et al., 2020; Mellahi et al., 2010). For instance, higher levels of team commitment might influence employees’ feelings of closeness, and positive communication among group members may increase voice behavior and decrease exit and neglect (Estell & Davidson, 2019; Mellahi et al., 2010; Rai & Agarwal, 2019). Thus, there is a lack of studies in the EVLN literature showing how team commitment levels may contribute to organizational commitment, and this is the second gap in the literature that will be addressed by this study. Therefore, this study provides valuable contributions to the explanation of reactions toward malpractices at work, considering both organizational and team commitment profiles.

This study essentially makes three contributions to the existing literature. First, it answers the question of how commitment components create diverse profiles, with the organization and the team being included as targets. Secondly, it tests the implications of profiles for voice behaviors in the EVLN model by showing how commitment profiles lead to different responses to malpractice at work. Thirdly, the study tests the person-centered approach to commitment and the EVLN model in a key emerging country, Turkey, which contributes to the extant literature by extending the application of this approach. In addition to using the person-centered approach, this study helps to create a distinctive view of organizational commitment, particularly in Turkey. The Turkish context is characterized by a relatively high power distance, face-saving, and conflict-avoidance culture, which differentiates individuals from Turkey from those from other cultures in their responses to wrongful situations (Furrer et al., 2012). The Turkish culture reflects greater respect toward authority and less accountability in reporting or voicing wrongdoing (Jakubanecs et al., 2018). Thus, this study contributes to an understanding of the importance of both organizational and team commitment levels in voice behavior (Morrison, 2014) and shows that different levels of organizational and team commitment can be the basis for understanding employees’ reactions (Lee & Varon, 2020).

The previous literature has already covered the different effects of organizational and team commitment. However, studies that include the indirect effect of commitment on voice and turnover intentions are scarce. The study of Wombacher and Felfe (2017) contributes to the literature by testing the interplay of commitments by expanding the context. To reveal a “commitment profile”, it is important to study the interplay of commitments, and there is a lack of studies that involve the different targets (organization and team) as “multifoci”. More studies are needed to improve the predictions about the possible outcomes of employees’ responses. In this regard, it is important to investigate employees’ organizational commitment levels by creating distinct profiles, which is one of the major aims of this study. There are two main research questions about validating the person-centered approach in a different context: (1) how does the different dominance of commitments (with multiple foci) lead to different clustering? and (2) how do significant differences in the clusters reflect on voice behaviors (EVLN)?

Employee voice

There is a plethora of research on factors causing satisfaction/dissatisfaction and on the outcomes of dissatisfaction in terms of both individual and organizational factors. Another fruitful area of research regarding satisfaction is the behavioral response of employees in the case of dissatisfaction. There are various behavioral approaches to dissatisfaction (Farrell, 1983): (1) An employee immediately chooses withdrawal (e.g., exit) or is voluntarily absent. (2) When an employee confronts a problematic situation, s/he first starts to use their voice. If nothing changes, the employee remains patient. Finally, destructive reactions (e.g., neglect and then exit) are chosen if the problem continues to develop (Grima & Glaymann, 2012). (3) The individual’s response varies depending on the context. Farrell (1983) argues that because the behavioral responses of individuals vary, a structured model is needed. The EVLN typology offers a multidimensional model for clarifying the different responses to job dissatisfaction.

At this point, Hirschman (1970) emphasizes the importance of understanding the reason for an employee’s reaction to problematic events arising from the organization. The EVLN model suggests three possible responses to dissatisfaction. Exit is voluntarily leaving the company or quitting the job. Another type of exit would be transferring to another unit within the same company. The reason behind such behaviors is that the employee has no hope of a solution to the problematic condition. Voice is “speaking out and challenging the status quo with the intent of improving the situation” (LePine & Dyne, 1998, p. 853). Here, the employee has hope that the destructive situation can be repaired. Hirschman (1970) explains that an individual’s legitimate involvement in problem-solving is a kind of active voice that needs to arise before exit. The third response is loyalty, which means waiting and not taking any action, with the belief that the problem will eventually be solved. Not taking any action might mean keeping silent, even if the individual has an idea. One more response that Hirschman did not mention is neglect, which means disregarding the situation and not attending to the problem (Rusbult et al., 1982). The initial model constructed by Hirschman listed the possible responses to dissatisfaction as exit, voice, and loyalty, and then the model was extended by Hagedoorn et al. (1999) with the neglect response. The EVLN model predicts and explains how people may respond to different severe conditions (work dissatisfaction, psychological contract violation, etc.) (Itzkovich & Alt, 2015; Peng et al., 2016).

As Farrell (1983) argues, both loyalty and voice are constructive, but the former is passive, and the latter is active. On the other hand, exit and neglect are both destructive, with the first being passive and the second active. Other researchers supported these multidimensional axes and called this the EVLN model (Farrell & Rusbult, 1992; Rusbult et al., 1988). In the model, active means acting and dealing with the problem in a constructive (i.e., voice) or destructive (i.e., exit) way. Passiveness is defined as waiting (i.e., patience) or just ignoring the situation (i.e., neglect), without action. There are some contrary ends for each response in the model (Hsiung & Yang, 2012). For instance, contacting management is voice; leaving or considering leaving is exit; trusting management and doing nothing since the problem will be solved is about loyalty; and believing that complaining will not change anything, or ignoring the situation, is about neglect.

Loyalty is sometimes explained as a moderator between exit and voice, so loyal individuals prefer to quit less and voice more. Kolarska and Aldrich (1980) define loyalty as “keeping silent” when things are not going well. Based on its multiple meanings, Leck and Saunders (1992) emphasize the difference between attitude and behavior for loyalty and suggest changing the “loyalty” category to “patience” to emphasize the attitude-behavior distinction. Loyalty functions as an attitude when it is considered to be a moderator between exit and voice, but patience, on the other hand, implies a behavioral option (being supportive) (Withey & Cooper, 1989). Therefore, we will refer to “patience” in our research model.

While some empirical studies have validated the EVLN model, some contradictions exist concerning the terms discussed above. As Farrell (1983) and Hagedoorn et al. (1999) assert, a circumplex structure of responses differentiates the intentions and makes the boundaries between them more precise. Although there are sub-typologies of EVLN, there is no consistency in the literature that evaluates the reasons for these different responses. The current study is based on a validated version of the EVLN model of Hagedoorn et al. (1999) that uses patience, considerate voice, exit, and neglect to measure employees’ reactions to problematic situations.

There are individual, managerial, and organizational factors that may influence employee voice behaviors (Botero & Van Dyne, 2009; Morrison, 2011). Like many other attitudes, organizational commitment may also differentiate behavior. At this point, there is uncertainty about the sources of commitment that shape behavior. Different commitment types may pertain to different targets like organizations, supervisors, or teams, which are explained as commitment clusters by Meyer and Herscovitch (2001).

The type of attachment to the organization may determine how an employee reacts to unpleasant situations (Luchak, 2003). Also, among the responses, one decision can be a mutual substitute for another. For example, one who reacts to an issue with a constructive voice might be patient the next time or might prefer to neglect the situation and later think of exit as the last option. The mutual substitution among behavioral responses might be found in the type and foci of commitment (Johnson et al., 2009). Also, Mellahi et al. (2010) note that employees might be highly committed to their company but not to their team, or vice versa.

To put it differently, an employee may be affectively committed to his team but calculatedly committed to his organization. Therefore, the different targets of commitment might have different roles in the employee’s behavior. Organizational and team commitment together may correspond to different levels of commitment that might have a distinct impact on employee behaviors and work outcomes (Becker, 1992). Similarly, the various profiles of commitment might predispose employees to behave or react distinctively. Thus, in this study, an attempt is made to describe how variations in commitment profiles are associated with different EVLN responses.

Organizational commitment and exit

Withey and Cooper (1989) discuss the EVLN model in terms of viable or desirable alternatives for employees. In these terms, employees consider the cost and the benefit of their behavior when reacting to an unpleasant situation. When an employee has several alternatives outside the organization, staying in the company is less likely to be considered as an option because leaving has a low cost of leaving. Continuance commitment (CC) is based on the cost of the decision to leave or stay in the organization (Meyer & Allen, 1997). People with a high CC consider that positions are less available in other organizations, and they, therefore, remain in their current position because they need to. Hirschman (1970) explains loyalty as a product of economic factors that are linked to CC and asserts that people with severe financial concerns are less likely to choose the exit option. Therefore, the exit decision is the result of pull and push reasons. If the person has viable alternatives elsewhere and problematic experiences in his/her current organization, s/he will be pushed out of the organization. However, if the options are fewer, s/he is pulled to stay in the company. Moreover, affective commitment (AC) is an emotional attachment to the organization (Knoll & Dick, 2013). Employees stay because they want to and because they identify themselves with the company, which, in return, would like them to stay, so they are less likely to exit. Employees who are attached to their companies emotionally do not prefer the exit option (Burris et al., 2008; Luchak, 2003; Withey & Cooper, 1989). Based on the cognitive-affective-behavior triangle, the affective and continuance commitments of Meyer and Allen (1997) fall within the affective and cognitive branches of the triangle, but the normative commitment, which is also dismissed in this study, does not.

Based on the “fight or flight” theory of Mayes and Ganster (1988), individuals’ commitment types in terms of the cognitive-affective-behavior triangle imply a decision to stay or leave (Mayes & Ganster, 1988). The theory proposes that individuals under stress can exhibit aggressive (fight) or withdrawal (flight) behavior. Employees with more job alternatives outside and less commitment are likely to use flight responses in stressful conditions. By contrast, for an individual with fewer job alternatives and more emotional commitment, the flight response is less likely to be preferred. Thus, it can be assumed that employees with CC dominance perceive fewer opportunities outside and are less likely to exit and that employees with AC dominance are attached to the organization. Even though their reasons are different, employees having continuance and those having AC dominant profiles might show similar motives concerning exit. Moreover, it has been found that organizational commitment (OC) type is not the single predictor of exit behavior in non-western cultures because of conflict avoidance, so team commitment has an important influence in predicting EVLN (Mellahi et al., 2010). At this point, since the target is similar (organization), the literature is not able to allow diverse commitment profiles to be used to predict EVLN.

Organizational commitment and voice

For the voice option, there are opposing results arising from the intention to choose to use a voice. Managers in a high power distance culture do not accept subordinates’ different ideas and opinions easily. They perceive speaking up to be a protest against authority and try to restrain shared decision-making by using retribution (Mellahi et al., 2010). Therefore, in such cultures, employees may prefer not to speak even if there is an unfair situation (Park & Kim, 2016). Also, in collectivistic and high power distance cultures individuals rarely take responsibility for wrongdoing and react constructively (Onyango, 2017). However, the commitment profile might be a driving force to alter the situation.

Voice is used as a way of contributing to the effectiveness of the company. Individuals with dominant CC might hesitate to speak up in case they are punished by their managers. They tend to keep silent even if they have valuable opinions. Their reason for staying with the company is the high cost of leaving it; employees with CC are not motivated to contribute to the company’s issues (Mellahi et al., 2010). Since they are engaged with the cost of opportunities to move outside the organization, they do not put more effort into the organization (LePine & Dyne, 1998; Luchak, 2003).

On the other hand, affectively committed employees consider their company as part of their family and are likely to look for opportunities to make a contribution (Meyer & Allen, 1991, 1997). Moreover, employees with AC identify themselves with the organization, which predisposes them to become involved in critical issues related to the organization. They feel psychologically more engaged and present at work. Their involvement is related to their psychological state, which makes the voice option more likely (Knoll & Dick, 2013). Employees try to exert more effort on behalf of the organization because of their high emotional bond.

Furthermore, the “social exchange theory” holds that individuals try to give back when they receive valuable gain (Blau, 1986). AC provides employees with relational benefits that encourage them to reciprocate (Beatty et al., 2012). As Mellahi et al. (2010) and Burris et al. (2008) highlight, employees with dominant AC like to speak up even if the consequences (managers’ retribution) could be negative. The fight or flight theory (Mayes & Ganster, 1988) suggests that individuals who are satisfied with their current situation and are affectively committed to the organization will fight against problems. They will attempt to voice their concerns and improve the situation.

Additionally, employees may see these alternatives as an opportunity for development and recognition, which are noted to be predictors of OC (Cicekli & Kabasakal, 2017). They may put their individual interests second to the organizational ones. Therefore, individuals who are CC dominant will have different motivations for using voice behavior from those who are AC dominant. Even though one individual may be AC dominant and another CC dominant, a certain level of emotional attachment would be enough for them to show no distinction in voice behavior (Wasti, 2005). Therefore, there is a need to study different profiles and targets (i.e., organization, team).

Organizational commitment and neglect

The conservation of resource theory (COR), which is a motivational theory referring to individuals choosing first to protect their own resources (Gorgievski & Hobfoll, 2008), might be used to explain “passive” responses (i.e., neglect and patience). According to this theory, individuals focus more on resource loss than on resource gain. They immediately recognize a negative situation and try to find the factors that will inhibit their loss. Eventually, they adapt to the new context. Thus, it can be assumed that these inhibiting passive responses to unpleasant or problematic situations can be destructive (neglect) or constructive (patience), depending on the level of commitment.

In this sense, CC predisposes people to neglect unpleasant situations (Burris et al., 2008). As mentioned above, employees with high CC are less likely to voice and exit. Because they stay in the organization for economic reasons, they may not try to do their best and may prefer to neglect the situation. They might remain indifferent toward problems because their only purpose is to “save face” (i.e., to protect their resources) (Knoll & Dick, 2013). Individuals with high AC, on the other hand, are attached to their organization with emotional loyalty. They are likely to be involved in the decision-making for the improvement of the company and not allow the situation to worsen (Hagedoorn et al., 1999). Thus, it can be assumed that employees with emotional attachments are less likely to neglect a problem. The reasons behind CC and AC mean that they have different effects on neglect. In this sense, individuals with CC, who are those with the least desirable profiles (Meyer & Morin, 2016), may have more passive behaviors. Again, the need for the study of different profiles emerges here.

Organizational commitment and patience

Past research implies that “employees who are bound by their economic exchange are least likely to be good citizens” (Shore & Wayne, 1993, p. 779). Employees with high CC do not try to add value to the company when they experience difficulties or issues but save face by being patient (Knoll & Dick, 2013).

Regarding AC, Chen and Francesco (2000) and Thomas and Pekerti (2003) emphasize that if employees identify themselves with an organization, they want to show a loyal attitude towards that organization. Accordingly, affectively committed employees may show patience or become passive but “constructive” until, at some point, their voice is heard. Even though the reasons for their patience are entirely different for the different OC forms, employees with CC and those with AC are expected to show patience. Using a different lens, if an employee hesitates to share their opinion and is passive, this might be because of their disengagement (Weiss & Morrison, 2019). At this point, not only employees’ AC but also the organizational environment is crucial to prevent voices not being heard and employees from feeling they are isolated (Alang et al., 2020). Thus, it can be assumed that both types of OC are sufficient to lead to patience, independent of their dominance in a profile.

Team commitment and EVLN

Team commitment (TC) is an important factor in shaping employees’ reactions. Bishop et al. (2000) conceptualize a model according to which the impact of task interdependence depends on both organizational and team commitment. They figure out that if there is a higher level of interdependence, then TC is more salient in determining employees’ behavior as the employees become more aware of their contribution to their immediate workgroup.

On the one hand, individuals may hesitate to share their opinions, considering the importance of group values. Thus, it would be easier for an employee to articulate their voice in a western country since an individualistic culture does not put group interests ahead of those of individuals (Wagner, 1995). Nevertheless, in eastern countries, in which collectivistic values are predominant, people relate to the colleagues they work with directly (Hui et al., 2004). In collectivist cultures, people attach importance to team harmony and fulfill their duties with good intentions (Beatty et al., 2012; Mellahi et al., 2010; Singelis et al., 1995). In such cultures, the collective interest is seen as a shared value that makes members feel obliged to keep the group harmonious (Kwon & Farndale, 2020). Considering the social closeness of a team, it has recently been found that workplace friendship also prevents exit and neglect behaviors (Rai & Agarwal, 2019). Therefore, individuals who are members of a team are interested in the well-being and performance of the group when they experience dissatisfaction or an unpleasant situation (Beatty et al., 2012; Singelis et al., 1995). They try to support the team because of their concern about the outcome. They do not like to go astray, even if the situation seems problematic, because diverse opinions are seen as the cause of conflict.

Accordingly, individuals try to contribute to the team’s results with a positive attitude. Mellahi et al. (2010) also found a significantly negative association between TC and neglect. Estell and Davidson (2019) asserted that when TC is high, voice is used to disclose the team’s collective opinions, which makes them feel stronger. Therefore, it can be assumed that constructive reactions (i.e., being patient/silent at some points and using one’s voice in the interests of the group) will be seen in employees with high TC, rather than destructive ones (i.e., neglecting the unpleasant situation and leaving the team) (Bishop et al., 2000), when one considers close group relationships in conflict-avoidant settings. Due to the emotional and social connection within a team, it is assumed that employees with high TC tend to behave constructively, which contributes to their voicing.

Commitment profiles and EVLN

Managerial attempts and organizational factors such as feedback, salary, and equitable rewards have significant impacts on employees’ EVLN responses (Si & Li, 2012). In particular, OC levels, which are also associated with leadership attitudes and behaviors, are assumed to be one of the most important factors in employees’ EVLN responses (Luchak, 2003; Rice & Cotton-Nessler, 2022). Regarding OC levels, Meyer and Allen (1991) determined that there are three components of commitment: the affective, continuance, and normative components. According to this model, the affective component, which refers to an employee’s emotional attachment to their organization, is associated with positive outcomes such as job involvement, performance, and organizational citizenship behavior. Although all three components are related to lower rates of leaving, employees with CC stay in the organization because they need to, and employees with normative commitment remain because of their feelings of obligation (Allen & Meyer, 1990; Meyer et al., 2002; Meyer & Allen, 1991).

However, the person-centered approach underlines the fact that an employee may have different levels for each component, which creates distinct “profiles” of employee commitment styles, and it is crucial to create these profiles by investigating the antecedents and outcomes of the commitment styles (Meyer & Herscovitch, 2001). AC styles are the most favorable outcome, especially when they have lower levels of CC (Wasti, 2005).

OC types cannot be the single determinant of employee responses, and the impacts of TC levels cannot be underestimated, especially when considering the situation of high power distance societies (Mellahi et al., 2010). For instance, it is accepted that managers’ attitudes toward employees are a critical determinant of employees’ responses, especially when we consider employee voice. Lack of awareness by managers is assumed to be one of the reasons for employees’ lack of engagement and voicing, because they have feelings of being isolated (Alang et al., 2020). In this context, relational leadership and leader-member exchange, which provide reciprocal trust, respect, and loyalty, are accepted as important determinants of employee voice, and especially of team voice (Zhao et al., 2020).

Even if their managers have supportive attitudes, employees may show passive or destructive responses because of personal factors such as their perceived safety, their core beliefs, or assumptions like “It is wrong to speak up against authority.” In this regard, it has been emphasized that it is important to consider the power distance context in the examination of voice behavior (Hofstede, 2013; Morrison, 2011).

Based on this consistency argument, first, TC, which is the “collective interest” in a power distance population, is expected to be common among those showing constructive patience and voice (Estell & Davidson, 2019). From the commitment profile perspective (Meyer & Morin, 2016), AC and TC dominant employees are said to belong to the highly committed cluster. They are expected to have a more positive attitude and to act more constructively than those with other profiles. Lastly, in contrast to those with dominant profiles, those with low (sometimes known as non-committed) or weakly-committed profiles produce the least desirable outcomes, namely withdrawal or intention to quit (Meyer & Morin, 2016; Wasti, 2005). Since CC weakens the effect of other commitments, and the combined effect of different forms of commitment is limited (Wasti, 2005), it is necessary to compare “commitment profiles” across cultures, and, in particular, studies on different targets have been suggested (Meyer & Morin, 2016; Wasti, 2005).

Figure 1 summarizes the theoretical framework.

Theoretical framework

Full size image

Importance of the study

Since the person-centered approach allows us to validate multi-target commitment profiles and the EVLN relationship, it is an essential contribution to the literature. Without this clarification, it is problematic that (1) pure relationships between variables have different results in different contexts, and (2) multi-target commitment is neglected in the EVLN model. Even though Wasti (2005) depicted OC profiles in the same context (Turkey), the need for multiple foci is emphasized. Thus, we are engaged in investigating whether multifocal commitments are applicable to EVLN based on the same person-centered approach.

Multi-target commitments may mutually strengthen each other, and employees’ feelings of belongingness are expected to be increased where individuals have “consistent” opinions and attitudes. Similar multiple foci maximize behavior predictions (Beatty et al., 2012; Mellahi et al., 2010; Singelis et al., 1995). Therefore, AC toward the organization and TC toward the team have similar foci but different targets in this study. This association will result in stronger citizenship behavior and weaker turnover intention (Wombacher & Felfe, 2017). At this point, it is suitable to test the contribution of TC to OC in a high power distance context, namely Turkey, to assess the interrelationships of the commitments.

For this reason, this study uses the cluster analytic approach that supports the empirical assessment of Meyer and Herscovitch (2001). Accordingly, this study uses cluster analysis to investigate the implications for voice behaviors. It contributes to the validation of the model, as Wasti (2005) did by collecting data in Turkey. This study’s originality lies in its inclusion of OC and TC with their different targets, and provides validation for Wasti’s (2005) clusters by expanding the context. In Wasti’s (2005) study, no hypothesis was added for the purposes of exploration. However here, based on the previous findings, it is hypothesized that:

1. (1)

   there is a significance differences between the means of the clusters that emerge, and

2. (2)

   commitment varies across voice behaviors (EVLN) for the clusters that emerge.

Participants

A self-administered questionnaire was adopted as the survey instrument. The questionnaire was initially developed in English and was later translated into Turkish. Piloting of the questionnaire was undertaken with a sample of 60 MBA students with at least two years of work experience to improve its content validity by incorporating diverse perspectives and also to verify the wording of the items.

The required sample size for the study was determined by sensitivity power analysis calculated in G*power (Faul et al., 2009). Using input parameters of 0.80 power, α = 0.05, and small effect size (f² = 0.03), the calculation indicated that 264 participants were needed for the data analysis. The sampling frame for the survey was an alumni database of the researchers’ affiliated universities with approximately 12,000 members. From this database, 2,500 MBA students working in various industries were approached. A total of 518 usable questionnaires were obtained, representing an effective response rate of 20.7%. From the calculation, 518 participants were sufficient.

The average level of work experience of the participants is 5.6 years, and the mean age is 32. The respondents’ characteristics are shown in Table 1.

A test for non-response bias for the survey was conducted by comparing the first wave of survey responses to the last wave (Armstrong & Overton, 1977). Almost half of the surveys were randomly selected for each of the first and last waves of questionnaires received. Then, t-tests and chi-square analysis were applied to the scores across the main characteristics of the sample, such as demographic features and the sector of the organization. The test results indicated no significant difference between early and late respondents (p > .1) for any of the variables in the study. Hence, no response bias was evident.

Procedure

The survey questionnaire was shared with the participants via an online link (Google Forms, with the help of in-house support). The first page of the questionnaire provided informed consent and stated the aim of the research, as well as explained confidentiality. After agreeing to participate in the research, the participants entered the survey. All the participants took part voluntarily, and the confidentiality of the responses was assured by the researchers. The questions were presented in the same order for all participants. The measures included commitment, employee voice, and sociodemographic questions. Completing the survey took an average of 15 min. The dataset from the current study is deposited on the Open Science Framework (OSF) repository, https://osf.io/qc37t/, in compliance with open science practices and to ensure research reproducibility.

Instruments

Organizational and team commitment

Both AC (eight items) and CC (three items) were drawn from the work of Lee et al. (2001), based on the prior literature (Meyer & Allen, 1991). The respondents were asked to assess their level of emotional attachment (AC) and evaluate their cost of leaving (CC), based on five-point Likert scales ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). The construct reliabilities (α) of AC and CC were 0.86 and 0.76, respectively.

TC is composed of five items adapted from Porter et al. (1974). Again relying on five-point Likert scales, the respondents were asked to evaluate the interdependence in their teamwork. The reliability of TC (α) ranged from 0.82 to 0.93.

Employee voice behavior

The validated modified version of the EVLN scale of Hagedoorn et al. (1999) was used based on the prior literature (Rusbult et al., 1988). It measures the four main underlying dimensions (exit, voice, loyalty, and neglect) and is composed of 23 items. There are four items for exit (α = 0.92), nine items for (considerate) voice (α = 0.88), five items for loyalty/patience (α = 0.69), and five items for neglect (α = 0.79). All items were measured through five-point Likert-type scales.

Hypothetical scenarios are widely used in investigating unethical behavior (Randall & Gibson, 1991). In this study, participants were provided with three hypothetical scenarios about “malpractice” in which they believed that their manager/supervisor was incompetent and which they believed might harm the organization. Scenario 1 was, “When your management/supervisor’s actions negatively affect the company’s performance, you would…”. Scenario 2 was, “When your management/supervisor behaves unethically or illegally, you would…”. Scenario 3 was, “When your management/supervisor behaves badly towards you (e.g., stops your promotion, harasses you), you would…”. They then answered questions about the EVLN factors in the three scenarios. Since the different scenarios may give different results, the differences were checked first, and the average for the three scenarios for every item was calculated.

Common method bias (CMB)

In self-reporting surveys, there is a threat of measurement error arising from obtaining the predictor and the criterion scores from the same sample. This is referred to as CMB (Podsakoff et al., 2003). In this study, Harman’s single-factor test, which is a traditionally used and common technique to assess whether study variables can be explained by one underlying factor, was used to test CMB (Chang et al., 2010). The items for each variable of the present study were entered into a single-factor analysis. The results indicated that CMB was not a problem as the emerging single factor accounted for 20.38% of the total variance, well below the critical value of 50%. However, Harman’s test has been criticized as being insensitive, particularly when the number of variables is high (Lindell & Whitney, 2001; Podsakoff et al., 2012). The common latent factor (CLF) technique was therefore used in AMOS to test for CMB. For this method, a latent factor was added to the existing CFA model and connected to all the observed items in AMOS 27. The standardized regression weights of the CLF model were then subtracted from the CFA model, and their difference was measured. None of the factor scores had a higher subtraction value than 0.2. Accordingly, it was concluded that CMB was not a concern in this study.

Before the data were analyzed, reliability and validity analyses, using both invariance analysis and confirmatory factor analysis (CFA) via AMOS 27, were conducted. Table 2 shows the descriptive statistics and the correlations among the variables. There is no serious multicollinearity problem, as none of the correlations is above 0.80. Cluster and variance analyses were then conducted using SPSS 27.

Reliability and validity of constructs

Since Turkish versions of the instruments were used, exploratory factor analysis (EFA) was first conducted to examine the factor structure of the instrument and its internal reliability. Varimax rotation was conducted to produce a smaller set of distinct variables from the full set of items. After the removal of one item for CC that had a very low level for the Kaiser–Meyer–Olkin (KMO) test, six factors were produced that explained 54.2% of the variance, as shown in Table 3. All six factors make conceptual sense, with two of them capturing the commitment constructs of AC and CC and the remaining four coming from the EVLN subscales.

The constructs also had an acceptable level of reliability, ranging from 0.68 to 0.94 (Kline, 2011), as shown in Table 3. However, TC emerged as a distinct factor (KMO Measure of Sampling Adequacy = 0.854; Bartlett Test of Sphericity = 8686.09, df = 496, p < .01).

Confirmatory factor analysis (CFA)

Before running the measurement model, a series of CFAs (Table 4) were applied for the scales using AMOS 27 to determine whether the constructs in the study provided a satisfactory fit to the data, and to determine the discriminant and convergent validity of the scales and their items in this study. A five-factor model, where exit and neglect were merged into one factor as the “destructive” part and voice and patience into one factor as the “constructive” part, was also tested, following Akhtar et al. (2016). The results indicated that the seven-factor model had the best fit (χ²/df = 4.43, GFI = 0.75, CFI = 0.79, RMSEA = 0.08), and all other alternative models had a significantly worse fit when compared to the measurement model (Hu & Bentler, 1995).

Table 4 demonstrates that the goodness-of-fit indices are within generally acceptable ranges (Hair et al., 2010; Hu & Bentler, 1995; Schumacker & Lomax, 2004). The seven-factor model had the lowest value for χ²/df, indicating that this model is a better fitting model than the others. The value for the CMIN/df ratio for the seven-factor model is within the range of 0 − 5, where lower values indicate a better fit. The GFI and CFI values for the constructs are also satisfactory, as they are close to the value of 1.0, which would indicate a perfect fit. The results reveal the distinctive validity of the measures and do not suggest any significant CMB threat related to validity concerns.

To achieve more satisfactory fit values, inter-item covariances were included on the scales based on the modification indices shown in Table 4. In Table 5, the model fit values are shown after the model was modified with the excluded items and covariances. In the seven-factor model, after including the covariances, the CFI and RMSEA values presented good fit values (χ²/df = 2.96, GFI = 0.82, CFI = 0.88, RMSEA = 0.06) for the default model (Hair et al., 2010) as shown in Table 5.

Cluster analysis

The participants were clustered on the basis of their three commitment scores to distinguish the commitment profiles (clusters). Each commitment score was standardized and used for k-means cluster analysis (Hartigan, 1975). This non-hierarchical data analysis method uses an algorithm to divide individual cases into a predetermined number (k) of clusters based on their “commitment” scores, maximizing between-cluster differences while minimizing within-cluster variance. Two considerations led to the number of clusters chosen: theoretical interpretability and the need for observations in each cluster for generalizability. Ultimately, the final 4-cluster solution met the two criteria for further analysis.

The 4-cluster solution is depicted in Fig. 2, which has profiles for the means for the scales. Based on the work of Meyer and Herscovitch (2001), the profiles were named depending on their elevation levels (high or low bar) and scatter levels (weak for small differences across the bar). Accordingly, in this study, one commitment profile is characterized by below-average levels of AC and TC (n = 71). Since this profile has individuals scoring at least one standard deviation below the sample average for both commitment forms, and CC is near zero, this group is labeled “low committed”. The second group is labeled “weakly-committed”, since it consists of individuals who are rated slightly below the average level for all commitment forms and are close to each other in terms of scatter (n = 156). Such a profile is also called “neutral” by Wasti (2005). Another profile labeled “AC–TC dominant” (dually committed) consists of individuals whose levels of affective and team commitment are almost one standard deviation above the average but whose level of CC is below average (n = 184). Thus there is a “dual” target for this profile whose members are emotionally attached to both their team and their organization. The final profile was labeled “CC dominant” and consisted of individuals who scored at least one standard deviation above the average for CC but who had an average level of affective and team commitment (n = 107).

Profiles of commitment

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Outcomes of the profiles

First, univariate analysis of variance (ANOVA) was conducted to see whether the profiles differed in terms of voice behaviors. Table 6 depicts the F values and the means for each voice behavior by commitment profile. The results show that all the outcome variables differed significantly across the groups of profiles, and post hoc comparisons of means using Bonferroni t-tests highlighted many interesting observations. The results show that the low commitment group demonstrated more of the undesirable side of voice behaviors than the other groups. Specifically, this group had higher levels of exit intentions and neglect in response to malpractice at work, especially compared to the AC–TC dominant group.

On the other hand, the weakly-committed group lies between the low and dominant groups and provides a comparison to the AC–TC and CC dominant groups. This group showed voice behavior between the low and dominant groups. This group also had significantly lower patience and neglect than the CC dominant group, but no differences emerged with the AC–TC dominant group. Thus, for passive behaviors (i.e., patience and neglect), no significant differences emerged between the weakly-committed (neutrals) and AC–TC dominant (dual target) groups.

The AC–TC dominant group had lower exit intentions and lower neglect and patience in response to malpractice at work, especially when compared with the low commitment and CC dominant groups. Although the AC–TC dominant group showed significantly higher voice behavior than the other groups, this group had no significant difference from the CC dominant group for voice. Despite differences in the affective and team commitment levels, voice behavior did not vary significantly between the AC–TC and CC dominant groups. Thus, certain levels of affective and team commitment are enough for the voice behavior that accompanies low or high levels of CC not to contribute to the prediction of individual voice.

The CC dominant group had significantly higher passive behaviors (patience and neglect) than other groups. However, no significant differences emerged between the low commitment and CC dominant groups for neglect. Thus, even though low committed employees are prone to leave the organization, CC dominant ones prefer neglect, for which they are no different from low committed ones.

Discriminant function analysis with a stepwise format was followed for the “best set” of voice outcomes to discriminate among the four profiles, using cluster as the dependent variable. This explained 90% of the between-group variance (Wilks’ Λ = 0.83, χ² (12, n = 514) = 98.987, p < .001). When all the variables were considered simultaneously, they significantly discriminated between the four commitment profiles. Thus, both hypotheses are supported: there is a significance in the means of the clusters and commitment corresponds to varying EVLN across clusters.

General discussion

Commitment profiles

Based on the eight profiles of commitment by Meyer and Herscovitch (2001) and the application of this concept in Turkey with six profiles of commitment by Wasti (2005), parallel commitment profiles were found in this study except for the AC dominant and highly-committed profiles. One reason for the missing profiles is that AC and TC are not distinct concepts. Since TC is also an important variable for employee voice, the involvement of the team in voice behaviors and also as one of the targets for commitment makes these study findings valuable.

Outcomes of commitment profiles

The study distinguishes the effect of different commitment profiles in association with the EVLN responses. As predicted, those with low commitment and weakly committed profiles demonstrated the least favorable outcomes (more exit and passive behaviors). This result validates Wasti’s (2005) study and theoretically supports that of Meyer and Morin (2016).

The best profiles for voice were exhibited by those in the AC–TC dominant (dual commitment) and CC dominant groups, with no difference between these clusters, in which, to some degree, affective and team commitment are above the average. In the same way as the normative–continuance commitment, highly-committed, and affective–normative dominant groups have been found to support organizational change (Herscovitch & Meyer, 2002), affective and team commitment levels were found to contribute to “voice” behavior in this study, since they are similarly multifocal (the affective side of commitment is to several targets) (Morin et al., 2011). This study contributes by showing not only that the single OC level (Mellahi et al., 2010) explains voice behaviors, but also that dual commitment strongly explains voice in a high power distance context.

Besides, CC does not contribute to desirable voice behaviors. CC indeed contributes to passive behaviors, namely patience and neglect. Thus, the CC dominant profile is as poor as the low commitment profile regarding neglecting malpractice. Similarly, Wasti (2005) found that the CC dominant profile is no better than the non-committed profile for altruism. Not much is gained through CC; more turnover intentions and withdrawal behaviors are seen (Wasti, 2005). Therefore, pure CC can be detrimental and the least desirable profile (Meyer & Morin, 2016). Thus, this study contributes to demonstrating that it is no different from low commitment in different contexts as well.

Also, TC did not show a dominant profile: TC, like normative commitment, does not contribute above and beyond the level of AC (Wasti, 2005). Although high CC lowers the positive impact on others (Meyer & Herscovitch, 2001), and the high affective and normative and low continuance profile has better outcomes than the pure affective profile, the difference is minimal (Herscovitch & Meyer, 2002). Similarly, in this study, although the AC–TC dominant group has a higher mean voice than the CC dominant one, the difference was minimal. However, Wasti (2005) pointed out that understanding which levels of high CC weaken the positive impact of other commitments is important. In relation to this, this study proposes that a CC dominance contributes to more passive behaviors (patience and neglect) than an AC–TC dominance; that is, there is a weakening effect of CC on active behavior (voice). Since passive behaviors are common in high power distance contexts, this study contributes to the suggestion that CC dominance is one of the reasons behind them.

Finally, turnover intentions and altruistic behaviors have already been shown to be related to the three main commitment profiles (Wasti, 2005). This study contributes results on multifocal commitment to different targets (i.e., organization, team), which has been stated to be needed for commitment profile models (Meyer & Morin, 2016). It also studies not just focal behaviors (i.e., a turnover) but also other voluntary behaviors (i.e., voice behavior) as has been suggested (Wasti, 2005). The discriminant analysis revealed that voice behaviors distinguish the profiles. This study contributes to the idea that commitment is important for decreasing not just detrimental behaviors but also benevolent behaviors in diverse contexts.

Theoretical implications

Contributions

The results of this study are consistent with the current EVLN literature in explaining the diverse responses, and this person-centered approach has implications for managers in the use of individualized management styles. Understanding the different targets of commitment when predicting employees’ responses to managerial-level malpractice provides a useful contribution to the extant literature on commitment, which is a central part of voice-based “dissatisfaction” literature (Grima & Glaymann, 2012; Withey & Cooper, 1989). This study makes an original contribution to the indicators of the EVLN model by using a person-centered approach to commitment. There is not just a linear relationship with commitment, but there is also a commitment to multiple targets in diverse contexts. Thus, the person-centered approach is cross-validated for applying commitment in a different context. Rather than average commitment level (variable-centered) per individual, individuals may show differentiation in their commitment levels toward different targets (commitment profiles).

This study provides essential input for future studies by exploring this approach for multifocal commitment profiles. Also, the cluster analysis method allows for inductive reasoning on commitment profiles which can be tested out for future path analysis. In this way, future studies may be compared using other organization-based variables with commitment profiles. Further research should be carried out to study how situational variables such as trust are integrated with multifocal commitments.

Employee voice

The study’s findings indicate that AC–TC dominant profiles are different in terms of voice, while CC dominance cannot be distinguished from AC–TC dominance since it includes a certain level of affective and team commitment. Employees who are emotionally attached to their organizations and their teams are more likely to contribute than those whose commitment is low or weak. AC is the type of organizational commitment that highlights individuals’ loyalty to their organization (Meyer & Allen, 1997). TC is found to be another critical factor in shaping individuals’ reactions. Employees with CC have no desire to contribute to solving problematic events since they are preoccupied with the cost of speaking out.

Considering Meyer and Allen’s (1997) commitment theory, the findings of this study reveal no clear differentiation between types of commitment when they are considered with outcomes. Instead, the theoretical contribution is that a certain level of multifocal commitment overcomes the negative effect of pure CC for voicing. Based on the idea of multi-target commitment (Wombacher & Felfe, 2017), this study contributes to the interrelation between the team and organizational commitment in the power distance context regarding the constructive aspects of voice. Thus, multi-target commitment profiles need to be considered in relation to voicing issues at work for future theories.

Passive voices (patience and neglect)

Another contribution is that CC dominant profiles are different in terms of passive behaviors (patience and neglect). Employees who are dominant in CC contribute to passive behaviors more than those with other profiles. Patience is found to be the typical response for those with OC (affective and continuance) in the case of malpractice. However, the motivations for those with different commitment types are different: (1) fear of loss for CC (Gorgievski & Hobfoll, 2008) and (2) relational benefit/gain for AC (Burris et al., 2008; Mellahi et al., 2010). Thus, patience is relevant and common between commitment types in a power distance setting. Patience may serve as a break before “active” responses since loyalty is embedded in a culture in which employees expect that problems will eventually be solved and keep silent to a certain point (Hirschman, 1970). Thus, one contribution of this study is that those with continuance dominant profiles are inclined to act passively in the first instance and that being afraid to lose is not an appropriate profile for voicing issues. Even though patience is considered to be constructive by its nature, it is not active behavior. Accordingly, those with affective–team dominant profiles prefer to act upon malpractice.

Additionally, those with continuance dominant profiles tend to neglect more and cannot be differentiated from those with low commitment profiles. On the other hand, weakly-committed and affective–team dominant committed employees prefer not to neglect problems. This study shows that employees who are CC dominant do not want to be involved in problematic or solution-focused situations in order to protect their existing resources, which is in line with the key assumptions of the COR theory. Instead of offering or exploring solutions, employees are predisposed to neglect (Knoll & Dick, 2013). The study also shows that CC dominant employees are as likely as low committed employees to neglect the problems at hand. This bystander effect may result in collective silence when a dilemma is faced by a team or organization member (Hussain et al., 2018). Based on the active nature of voice, a standard by managers to differentiate individuals in terms of being authentic contributors can be considered for attribution to commitment in future theories.

Intention to quit (exit)

Affectively committed employees (AC–TC dominant) can be differentiated from low committed employees and show less exit behavior. They are likely to stay because of the affective connection that they have with both their team and their organization. Affectively committed employees invest more in their organization, and this study demonstrates that they, therefore, prefer to remain rather than exit in order to realize the outcome of their investments (Withey & Cooper, 1989).

Practical implications

One of the main contributions of this study is that immediate workgroup (team) commitment is a necessary base for voice. As mentioned above, eastern cultures are more focused on interpersonal harmony and emphasize emotional self-control, emotional restraint, and emotional suppression more than western cultures. As also put forward by Triandis (1994), people exhibit a strong attachment to their groups and give high importance to group harmony. They fulfill their duties and work hard for the sake of their team. In such a culture, collective interest is seen as a shared value that makes members feel obliged to keep the group harmonious. When TC is high, voice is used to disclose the team members’ collective opinion, which makes them feel stronger.

The results of this study have an important implication for organizations. Because of the decreased loyalty levels resulting from remote working during the Covid-19 pandemic, commitment might empower collective identity and performance if managers pay attention to team dynamics. Trust is one of the most significant determinants of the subordinate–supervisor relationship. It can be built by the constructive attitudes of managers toward their employees. Managers who focus on harmony within their units or teams by emphasizing involvement can boost commitment despite remote working or physical distance, and it is recommended that they do this by being aware of themselves in order to improve their self-leadership skills. In that way, despite physical distance, relationships between their subordinates can be enriched.

Another contribution is that different but similar commitment targets contribute to voice. Considering the contextual basis mentioned above, employees are motivated first by group success. Otherwise, they are considered disengaged or less community-spirited. Thus, employees who speak up are appreciated and seen as helpful by the immediate workgroup. Also, they will be more psychologically safe if they speak out for the group’s well-being (Hussain et al., 2018). Therefore, an affective organization and a team of committed employees try to improve their unit’s performance by offering constructive opinions and change-oriented ideas. Their close relations with both the organization and the team (relational benefits) make them invest more, a finding which is in line with the premises of social exchange theory (Beatty et al., 2012). They fight against problems by voicing their issues (in accordance with the fight or flight theory) (Mayes & Ganster, 1988). For this reason, maintaining exchanges between the team and its members is one way to extend the quality of voice behavior (Shih & Wijaya, 2017). Employees support the team when they are uneasy about an outcome. Therefore, their attitude towards problematic events is positive and constructive for the sake of group well-being.

The managerial implications of this result can be explained by the managers’ attitude towards employee voice. If managers welcome opinions that are used by the organization, they will not only reinforce the spokesperson but also encourage group identity. According to a Gallup report (2022), during the Covid-19 period between 2019 and 2021, employees who felt listened to by their managers displayed more loyalty than those who felt unheard. These results are significant to encourage managers to care for employee voice in identifying loyalty and performance.

Finally, this study contributes to the idea that employees need to be dually committed to both their organization and their team for more voice and less exit orientation. Even continuance dominant profiles have a certain level of AC to both the team and the organization. The opening of both organizational and team communication channels is important in such a power distance context (Erjavec et al., 2018). Managers need to recognize dual commitment (Lin et al., 2019) because employees’ sense of power in voice surfaces with dual commitment. Also, leadership integrity may facilitate voicing in unethical situations when both team and corporate values are involved (Peng & Wei, 2020), and it may decrease turnover intentions (Ali et al., 2020). It is suggested that, from an HR practices perspective, high-commitment work systems (HCWS) integrate more voice through increasing psychological safety and voice efficacy (Unler & Caliskan, 2019; Zhang et al., 2019). The main aim is emotional attachment and trust in the organization overall. This perspective contributes to the idea that contextual dependence on the voice enhances the communication skills of employees and an inclusive climate.

Limitations and future research

The study is not without limitations. First, it focuses on voice from the perspective of the actors; voice can be examined from different perspectives to eliminate self-serving biases by, for example, asking supervisors to rate voice behavior. Although Harman’s single-factor test and common latent factor technique indicated that the present study is free from CMB, multi-source data collection or using time-lagged data could be an alternative to single-source data collection. Since the data is self-reported, other objective indicators like organizational cynicism (Grima & Glaymann, 2012; Naus et al., 2007) may give a more complete understanding of employees’ reactions to distressing situations at work and increase the validity of this study.

The cluster analysis in our data did not reveal some of the profiles that were found by Wasti (2005), like the highly-committed or affective dominant profiles. However, what is revealed as clusters are theoretically comparable and the findings contribute to a different context. For further studies, it is suggested that the commitment profiles found here are tested for multigroup comparison in path models to add to the voice behavior literature. This would reveal not just preferable profiles but also “how multi-target commitments contribute to each other” in diverse settings.

Even though the main aim of the study is to expand on the relationship between commitment profiles and EVLN responses in a different context, the scenarios given in the survey (a case in which the company’s performance is negatively affected, a case of unethical behavior, and a case of bad behavior towards the employee) raise more questions. The ethical sensitivity of employees and leaders can be a control variable for future research. “Is it the belief that the organization lacks integrity or the employees’ loss of trust in the leaders that lead to an adverse effect?” is an important question. In future research, the link with leadership types will extend the horizon of practical implications. For further studies, the question “what kind of leadership do these voice-prone individuals expect?” should be answered to reveal local profiles for voicing in diverse contexts.

Finally, this study collects data from employees operating in a wide variety of sectors and at various managerial levels, and this provides a useful contribution to the extant literature. However, TC is self-reported here, which limits the inferences. Collecting data about real teams (i.e., whether they are loose or tight teams, whether they work together regularly or temporarily by project) and specifying which team the respondents should think about (in order to differentiate between organizational and team commitment) should be considered for further analysis.

Conclusion

In summary, this study puts commitment profiles into the discussion on employee voice and contributes results on how immediate workgroups may have different voice reactions depending on the social context. The study shows that team commitment is common ground for a constructive voice, and that this is built upon collective well-being. Affective–team commitment dominant employees have the most active voice behavior, and continuance commitment dominant employees have the most passive behaviors. The study also exemplifies the least desirable employee commitment profiles to explain destructive voice behaviors. The study provides new insights into commitment profiles and targets while explaining diverse voice behaviors in case of malpractice and has practical and theoretical implications.