Introduction

Growing consensus about the significance of workplace proactivity for organizations’ success has transformed our understanding of the organization dynamics in the past decades (Bateman & Crant, 1993; Crant & Bateman, 2000). Employees are expected to be more proactive than ever in the current turbulent business environment. Put forward by Bateman & Crant (1993), proactive personality is defined as a stable dispositional tendency, employees with which actively take initiatives to incite environment changes. Proactive employees are consistently predicted to demonstrate higher job performance (Fuller & Marler, 2009; Han, Harold, & Cheong et al., 2019), more helping behavior (Spitzmuller & van Dyne, 2013; Sun & van Emmerik, 2015), increasing innovative behavior (Horng, Tsai, Yang, Liu, & Hu et al., 2016), to generate greater job satisfaction (Li, Liang, & Crant et al., 2010), and to initiatively shape leaders’ behaviors (Han et al., 2019; Lam, Lee, Taylor, & Zhao et al., 2018). Moreover, evidence showed that those employees also contributed to higher organizational performance (Li, Harris, Boswell, & Xie et al., 2011; Thompson, 2005).

Despite the significance of proactive personality in promoting personal success and organizational effectiveness, relatively scarce research has investigated whether proactive employees are capable of accumulating leadership capacities (Seibert, Sargent, Kraimer, & Kiazad et al., 2017) such as promotability. This is a problematic omission since leadership development is perceived as the number one “human capital” priority for practitioners and a proliferated concern for scholars (e.g., Avolio, Reicherd, Hannah, Walumbwa, & Chan et al., 2009; Day, Fleenor, Atwater, Sturm, & McKee et al., 2014; Galli & Muller-Stewens, 2012). Hence, we extend previous research by linking proactive personality to promotability to figure out whether proactive employees are more likely to stand out among team members. Additionally, employees with proactive personality are prone to take initiatives to contribute, and may actively look for opportunities to improve the organization’s situation (Kim, Van Dyne, Kamdar, & Johnson et al., 2013), resulting in more taking charge behaviors. Such voluntary and constructive efforts that help change working conditions are functional in enhancing employees’ evaluations in organizations (Moon, Kamdar, Mayer, & Takeuchi et al., 2008). Thus, we further address the above issue by testing the mechanism of taking charge to test the mediating role of proactive work behaviors in the relationship of proactive personality with job outcomes (Spitzmuller et al., 2015).

Most importantly, we assume proactive employees may not get high possibilities to be promoted in all work conditions and whether they are the “best employees” may be context specific. Emerging research has employed a person-by-situation interaction approach to examine how environmental factors interact with personality to influence individual behaviors (Mccormick, Guay, Colbert, & Stewart et al., 2019; Schmidt, Ogunfowora, & Bourdage et al., 2012). Since employees do not operate in a social vacuum, the dynamics and interactions within their teams have crucial influence on their behaviors. Additionally, research has emphasized on the significant role of team in promoting employee proactive behaviors (Ehrhart, 2004; George, 1991; Somech, & Khotaba, 2017). Therefore, we respond to the cohort of literature by examining how a situational team context - task structure - interacts with proactive personality to influence employee taking charge and promotability (Li et al., 2010).

Task structure refers to “the sum total of ways in which labor is divided into distinct tasks and coordination is achieved among them” (Mintzberg, 1979; p. 2). It is important because it provides a shared perception of policies and practices that an organization rewards, supports and expects (Schneider & Reichers, 1983), which shape decision-making, cooperation and information in the team (Burns & Stalker, 1961). Drawing upon trait activation theory, team members’ personalities are enacted only under relevant situations, as those situations provide cues about whether personality expression is possible or pertinent (Tett & Burnett, 2003). Accordingly, task structure, as one of the most ubiquitous aspects of organizations (Clegg & Hardy, 1996), may exert “press” to team members on whether they can act in a trait-related way (Yang, Qian, Tang, & Zhang et al., 2016) especially in a team context. As such, we incorporate task structure as one potential situational cue that helps determine to what extend team members may benefit from proactive personality under dynamic team conditions.

In summary, our study contributes to proactive personality literature in three ways. First, we showed the boundary condition under which proactive employees may feel their “hands are fold”. Building on trait activation theory, we incorporate task structure into explanations of proactive personality to better understand how different organizational contexts interact with personality to influence employee outcomes. Although prior researchers have put efforts in investigating the interaction between individual and situational factors (e.g., Li et al., 2010), most of which focused on examining proactive personality at a single level (e.g., Erdogan & Bauer, 2005; Zhang, Wang, & Shi et al., 2012). Research regarding whether the collective characteristics of a work group at a high level (e.g., task structure) play a role in determining the effects of proactive personality remains inconclusive and underdeveloped. Hence, our research incorporates task structure as a moderator to investigate the odds that proactive personality can be expressed by locating it within different teams. Second, by identifying employee promotability as one outcome of proactive personality, our research extends previous knowledge about proactive personality in the staffing literature by showing the positive effects of proactive employees in their career development. Third, in the process of testing taking charge as a mediator, our study enhances understandings of how employees’ proactivity translates into good career outcomes. Figure 1 depicts our theoretical model.

Fig. 1
figure 1

Proposed theoretical model

Note. T1E = variables rated by employees at Time 1; T2E = variables rated by employees at Time 2, 1 month after Time 1; T3L = variables rated by leaders at Time 3, 2 months after Time 1

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Theoretical background and hypotheses

Proactive personality and promotability

Promotability refers to the ability of an employee to be rewarded by an organization for a deserved promotion (Shore, Barksdale, & Shore et al., 1995), and it demonstrates one’s projected performance in a higher leadership role (London & Stumpf, 1983). The antecedents and processes of promotabiltiy deserve more attention in the managerial studies because promotability is well proved as a strong predictor of individual success (Wayne, Liden, & Graf et al., 1999) and has profound implications for employee retention literature (Chan, Mai, Kuok, & Kong, 2016).

We propose proactive personality will be beneficial for an employee to be promoted. On one hand, team members with proactive personality maintain great inner desires to seek opportunities and emphasis persistence even facing with difficulties (Frese & Fay, 2001). Their inner desires to make great difference (Spitzmuller, Sin, Howe, & Fatimah at al., 2015) increase the possibility of making achievements in working conditions, which increases the possibilities for them to get promoted. On the other hand, proactive team members put much efforts to change environment around them in order to improve problematic organizational policies and procedures (Crant, 2000). By doing so, they build a proper situation for themselves to generate better performance (Chan, 2006). Consequently, their better performance helps achieve a higher evaluation for promoting from their leaders (Thompson, 2005). Indeed, investigations from previous literature have shown employees with proactive personality are more likely to achieve career success both subjectively and objectively (Converse, Pathak, DePaul-Haddock, Gotlib, Merbedone et al., 2012; Seibert et al., 1999; van den Born & van Witteloostuijn, 2013). Based on these evidences, we propose that employee proactive personality will have a positive effect on promotability:

Hypothesis 1

Employee proactive personality is positively related to promotability.

The mediating role of taking charge behavior

Taking charge is a discretionary behavior which usually challenges the status quo and makes constructive changes toward the organization (Morrison & Phelps, 1999). Different from other types of proactive behaviors (e.g., voice), it stresses on both identifying problems and opportunities for organizational changes and acting on the problems to improve organizational procedures and policies (Fuller, Marler, & Hester et al., 2012). By definition, employees’ proactive personality implies an inclination to act proactively if there are opportunities to do so. As a special aspect of the general concept of proactive behavior, it is rational to anticipate that proactive team members are likely to generate more taking charge behaviors.

Specifically, proactive team members possess a high possibility of success due to their characteristics of sticking to solving the problems until they conquer them (Crant, 2000). Such high anticipation about success removes their worries about risks (e.g., disagreements among team members), promoting them to engage in more taking charge behaviors. Furthermore, employees with proactive personality have the belief and strong inner motivation that they are obligated to bring about constructive changes for the good of the organization (Chen & Kao, 2014). This motivation makes them feel responsible to take charge. More taking charge behaviors, in turn, lead to higher promotability. Team members engaging in taking charge put voluntary and constructive efforts to make changes in environment and improve their own work effectiveness (Morrison & Phelps, 1999). Hence, they are able to receive more recognition and credit from their leaders and peers, at the same time, facing with fewer organizational constraints (Zhang, Waldman, & Wang et al., 2012), which in turn leads to higher promotability. Taken together, the rationales developed so far imply an indirect relationship. Therefore, we propose:

Hypothesis 2

Taking charge behavior mediates the relationship between proactive personality and promotability.

The moderating role of task structure

According to the principle of trait activation theory, the expression of personalities depends on the strength of situations or cues (Tett & Burnett, 2003). Specifically, strong situations constrain the expression of individuals’ differences by dictating acceptable behaviors. On the contrary, weak situations provide freedom for personality expression because there are no specific expectations about how to behave (Mischel, 1977). Accordingly, situational strength may exert great influences on the effects of proactive personality. As one of the most ubiquitous aspects of an organization (Clegg & Hardy, 1996), task structure shapes the strength of situations and conditions where employees are embedded. Indeed, structure has been shown to exert influences on a wide range of outcomes on individual, team, and organizational level (e.g., Ambrose, Schminke, & Mayer et al., 2013; Dragoni & Kuenzi, 2012; Hollenbeck et al., 2002). Thus, based on trait activation theory, we anticipate task structure may determine the extent to which employee proactive personality can be expressed.

Defined as the ways an organization or its teams divide the work labor into different tasks (Mintzberg, 1979), task structure is the basic feature of an organization. It includes – but is not limited to – power and reporting relationships restricted by organizational charts, behaviors required by organizational rules, patterns of decision-making and communications, and formal or informal relationship between organizational members (Donaldson, 1996). Compared to job autonomy, which refers to the extent to which individuals have discretion over their work, such as scheduling their work, and determining their work procedures (Parker, Axtell, & Turner et al., 2001), task structure describes a unite-level characteristic that shapes various aspects of employees’ attitudes and behaviors. By contrast, job autonomy reflects a job-level characteristic that directly and merely influences employee independence toward their work. Since trait activation theory posits on the facilitative/constraining effects of general working situations, we focus on a team-level characteristic that may exert greater influences on the expressions of employees’ personalities, namely task structure. Meanwhile, task structure has been proved to provide boundary conditions for a variety of individual differences (e.g., goal orientation, Dragoni & Kuenzi, 2012) and perceptions (e.g., perceptions of organizational politics, Yang, 2017).

Task structure is described as mechanistic structure and organic structure. Mechanistic structure refers to highly formalized, centralized structures, characterized by high levels of task differentiation, formal rules and procedures at work and strict job descriptions to obey (Burns & Stalker, 1961). In mechanistic structure, behaviors are governed by clear rules and policies. It reduces opportunities for team members and limits their freedom by emphasizing on hierarchy and command chain (Dickson, Resick, & Hanges et al., 2006) when operating in a team. Therefore, mechanistic structure, by definition, provides a strong situation for team members. Conversely, organic structure refers to a more fluid structure, characterized by decentralized decision making, few formal rules and relying more on employees themselves (Burns & Stalker, 1961). In organic structure, behaviors are decided by a shared set of goals and values rather than by formal rules and policies. It provides individuals freedom to act according to their own wills when performing in the team context. Thus, organic structure, by definition, provides a weak team context. Based on trait activation theory, we propose that organic structure (weak situation) will magnify the expression of employee proactive personality due to the informal rule and decentralized structure, which in turn results in more taking charge behaviors.

Furthermore, trait activation theory posits that in order to behave in a trait-like way, individuals should be embedded in situations that are relevant to and suitable for a given trait (Tett & Burnett, 2003). For example, a proactive employee is free of performing proactively only under relevant situations or social cues that encourage or welcome personal initiatives. Specifically, in a team that works organically characterized by freedom and decentralization, proactive employees will find it easier and more comfortable to display their proactivity. By contrast, when working in a team with mechanistic task structure that highlighting strict policies and procedures, they tend to behave cautiously even though they are proactive in nature. Taken together, we propose:

Hypothesis 3

The relationship between proactive personality and employee taking charge behavior will be moderated by task structure, such that the relationship will be stronger when task structure is more organic.

Considering the moderating role of task structure on the relationship between proactive personality and taking charge behavior and the mediation role of taking charge behavior on the positive link between proactive personality and promotability, we propose a moderated mediation model (Preacher, Rucker, & Hayes et al., 2007). Specifically, we propose the indirect relationship between proactive personality and promotability via taking charge behavior may depend on task structure, such that the indirect relationship will be strengthened when task structure is more organic. Therefore, we propose:

Hypothesis 4

The indirect relationship between proactive personality and promotability via taking charge behavior is moderated by task structure, such that the indirect relationship will be stronger when the team operates in an organic structure as opposed to a mechanistic structure.

Method

Participants and procedure

Participants were employees and their direct supervisors drawn from two information and technology (IT) companies in China. All the investigation procedures were approved by the university ethical committee. Teams surveyed in the current research came from different departments of an organization and were responsible for different types of tasks. Moreover, we selected teams required for proactivity, for example, teams from sales department where proactivity may be linked to their performance. Among these teams, interdependence existed among team members, since they were responsible for same tasks. At the same time, each team can decide their own task structure (to ensure there were variations on task structure between teams), even though teams from the same company were working for the same organizational goal. Finally, to effectively evaluate employee promotability, team leaders surveyed should be authorized to evaluate the employees’ performance in their teams and determine their promotions.

With strong support from the management teams, we collected data by paper-and-pencil surveys at three-time points separated by 1 month from both employees and their direct supervisors to minimize the concern of common method variance. Before data collection, we obtained a list of the last four digits of team members’ personal phone numbers with the support of human resource departments. During data collection, participants were asked to report the last four digits of their phone numbers for the purpose of match among three time points and identification of their team membership. Further, participation was voluntary and participants were assured the confidentiality of their responses throughout the whole process. At Time 1, employees responded to measures of demographic statistics (including gender, age, education and tenure), proactive personality and task structure. One month later, at Time 2, employees were asked to rate their taking charge behaviors. Two months later, supervisors rated promotability for each employee in their work teams.

Due to the Covid-19 and Chinese policy of telecommuting when individuals were with high risk to be infected, our sample size was relatively small. Specifically, we received a total of 237 responses out of 308 employee surveys distributed (76.9%) and 31 supervisor responses out of 36 surveys (86.1%). Five teams were eliminated from the sample because these teams did not have at least three employees or a supervisor. Moreover, in order to avoid the influence of team composition, we selected teams that had basically the same characteristics in terms of gender, age, and profession compositions among team members. Our final sample comprised 229 employees and 26 supervisors from 26 work teams in two organizations after matching across the three waves of data over three months, with 12 teams from one organization and 14 teams from the other. Among the 229 employees, 66.4% were male, and most of the employees were in age between 25 and 35 (74.7%). In addition, 82.9% received a college education, 55% have worked for more than three years. The number of employees in each team range from 3 to 19, and the average team size was 8.81. Since employees within each team worked for the same task and in the common workplace, they met face to face in every working day.

Measures

English items of each full version questionnaires were translated into Chinese following translation-back-translation procedure (Brislin, 1986). All variables were measured using 5-point Likert-type scales with 1 = strongly disagree and 5 = strongly agree.

Proactive personality We used a total of 10 items from Seibert et al. (1999)’s scale to measure employee proactive personality. A sample item was “I am constantly on the lookout for new ways to improve my life”. Cronbach’s alpha for the current research was 0.79.

Taking charge behavior We used a total of 10-item scale from Morrison & Phelps (1999) to measure employee taking charge behavior. A sample item was “I often try to bring about improved procedures for the team or department”. Cronbach’s alpha was 0.88.

Task structure Following Covin & Slevin (1989) and Slevin & Covin (1997), we used Khandwalla’s (1996/1997) seven-item scale to measure task structure. Participants rated on the paired statements about the degree to which their work teams reflected organic or mechanistic characteristics. A sample item was “Loose informal control, heavy dependence on informal relationships and the norm of cooperation or getting things done” versus “Tight formal control of most operations by means of sophisticated control and information systems”. Items were scored such that higher values represented a more mechanistic structure. Cronbach’s alpha was 0.76 for this scale.

Promotability We used supervisor-rated scores to measure employee promotability with a four-item scale from Tolentino, Garcia, Restubog, Bordia, & Tang (2013). A sample item was “If I want to select someone to succeed me in my position, it will be this person”. Cronbach’s alpha was 0.84.

Control variables Following previous research on proactive personality and proactive behaviors (e.g., Lam et al., 2018; Seibert et al., 1999; Wang, Zhang, Thomas, Yu, & Spitzmueller et al., 2017), we controlled for demographic characteristics, including gender (0 = male, 1 = female), age (1 = under 25 years old, 2 = 25–35 years old, 3 = 35–45 years old, 4 = above 45 years old), education (1 = high school and below, 2 = college, 3 = undergraduate, 4 = master or above), and tenure (1 = less than I year, 2 = 1–3 years, 3 = 3–5 years, 4 = more than 5 years), which may exert an influence on data analysis and results. For example, evidences from previous research suggested that age and tenure related to individual proactivity since as age and tenure increased, employees may engage in proactive behaviors more effectively (Thomas, Whitman, & Viswesvaran et al., 2010). Furthermore, research also suggested that a relationship between gender and proactive behaviors by discussing that supervisors may exert different degree of expectations on men and women regarding their proactive behaviors (Bohlmann & Zacher, 2020).

Furthermore, given the nested nature of our data in three levels (Teams were nested under organizations, and employees were nested under teams), a three-level analysis should be conducted. However, the sample size of level three was extremely small (only 2). Therefore, we tried to eliminate the influence of organizations by introducing a dummy - variable for organization (organization 1 = 0; organization 2 = 1) as a control variable. Results showed organizations exercised no significant influence. To keep the number of parameters within acceptable limits, we therefore tested our hypotheses without including organization as a control variable.

Aggregation analysis

Conceptually, task structure described a group-level phenomenon that taps into how labour was divided into distinct tasks and how coordination was achieved among them (Ambrose, Schminke, & Mayer, 2013; Yang et al., 2017). Methodologically, task structure referred to employees’ shared perceptions about their work-group structures, which should be aggregated to team-level for analysis. Indeed, task structure has been treated as a team-level construct by previous research (Ambrose & Schminke, 2003; Birkinshaw, Nobel, & Ridderstrale et al., 2002; DeGroot & Brownlee, 2006; Dimotakis, Davison, & Hollenbeck et al., 2012). Therefore, we followed previous research and analyzed it at team level.

Prior aggregating task structure into a team-level variable, we assessed whether there were sufficient agreements among employees in a same team to justify aggregation (James, 1982; Kozlowski & Klein, 2000). We calculated mean rwg and interclass correlation (ICC) statistics. We found mean rwg value of 0.79, suggesting aggregation is appropriate (George, 1990; George & James, 1993). ICC (1) was 0.17 and ICC (2) was 0.65, exceeding the cutoff point for justifying aggregation (Glick, 1985). Therefore, we aggregated task structure to the team level and applied multilevel structural equation modelling to test our hypotheses. Accordingly, we followed the suggestion of Geldhof, Preacher, and Zyphur et al., (2014), and did an analysis to test the reliability of task structure at multiple levels with Mplus. Results displayed that the reliability of task structure was acceptable at each level and indicated that the scale was slightly more reliable between groups (α = 0.92, 95% CI [0.39, 2.46]) than within groups (α = 0.73, 95% CI [0.62, 0.79]), indicating task structure was suitable to be treated on team level.

Results

Confirmatory factor analysis and descriptive statistics

A series of confirmatory factor analysis (CFAs) was conducted to evaluate the discriminant validity of our study variables. As suggested by prior research, the fit indices were likely to be impaired because of scales with many items, as they decreased the ratio of sample size to estimate parameter (Little, Cunningham, Shahar, & Widaman, 2002; Williams, Vandenberg, & Edwards, 2009). Given that scales with many items might impair the fit indices of CFAs, we used item parcels by the item-to-construct balance approach based on factor loadings to deal with this issue (Little et al., 2002; Qin, Liu, Brown, Zheng, & Owens, 2021; Williams et al., 2009). According to items’ factor loadings, indicators of each variable were generalized by paring the highest with the lowest, the second high with the second low, and so on. Finally, we achieved five indicators for proactive personality, five indicators for taking charge, four indicators for task structure, and two indicators for promotability.

The results showed that the hypothesized four-factor model had a reasonable fit to the data (χ2 (98) = 167.8, p < .001; comparative fit index (CFI) = 0.95, over 0.90, standardized root mean square residual (SRMR) = 0.05, less than 0.11, root mean square error of approximation (RMSEA) = 0.06, less than 0.08; Hu & Bentler, 1999). All factor loadings were statistically significant (p < .001), and ranged from 0.55 to 0.78 for proactive personality indicators, 0.72 to 0.82 for taking charge indicators, 0.54 to 0.76 for task structure indicators, and 0.68 to 1.02 for promotability. We tested all alternative models and results showed that the four-factor model was better than three-factor model (i.e., proactive personality and taking charge behavior were combined as one factor; χ2 (101) = 307.08, p < .001; CFI = 0.86, SRMR = 0.07, RMSEA = 0.09), two-factor model (i.e., variables rated by employees were combined into one factor; χ2 (103) = 536.02, p < .001; CFI = 0.70, SRMR = 0.11, RMSEA = 0.14), and one-factor model (all variables were combined into one factor; χ2 (104) = 675.13, p < .001; CFI = 0.60, SRMR = 0.12, RMSEA = 0.16), providing support for the distinctiveness of our key variables (i.e., proactive personality, taking charge behavior, task structure and promotability) (See Table 1). Additionally, results of CFA showed that the correlations between our key latent variables were significant, providing a preliminary support for our hypotheses (See Fig. 2). Table 2 shows the means, standard deviations, and correlations among study variables.

Table 1 Means, standard deviations, and correlations among study variables
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Table 2 Confirmatory factor analysis
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Fig. 2
figure 2

Results of latent variables’ correlations of CFA

Note. N = 229. Unstandardized coefficient estimates including control variables are reported and standard errors for each estimate are displayed in parentheses. *p < .05, **p < .01, ***p < .001

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Hypotheses testing

We used multilevel structural equation model (SEM) with Mplus 7.4 to test our hypothesized multilevel model with proactive personality, taking charge, promotability at individual level and task structure at team level. We first estimated a SEM model (Model 1) that did not include interaction effect to test direct effect and mediation effect after controlling for employee gender, age, education, and tenure. As shown in Fig. 3, proactive personality was positively related to taking charge behavior (γ = 0.65, p < .001), which was in turn, positively related to promotability (γ = 0.43, p < .001), supporting hypotheses 1. In addition, we found the indirect effect of proactive personality on promotability via taking charge behavior was significant (γ = 0.28, p < .001, 95% CI [0.16, 0.40], excluding zero), providing support for hypothesis 2.

Fig. 3
figure 3

Results of multilevel path analysis

Note. N = 229. The figure shows results of hypothesized paths of the theoretical model

T1E = variables rated by employees at Time 1; T2E = variables rated by employees at Time 2, 1 month after Time 1; T3L = variables rated by leaders at Time 3, 2 months after Time 1. Unstandardized coefficient estimates are reported after controlling for gender, age, education, and tenure. Standard errors for each estimate are displayed in parentheses. p < .05, **p < .01, ***p < .001

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Next, we estimated the other MSEM model (Model 2) to test the moderating role of task structure after controlling for employee gender, age, education, and tenure based on Model 1. Results revealed that task structure (γ = − 0.51, p < .05) had negative moderating effects on the relationship between proactive personality and taking charge behavior. Additionally, results of simple slope test showed that employee proactive personality was positively related to taking charge when task structure was organic (γ = 0.46, p < .001). However, the relationship turned negative but not significant when task structure was mechanistic (γ = − 0.16, p = .44). In addition, in order to illustrate the moderating role of task structure more clearly, we drew a diagram according to the results of simple slope test of the moderating effect. Figure 4 further showed that the nature of interactive effects was consistent with Hypothesis 3, such that the relationship between proactive personality and taking charge behavior was stronger when task structure was more organic than mechanistic.

Fig. 4
figure 4

Simple slope test for the moderating role of task structure

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In order to test the moderated mediation model, we estimated Model 3 by conducting a MSEM model through Mplus. Although the indirect effect was nonsignificant neither when task structure was mechanistic (γ = − 0.39, 95% CI [-0.89, 0.11], including zero) nor when it was organic (γ = − 0.23, 95% CI [-0.60, 0.14], including zero), results showed that the difference between the indirect effects via taking charge behavior at different degree of task structure (Δ γ = − 0.16, p < .05, 95% CI [-0.29, − 0.03], excluding zero) was significant. Therefore, Hypotheses 4 was supported.

Discussion

Theoretical implications

The current study makes several contributions to the literature. First, our major contribution lies in uncovering the boundary condition of proactive personality. Given the insufficient investigations of research on underlying the conditions under which proactive personality is more effective, an important implication from the current investigation is the demonstration of the moderating role of task structure. Our results showed that the relationship between proactive personality and taking charge behavior was stronger when task structure was more organic. In effect, in organic structure, employees are authorized with great freedom (Burns & Stalker, 1961; Stopford & Baden-Fuller, 1994) so as to better perform their proactive personality without constraints, thus, following more taking charge behaviors. By doing this, our research responds to assertions of testing when proactive employees can play their full roles (Tett & Burnett, 2003; Spitzmuller et al., 2015). Future research should continue this line of work by testing how situational cues such as organization climate or leadership can impact the effectiveness of proactive personality.

Additionally, using trait activation theory as our theoretical lens, we examine how different environment features interact with personality to influence job outcomes (Schmidt et al., 2012). Based on trait activation theory, trait differences must be put in weak situations if their expression is to be effective (Tett & Guterman, 2000). Specifically, mechanistic structure constrains the expression of employee proactive personality because of its rigid rules and regulations, resulting in less proactive behaviors. On the contrary, organic structure promotes employees’ proactivity by providing a loose and authorized environment. By doing this, our empirical investigation provides a more complete understanding of proactive personality as whether and when proactive employees are more likely to get promoted by shedding light on the boundary conditions of proactive personality.

Last, our findings also contribute in two ways to the research of proactive personality in general and taking charge in particular. On one hand, by linking proactive personality to employee promotability, our research extends the outcomes of proactive personality to employee career development, indicating the benefits of proactive personality to employee leadership capacities. On the other hand, we uncover the internal mechanism in the linkage between proactive personality and promotability by theoretically proposing and empirically testing the mediating role of taking charge.

Practical implications

The current research has practical implications as well. First, the results suggest proactive employees are more likely to perform better and get more opportunities to be promoted, which reminds organizations to select proactive employees during recruitment, such as using measurements of personality in the process of selection. In addition, consistent with the mediating role of taking charge behavior, it is also helpful for organizations to encourage employees to take initiatives to improve work environment. For example, organizations could include taking charge behavior as one of their evaluations toward employees. Third, our findings indicate that employee proactive personality is more productive in organizations with more organic structure. Therefore, it is crucial for organizations and leaders to develop more organic practices, for example, providing more decentralized decision-making processes, displaying informal rules and offering more autonomy to employees. Fourth, if teams are organized with a mechanistic structure, organizations should encourage employees to take charge especially since the potential of proactive employees may not be appreciated in such work environments.

Limitations and future directions

Like all studies, this research has several limitations, which give directions for future research. First, we collected data from organizations operating in China, a culture that is very different from that of Western countries. Therefore, specific Chinese cultural characteristics may limit the generalizability of our results. In more detail, employees in Chinese context are high collectivistic and power distance orientated (Hofstede, 1980). They are respectful and fearful to their leaders (Lian Ferris, & Brown et al., 2018), thus, their proactivity will be prohibited. Similarly, our results showed that employees’ proactive personality would not translate into taking charge when the working condition was constrained on decision-making and strengthening on formal roles and policies. Such evidence provides indirect support that situations where stress on formal hierarchies may inhibit employee proactivity. In such condition, future research needs to examine these findings under different cultural context to determine whether our results are cultural- specific or generalized.

Second, another limitation regarding the sample of the current research is that the number of teams surveyed is relatively small, which may also lead to the concern of generalizability. However, we believe our results are reasonable based on the evidence of previous research who has conducted a similar research design (e.g., Feng, Zhang, Liu, Zhang, & Han et al., 2018). Moreover, given the significant statistical results of hypotheses testing, we believe our findings based on the current sample have shed light on understanding how proactive personality contributes to employee promotability. Nevertheless, we still encourage future research to extend our theoretical model using a larger sample to add more evidence for our theoretical rationales.

Third, as recommended by Kim, Liu, and Diefendorff et al. (2015), we didn’t control for some key variables that have been shown as predictors of taking charge behaviors. For example, we did not consider the role of organizational characteristics (e.g., perceptions of organizational politics) in the process and whether they will affect taking charge jointly with proactive personality. Previous research has found both organizational features (Yang, 2017) and psychological states (Kim et al., 2015) can affect taking charge. Therefore, future research is encouraged to control these relevant variables to test the incremental validity of proactive personality in explaining employee taking charge behavior.

Last but not least, although we focused on the effect of employee proactivity on proactive behavior and promotability, it is interesting whether employee proactive personality will change as their taking charge and promotability increase. Specially, Caspi, Roberts, and Shiner et al. (2005) proposed when proactive employees improve the environment successfully, their proactive behaviors will be repeated and strengthened, as well as their proactive orientation. Therefore, when positive behaviors relevant to proactivity are strengthened or negative behaviors are weakened, proactive personality will get promoted at the same time (Hudson, Roberts, & Lodi-Smith et al., 2012). In that case, we recommend future research to extend our theoretical model by using longitudinal research to further investigate the dynamics of proactive personality and its longitudinal effects on taking charge and promotability.