Scholars and practitioners are increasingly investigating means of achieving career success (Guan et al., 2018). An increasing number of studies have indicated that individual proactive socialization strategies are an indispensable component in career development (Forret & Dougherty, 2004; Morrison, 2002; Wolff & Moser, 2009). Having relationships that are extensive in quality can help individuals to identify job opportunities and to obtain recommendations, career protection, and favorable information in workplaces (Zheng et al., 2020). Additionally, scholars have suggested that relationship quality and network behavior contribute to the objective and subjective measures of career success (Wolff & Moser, 2009). However, previous studies have not investigated (a) how relationship-building behavior leads to career success, or (b) the effect of the internal and external factors influencing career success in different social environments.

Recent research has provided evidence that social capital contributes significantly to promoting career development, especially in the early stages of the career (Raub et al., 2021). Social capital can be defined as the resources embedded in, available via, and derived from an individual’s relationship network (Lin, 1990). Compared to being in a poor social capital condition, being in a good social capital condition can offer the individual more information, resources, sponsorship, and social qualifications (Burt, 1992). Insiders in an organization, such as mentors, can offer information advantages, career sponsorship, and emotional support, and can be considered a special form of social capital (Van Vianen et al., 2017). In addition, Meeuwissen et al. (2019) suggested that having multiple mentors has other advantages, such as effectively solving confusion in the workplace, and inducing a range of positive career outcomes. However, most studies about mentoring have been conducted in the West, and some scholars have doubted whether the conclusions of these studies can be extended to other cultures (Ragins & Kram, 2008). For example, it has been pointed out that it is easy for everyone to have a mentor in the Chinese Confucian culture, in which older people consider it their responsibility to help younger people (Liu et al., 2018), and so they are more likely to help others in this way compared with other cultures. However, if most people have a mentor, the unique advantage of having a mentor may not be guaranteed. Additionally, Lin (1990) highlighted the importance of the social environment, and Burt (1997) suggested that the effect of social capital depends on contextual factors, such as social networks. From this point of view, we posited that the relationship between mentor tie strength and newcomers’ career outcomes may depend on general characteristics of a newcomer’s larger social network. Therefore, in the Chinese context, we investigated whether relationship-building behavior influences the strength of mentor ties, which subsequently affects newcomers’ career success in varying social environments.

Theory and Hypotheses

Relationship-Building Behavior and Career Success

Relationship-building behavior is categorized into three aspects of proactivity (Kim et al., 2015): building relationships with supervisors and peers (e.g., working hard to get to know one’s supervisors and coworkers), general socializing (e.g., participating in social functions held in the office), and network building (e.g., communicating with as many people as possible in other departments of the company). The focus in most studies has been on the aspects of building relationships and networks (Wanberg & Kammeyer-Mueller, 2000), because general socializing relies on the propensity to offer social activities in the organization. We followed this reasoning, and in our study focused on individuals’ relationship building with their supervisors and peers, and with people in other sections of the organization.

Career success is defined as the positive work and psychological outcomes that result from one’s work experience (Seibert et al., 2001). It can be evaluated in two ways: objective career success (i.e., promotions, salary raises) and subjective career success (i.e., career development, job/career satisfaction). On the basis of the career model learning cycle of goal setting, hard work, psychological achievement, and change of identity, objective career success does not inevitably result in subjective success (Guan et al., 2018).

The subjective and objective evaluation of career success can be attributed to the establishment of relationships (Gong et al., 2014). Evaluation of objective career success on the basis of rate of advancement, number of promotions, total compensation, and salary growth shows that it is positively related to networking behavior (Forret & Dougherty, 2004). Additionally, evaluation of subjective career success based on career satisfaction, role clarity, social integration, and perceived career success shows that it is positively associated with relationship building (Wanberg & Kammeyer-Mueller, 2000). Relationship-building behavior is significant for new employees because it helps them avoid loneliness and social isolation, gain a situational identity, acquire relevant skills and role behavior, and obtain knowledge about organizational policies and procedures (Kim et al., 2005), all of which help facilitate new employees’ career development. Thus, we proposed the following hypothesis:
Hypothesis 1a: Relationship-building behavior will positively influence promotion.
Hypothesis 1b: Relationship-building behavior will positively influence career satisfaction.

Mediating Role of Mentor Tie Strength

Active relationship-building behavior increases the probability of a newcomer being chosen by potential mentors, and enhances the strength of that individual’s relationships (Morrison, 2002). Bozionelos and Wang (2006) found that employees’ initiation of mentoring relationships was positively associated with the level of mentoring they received.  Therefore, we proposed the following hypothesis:
Hypothesis 2: Relationship-building behavior will positively influence mentor tie strength.

Mentoring relationships that can supply the protégé with career and psychosocial support have been considered a developmental process involving multiple relationships with immediate bosses, managers in other units, and other senior managers (van Emmerik, 2004). From this viewpoint, we defined individuals’ mentors based predominately on two characteristics: (a) holding a higher position in the organization than the protégé holds, and (b) benefiting the protégé’s career development (Ragins & Kram, 2007). Tie strength can be defined as an alliance of time, emotional intensity, intimacy, and reciprocal service (Granovetter, 1973). On the basis of these definitions, mentor tie strength refers to the level of emotional influence, mutual benefits, and frequent communication between protégés and their mentors.

According to Granovetter’s (1973) strength of weak ties theory, strong ties refer to network relationships that are stable, close, and binding, and that fulfill psychosocial functions (e.g., sense of competence, awareness of a professional role; see also Ibarra, 1995). We asserted that strong relationships between new employees and mentors could improve the career success of those new employees for the following reasons: First, strong ties within a network lead to frequency of contact, reciprocity, and friendship (Granovetter, 1973). Therefore, in strong relationships, mentors are significantly motivated to help protégés obtain substantial and readily available assistance, especially when protégés are at a disadvantage because of their newcomer status in regard to lack of information about and experience in tasks and roles (Zheng et al., 2020).

Second, emotional intensity, such as loyalty and trust embedded in strong relationships, will help new employees gain more psychosocial assistance from mentors, which could consequently help them become familiar more rapidly with competencies and professional roles. As Higgins and Kram (2001) pointed out, strong ties provide relatively more psychosocial support than weak ties do, owing to the emotional intensity they involve.

Third, strong ties facilitate interpersonal similarities that promote reciprocal relationships between mentors and new employees. Thus, new employees are more likely to gain exposure to the social environment of their mentors. According to the sponsored-mobility model, employees who have been sponsored and supported by mentors are more likely than are other employees to access development opportunities and to work in positions with more resources, which may facilitate their career development (Kraiger et al., 2018). Therefore, we proposed the following hypothesis:
Hypothesis 3a: Mentor tie strength will positively influence promotion.
Hypothesis 3b: Mentor tie strength will positively influence career satisfaction.

Social capital theory suggests that resources embedded in social relationships can lead to desirable outcomes (Lin, 1990). In the case of career development, individuals who engage in relationship-building behavior foster their social capital by establishing relationships with mentors who possess information, relationships, and power, which are resources that new employees do not have (Bagdadli & Gianecchini, 2019). Relationship-building behavior contributes to effective connections with potential mentors who can benefit the protégé’s career development (Zheng et al., 2020). Having strong ties with mentors helps establish mutual trust between mentor and the new employee (protégé), and enhance the mentors’ willingness to share resources, which consequently facilitates career advancement and career satisfaction for the new employee (Eby & Robertson, 2020). Therefore, through the underlying mechanism of social capital, we posited that mentor tie strength could regulate the connection between new employees’ relationship-building behavior and their career success.
Hypothesis 4a: Mentor tie strength will mediate the connection between relationship-building behavior and promotion.
Hypothesis 4b: Mentor tie strength will mediate the connection between relationship-building behavior and career satisfaction.

Moderating Role of Social Network Density

Burt (1992) indicated that contextual factors could have a strong influence on the benefits of social capital. We believed that the association between mentor tie strength and new employees’ career development would also depend on the larger social networks of the new employee. From a social network perspective, some scholars have suggested that network density could weaken the advantages embedded in individuals’ social resources (Zou et al., 2015). Network density refers to the ratio between the number of real connections and the greatest number of possible connections in a social network (Scott, 2000).

Compared to low-density networks, dense networks have more rules and sanctions and more mutual obligations; hence, they are more trustworthy (Morrison, 2002). Consequently, in a dense network, given the threats to other members, mentors may not offer additional advantages for protégés. Employees are less likely to adopt selfish, rule-breaking, and speculative behavior, such as obtaining special interest from mentors, owing to the supervision and sanctions from their coworkers (Labianca & Brass, 2006). Moreover, in high-density social networks, gossip spreads easily (Zou et al., 2015), and the information provided to employees is more likely to overlap with other information, owing to the connectivity of all the contacts (Bozionelos & Wang, 2006). Consequently, the influence of mentor tie strength may be reduced in an intensive social network, owing to redundant information and pressure through supervision and sanctions against unfair treatment from other members of the network.

Conversely, mentors are willing to offer special benefits in low-density social networks, where there is no supervision and sanction from other people. Additionally, sparse networks have fewer third parties (Van Vianen et al., 2017). Hence, a less competitive environment increases the probability of the employees benefitting from mentor tie strength. Low-density social networks have an additional advantage that the contacts with mentors are even closer between the members’ contacts (Scott, 2000) but the protégé’s mentors are not well connected among themselves. Therefore, protégés may be provided with unique resource and information, owing to fewer resources and less information similarity among the mentors. We expected that the effect of mentor tie strength on newcomers’ career outcomes would vary depending on the density of the social network. Accordingly, we formed the following hypotheses:
Hypothesis 5a: Social network density will moderate the relationship between mentor tie strength and protégés’ promotion, such that the positive relationship between mentor tie strength and promotion becomes stronger when the social network is less dense.
Hypothesis 5b: Social network density will moderate the relationship between mentor tie strength and protégés’ career satisfaction, such that the positive relationship between mentor tie strength and career satisfaction becomes stronger when the social network is less dense.

People in dense social networks interact with others frequently; therefore, it is easy for everyone in the network to build relationships with a member who is mentoring others in the group. In a dense social network the advantage of mentoring on career outcomes will be weakened owing to the rules and sanctions in the network, supervision and competition from other network members, and the constant presence of gossip within the network (Labianca & Brass, 2006; Zou et al., 2015). Conversely, the unique advantage of having mentor support exists in low-density social networks. Therefore, the effect of experiencing a mentoring relationship varies according to the density of the social network. On the basis of the above analysis, in addition to the moderating effects of social network density we further anticipated that social network density would conditionally influence the strength of the indirect effect of mentor tie strength. When the social network of new employees has low density, the mediating effect of mentor tie strength will be strong. Correspondingly, when the social network of new employees has high density, the indirect impact of their relationship-building behavior on career success through mentor tie strength will be relatively small. Therefore, we made the following predictions:
Hypothesis 6a: Social network density will moderate the indirect effect of relationship-building behavior on promotion through mentor tie strength, such that the mediating effect will be stronger when there is a lower rather than a higher density of social network.
Hypothesis 6b: Social network density will moderate the indirect effect of relationship-building behavior on career satisfaction through mentor tie strength, such that the mediating effect will be stronger when there is a lower rather than a higher density of social network.

In Figure 1 the hypotheses in this study are summarized and illustrated.

Method

Participants and Procedure

The original participant group included 252 new employees of a listed Chinese company that is one of the largest copper-refining companies in the world, and was ranked 109th in China’s top 500 manufacturing companies in 2020. Before conducting the survey, we obtained formal approval from the Ethics Committee for Research at the School of Economics and Management, Beijing Information Science and Technology University. The involvement of all participants was voluntary, and their responses were kept confidential and anonymous. To reduce the influence of previous social connections (Seibert et al., 2001), we chose employees hired within the last 2 years as our first data pool.

A longitudinal design was used to gather data at two time points. The items of the investigation conducted at Time 1 focused on evaluating relationship-building behavior, demographic variables, mentor tie strength, and social network density. A four-digit private number based on their cell phone or home phone number was used to match respondents across the two time points. Similar to previous research (Wanberg & Kammeyer-Mueller, 2000), a year after Time 1 we evaluated career success (promotion, career satisfaction; Time 2).

At Time 1 we collected 227 effective survey forms (return rate = 90%). We identified 186 respondents who had at least one mentor. In this group, 119 were men (64%) and 67 were women (36%). The mean tenure was 0.56 years (SD = 0.41, range = 3 to 15 months). The respondents were employed in one of the four following occupations: technological industry (83.4%), administration (12.2%), manufacturing (2.5%), and marketing (1.9%). Regarding education level, 29 had a master’s degree or higher academic qualification (15.4%), 151 had a bachelor’s degree (81.2%), five had an associate degree (2.9%), and one was a high school graduate (0.5%). At Time 2, we collected 194 effective survey forms (return rate = 91%). After matching data from both waves, we found that 151 participants whom we had identified as having at least one mentor at Time 1 had responded to the measure to assess their career success at Time 2.

Measures

All the scales in this study have been widely used in studies conducted in countries other than China. We recruited two experienced bilingual translators to translate all items into Chinese and then check the accuracy of the items by back-translating these into English (Brislin, 1970).

Relationship-Building Behavior
We assessed relationship-building behavior using two scales developed by Ashford and Black (1996). One scale (three items) assessed relationship building (e.g., “I make an effort to know my supervisor and coworkers”) and the other scale (three items) measured network building (e.g., “I try to socialize with people in other departments of the company as much as possible”).

We used confirmatory factor analysis to assess the discriminant validity of the two scales. Using maximum likelihood estimation with LISREL version 8.8 (Jöreskog & Sörbom, 2006), we compared two-factor and one-factor models. Root mean square error of approximation (RMSEA) and comparative fit index (CFI) are appropriate for testing small sample-based models (N < 200) as they are less sensitive to the size of the sample. The one-factor model showed the better fit of the two, with an overall adequate fit, chi square (χ²) = 16.23, degrees of freedom (df) = 9.0, RMSEA = .08, CFI = .98. The fit of the two-factor model, χ² = 24.21, df = 8, RMSEA = 0.12, CFI = .97, was not acceptable (fit criteria: χ²/df > 3; RMSEA > 0.10). The chi-square difference between the two models also signaled that the one-factor model was the better model of the two we tested, χ²(1) = 7.98, p < .001. Therefore, we combined relationship building and network building into one factor (relationship-building behavior; α = .87).

Mentor Tie Strength
Morrison (2002) indicated that a focus on egocentric networks is ideal for studying organizational newcomers since they represent only a small fraction of the social system in which they are embedded. An egocentric network refers to an individual’s unique social contact circle. The aim in research on egocentric networks is to determine how an individual’s social contacts are related to the variables of analysis at the individual level (Morrison, 2002). We used an egocentric network to collect the network data of new employees.

On the basis of previous research on mentoring (Higgins & Kram, 2001; Marsden, 1990), we asked participants to complete a table. In the first column, participants were required to note the person they thought would help them when they encountered difficulties in their job and in the organization. Similar to Morrison (2002), we provided participants with eight rows to list names (possible total of eight people named). As nominated mentors should work at a higher level than the individual, we chose nominated individuals as mentors only if they matched both the following standards: (a) a more senior position than the participant in the organization, and (b) having given the participant career-related help. In our investigation, the respondent wrote the name in the first column and assigned a score from the following alternatives (1 = junior staff, 2 = senior staff, 3 = supervisor, 4 = department manager, and 5 = company leader). Bozionelos and Wang (2006) found that supervisory guidance was positively correlated with the career success of the employees; therefore, we selected mentors whose scores were equal to or greater than three (supervisor). Similar to Dobrow and Higgins (2005), to represent the mentoring relationship between the individuals nominated and the participants who nominated them, we instructed participants to “Evaluate the extent to which this person is helpful to your career,” scored on a 4-point Likert scale ranging from 1 (not helpful at all) to 4 (greatly helpful). Only those contacts with a score of four were chosen; thus, the respondents had up to seven mentors (M = 1.78, SD = 1.10).

We used the following instruction to evaluate tie strength: “Evaluate the extent to which you are emotionally close to this person” with scores ranging from 1 to 4 (1 = distant, 2 = neither distant nor close, 3 = close, 4 = particularly close). Additionally, the mentor tie-strength scores were calculated by averaging the scores of the emotional intimacy of all the dyadic (mentor–protégé) relationships.

Social Network Density
Krackhardt (1990) suggested that social networks can be divided into friendship, advice, trust, and information types. Although social networks include these multiple types of social ties, we focused on advice ties owing to the greater influence of advice contact in the workplace. The advice network is an instrumental network formed privately because of the requirements of the work (Hu et al., 2018). Our focus was on the advice networks of new employees, and we mainly used the density of the advice network to describe its composition.

Consistent with extant social networks research, density was calculated as the ratio of actual contacts (including ego) to the total number of all possible contacts (Wang et al., 2017). In the current study, this variable was 2 × T_j ÷ n (N – 1), where T_j denotes the sum of the alter–alter connection number of person _j and the ego–alter connection number, and N – 1 corresponds to the total alter number. The value of the density can be any number from 0 to 1.

Career Success
Promotion is considered an objective criterion for assessing career success. Following Whitely et al. (1991), we evaluated the promotion of participants using a composite scale with three items to evaluate promotion within 1 year: “Whether the participant has had a significant increase in the scope of duties,” “Whether the participant has been promoted,” and “Whether the participant has received significant honors.” Score 0 means No, and score 1 means Yes. By summing the scores of the three items, we determined the promotion score, which may be 0, 1, 2, or 3.

Career satisfaction was evaluated using five items measured on a 5-point Likert scale (1 = strongly dissatisfied, 5 = strongly satisfied), and was considered as a subjective criterion of career success. The five items were satisfaction with career achievement, development, salary, position advancement, and new-skill development (Greenhaus et al., 1990). Sample items include “The success I have achieved in my career” and “The progress I have made toward meeting my goals for income.” Cronbach’s alpha in our study was .90.

Control Variables
Consistent with Seibert et al. (2001), we controlled for gender, level of education, organizational tenure, and occupational category. These were evaluated at Time 1.

Results

Common Method Variance

We used various methods, such as random arrangement, to control for common method bias in the survey design and data collection. Data were collected at two time points to mitigate the influence of common method variance (CMV). However, data for analysis of all variables were derived from self-reporting by participants; this may cause CMV problems. Through Harman’s single-factor test, multiple factors were obtained (Podsakoff et al., 2003). Further, the first factor accounted for 29.08% of the explained variance during rotation; this value is significantly below the threshold of 40%. This indicates that CMV was not a significant problem and did not influence the reliability of the conclusions of the research (Cohen & Cohen, 1983).

Descriptive and Correlation Analyses

The variables in this study were examined using descriptive and correlation analyses. SPSS 23.0 was used to perform the descriptive and correlation analyses of the samples. The means, standard deviations, reliabilities, and intercorrelations of the variables are shown in Table 1. Relationship-building behavior was positively correlated with mentor tie strength and career satisfaction. Mentor tie strength was positively correlated with promotion and career satisfaction. The two career success variables were correlated.

Multiple Regression Analyses

Results in Table 2 show that relationship-building behavior was associated with mentor tie strength (Step 2) and career satisfaction (Step 2). Therefore, Hypotheses 1b and 2 were supported. However, we did not find evidence that relationship-building behavior positively influenced promotion (Step 2); thus, Hypothesis 1a was not supported. As hypothesized (Hypothesis 3a), mentor tie strength significantly predicted promotion (Step 3) and career satisfaction (Hypothesis 3b, Step 3).

We further conducted a hierarchical regression analysis to test our hypotheses that mentor tie strength would mediate the connections between relationship-building behavior and promotion (Hypothesis 4a) and between relationship-building behavior and career satisfaction (Hypothesis 4b). Following Baron and Kenny’s (1986) recommendations, we found that when we incorporated mentor tie strength into the model the correlation between relationship-building behavior and career satisfaction (dependent variable) was no longer significant (Step 3). Therefore, Hypothesis 4b gained preliminary support. However, we did not find evidence to support the mediating effect of mentor tie strength between relationship-building behavior (Step 2) and promotion (Step 3). Thus, Hypothesis 4a was not supported.

Table 2 shows the results of testing the moderating effect of social network density. When using promotion as the dependent variable (Hypothesis 5a), we did not find evidence that the positive relationship between mentor tie strength and promotion would become stronger when the social network is less dense (Step 5). When considering career satisfaction as the dependent variable (Hypothesis 5b), the results demonstrate that network density moderated the correlation between mentor tie strength and career satisfaction (Step 5). These results supported Hypothesis 5b.

Mediating and Conditional Effects Test

To further support the rationality and accuracy of the above analysis, for cross-validation we used Model 14 of the SPSS PROCESS macro (Hayes, 2013). Results are shown in Tables 3 and 4. Relationship-building behavior was positively correlated with career satisfaction (see Table 3), mentor tie strength was positively correlated with career satisfaction (see Table 3), and the indirect effect of relationship-building behavior on career satisfaction was significant (see Table 4). However, the direct effect was nonsignificant. Therefore, mentor tie strength fully mediated the correlation between relationship-building behavior and career satisfaction. Thus, Hypothesis 4b was supported.

The interaction of mentor tie strength with social network density was significant in predicting career satisfaction (see Table 3). We further examined the conditional indirect effects of relationship-building behavior on career satisfaction at three levels of social network density (M − 1 SD; M; M + 1 SD). As shown in Table 4, the indirect effect of relationship-building behavior on career satisfaction through mentor tie strength was significant at a low level of network density rather than at a high level.

The results indicate that when social network density was low, mentor tie strength mediated the relationship between relationship-building behavior and career satisfaction. However, the mediating role of mentor tie strength was not significant in the condition of higher density networks. The mediating effects differed significantly between the two conditions. Following Preacher et al. (2007), we concluded that social network density negatively moderated the mediating effect of mentor tie strength between relationship-building behavior and career satisfaction, thus supporting Hypothesis 6b. Because Hypotheses 4a and 5a were not supported, Hypothesis 6a that social network density would moderate the mediating effect of mentor tie strength between relationship-building behavior and promotion was necessarily not supported.

Following Aiken and West’s (1991) suggestion, a t test was conducted to assess the significance level of the regression effect. As shown in Figure 2, the correlation between mentor tie strength and career satisfaction was positive when social network density was low. However, it was negative when the density of the social network was high. Both the slopes (t_L = 2.17, p < .05; t_H = –1.91, ns) and the difference between the slopes (t = –2.04, p < .05) were statistically significant, further supporting the moderating effect of social network density.

Discussion

To add insight into how new employees’ relationship-building behavior leads to their career success, we extended this burgeoning line of research by not only investigating mentor tie strength as a key mechanism that links relationship-building behavior to career success, but also exploring the impact of the social network environment on the career success of new employees.

Consistent with our expectations, we found that new employees’ relationship-building behavior significantly influenced mentor tie strength and career satisfaction. However, we did not find any evidence to support a positive influence of new employees’ relationship-building behavior on their promotion. Mentor tie strength significantly predicted promotion and career satisfaction. Furthermore, our results indicate that mentor tie strength fully mediated the positive correlation between new employees’ relationship-building behavior and their career satisfaction. We did not find the same mediating role played by mentor tie strength in regard to new employees’ promotion.

We also found that social network density negatively moderated the relationship between mentor tie strength and new employees’ career satisfaction. Moreover, social network density negatively moderated the mediating role of mentor tie strength between new employees’ relationship-building behavior and their career satisfaction, such that the conditional indirect effect of relationship-building behavior on career satisfaction via mentor tie strength was stronger when the social network density was low compared to when social network density was high.

Our results did not support our hypotheses regarding promotion. This may be because, compared with career satisfaction, promotion is an objective measure that is influenced more by factors outside an individual’s control, such as departmental environment and supervisor preferences. In addition, the participants in this study were new employees who are at the beginning of their career, with fewer promotional opportunities. Future research could replicate this research with long-tenured employees to provide a greater variety of promotional statuses to facilitate better determining the effects of promotion in the relationship of mentor ties with newcomers’ relationship-building behavior and career success.

Theoretical Contributions

In this research we have made several theoretical contributions. First, we offer insight into the correlation between relationship-building behavior and career success, which has received little research attention (Wolff & Moser, 2009). Empirical research in which the role of mentors in newcomers’ socialization has been examined has so far been limited (Zheng et al., 2020). We have extended existing research, in that our results suggest relationship-building behavior is an effective socialization tactic for newcomers to strengthen ties with mentors who could help them achieve better career outcomes.

Second, our finding that mentor tie strength contributes to career outcomes differs from the structural holes and weak ties theory, in which it is stated that loose connections with a wide range of people are conducive to career success (Seibert et al., 2001). Our findings show that one type of strong tie (i.e., with mentors) is crucial for career satisfaction. When a person’s network is looked at as a whole, having weaker ties and more structural holes provides insight (Burt, 1992; Granovetter, 1973; Liu, 2018); however, close ties with a specific part of one’s network (people who are higher in status and who can provide career assistance) have more advantages when looking at career success specifically.

Third, our findings show that protégés can obtain career and psychological benefits from the establishment of strong ties with mentors in a sparse social network. In addition, network density is usually the most frequently used indicator to reflect social cohesion (Scott, 2000), suggesting that the superiority embedded in the social resources of individuals may be weakened by high social cohesion. These findings are consistent with prior mentoring research (Eby & Robertson, 2020), which shows that the effect of mentoring depends on contextual factors, such as developmental climate and open communication climate. These results also provide additional evidence for Burt’s (1997) proposal that social capital has contingent value. Burt used network and performance data from a sample of senior managers to show how the value of social capital varies as a power function of the number of people doing the same work. This exploration can open new avenues for researchers of mentoring to consider more social network approaches.

Practical Implications

Our findings suggest that strong ties with mentors and an effective socialization tactic (relationship-building behavior) have a positive effect on new employees’ career satisfaction. Thus, it is essential for them to proactively establish close relationships with mentors who can supply career-related help. Furthermore, our results show that when the density of social networks is low, the value to the new employee of stronger ties with mentors is more prominent than it is in high-density social networks. Specifically, when new employees are in a low-density network, stronger ties with mentors are crucial for them to achieve higher career satisfaction. Nevertheless, the same strength of the relationship may be counterproductive when the network density is high. In such circumstances, both mentors and protégés need to adjust the closeness of their relationships to help new employees to gain promotions and achieve higher career satisfaction.

In addition to establishing formal mentors to guide new employees, managers and leaders of organizations should encourage new employees to actively establish informal mentoring relationships. Moreover, leaders and policy makers are advised to establish not only a mentoring system, but also to help newcomers to actively build relationships by building a better and more supportive communication platform to promote communication and emotional cultivation efficiency.

Limitations and Future Research Directions

This study has several limitations. First, we conducted our research in a culture of high power distance and collectivism. Compared with a low power-distance culture, strong ties with higher-status people in a high power-distance culture might be more beneficial to the career success of new employees. Additionally, group sanctions may be higher in collectivism than in individualism. Therefore, the negative effect of social network density analyzed in this study may be more significant in a culture of collectivism than it would be in a culture of individualism. Future studies can investigate whether the effects we found differ in cultures of low power distance or individualism. Second, the occupational homogeneity of the respondents in our research was high. Eby and Robertson (2020) indicated that occupation may be relevant in the context of the construct of mentoring. Hence, future studies can examine whether the mentor network has different effects on protégés’ career outcomes according to the protégé’s occupation. Third, the mentor source was limited to the organizations in our sample. Following the definition of developmental mentors set out by van Emmerik et al. (2004), future researchers could broaden the range of mentors beyond the boundaries of the organization to cover families and communities. Additionally, we recommend that future studies focus on mentors’ social network and explore how this influences the career success of new employees.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Sage Publications.

Ashford, S. J., & Black, J. S. (1996). Proactivity during organizational entry: The role of desire for control. Journal of Applied Psychology, 81(2), 199–214.
https://doi.org/10.1037/0021-9010.81.2.199

Bagdadli, S., & Gianecchini, M. (2019). Organizational career management practices and objective career success: A systematic review and framework. Human Resource Management Review, 29(3), 353–370.
https://doi.org/10.1016/j.hrmr.2018.08.001

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
https://doi.org/10.1037/0022-3514.51.6.1173

Bozionelos, N., & Wang, L. (2006). The relationship of mentoring and network resources with career success in the Chinese organizational environment. International Journal of Human Resource Management, 17(9), 1531–1546.
https://doi.org/10.1080/09585190600878345

Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216.
https://doi.org/10.1177/135910457000100301

Burt, R. S. (1992). Structural holes: The social structure of competition. Harvard University Press.

Burt, R. S. (1997). The contingent value of social capital. Administrative Science Quarterly, 42(2), 339–365.
https://doi.org/10.2307/2393923

Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
https://doi.org/10.4324/9781410606266

Dobrow, S. R., & Higgins, M. C. (2005). Developmental networks and professional identity: A longitudinal study. Career Development International, 10(6/7), 567–583.
https://doi.org/10.1108/13620430510620629

Eby, L. T., & Robertson, M. M. (2020). The psychology of workplace mentoring relationships. Annual Review of Organizational Psychology and Organizational Behavior, 7, 75–100.
https://doi.org/10.1146/annurev-orgpsych-012119-044924

Forret, M. L., & Dougherty, T. W. (2004). Networking behaviors and career outcomes: Differences for men and women? Journal of Organizational Behavior, 25(3), 419–437.
https://doi.org/10.1002/job.253

Gong, R., Chen, S.-Y., & Yang, M.-L. (2014). Career outcome of employees: The mediating effect of mentoring. Social Behavior and Personality: An international journal, 42(3), 487–502.
https://doi.org/10.2224/sbp.2014.42.3.487

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.
https://doi.org/10.1086/225469

Greenhaus, J. H., Parasuraman, S., & Wormley, W. M. (1990). Effects of race on organizational experiences, job performance evaluations, and career outcomes. The Academy of Management Journal, 33(1), 64–86.
https://doi.org/10.5465/256352

Guan, Y., Arthur, M. B., Khapova, S. N., Hall, R. J., & Lord, R. G. (2018). Career boundarylessness and career success: A review, integration and guide to future research. Journal of Vocational Behavior, 110(B), 390–402.
https://doi.org/10.1016/j.jvb.2018.05.013

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.

Higgins, M. C., & Kram, K. E. (2001). Reconceptualizing mentoring at work: A developmental network perspective. Academy of Management Review, 26(2), 264–288.
https://doi.org/10.2307/259122

Hu, S., Zhong, Z., Zhang, J., & Zheng, X. (2018). Cognitive flexibility and advice network centrality: The moderating role of self-monitoring. Frontiers in Psychology, 9, Article 1947.
https://doi.org/10.3389/fpsyg.2018.01947

Ibarra, H. (1995). Race, opportunity, and diversity of social circles in managerial networks. The Academy of Management Journal, 38(3), 673–703. https://bit.ly/3ArxZXt

Jöreskog, K., & Sörbom, D. (2006). LISREL (version 8.8) [Computer software]. Scientific Software International Inc. https://bit.ly/3FtoSt0

Kim, T.-Y., Cable, D. M., & Kim, S.-P. (2005). Socialization tactics, employee proactivity, and person–organization fit. Journal of Applied Psychology, 90(2), 232–241.
https://doi.org/10.1037/0021-9010.90.2.232

Krackhardt, D. (1990). Assessing the political landscape: Structure, cognition, and power in organizations. Administrative Science Quarterly, 35(2), 342–369.
https://doi.org/10.2307/2393394

Kraiger, K., Finkelstein, L. M., & Varghese, L. S. (2018). Enacting effective mentoring behaviors: Development and initial investigation of the cuboid of mentoring. Journal of Business and Psychology, 34, 403–424.
https://doi.org/10.1007/s10869-018-9551-z

Labianca, G., & Brass, D. J. (2006). Exploring the social ledger: Negative relationships and negative asymmetry in social networks in organizations. Academy of Management Review, 31(3), 596–614.
https://doi.org/10.5465/amr.2006.21318920

Lin, N. (1990). Social resources and social mobility: A structural theory of status attainment. In R. L. Breiger (Ed.), Social mobility and social structure (pp. 241–271). Cambridge University Press.

Liu, J., Nandhakumar, J., & Zachariadis, M. (2018). When guanxi meets structural holes: Exploring the guanxi networks of Chinese entrepreneurs on digital platforms. The Journal of Strategic Information Systems. 27(4), 311–334.
https://doi.org/10.1016/j.jsis.2018.10.003

Marsden, P. V. (1990). Network data and measurement. Annual Review of Sociology, 16, 435–463.
https://doi.org/10.1146/annurev.so.16.080190.002251

Meeuwissen, S. N. E., Stalmeijer, R. E., & Govaerts, M. (2019). Multiple-role mentoring: Mentors’ conceptualizations, enactments and role conflicts. Medical Education, 53(6), 605–615.
https://doi.org/10.1111/medu.13811

Morrison, E. W. (2002). Newcomers’ relationships: The role of social network ties during socialization. Academy of Management Journal, 45(6), 1149–1160.
https://doi.org/10.5465/3069430

Podsakoff, P. M., Mackenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.
https://doi.org/10.1037/0021-9010.88.5.879

Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227.
https://doi.org/10.1080/00273170701341316

Ragins, B. R., & Kram, K. E. (2008). The handbook of mentoring at work: Theory, research, and practice. Sage Publications.

Raub, S., Borzillo, S., Perretten, G., & Schmitt, A. (2021). New employee orientation, role-related stressors and conflict at work: Consequences for work attitudes and performance of hospitality employees. International Journal of Hospitality Management, 94, Article 102857.
https://doi.org/10.1016/j.ijhm.2020.102857

Scott, J. (2000). Social network analysis: A handbook (2nd ed.). Sage Publications.

Seibert, S. E., Kraimer, M. L., & Liden, R. C. (2001). A social capital theory of career success. The Academy of Management Journal, 44(2), 219–237. https://bit.ly/3oZHBqr

van Emmerik, I. J. H. (2004). The more you can get the better: Mentoring constellations and intrinsic career success. Career Development International, 9(6), 578–594.
https://doi.org/10.1108/13620430410559160

Van Vianen, A. E. M., Rosenauer, D., Homan, A. C., Horstmeier, C. A. L., & Voelpel, S. C. (2017). Career mentoring in context: A multilevel study on differentiated career mentoring and career mentoring climate. Human Resource Management, 57(2), 583–599.
https://doi.org/10.1002/hrm.21879

Wanberg, C. R., & Kammeyer-Mueller, J. D. (2000). Predictors and outcomes of proactivity in the socialization process. Journal of Applied Psychology, 85, 373–385.
https://doi.org/10.1037/0021-9010.85.3.373

Wang, C.-C., Sung, H.-Y., Chen, D.-Z., & Huang, M.-H. (2017). Strong ties and weak ties of the knowledge spillover network in the semiconductor industry. Technological Forecasting and Social Change, 118(5), 114–127.
https://doi.org/10.1016/j.techfore.2017.02.011

Whitely, W., Dougherty, T. W., & Dreher, G. F. (1991). Relationship of career mentoring and socioeconomic origin to managers’ and professionals’ early career progress. Academy of Management Journal, 34(2), 331–351.
https://doi.org/10.5465/256445

Wolff, H.-G., & Moser, K. (2009). Effects of networking on career success: A longitudinal study. Journal of Applied Psychology, 94(1), 196–206.
https://doi.org/10.1037/a0013350

Zheng, Y., Zheng, X., Wu, C.-H., Yao, X., & Wang, Y. (2020). Newcomers’ relationship-building behavior, mentor information sharing and newcomer adjustment: The moderating effects of perceived mentor and newcomer deep similarity. Journal of Vocational Behavior, 125, Article 103519.
https://doi.org/10.1016/j.jvb.2020.103519

Zou, X., Ingram, P., & Higgins, E. T. (2015). Social networks and life satisfaction: The interplay of network density and regulatory focus. Motivation and Emotion, 39(5), 693–713.
https://doi.org/10.1007/s11031-015-9490-1

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Sage Publications.

Ashford, S. J., & Black, J. S. (1996). Proactivity during organizational entry: The role of desire for control. Journal of Applied Psychology, 81(2), 199–214.
https://doi.org/10.1037/0021-9010.81.2.199

Bagdadli, S., & Gianecchini, M. (2019). Organizational career management practices and objective career success: A systematic review and framework. Human Resource Management Review, 29(3), 353–370.
https://doi.org/10.1016/j.hrmr.2018.08.001

Baron, R. M., & Kenny, D. A. (1986). The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173–1182.
https://doi.org/10.1037/0022-3514.51.6.1173

Bozionelos, N., & Wang, L. (2006). The relationship of mentoring and network resources with career success in the Chinese organizational environment. International Journal of Human Resource Management, 17(9), 1531–1546.
https://doi.org/10.1080/09585190600878345

Brislin, R. W. (1970). Back-translation for cross-cultural research. Journal of Cross-Cultural Psychology, 1(3), 185–216.
https://doi.org/10.1177/135910457000100301

Burt, R. S. (1992). Structural holes: The social structure of competition. Harvard University Press.

Burt, R. S. (1997). The contingent value of social capital. Administrative Science Quarterly, 42(2), 339–365.
https://doi.org/10.2307/2393923

Cohen, J., & Cohen, P. (1983). Applied multiple regression/correlation analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
https://doi.org/10.4324/9781410606266

Dobrow, S. R., & Higgins, M. C. (2005). Developmental networks and professional identity: A longitudinal study. Career Development International, 10(6/7), 567–583.
https://doi.org/10.1108/13620430510620629

Eby, L. T., & Robertson, M. M. (2020). The psychology of workplace mentoring relationships. Annual Review of Organizational Psychology and Organizational Behavior, 7, 75–100.
https://doi.org/10.1146/annurev-orgpsych-012119-044924

Forret, M. L., & Dougherty, T. W. (2004). Networking behaviors and career outcomes: Differences for men and women? Journal of Organizational Behavior, 25(3), 419–437.
https://doi.org/10.1002/job.253

Gong, R., Chen, S.-Y., & Yang, M.-L. (2014). Career outcome of employees: The mediating effect of mentoring. Social Behavior and Personality: An international journal, 42(3), 487–502.
https://doi.org/10.2224/sbp.2014.42.3.487

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380.
https://doi.org/10.1086/225469

Greenhaus, J. H., Parasuraman, S., & Wormley, W. M. (1990). Effects of race on organizational experiences, job performance evaluations, and career outcomes. The Academy of Management Journal, 33(1), 64–86.
https://doi.org/10.5465/256352

Guan, Y., Arthur, M. B., Khapova, S. N., Hall, R. J., & Lord, R. G. (2018). Career boundarylessness and career success: A review, integration and guide to future research. Journal of Vocational Behavior, 110(B), 390–402.
https://doi.org/10.1016/j.jvb.2018.05.013

Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press.

Higgins, M. C., & Kram, K. E. (2001). Reconceptualizing mentoring at work: A developmental network perspective. Academy of Management Review, 26(2), 264–288.
https://doi.org/10.2307/259122

Hu, S., Zhong, Z., Zhang, J., & Zheng, X. (2018). Cognitive flexibility and advice network centrality: The moderating role of self-monitoring. Frontiers in Psychology, 9, Article 1947.
https://doi.org/10.3389/fpsyg.2018.01947

Ibarra, H. (1995). Race, opportunity, and diversity of social circles in managerial networks. The Academy of Management Journal, 38(3), 673–703. https://bit.ly/3ArxZXt

Jöreskog, K., & Sörbom, D. (2006). LISREL (version 8.8) [Computer software]. Scientific Software International Inc. https://bit.ly/3FtoSt0

Kim, T.-Y., Cable, D. M., & Kim, S.-P. (2005). Socialization tactics, employee proactivity, and person–organization fit. Journal of Applied Psychology, 90(2), 232–241.
https://doi.org/10.1037/0021-9010.90.2.232

Krackhardt, D. (1990). Assessing the political landscape: Structure, cognition, and power in organizations. Administrative Science Quarterly, 35(2), 342–369.
https://doi.org/10.2307/2393394

Kraiger, K., Finkelstein, L. M., & Varghese, L. S. (2018). Enacting effective mentoring behaviors: Development and initial investigation of the cuboid of mentoring. Journal of Business and Psychology, 34, 403–424.
https://doi.org/10.1007/s10869-018-9551-z

Labianca, G., & Brass, D. J. (2006). Exploring the social ledger: Negative relationships and negative asymmetry in social networks in organizations. Academy of Management Review, 31(3), 596–614.
https://doi.org/10.5465/amr.2006.21318920

Lin, N. (1990). Social resources and social mobility: A structural theory of status attainment. In R. L. Breiger (Ed.), Social mobility and social structure (pp. 241–271). Cambridge University Press.

Liu, J., Nandhakumar, J., & Zachariadis, M. (2018). When guanxi meets structural holes: Exploring the guanxi networks of Chinese entrepreneurs on digital platforms. The Journal of Strategic Information Systems. 27(4), 311–334.
https://doi.org/10.1016/j.jsis.2018.10.003

Marsden, P. V. (1990). Network data and measurement. Annual Review of Sociology, 16, 435–463.
https://doi.org/10.1146/annurev.so.16.080190.002251

Meeuwissen, S. N. E., Stalmeijer, R. E., & Govaerts, M. (2019). Multiple-role mentoring: Mentors’ conceptualizations, enactments and role conflicts. Medical Education, 53(6), 605–615.
https://doi.org/10.1111/medu.13811

Morrison, E. W. (2002). Newcomers’ relationships: The role of social network ties during socialization. Academy of Management Journal, 45(6), 1149–1160.
https://doi.org/10.5465/3069430

Podsakoff, P. M., Mackenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903.
https://doi.org/10.1037/0021-9010.88.5.879

Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227.
https://doi.org/10.1080/00273170701341316

Ragins, B. R., & Kram, K. E. (2008). The handbook of mentoring at work: Theory, research, and practice. Sage Publications.

Raub, S., Borzillo, S., Perretten, G., & Schmitt, A. (2021). New employee orientation, role-related stressors and conflict at work: Consequences for work attitudes and performance of hospitality employees. International Journal of Hospitality Management, 94, Article 102857.
https://doi.org/10.1016/j.ijhm.2020.102857

Scott, J. (2000). Social network analysis: A handbook (2nd ed.). Sage Publications.

Seibert, S. E., Kraimer, M. L., & Liden, R. C. (2001). A social capital theory of career success. The Academy of Management Journal, 44(2), 219–237. https://bit.ly/3oZHBqr

van Emmerik, I. J. H. (2004). The more you can get the better: Mentoring constellations and intrinsic career success. Career Development International, 9(6), 578–594.
https://doi.org/10.1108/13620430410559160

Van Vianen, A. E. M., Rosenauer, D., Homan, A. C., Horstmeier, C. A. L., & Voelpel, S. C. (2017). Career mentoring in context: A multilevel study on differentiated career mentoring and career mentoring climate. Human Resource Management, 57(2), 583–599.
https://doi.org/10.1002/hrm.21879

Wanberg, C. R., & Kammeyer-Mueller, J. D. (2000). Predictors and outcomes of proactivity in the socialization process. Journal of Applied Psychology, 85, 373–385.
https://doi.org/10.1037/0021-9010.85.3.373

Wang, C.-C., Sung, H.-Y., Chen, D.-Z., & Huang, M.-H. (2017). Strong ties and weak ties of the knowledge spillover network in the semiconductor industry. Technological Forecasting and Social Change, 118(5), 114–127.
https://doi.org/10.1016/j.techfore.2017.02.011

Whitely, W., Dougherty, T. W., & Dreher, G. F. (1991). Relationship of career mentoring and socioeconomic origin to managers’ and professionals’ early career progress. Academy of Management Journal, 34(2), 331–351.
https://doi.org/10.5465/256445

Wolff, H.-G., & Moser, K. (2009). Effects of networking on career success: A longitudinal study. Journal of Applied Psychology, 94(1), 196–206.
https://doi.org/10.1037/a0013350

Zheng, Y., Zheng, X., Wu, C.-H., Yao, X., & Wang, Y. (2020). Newcomers’ relationship-building behavior, mentor information sharing and newcomer adjustment: The moderating effects of perceived mentor and newcomer deep similarity. Journal of Vocational Behavior, 125, Article 103519.
https://doi.org/10.1016/j.jvb.2020.103519

Zou, X., Ingram, P., & Higgins, E. T. (2015). Social networks and life satisfaction: The interplay of network density and regulatory focus. Motivation and Emotion, 39(5), 693–713.
https://doi.org/10.1007/s11031-015-9490-1

This research was supported by grants from the National Natural Science Foundation of China (72002016

71801120) and the Social Science Foundation of Beijing (18GLC064).

Miaomiao Li contributed to the conceptual design of the study and the drafting of the article. Miaomiao Li

Zhenxing Gong

and Ganli Liao contributed to the data collection

data analyses

and final approval of the article.

Miaomiao Li, School of Economics and Management, Beijing Information Science and Technology University, 12 East Qinghexiaoying Road, Haidian District, Beijing 100192, People’s Republic of China. Email: [email protected]