This is a self-archived – parallel published version of this article in the publication archive of the University of Vaasa. It might differ from the original. Proactive career behaviors and subjective career success: the moderating role of national culture Author(s): Smale, Adam; Bagdadli, Silvia; Cotton, Rick; Dello Russo, Silvia; Dickmann, Michael; Dysvik, Anders; Gianecchini, Martina; Kaše, Robert; Lazarova, Mila; Reichel, Astrid; Rozo, Paula; Verbruggen, Marij Title: Proactive career behaviors and subjective career success: the moderating role of national culture Year: 2019 Version: Published version Copyright © 2019 John Wiley & Sons, Ltd. Please cite the original version: Smale, A., Bagdadli, S., Cotton, R., Dello Russo, S., Dickmann, M., Dysvik, A., Gianecchini, M., Kaše, R., Lazarova, M., Reichel, A., Rozo, P. & Verbruggen, M. (2019). Proactive career behaviors and subjective career success: the moderating role of national culture. Journal of Organizational Behavior 50(1), 105-122. https://doi.org/10.1002/job.2316 S P E C I A L I S S U E A R T I C L E Proactive career behaviors and subjective career success: The moderating role of national culture Adam Smale1* | Silvia Bagdadli2* | Rick Cotton3* | Silvia Dello Russo4* | Michael Dickmann5* | Anders Dysvik6* | Martina Gianecchini7* | Robert Kaše8* | Mila Lazarova9* | Astrid Reichel10* | Paula Rozo11* | Marijke Verbruggen12* | On behalf of the Cross‐Cultural Collaboration on Contemporary Careers (5C) research collaborative† 1University of Vaasa, Vaasa, Finland 2Bocconi University, Milan, Italy 3University of Victoria, Victoria, British Columbia, Canada 4 Instituto Universitário de Lisboa (ISCTE‐IUL), Lisbon, Portugal 5School of Management, Cranfield University, Cranfield, UK 6BI Norwegian Business School, Oslo, Norway 7University of Padova, Padova, Italy 8Faculty of Economics, University of Ljubljana, Ljubljana, Slovenia 9Beedie School of Business, Simon Fraser University, Vancouver, British Columbia, Canada 10University of Salzburg, Salzburg, Austria 11Los Andes University, Bogotá, Columbia 12KU Leuven, Leuven, Belgium Correspondence Adam Smale, University of Vaasa, P.O. Box 700, 65101 Vaasa, Finland. Email: adam.smale@uva.fi Summary Although career proactivity has positive consequences for an individual's career suc- cess, studies mostly examine objective measures of success within single countries. This raises important questions about whether proactivity is equally beneficial for different aspects of subjective career success, and the extent to which these benefits extend across cultures. Drawing on Social Information Processing theory, we exam- ined the relationship between proactive career behaviors and two aspects of subjec- tive career success—financial success and work‐life balance—and the moderating role of national culture. We tested our hypotheses using multilevel analyses on a large‐ scale sample of 11,892 employees from 22 countries covering nine of GLOBE's 10 cultural clusters. Although we found that proactive career behaviors were positively related to subjective financial success, this relationship was not significant for work‐ life balance. Furthermore, career proactivity was relatively more important for sub- jective financial success in cultures with high in‐group collectivism, high power dis- tance, and low uncertainty avoidance. For work‐life balance, career proactivity was relatively more important in cultures characterized by high in‐group collectivism and humane orientation. Our findings underline the need to treat subjective career suc- cess as a multidimensional construct and highlight the complex role of national culture in shaping the outcomes of career proactivity. KEYWORDS career self‐management, career success, national culture, proactive career behaviors *These 12 authors contributed equally to the article. †The quantitative part of this research endeavor has taken a number of years from conceptualization through to implementation. During this time, we have tried to ensure that we gained the maximum possible through this multiauthor approach while maintaining the integrity of our research. Many of the authors were involved in conceptualizing the research at face‐to‐face meetings held twice a year for this purpose during 2007–2014. All of the authors were involved in data collection in some capacity in their representative countries. All of the 12 main authors and many of the authors in the 5C collaborative were then involved in the subsequent initial analysis and interpretation of the data in similar biannual meetings held during 2014–2018. In between each of the whole‐collaborative meetings, the 12 main authors took the group's inputs away to work on them in meetings held face‐to‐face, via email and Skype. The original text was drafted and revised among the 12 first‐named authors before inviting critical input and revisions from the other 34 authors. The final text emerged from the input received from the collaborative, and all authors have signed off on the submission. This submitted version of the paper thus reflects the input and views of all 46 authors, and all are prepared to be accountable for its content. This process was repeated during the revision and resubmission stage. The large number of authors has facilitated the collection of an extensive, multi‐ country dataset and has added credibility to both the data and its interpretation that, we believe, could not have been achieved with a smaller group. The 5C collaborative includes a larger number of scholars than are included here. Received: 30 November 2016 Revised: 22 May 2018 Accepted: 11 June 2018 DOI: 10.1002/job.2316 J Organ Behav. 2019;40:105–122. © 2018 John Wiley & Sons, Ltd.wileyonlinelibrary.com/journal/job 105 1 | INTRODUCTION In conjunction with employment relationships becoming shorter and more flexible, the planning and managing of careers has become more self‐directed (Sullivan & Baruch, 2009). At the same time, traditional conceptualizations of careers as “a job for life” (Simons, Goddard, & Patton, 2000) or “upward progression within one or two organiza- tions” (Eby, Butts, & Lockwood, 2003) have become less salient. In order to achieve career success, employees in this more dynamic, boundaryless career context are thus being advised—and expected— to manage their careers proactively (Direnzo & Greenhaus, 2011; Verbruggen & Sels, 2010). Proactive behaviors refer to behaviors that are self‐initiated, future‐oriented, and change‐inducing (Grant & Ashford, 2008). They can take a variety of forms such as voice, personal initiative, feedback seeking, and issue selling (Parker & Collins, 2010). This study focuses on one set of proactive behaviors—proactive career behaviors—which refer to self‐directed activities individuals engage in to manage their careers (Seibert, Kraimer, & Crant, 2001). Research shows that proactive career behaviors are positively related to career success (De Vos, Dewettinck, & Buyens, 2009; Verbruggen, Sels, & Forrier, 2007). However, this research comprises a small number of studies demonstrating the positive effect of career initiatives (Seibert, Kraimer, & Crant, 2001), career‐enhancing strategies (Nabi, 1999), and career self‐management (Abele & Wiese, 2008) on objective career success (e.g., salary and promotions). In contrast, studies on the effects of proactive career behaviors on subjective career success (e.g., perceived career success and career satisfaction) are scarce, inconclusive, and do not acknowledge the multidimensionality of the subjective career success concept. Subjective career success, which “capture (s) individuals' subjec- tive judgments about their career attainments” (Ng, Eby, Sorensen, & Feldman, 2005, p. 368), has emerged as an important variable in careers research. Objective career success, such as promotions and increases in salary, is often not available to everyone in organizations, especially because organizations have become flatter and careers less hierarchical and predictable. Therefore, other evaluation criteria—how personally meaningful careers are and how one experiences one's own career success—have become more salient (Ng & Feldman, 2014). Furthermore, satisfaction with one's career has been shown to be important in understanding people's life satisfaction, more important than job satisfaction, for example, (Erdogan, Bauer, Truxillo, & Mansfield, 2012). For both of these reasons, it is beneficial for organi- zations to understand how employees feel about their subjective career success and what affects it. Individuals from different cultures are likely to use different means and to be led by different values and norms when evaluating how successful various aspects of their careers have been (Dries, Pepermans, & Carlier, 2008). It is thus problematic that the vast major- ity of studies on proactive career behaviors have been conducted in single countries, predominantly the United States (Seibert, Kraimer, & Crant, 2001; Shockley, Ureksoy, Rodopman, Poteat, & Dullaghan, 2016) and Western Europe (e.g., De Vos et al., 2009; Verbruggen et al., 2007). Because these countries mostly reflect the WEIRD perspective—Western, Educated, Industrialized, Rich, and Democratic countries (Henrich, Heine, & Norenzayan, 2010)—where a strong emphasis on self‐management is more prevalent (Inkson, Gunz, Ganesh, & Roper, 2012)—the positive consequences of proactive career behaviors may not be surprising. Although this research has contributed to our understanding of the effects of career proactivity, the lack of cross‐country research has meant that we are unable to draw conclusions about whether these effects are generalizable across cultures (cf. Shockley et al., 2016; Pan & Zhou, 2015). Collectively, important questions remain regarding whether proactive career behaviors are equally beneficial for different aspects of an individual's subjective career success, and the extent to which these benefits vary across cultures. We focus on the relationship between proactive career behaviors and the perceived achievement of two inherently different meanings of subjective career success that have been shown to be consistently important yet are sensitive to cultural differences (Briscoe, Hall, & Mayrhofer, 2012; Chudzikowski et al., 2012)—subjective financial success and work‐life balance. This study thus sets out to address the following research questions: Are proactive career behaviors associated with higher levels of subjective career success in the form of financial success and work‐life balance, and to what extent are these relationships influenced by national culture? Based on a multi‐country dataset, we develop and test hypotheses on the relationship between proactive career behaviors and subjective financial success and work‐life balance, as well as the moderating role of five dimensions of culture (in‐group collectivism, humane orientation, power distance, uncertainty avoidance, and performance orientation). The study seeks to contribute to the literature in two main ways. First, by investigating career proactivity and two different dimensions of subjective career success, the study contributes to the careers liter- ature by shedding light on the extent to which the positive outcomes of proactive career behaviors extend beyond the objective measures of career success to include different personal meanings of subjective career success. And second, by examining the moderating role of culture across a large number of Western and non‐Western countries, the study contributes to the general proactivity literature by revealing how the cultural context, within which individuals enact their proactive behaviors and form assessments about their subjective career success, influences the relationship between proactivity and attitudinal outcomes. 2 | THEORETICAL MODEL AND HYPOTHESES 2.1 | Proactive career behaviors and subjective career success Proactive career behaviors in the careers literature have included indi- vidual career management (Sturges, Guest, Conway, & Davey, 2002; Verbruggen et al., 2007), career self‐management (Abele & Wiese, 2008; De Vos & Soens, 2008), and career‐enhancing strategies (Nabi, 2003), all generally referring to the self‐directed activities employees display with respect to managing their careers (Seibert, Kraimer, & Crant, 2001). These behaviors allow individuals to make a realistic 106 SMALE ET AL. self‐assessment of their capabilities in light of organizational career opportunities and include concrete actions undertaken to realize these ambitions (Sturges et al., 2002). In this study, we focus on an individual's behavioral proactivity in the form of Enacted Managerial Aspirations (EMA), which includes career planning, skill development, and consultation with more senior colleagues (Tharenou & Terry, 1998). Despite what this label suggests, these behaviors are important regardless of whether one aspires to be a manager or not (Parker & Collins, 2010). Compared with studies on objective career success, empirical work concerning the effects of career proactivity on subjective perceptions of success is scarce and inconclusive. For instance, although subjective career success is positively affected by career strategies such as networking (Nabi, 1999), creating opportunities (Park, 2010), and career planning (Murphy & Ensher, 2001), Nabi's (1999) study also points to the negative influence of individual efforts at developing skills useful for future promotions. Similarly, in terms of career satisfaction, there is evidence for both positive (Abele & Wiese, 2008; Raabe, Frese, & Beehr, 2007) and insignificant (De Vos & Soens, 2008) effects of self‐directed career behaviors. Potential explanations for these mixed findings are that subjective career success has not been treated as a multidimensional concept, and the studies have been conducted in different single‐country settings. Regarding the former, the scale validation study by Shockley et al. (2016) provides strong evidence that subjective career success, like job satisfaction, should be considered as an aggregate, multidi- mensional construct (Law, Wong, & Mobley, 1998). Although one can thus examine subjective career success as a global construct, their study's relative importance analyses strongly support the need to study the individual dimensions in order to provide more nuanced explanations. Here, we focus on two dimensions of subjective career success: a sense of achieving financial success and a sense of achieving work‐life balance. We define subjective financial success as how happy individ- uals are with their level of achievement in terms of financial rewards (e.g., money, incentives, and bonuses), with an emphasis on perceived wealth accumulation rather than financial security (Kets de Vries, 2010). It is important to note that subjective financial success is related to but not the same as objectively defined financial success, as individuals consider a range of factors when evaluating (subjec- tively) their own financial success. For instance, although career satis- faction has been shown to be positively associated with indicators of objective career success such as salary (see the Ng et al. (2005) meta‐analysis), research has also suggested that “within each level of wealth and occupational status, some people view their careers as much more (or less) successful than do others” (Heslin, 2005a, p. 377). Our second dependent variable, perceived work‐life balance, is defined as how happy individuals are with their level of achievement in finding a balance between work on the one hand and nonwork/ family life on the other (Guest, 2002). These two dimensions of subjective career success were chosen because they have a long tradition in careers research (Arthur, Khapova, & Wilderom, 2005) and have been used in most of the stud- ies that were part of a recent review of career success research from the past 30 years (Shockley et al., 2016). In addition, cross‐cultural careers research has shown that these two meanings of career success can be found among employees in countries all around the world (Briscoe et al., 2012; Zhou, Sun, Guan, Li, & Pan, 2013), yet their salience differs in accordance with cultural and institutional variations (Chudzikowski et al., 2012; Khapova, Briscoe, & Dickmann, 2012). There have been various attempts to categorize the different meanings of subjective career success. In the selection of our two dependent variables, we opted for financial success and work‐life balance because these meanings of career success have been shown, in qualitative studies, to belong to different categories. Subjective financial success is the more traditional notion of career success and is related to the “person” (Demel, Shen, Las Heras, Hall, & Unite, 2012) and their self‐oriented “material concerns” (Mayrhofer et al., 2016). Work‐life balance, on the other hand, is related to an individual's “interaction with the environment” (Demel et al., 2012) and their other‐oriented “social relations” (Mayrhofer et al., 2016). Focusing on these two dimensions thus offers the possibility to analyze the association between career proactive behaviors and two different yet core meanings of subjective career success. It also allows us to examine proactive career behaviors and two dimensions of career success that are both identifiable in different country contexts yet are likely to be influenced by national culture in different ways. In developing our hypotheses, we draw on arguments from the proactivity literature (Parker & Collins, 2010; Seibert, Kraimer, & Crant, 2001) regarding why an individual's proactive career behav- iors contribute to subjective career success. Based on social informa- tion processing theory (Salancik & Pfeffer, 1978), which suggests that an individual's attitudes are also going to be shaped by the informational and social context within which their behaviors are carried out, we go on to argue how certain dimensions of national culture are likely to moderate this relationship. Figure 1 presents our conceptual model. The proactivity literature characterizes proactive career behav- iors as involving three core components, namely, taking control, anticipation, and information retrieval (Parker & Collins, 2010; Seibert, Kraimer, & Crant, 2001). First, proactive behaviors involve taking control, implying that employees engaging in proactive career behaviors consciously take control of their careers. Proactive career behaviors are likely to be experienced as volitional and self‐endorsed, which should satisfy the basic need for autonomy (Broeck, Ferris, Chang, & Rosen, 2016; Gagné & Deci, 2005). This can, in turn, induce feelings of personal success and accomplishment (Baard, Deci, & Ryan, 2004), where one emphasizes the self as the locus of causality for one's own behaviors (DeCharms, 1968). In support of this, feeling in control of one's career has been associated with higher levels of subjective career success (Raabe et al., 2007; Seibert, Kraimer, & Crant, 2001), because through proactivity, one can achieve personally valued goals, which enhance career satisfaction (Barnett & Bradley, 2007). Turning to anticipation, acting in advance of a future situation— here, the aspired realization of one's personal career goals—has been shown to be positively related to subjective career success (Verbruggen & Sels, 2010). It is even suggested that working on one's goals can be more important for achieving satisfaction than actually SMALE ET AL. 107 realizing one's goals (Amabile & Kramer, 2011; Lent & Brown, 2008). This is partly attributable to the fact that behaviors people are committed to tend to induce positive attitudes via a behavioral rationalization process (Salancik & Pfeffer, 1978). In terms of information retrieval, proactive career behaviors should facilitate access to relevant career information and resources that will help individuals to improve the fit between their aspired and perceived current career position (e.g., Forret & Dougherty, 2004; Heslin, 2005a; Ng et al., 2005). Information retrieval can be seen as an important form of feedback seeking, which can also improve an individuals' reputation and influence within the organization (De Vos & Soens, 2008; Sturges, Conway, Guest, & Liefooghe, 2005), which in turn influences career satisfaction (Judge & Bretz, 1994). These three mechanisms underlying proactive behaviors suggest that proactive individuals who pursue their goals will derive greater satisfaction, including feelings of career success, from the actions they undertake to this end (Parker & Liao, 2016). As reflected in extant research, we expect that these powerful mechanisms will extend across different dimensions of subjective career success, in this case both subjective financial success and work‐life balance. We therefore present the following hypothesis: Hypothesis 1. An individual's proactive career behav- iors are positively related to subjective career success in the form of (a) financial success and (b) work‐life balance. 2.2 | Moderating role of national culture Social information processing theory posits that the relationship between individuals' behaviors and their attitudes depends on the social context, because individuals, as adaptive organisms, adjust their attitudes to the informational and social environment within which their behaviors are embedded (Salancik & Pfeffer, 1978). We argue that a central aspect of the social context that will affect the relation- ship between proactive career behaviors and career attitudes is national culture. Although there are points of contention regarding the conceptualization and measurement of culture (Caprar, Devinney, Kirkman, & Caligiuri, 2015), we adopt the frequently used definition of culture as a system of values, practices, attitudes, and behavioral norms that are shared by members of a societal group and are passed on from generation to generation (Thomas & Peterson, 2015). Culture has emerged as “a primary candidate” for a “source for [career] differences and peculiarities” (Briscoe et al., 2012, p. 7). Culture can influence careers by affecting individual perceptions, attitudes, and beliefs and through the societal legitimization of career practices, values, and norms (Khapova et al., 2012; Thomas & Inkson, 2007). These cultural influences, in turn, can affect various individual career behaviors and attitudes (Ollier‐Malaterre, Valcour, Den Dulk, & Kossek, 2013). Studies have thus started to explore the role of culture in career success (Mayrhofer et al., 2016), career transitions (Chudzikowski et al., 2009), career meanings (Claes & Ruiz‐Quintanilla, 1994), and career commitment (Noordin, Williams, & Zimmer, 2002). Drawing upon the social information processing framework and the three core components of proactivity, we argue that culture will affect the baseline relationship between proactive career behaviors and subjective career success in different ways. First, culture exerts a social influence on the extent to which proactive career behaviors are seen as expected by significant others in a given social context (e.g., boss, colleagues, and family) and therefore the degree to which individuals who engage in these behaviors are likely to experience them as volitional. Specifically, if the behavior is congruent with the social context, that is, when “social guidance” provides sufficient external justification for engaging in a certain behavior (Vaux, Riedel, & Stewart, 1987), individuals will experience the behavior as less voli- tional, and the attitudes associated with proactive behaviors generally will be less positive. Second, culture will affect how people interpret their own needs and values and, thus, which career goals they are likely to focus on (Salancik & Pfeffer, 1978). In this way, national culture can affect the anticipation component of proactive behavior. According to social information processing theory, individuals understand and shape their needs, values, and perceptions based on interactions with others, and this social influence provides a lens through which individuals make evaluations of their work and career environment (Bhave, Kramer, & Glomb, 2010). For instance, a culture in which financial success is highly valued may lead individuals to believe that financial success should be important to themand that they should direct their career goals towards achieving financial success. Consequently, when individuals engage in anticipatory, proactive career behaviors, these behaviors are likely to be oriented towards achieving financial success. These behaviors are then likely to be more strongly related with individuals' feelings of financial success either because of this emphasis or via a behavioral rationalization process (Salancik & Pfeffer, 1978). FIGURE 1 The theoretical model of proactive career behaviors, national culture, and subjective career success 108 SMALE ET AL. Third, culture will affect the kind of information and resources peo- ple are likely to obtain in a certain context—and thus the information retrieval component of proactive behavior. Social information process- ing theory suggests that the informational environment affects an individual's attentional processes towards the most salient aspects of that context (Salancik & Pfeffer, 1978). Therefore, the information and resources people obtain through their proactive career behaviors are likely to be in line with the most salient aspects of their culture. This is likely to contribute to individuals achieving those career goals that are most congruent with the prevailing values and norms of that culture. When considering the dimensions of culture, like Rabl, Jayasinghe, Gerhart, and Kuhlmann (2014), we followed the advice of Zaheer, Schomaker, and Nachum (2012) and focused on carefully selected dimensions that extant research shows to be the most relevant in understanding how proactive career behaviors might be differentially effective in different parts of the world.1 Taken from the GLOBE stud- ies framework (House, Hanges, Javidan, Dorfman, & Gupta, 2004), we thus examine the moderating roles of five cultural dimensions (“prac- tices”) that have been shown to have important contextual effects on careers or career proactivity: in‐group collectivism (e.g., Spector et al., 2007), humane orientation (e.g., Ollo‐López & Goñi‐Legaz, 2017), power distance (e.g., Ramaswami, Huang, & Dreher, 2014), uncertainty avoidance (e.g., Claes & Ruiz‐Quintanilla, 1998), and per- formance orientation (e.g., Gentry, Weber, & Sadri, 2008). 2.3 | In‐group collectivism The GLOBE studies (House et al., 2004) define in‐group collectivism as the degree to which individuals express pride, loyalty, and cohesive- ness in their organizations or families. In individualistic societies (i.e., low on in‐group collectivism), individuals view themselves as relatively independent and free to pursue behaviors that benefit them without extensive consideration of the consequences for the larger collective. They exhibit greater preference for social recognition, career advance- ment, and merit‐based promotions and are more motivated by compe- tition and report lower normative and affective commitment (Khapova et al., 2012). Individuals in collectivist societies (i.e., high on in‐group collectivism) view themselves as interdependent with members of the group(s) to which they belong, are concerned about the conse- quences of their behaviors for their reference group(s), and are more likely to sacrifice personal interests for the benefit of the larger collec- tive. In collectivistic countries, people tend to prioritize common goals, including family ones, over personal needs (Haar, Russo, Suñe, & Ollier‐Malaterre, 2014). Accordingly, we argue that societies that differ on this dimension are likely to view financial success and work‐life balance differently in terms of legitimacy. This will also affect how salient subjective financial success and work‐life balance are to individuals within a culture. In cul- tures high on in‐group collectivism, the pursuit of individual financial success can be seen as a challenge to group harmony (Noordin et al., 2002). At the same time, a greater number of important social referents (employer and family) will be advocating the pursuit of work‐life balance. The social information processing perspective would suggest that in an environment that endorses work‐life balance as a more legit- imate goal to pursue and discourages the pursuit of financial success, it will be easier for individuals to rationalize their proactive career behav- iors as being instrumental for their feelings of greater work‐life balance, but not for feelings of financial success. Further, individuals are more likely to direct their proactive career behaviors in such a way that they can obtain resources, support, and information that advances their pur- suit of work‐life balance rather than the pursuit of subjective financial success. This leads us to the following hypotheses: Hypothesis 2a. In countries higher on in‐group collectiv- ism, the positive relationship between proactive career behaviors and subjective financial success will be weaker. Hypothesis 2b. In countries higher on in‐group collec- tivism, the positive relationship between proactive career behaviors and work‐life balance will be stronger. 2.4 | Humane orientation Humane orientation is defined as “the degree to which an organization or society encourages and rewards individuals for being fair, altruistic, friendly, generous, caring and kind to others” (House et al., 2004, p. 569). Societies high on humane orientation are characterized by a shared understanding that the interests of others are important. Behav- iors that promote the well‐being of others (e.g., family and colleagues) are expected, and people are motivated by a sense of affiliation and belonging (House et al., 2004), with equality and nondiscrimination as important underlying values. Individuals are expected to be motivated by a desire to be friendly and caring towards others rather than by a drive to advance one's own interests. In such societies, the pursuit of one's own interests for the purposes of accumulating material posses- sions will not be seen as important or legitimate (Khapova et al., 2012). In line with social information processing logic, we therefore argue that in countries with a higher humane orientation, the prevail- ing cultural practices will make it difficult for individuals to construct a meaning for their enhanced sense of financial success as due to their proactive career behaviors. However, in such countries, where cultural practices make affiliation, generosity and the well‐being of others both more salient and expected of individuals, the achievement of greater work‐life balance is likely to be seen as a socially legitimate reason for career proactivity and thus more likely to strengthen this positive relationship. We thus propose the following hypotheses: Hypothesis 3a. In countries higher on humane orienta- tion, the positive relationship between proactive career behaviors and subjective financial success will be weaker. Hypothesis 3b. In countries higher on humane orienta- tion, the positive relationship between proactive career behaviors and work‐life balance will be stronger. 2.5 | Power distance Power distance concerns society's views about individual status and the degree to which it accepts that there is an unequal distribution 1We thank an anonymous reviewer for suggesting the examination of Humane Orientation as a potentially useful moderator. SMALE ET AL. 109 of power and authority. High power distance cultures are characterized by strong hierarchies and control mechanisms, less communication among organizational levels, and limited upward social mobility (Hofstede, 1993). In contrast, in low power distance cultures, organiza- tions are decentralized, employees expect to be consulted, and author- ity figures are viewed as resourceful democrats (Hofstede, 1993). In high power distance countries, power is seen as providing social order, and information access is often restricted (House et al., 2004). Superiors in high power distance cultures are particularly influential career “gate- keepers” (King, 2004), requiring individuals to look to their superiors for guidance in their pursuit of subjective career success. In such cultures, financial success is a material and visible representation of one's per- sonal status, and as such, it is highly respected and valued, and its pursuit is both legitimate and socially endorsed. Achievingwork‐life balance, on the other hand, is likely to be seen as a comparatively lower priority and its pursuit not actively encouraged. In such settings, employees are more likely to channel their career proactive behaviors in ways that can enhance their feelings of financial achievement rather than in ways that could contribute to their perceived work‐life balance. They will also be more likely to develop a rationalization for their proactive behaviors as being instrumental for their pursuit of subjective financial success, which is viewed as a legitimate, even expected, course of action. Thus Hypothesis 4a. In countries higher on power distance, the positive relationship between proactive career behav- iors and subjective financial success will be stronger. Hypothesis 4b. In countries higher on power distance, the positive relationship between proactive career behav- iors and work‐life balance will be weaker. 2.6 | Uncertainty avoidance Project GLOBE defines uncertainty avoidance as the way people in a given society deal with unforeseen events and change. Countries that score low on uncertainty avoidance tend to be better at accepting change, are more willing to take risks, and favor informal interactions instead of regulating situations with predetermined norms (House et al., 2004). Countries that score high on uncertainty avoidance tend to be more change‐aversive and resistant, take only minimal risks, and set up a number of rules and procedures to manage the unpredictabil- ity of the future. High uncertainty avoidance cultures tend to create detailed plans, seek feedback, and enforce rules, attempting to minimize the likelihood and impact of unforeseen events. Given this emphasis on predictability and formal rules that can be seen as impos- ing restraints on individual initiative, high uncertainty avoidance cultures are unlikely to signal to individuals that career proactivity is an expected or socially legitimate behavior. Instead, it views proactivity as being of limited use relative to the formal procedures and collectively held norms that are in place (Fischer, 2008). However, unlike the previous dimensionswe have presented, the lit- erature does not provide grounds to suggest that cultures characterized by high uncertainty avoidance will place a greater value on the pursuit of financial success over work‐life balance, or vice versa. Formal rules are perhapsmore easily identifiable at the workplace, but strong informal norms are likely to act as “social guidance”onwhat individuals are encour- aged to pay attention to outside of work as well. We expect that in high uncertainty avoidance cultures, the pathways to greater perceptions of financial success as well as work‐life balance would be constructed as previously defined by existing rules, societally endorsed norms, and established ways of doing things, rather than as attributable to individual taking control, anticipation, and information retrieval (Ollo‐López &Goñi‐ Legaz, 2017).We therefore posit that uncertainty avoidance has a similar negative moderating influence on the relationship between proactive career behaviors and the two facets of subjective career success. Hence Hypothesis 5a. In countries higher on uncertainty avoid- ance, the positive relationship between proactive career behaviors and subjective financial success will be weaker. Hypothesis 5b. In countries higher on uncertainty avoidance, the positive relationship between proactive career behaviors and work‐life balance will be weaker. 2.7 | Performance orientation Countries that score high on performance orientation value competi- tiveness, individual achievement, feedback that supports performance improvements and what one has done (achieved status) over who one is (ascribed status; House et al., 2004). Conversely, countries low on performance orientation value harmony, quality of life, belongingness, and societal/family relationships and view behaviors that may jeopar- dize this harmony in a negative light, considering them as a potential source of conflict. High performance orientation societies will place more value on seeking performance improvements and on personal achievement (i.e., achieved status). In such contexts, materialism and the pursuit of financial success are more likely to be socially legiti- mized compared with prioritizing work‐life balance. In line with social information processing theory, individuals in high performance orientation cultures will be more sensitized towards pursu- ing financial success and will attach less salience to achieving work‐life balance, which one might associate more with low performance orienta- tion cultures. In light of this, it will be easier for individuals to view proac- tive career behaviors as having returned a greater sense of achievement in the pursuit of financial success, which will not be the case for the pursuit of work‐life balance. Our final set of hypotheses is thus Hypothesis 6a. In countries higher on performance ori- entation, the positive relationship between proactive career behaviors and subjective financial success will be stronger. Hypothesis 6b. In countries higher on performance orientation, the positive relationship between proactive career behaviors and work‐life balance will be weaker. 3 | METHOD 3.1 | Sample and data collection Our individual‐level data are from a large, multi‐country, cross‐cultural research project, which builds on earlier qualitative work from this 110 SMALE ET AL. same project (Shen et al., 2015). The questionnaire was translated and back‐translated to the local languages of all participating countries following standard procedures (Brislin, 1970). Data were collected during 2014–2015 by national representatives of the research collab- oration using predetermined screening criteria to achieve heteroge- neous within‐country samples (cf. Cook & Campbell, 1979) with regard to relevant respondents' demographic characteristics (i.e., work experience, occupation, and age).2 Each national sample includes indi- viduals who have at least 2 years of post‐educational work experi- ence, close to equal, tripartite age distribution (under 30; 30–50; over 50 years), and is gender balanced. The target was at least 400 respondents per country with 100 from each of the following occupa- tional categories: managers, professionals, clerical/service workers, and skilled workers.3 The final sample comprised 11,892 participants from 22 coun- tries (Argentina, Austria, China, Finland, Germany, Greece, India, Italy, Japan, Malawi, Mexico, Nigeria, Norway, Pakistan, Portugal, Russia, Serbia, Slovakia, Slovenia, South Korea, Switzerland, and the United States), representing nine of GLOBE's 10 cultural regions (all but the Middle East cluster). The average age of the respondents was 40 years, and they had an average of 16 years of work experience and were positioned, on average, in the middle of their organizational hierarchy (5.56 on a 10‐point scale). Gender distribution was equal at 50%, with 34% categorizing themselves as professionals, 26% as managers, 24% as clerical/service, and 16% as skilled workers. In terms of highest educational level achieved, 11% of participants had lower secondary education or below, 35% had upper secondary, post- secondary, or short‐cycle tertiary education, and 54% had tertiary education. 3.2 | Measures 3.2.1 | Subjective career success Because our research is cross‐cultural, we used a newly developed, culturally invariant scale of subjective career success (Briscoe et al., 2014). The scale is multidimensional and captures the achievement and importance aspects of different dimensions of subjective career success (cf. Greenhaus, Parasuraman, & Wormley, 1990; Gunz & Heslin, 2005). In this study, we used the achievement aspect of sub- jective career success. For each career dimension, participants were asked to report on a 5‐point scale (from strongly disagree to strongly agree), “in regard to this career aspect, I have achieved a level I am happy with.” Financial Success was measured with respect to (a) wealth, (b) receiving incentives, perks, or bonuses, and (c) steadily making more money (α = 0.74; composite reliability [CR] = 0.75). Work‐Life Balance (WLB) was measured in the same way in regard to (a) achieving a satisfying balance between work and family life, (b) hav- ing time for nonwork interests, and (c) achieving balance between work and nonwork activities (α = 0.79; CR = 0.79). Both scales were examined for measurement equivalence with the alignment procedure for establishing metric and scalar invariance (Asparouhov & Muthén, 2014). The overall non‐invariance was 15.0% for WLB and 18.17% for financial success, which is below the 25% threshold set by Muthén and Asparouhov (2014, p. 3). Confirmatory factor analyses showed convergent and discriminant validity for both measures. 3.2.2 | Proactive career behaviors Proactive career behaviors were operationalized using Tharenou and Terry's (1998) scale for EMA. Due to the factor loading of one of the items in the original validation study, and in line with previous research (Parker & Collins, 2010), we used five of the six original EMA items, which were reported on a 7‐point scale ranging from never to very frequently: (1) I have discussed my career prospects with some- one with more experience in the department/organization; (2) I have discussed my aspirations with a senior person in the department/orga- nization; (3) I have engaged in career planning; (4) I have sought feed- back on my performance; and (5) I have updated my skills in order to be more competitive for promotion (α = 0.85; CR = 0.85). This scale was also examined for measurement invariance: 12.0% of item‐coun- try combinations were non‐invariant, which is again below the sug- gested threshold (Muthén & Asparouhov, 2014, p. 3). 3.2.3 | National culture For country‐level data on cultural dimensions, we used the published country scores from the GLOBE project (House et al., 2004). The cul- tural measures used reflect reported practices (“as is”) and indicate the perceptions of each culture (as opposed to cultural aspiration values, “should be”). Aspiration values refer to the society's ideal values, whereas practical values measure the society's actual engagement in a particular value. Although the GLOBE study is not without critics (e.g., Hofstede, 2006), the use of the GLOBE measures is widely accepted in cross‐cultural research and cross‐cultural management scholars commonly use cultural practices when attempting to investi- gate the effects of societal culture on performance and other out- comes (for a review, see Tung & Verbeke, 2010). The country data for our targeted cultural dimensions (i.e., in‐group collectivism, humane orientation, power distance, uncertainty avoidance, and per- formance orientation) were available for 17 of our 22 countries, so the remaining five countries (Malawi, Norway, Pakistan, Serbia, and Slovakia) were excluded from the analyses testing the cultural moder- ation hypotheses (Hypotheses 2a–6b). 2We intentionally utilized stratified purposive sampling (Kothari, 2004; Orcher, 2016) as our sampling strategy in this multi‐country study as a priori research has shown that different strata of workforce respondents may have unique, different, or important perspectives (Kothari, 2004) not just by work country but also by occupation and age (Ng et al., 2005; Seibert, Kraimer, & Liden, 2001). Additionally, given the increasingly widespread long‐term trend of greater numbers of women in the workforce in developed and developing countries (Beck, 2014), we sought to peg each country's sample as close to a 50/50 male/female split to ensure representation for this demographic variable. In these ways, we sought a cross‐contextual sample (Robinson, 2014) where the heterogeneity of the sample was such that any commonality found across such a diverse set of cases would be more likely to be a widely generalizable theoret- ical phenomenon versus a commonality found among a more homogeneous set of cases (Kothari, 2004; Orcher, 2016). 3The cultural representativeness of the respondents was ascertained post hoc by conducting supplemental descriptive analyses, which indicated that coun- try‐level aggregation of the self‐perceived importance of financial success and work‐life balance showed consistencies with GLOBE clustering (House et al., 2004) for scores on performance orientation and human orientation, respectively. SMALE ET AL. 111 3.2.4 | Control variables We included a number of relevant controls based on the meta‐analysis of career success antecedents by Ng et al. (2005). These included age in years, gender (1 = male, 0 = female), and educational level (1 = primary education, 2 = lower secondary, 3 = upper secondary, 4 = postsecond- ary non‐tertiary or short‐cycle tertiary, 5 = bachelor's degree, 6 = master's degree, 7 = doctorate). Because seniority is likely to affect perceptions of financial success and work‐life balance, we also included hierarchical level and whether the respondent was currently a manager of others in their organization (1 = yes, 0 = no). To measure hierarchical level, participants were asked to use a number between 1 and 10 to depict their position in the organization's hierarchy (1 = highest level [CEO or President], 10 = lowest level). Because subjective career success is likely to be the result of both organizational and individual career management (De Vos et al., 2009; Sturges et al., 2005), we included two further controls to capture orga- nizational career support: perceived investment in employee development (PIED) and size of the organization. Perceived investment in employee development was measured based on a scale by Lee and Bruvold (2003) and further developed by Kuvaas and Dysvik (2009), which consisted of 7 items on a 5‐point scale ranging from strongly disagree to strongly agree. Example items include “by investing resources in employee development, my organization demonstrates that it actually invests in its employees” and “my organization invests heavily in employee development” (α = 0.92; CR = 0.92). The size of the organiza- tion—a proxy for the amount of resources an organization has to distrib- ute to its employees (Whitely, Dougherty, & Dreher, 1991)—was measured in six classes ranging from “less than 10 employees” to “more than 5,000.” Lastly, to control for country‐level effects in cross‐level interaction analyses, we included a robust indicator of the general development of a country. We used the Human Development Index— the United Nations' composite statistic of life expectancy, education, and per capita income indicators.We used the levels reported for 2015. 3.3 | Confirmatory factor analysis and test of common method variance We first assessed our measurement model using confirmatory factor analysis (CFA). As our data for latent, multi‐item variables were nested within countries, we first assessed independence. The ICC (1) for items of our latent variables had the following ranges: EMA (0.071 to 0.131), WLB (0.033 to 0.056), and financial success (0.057 to 0.14). We controlled for the nesting of observations without explicitly modeling factors at individual and country level by using Mplus 7.4 (Muthén & Satorra, 1995). The CFA results demonstrated an adequate fit of our measurement model with the data (RMSEA = 0.025; CFI = 0.955; TLI = 0.946; SRMR = 0.028).4 Given the cross‐sectional nature of our data, we examined the pos- sibility that our results were affected by common method variance (CMV). We thus performed an additional CFA, allowing all items to load on a single factor. The results of this measurement model indicated a poorer fit with our data (RMSEA = 0.08; CFI = 0.528; TLI = 0.465; SRMR = 0.143). We then used a common latent factor and marker var- iable technique (cf. Williams, Hartman, & Cavazotte, 2010) to examine the amount of variance due to CMV. Our analyses showed that the var- iance ranged between 16.2% (marker variable) and 17.9% (common fac- tor), which is well below the 50% threshold (Hair, Anderson, Tatham, & Black, 1998). Thus, although we cannot rule out CMV, it does not appear to represent a serious threat to our results. 3.4 | Analytical procedure Our analytical strategy involved incorporating our hypothesized cross‐ level interactions, while also taking into account that our data were nested, skewed, and that we had some missing data. Because we had constructs at two levels, and the ICC (1) levels of our dependent variables indicated that variance existed at both levels of analyses (ICC [1] for financial success was 0.114 and for WLB was 0.054), we utilized multilevel modeling in Mplus 7.4 (Muthén & Muthén, 2016). To reduce the number of estimated parameters and to accommodate for the estimation of interaction effects across levels, we calculated the simple means of our items as manifest variables. We used the full information likelihood procedure to resolve the missing data problem, and we used robust maximum likelihood (MLR) estimators wherever possible in our analyses to address the issue of skewed data. We carried out our multilevel modeling by first estimating an inter- cept only (null) model, followed by two random intercept models to esti- mate the fixed effects of individual‐level variables. For models where cross‐level interactions were examined (i.e., those including the modera- tion by each cultural dimension), we adopted random intercept and slope models. Consistent with our theoretical approach, all independent vari- ables were grand‐mean centered beforemodel estimation.We estimated two series of empirical models. One series of models (1–3 and 7–11) pre- dicted career success in the form of subjective financial success, whereas the other series (4–6 and 12–16) predicted career success in the form of subjectivework‐lifebalance. For allmultilevelmodels,we report fixedand random effects, deviance, deviance change to respective models (and their significance), and Pseudo R2. Reports of random effects for random intercept models feature residual variance between andwithin countries, whereas reports for random intercept random slope models additionally include residual slope variance between countries and residual covari- ance between intercept and slope across countries. 4 | RESULTS Table 1 presents the descriptive statistics (means, standard deviations, and bivariate correlations) of the variables used at both levels. In Hypothesis 1a,b, we argued that an individual's proactive career behaviorswould be positively related to her/his subjective career success in the formof financial success (Hypothesis 1a) andWLB (Hypothesis 1b). Model 3 inTable 2 shows that the relationship between proactive career 4Based on the CFA, we also calculated average variance extracted (AVE) and composite reliability (cf. Fornell & Larcker, 1981). AVE was above the 0.5 threshold for all constructs: 0.54 for EMA, 0.55 for WLB, and 0.5 for financial success. This is an indication of the convergent validity of our measures. Finally, we calculated the square root of AVE for all latent variables and compared these values to correlations with other latent variables. All square roots of AVE were higher than the respective correlations, demonstrating support for the claim that our latent variables are distinct. 112 SMALE ET AL. behaviors and subjective financial success was positive and statistically significant (γ = 0.094, p < 0.001). Model 6 inTable 3 shows that the rela- tionship between proactive career behaviors and WLB was positive, but not statistically significant (γ = 0.037, p = 0.126). Hence, Hypothesis 1a was supported, whereas Hypothesis 1b was not. The next set of hypotheses concerned the cross‐level interactions of the national culture dimensions and proactive career behaviors in predicting subjective financial success and WLB. Hypotheses 2a and 2b predicted that the positive relationship between proactive career behaviors and financial success (Hypothesis 2a) will be weaker and the positive relationship between proactive career behaviors and WLB (Hypothesis 2b)will be stronger in countrieswith higher in‐group collec- tivism. Model 7 inTable 4 and Model 12 inTable 5 present the respec- tive results. Although the estimation for subjective financial success TABLE 1 Descriptive statistics: Means, standard deviations (SD), and bivariate correlations among variables Variable Mean SD 1 2 3 4 5 6 7 8 9 Level 1 1 Gender 0.50 0.50 2 Age 39.89 10.79 0.024** 3 Education 4.48 1.39 0.004 −0.084** 4 Manager 0.43 1.39 0.146** 0.113** 0.154** 5 Hierarchical level 5.56 2.29 −0.067** −0.124** −0.228** −0.271** 6 PIED 3.11 0.94 0.035** −0.022* 0.047** 0.133** −0.097** 7 Size of organization 3.67 1.56 0.052** 0.032** 0.167** 0.037** 0.084** 0.105** 8 Proactive career behaviors 3.97 1.47 0.079** −0.248** 0.191** 0.170** −0.101** 0.264** 0.089** 9 Work‐life balance 3.64 0.85 −0.034** 0.082** −0.068** −0.001 −0.053** −0.044** 0.049** 0.196** 10 Financial success 3.29 0.89 0.081** 0.088** 0.022* 0.193** −0.152** 0.027** 0.168** 0.365** 0.363** Level 2 1 In‐group collectivism 5.12 0.66 2 Humane orientation 3.93 0.36 0.437 3 Power distance 5.27 0.29 0.536* −0.116 4 Uncertainty avoidance 4.32 0.64 −0.440 0.017 −0.624** 5 Performance orientation 4.09 0.45 −0.220 0.300 −0.488* 0.611** 6 HDI 0.83 0.11 −0.675** −0.580* −0.439+ 0.041 0.050 Note. Level 1 (n = 11,445 to 11,892); Level 2 (n = 17). PIED: perceived investment in employee development; HDI: Human Development Index. +p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001. TABLE 2 Multilevel models predicting subjective financial success Model 1 Model 2 Model 3 Intercept 10.791 (1.497)*** 13.248 (1.772)*** 13.337 (1.848)*** Level 1 Manager 0.093 (0.018)*** 0.084 (0.018)*** Gender 0.044 (0.012)*** 0.040 (0.012)** Size of organization −0.005 (0.018) −0.012 (0.021) Age 0.094 (0.017)*** 0.117 (0.016)*** Education −0.006 (0.022) −0.017 (0.023)* Hierarchical level −0.065 (0.038)+ −0.059 (0.037) PIED 0.334 (0.025)*** 0.315 (0.023)*** Proactive career behaviors 0.094 (0.021)*** Variance components Residual variance (within) 0.716 (0.037)*** 0.607 (0.031)*** 0.602 (0.030)*** Residual variance (between) 0.092 (0.026)*** 0.057 (0.015)*** 0.057 (0.015)*** Deviance (FIML) 29,748 26,497 26,377 Deviance change 3,521*** 120*** Pseudo R2 0 0.109 0.113 Note. Standardized coefficients reported for fixed effects with standard errors in parentheses; unstandardized coefficients reported for random effects (variance components); deviance change significance determined by using the Satorra–Bentler scaled chi‐square (Model 2 is compared with Model 1, Model 3 is compared with Model 2). n (Level 1) = 11,282 to 11,844; n (Level 2) = 22; average cluster size from 512.8 to 538.4. PIED: perceived investment in employee development; FIML: full information likelihood procedure. +p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001. SMALE ET AL. 113 TABLE 3 Multilevel models predicting work‐life balance Model 4 Model 5 Model 6 Intercept 18.280 (3.673)*** 22.461 (4.819)*** 22.729 (4.924)*** Level 1 Manager −0.056 (0.014)*** −0.060 (0.012)*** Gender −0.030 (0.009)** −0.031 (0.009)*** Size of organization −0.046 (0.011)*** −0.049 (0.011)*** Age 0.086 (0.013)*** 0.095 (0.014)*** Education −0.057 (0.017)** −0.062 (0.016)*** Hierarchical level −0.032 (0.013)* −0.030 (0.012)* PIED 0.180 (0.018)*** 0.173 (0.017)*** Proactive career behaviors 0.037 (0.024) Variance components Residual variance (within) 0.685 (0.038)*** 0.650 (0.037)*** 0.649 (0.037)*** Residual variance (between) 0.039 (0.015)* 0.027 (0.011)* 0.027 (0.011)* Deviance (FIML) 29,320 27,264 27,225 Deviance change 2,056*** 39*** Pseudo R2 0 0.070 0.071 Note. Standardized coefficients reported for fixed effects with standard errors in parentheses; unstandardized coefficients reported for random effects (variance components); deviance change significance determined by using the Satorra–Bentler scaled chi‐square (Model 5 is compared with Model 4, Model 6 is compared with Model 5). n (Level 1) = 11,290 to 11,892; n (Level 2) = 22; average cluster size from 513.182 to 540.545. PIED: perceived investment in employee development; FIML: full information likelihood procedure. *p < 0.05; **p < 0.01; ***p < 0.001. TABLE 4 Multilevel models with cross‐level interactions predicting subjective financial success Model 7 Model 8 Model 9 Model 10 Model 11 Cultural dimension In‐group collectivism Humane orientation Power distance Uncertainty avoidance Performance orientation Intercept 3.161 (0.052)*** 3.148 (0.055)*** 3.160 (0.051)*** 3.170 (0.046)*** 3.155 (0.049)*** Level 1 Manager 0.135 (0.036)*** 0.135 (0.036)*** 0.135 (0.036)*** 0.135 (0.036)*** 0.135 (0.036)*** Gender 0.069 (0.023)** 0.069 (0.023)** 0.070 (0.023)** 0.070 (0.023)** 0.069 (0.023)** Size of organization −0.001 (0.011) −0.001 (0.011) −0.001 (0.011) −0.001 (0.011) −0.001 (0.011) Age 0.010 (0.001)*** 0.010 (0.001)*** 0.010 (0.001)*** 0.010 (0.001)*** 0.010 (0.001)*** Education −0.002 (0.016) −0.002 (0.016) −0.002 (0.016) −0.002 (0.016) −0.002 (0.016) Hierarchical level −0.022 (0.016) −0.022 (0.016) −0.022 (0.016) −0.022 (0.016) −0.022 (0.016) PIED 0.285 (0.027)*** 0.285 (0.027)*** 0.284 (0.027)*** 0.284 (0.027)*** 0.284 (0.027)*** Proactive career behaviors 0.057 (0.013)*** 0.061 (0.015)*** 0.058 (0.015)*** 0.057 (0.015)*** 0.061 (0.016)*** Level 2 HDI −0.796 (0.654) −0.134 (0.443) −0.680 (0.505) −0.421 (0.465) −0.433 (0.446) Cultural dimension −0.119 (0.089) 0.146 (0.219) −0.256 (0.179) 0.112 (0.063)+ 0.152 (0.118) Cross‐level interaction Proactive career behaviors * cultural dimension 0.038 (0.021)+ 0.029 (0.033) 0.070 (0.035)* −0.024 (0.011)* −0.029 (0.024) Variance components Residual variance (within) 0.603 (0.018)*** 0.603 (0.018)*** 0.603 (0.018)*** 0.603 (0.018)*** 0.603 (0.018)*** Residual variance (between) 0.037 (0.012)** 0.039 (0.011)** 0.037 (0.012)** 0.034 (0.010)** 0.036 (0.010)** Slope variance 0.002 (0.001)* 0.003 (0.002)+ 0.003 (0.002) 0.003 (0.002)+ 0.003 (0.002)+ Intercept‐slope covariance 0.000 (0.003) −0.001 (0.003) −0.001 (0.002) 0.000 (0.003) 0.000 (0.003) Deviance (FIML) 20,842 20,845 20,843 20,843 20,844 Deviance change 49*** 46*** 48*** 48*** 47*** Pseudo R2 0.12429 0.12417 0.12426 0.12428 0.12424 Note. Unstandardized coefficients are reported with standard errors in parentheses; deviance change significance determined by using the Satorra–Bentler scaled chi‐square (the comparative model for Models 7–11 is a country‐number‐adjusted variant of Model 3). n (Level 1) = 8,900; n (Level 2) = 17; average cluster size 523.5. PIED: perceived investment in employee development; HDI: Human Development Index; FIML: full information likelihood procedure. +p < 0.10. *p < 0.05; **p < 0.01; ***p < 0.001. 114 SMALE ET AL. (γ = 0.038) was not statistically significant (p < 0.10), the positive rela- tionship forWLBwas (γ = 0.054, p < 0.05). Figure 2 plots the interaction effects. In countries with higher in‐group collectivism, the relationship between proactive career behaviors and WLB was stronger (the slope was steeper) than in those with lower in‐group collectivism. Thus, Hypothesis 2b was supported, whereas Hypothesis 2a was not. Hypotheses 3a and 3b predicted that the positive relationship between proactive career behaviors and financial success (Hypothe- sis 3a) will be weaker and the positive relationship between proactive career behaviors and WLB (Hypothesis 3b) will be stronger in coun- tries higher in humane orientation. Model 8 inTable 4 and Model 13 in Table 5 present the results. Although the estimation for subjective financial success was not statistically significant (γ = 0.029, p = 0.381), the estimation for WLB was (γ = 0.081, p < 0.001). Figure 3 plots this interaction effect. In countries with higher humane orientation, the relationship between proactive career behaviors and WLB was stronger (the slope was steeper) than in those with lower TABLE 5 Multilevel models with cross‐level interactions predicting work‐life balance Model 12 Model 13 Model 14 Model 15 Model 16 Cultural dimension In‐group collectivism Humane orientation Power distance Uncertainty avoidance Performance orientation Intercept 3.650 (0.041)*** 3.653 (0.044)*** 3.664 (0.036)*** 3.660 (0.041)*** 3.652 (0.047)*** Level 1 Manager −0.122 (0.023)*** −0.123 (0.023)*** −0.122 (0.023)*** −0.122 (0.023)*** −0.122 (0.023)*** Gender −0.048 (0.018)** −0.048 (0.018)** −0.048 (0.018)** −0.048 (0.018)** −0.048 (0.018)** Size of organization −0.025 (0.006)*** −0.025 (0.006)*** −0.026 (0.006)*** −0.026 (0.006)*** −0.026 (0.006)*** Age 0.007 (0.001)*** 0.007 (0.001)*** 0.006 (0.001)*** 0.007 (0.001)*** 0.007 (0.001)*** Education −0.044 (0.009)*** −0.043 (0.009)*** −0.044 (0.009)*** −0.043 (0.009)*** −0.044 (0.009)*** Hierarchical level −0.011 (0.005)* −0.011 (0.005)* −0.011 (0.005)* −0.011 (0.005)* −0.011 (0.005)* PIED 0.156 (0.015)*** 0.156 (0.015)*** 0.155 (0.014)*** 0.156 (0.015)*** 0.156 (0.015)*** Proactive career behaviors 0.027 (0.013)* 0.031 (0.016)* 0.030 (0.016)+ 0.029 (0.016)+ 0.035 (0.017)* Level 2 HDI −0.692 (0.492) −0.448 (0.333) −0.851 (0.386)* −0.579 (0.356) −0.557 (0.342) Cultural dimension −0.067 (0.085) 0.024 (0.087) −0.289 (0.165)+ 0.047 (0.045) −0.036 (0.074) Cross‐level interaction Proactive career behaviors * cultural dimension 0.054 (0.019)* 0.081 (0.021)*** 0.079 (0.043)+ −0.028 (0.017) 0.027 (0.029) Variance components Residual variance (within) 0.680 (0.031)*** 0.680 (.031)*** 0.680 (0.031)*** 0.680 (0.031)*** 0.680 (0.031)*** Residual variance (between) 0.018 (0.009)* 0.019 (0.011)+ 0.015 (0.006)* 0.018 (0.009)+ 0.019 (0.010)+ Slope variance 0.003 (0.002)* 0.004 (0.002)+ 0.004 (0.002)+ 0.004 (0.002)+ 0.004 (0.002)+ Intercept‐slope vovariance −0.002 (0.004) −0.003 (0.004) −0.002 (0.003) −0.002 (0.004) −0.003 (0.005) Deviance (FIML) 21,905 21,906 21,904 21,908 21,909 Deviance change 67*** 66*** 68*** 64*** 63*** Pseudo R2 0.07885 0.07877 0.07887 0.07872 0.07867 Note. Unstandardized coefficients are reported with standard errors in parentheses; deviance change significance determined by using the Satorra–Bentler scaled chi‐square (the comparative model for Models 12–16 is a country‐number‐adjusted variant of Model 6. n (Level 1) = 8,905; n (Level 2) = 17; average cluster size 523.8. PIED: perceived investment in employee development; HDI: Human Development Index; FIML: full information likelihood procedure. +p < 0.10. *p < 0.05; **p < 0.01; ***p < 0.001. FIGURE 2 Cross‐level interaction plot of proactive career behaviors and in‐group collectivism practices predicting work‐life balance FIGURE 3 Cross‐level interaction plot of proactive career behaviors and humane orientation practices predicting work‐life balance SMALE ET AL. 115 humane orientation. Thus, Hypothesis 3b was supported, whereas Hypothesis 3a was not. Hypotheses 4a and 4b predicted that the positive relationship between proactive career behaviors and subjective financial success (Hypothesis 4a) will be stronger and the positive relationship between proactive career behaviors and WLB (Hypothesis 4b) will be weaker in countries with higher power distance. The results are presented in Model 9 in Table 4 and Model 14 in Table 5. Although the estimation for WLB was not statistically significant (γ = 0.079, p < 0.10), the esti- mation for subjective financial success was (γ = 0.070, p < 0.05). Figure 4 plots the interaction effects. In countries with higher power distance, the relationship between proactive career behaviors and financial success was stronger (the slope was steeper) than in those with lower power distance. Thus, Hypothesis 4a was supported, whereas Hypothesis 4b was not. Hypotheses 5a and 5b stated that the positive relationship between proactive career behaviors and subjective financial success (Hypothesis 5a) and WLB (Hypothesis 5b) will be weaker in countries with higher uncertainty avoidance. Model 10 inTable 4 shows that the interaction term predicting financial success was, as hypothesized, sig- nificantly negative (γ = −0.024, p < 0.05). The interaction term is illus- trated in Figure 5. In countries higher in uncertainty avoidance, the relationship between proactive career behaviors and subjective finan- cial success was weaker (the slope was flatter) than in those lower in uncertainty avoidance. As shown in Model 15 in Table 5, for WLB, the respective interaction term was also negative, but not statistically significant (γ = −0.028, p = 0.114). Thus, Hypothesis 5a was supported, whereas Hypothesis 5b was not. Finally, Hypotheses 6a and 6b predicted that the positive relation- ship between proactive career behaviors and subjective financial suc- cess (Hypothesis 6a) will be stronger and the positive relationship between proactive career behaviors and WLB will be weaker in coun- tries with higher performance orientation. As Model 11 in Table 4 and Model 16 in Table 5 demonstrate, we found a negative effect for financial success and a positive effect for WLB. However, none of the estimators reached a statistically significant level (γ = −0.029, p = 0.213 and γ = 0.027, p = 0.342). Thus, neither Hypothesis 6a nor Hypothesis 6b was supported. 5 | DISCUSSION AND CONCLUSION This study set out to examine whether proactive career behaviors are associated with higher levels of subjective career success in the form of financial success and work‐life balance, and the extent to which these relationships are influenced by national culture. Based on a multi‐country dataset, the study firstly contributes to the careers liter- ature by showing how the positive outcomes of proactive career behaviors extend beyond the more objective measures of career suc- cess to include subjective measures of career success. In this regard, our findings revealed that proactive career behaviors were signifi- cantly related to perception of financial success, but not of work‐life balance, and were differentially important for these two dimensions of subjective career success depending on the kind of culture to which an individual belongs. Collectively, this study provides further grounds for the differen- tial treatment of the individual dimensions of subjective success, and our results emphasize the need for future research to examine specific dimensions rather than treat subjective career success as an aggregate construct (Gunz & Heslin, 2005; Shockley et al., 2016). Contrary to expectations, career proactivity was not significantly associated with perceptions of greater work‐life balance as it was with subjective financial success. One potential explanation for this is that our mea- sure of career proactivity (EMA) focused on workplace proactivity and did not include other nonwork domain forms of proactivity such as seeking out the expectations and feedback of family members, which is common to theories on work‐life boundaries (Ashforth, Kreiner, & Fugate, 2000) and border management (Clark, 2000). Espe- cially if one's work‐life boundary is permeable (i.e., psychological or behavioral aspects from one domain easily enter the other), proactivity at the workplace but not outside of it may have a weaker effect on achieving a sense of work‐life balance. On the other hand, how much perceived organizational support an individual feels he/she is receiving may be more important than what the individual is proactively doing for feelings of work‐life balance. Alternatively, given the number and variety of external‐to‐work stakeholders that are likely to affect perceptions of work‐life balance, feelings of control and the ability to act in advance of future situations may be more difficult to achieve than expected. Similarly, more feed- back via information retrieval may not lead to greater satisfaction if FIGURE 4 Cross‐level interaction plot of proactive career behaviors and power distance practices in predicting subjective financial success FIGURE 5 Cross‐level interaction plot of proactive career behaviors and uncertainty avoidance practices in predicting subjective financial success 116 SMALE ET AL. this feedback is viewed across different stakeholders as contradictory and involves big trade‐offs. Lastly, this insignificant relationship may be attributable to differing levels of career salience (Greenhaus, 1974) among our respondents in terms of the relative importance they attach to work and nonwork activities. Although some aspects of career salience may be reflected in one's level of career proactivity, this is also likely to affect one's degree of satisfaction with the balance between work and nonwork domains (Chi‐Ching, 1995). The study's second main contribution is to the general proactivity literature by revealing that cultural context matters in the relationship between proactivity and individual outcomes. Based on multilevel analyses across a large number of Western and non‐Western coun- tries, career proactivity was relatively more important for subjective financial success in cultures with high power distance and low uncer- tainty avoidance. For perceptions of work‐life balance, career proactivity was relatively more important in cultures characterized by high in‐group collectivism, high humane orientation, and, margin- ally, high power distance. We interpret these results in light of social information processing theory, which regards the social context as a primary source of information in shaping one's attitudinal and behav- ioral responses (Salancik & Pfeffer, 1978). Accordingly, the values, practices, and behavioral norms shared by individuals in the broader national context are likely to offer cues on how to interpret their career achievements. As suggested by the main effects, our results indicate that views on proactivity in the pursuit of subjective financial success are more universally accepted, whereas legitimatization of proactive behaviors towards greater work‐life balance is more culturally contingent. Although we find no main effect for career proactivity on work‐life balance, we provide evidence to suggest that career proactivity's rela- tionship with work‐life balance changes depending on cultural values, with different slopes in different cultural contexts. We interpret this as evidence that how members of a culture view the goals of individual proactivity plays an important role in explaining attitudinal outcomes. Unexpectedly, however, career proactivity was also more strongly related to subjective financial success in cultures high in in‐ group collectivism, albeit only marginally. One explanation might be that in‐group collectivist societies assume that individuals will use their financial success for the benefit of their own group rather indi- vidualistic or self‐centered goals. When considering countries such as China, for example, an emphasis on individual achievement and finan- cial success can be seen as legitimate and coexist with strong collec- tivistic cultural practices. Indeed, in collectivist cultures, people tend to view work–family conflict as an inevitable cost in the pursuit of financial stability for the family and family well‐being (Aryee, Luk, Leung, & Lo, 1999). Also unexpected was the finding that career proactivity was more important for work‐life balance in countries with high power distance, as revealed by a marginally significant coef- ficient. A possible explanation is that because work‐life balance in these contexts is likely to be a lower priority and not necessarily granted by those further up the hierarchy, individual proactive behav- iors may be needed in order to approach those who are in a position to help one achieve it. Therefore, all other things equal, individuals may be happier with their level of achievement on this dimension of subjective career success. Nevertheless, although we foundmoderating effects for at least one aspect of subjective career success for four out of the five cultural dimen- sions, the lack of support for the remaining hypothesesdemonstrates that the role of culture was still not as strong as expected. As mentioned above, and as evidenced in the small effect sizes for several of the inter- actions, thismight be due to the benefits of career proactivity beingmore universal than we anticipated. Alternatively, although we controlled for perceived organizational support, the role of the organization and imme- diate supervisor (Wayne, Liden, Kraimer, & Graf, 1999)—the more imme- diate context within which proactivity takes place and where key career gatekeepers reside (King, 2004)—may represent an important part of the missing link. And although we controlled for age, we cannot rule out completely the effects of age, generation, and career stage, which may not only determine how invested individuals are in their culture's norma- tive valuesbut also themeanings and salience they attach to financial suc- cess and work‐life balance. 5.1 | Limitations and future research This study is subject to certain limitations, which themselves present opportunities for interesting future research. First, although CMV does not appear to be significantly present in our data, the studywas neverthe- less cross‐sectional and based on single respondents, which limits our ability to make causal inferences. This, together with our unexpected findings, reinforces the need for more longitudinal and qualitative research that examines individual proactive behaviors and how joint self‐ and organization‐career management interacts and unfolds over time (e.g., Feij, Whitely, Peiró, & Taris, 1995) in different cultural settings. This is especially important when one could argue for reverse causality insofar as subjective career success may drive career proactivity. Second, we focused on several cultural dimensions and a large number of countries in order to seek broadly generalizable findings regarding the role of culture with respect to our focal variables. Although we controlled for Human Development Index scores, our results did not shed light on other potentially significant country differ- ences. Echoing some of the recent international careers research (e.g., Briscoe et al., 2012;Mayrhofer et al., 2016), our understanding of career proactivity and its benefits around the world could be further improved via a more fine‐grained understanding of national career systems and institutional arrangements grounded in institutional theory. This could be achieved by adopting a country comparative approach to careers (Dany,Mallon, &Arthur, 2003;Mayrhofer,Meyer, & Steyrer, 2007)with an emphasis on institutional context and structure to counterbalance the actor‐centric tendency in proactivity and careers research. This could include questions around what “proactivity” means in different cultures and how it is perceived by others—seeking feedback on your performance from your supervisor may be a modest step in some cul- tures, but a very bold step in others. Similar to cultural differences in, for instance, the propensity for employee voice due to power distance (e.g., Huang, van de Vliert, & van der Vegt, 2005), we believe that there is scope for emic research to examine more closely the cultural mean- ings attached to career proactivity and how these might affect career behaviors and outcomes. Third, the relatively small effect sizes in our models indicate a great deal of unexplained variance. At the individual level, one could examine SMALE ET AL. 117 the relative importance of proactive career behaviors compared with other proactive person‐environment fit behaviors such as job change negotiation (Parker &Collins, 2010), influence tactics such as networking, ingratiation, and enhancing one's visibility (Judge & Bretz, 1994; King, 2004), or individual attributes such as age/generation (Van der Heijden, de Lange, Demerouti, & Van der Heijde, 2009) andwork/goal orientation (Heslin, 2005b). At the organizational level, there are likely to be impor- tant variables capturing thework context thatwill help future researchers to understand the effects of agentic career proactivity and their interplay, such as supervisor support and sponsorship (Ng et al., 2005), develop- mental network support at work (e.g., Higgins & Kram, 2001), or the exis- tence of mentoring cultures (e.g., Ragins & Scandura, 1999). And lastly, we suggest that future research integrates the other lesser studied individual dimensions of subjective career success. Of particular interest from a proactivity perspective that were not studied here, and in light of individuals increasingly looking for meaning, pur- pose, and values compatibility in their self‐directed career choices (e.g., Briscoe & Hall, 2006), the dimensions of “Positive Impact” (Briscoe et al., 2014), “Meaningful Work,” and “Authenticity” (Shockley et al., 2016) would be timely inclusions in future careers research. What the relationships between proactivity and these different kinds of subjective career success look like around the world and across dif- ferent occupations (e.g., nurses vs. blue‐collar workers) would also help in understanding which relationships are more universalistic and which are more country and occupational context dependent. 5.2 | Implications for practice Understanding what contributes to individuals' subjective career suc- cess is important for at least two reasons. First, it is important for indi- viduals themselves because it is associated with greater life satisfaction and psychological well‐being (Nicholson & DeWaal‐ Andrews, 2005; Rain, Lane, & Steiner, 1991); and second, it is impor- tant for organizations because subjective career success can lead to lower turnover intentions and more support for organizational change (Nauta, Vianen, Van der Heijden, Dam, & Willemsen, 2009). Our find- ings present interesting implications for these two careers' stake- holders, who today are expected to share the responsibility for career success, having to make difficult decisions about how much to invest in supportive organizational practices (Human Resource Development, supervisor support) on the one hand and how much to encourage proactive career self‐management on the other (De Vos et al., 2009; Jung & Takeuchi, 2018). For the individual careerist, our findings suggest that proactive career behaviors generally pay off on a psychological level in terms of intrinsic success criteria like subjective financial achievement, irre- spective of cultural context. Such proactivity, which itself can contrib- ute to career resilience and adaptability (Seibert, Kraimer, & Heslin, 2016), will be especially beneficial for employees in high power dis- tance and low uncertainty avoidance cultures. Regarding more well‐ being‐related criteria like work‐life balance, career proactivity may not automatically translate into a greater sense of achievement but is more likely to do so in cultures characterized by high in‐group col- lectivism and humane orientation. Even in countries where heightened proactivity might not be the norm, such behaviors are advisable as there is certainly no evidence in this study to suggest that greater proactivity is associated with more negative feelings about one's career. One may just need to keep in mind how the culture one is in may influence the kind of career goals held as important and how this is likely to influence how individuals construct interpretations about the importance of being proactive. For organizations, the results suggest that encouraging and supporting employees to become more proactive in managing their careers is likely to improve their subjective career success. Although the positive effects of our control variable concerning the organization's perceived investment in employee development suggest that the orga- nization still has an important role to play in the joint responsibility for career management, directing some of this support towards creating an enabling environment that supports and rewards proactivity could be beneficial to both parties, provided that organizations can at the same time promote employee loyalty and contributions to the organiza- tion. For organizations that are “managing” careers across countries and cultures (e.g., multinational firms), this approach may not need to be adjusted extensively to cater for cultural differences but would never- theless benefit from understanding how a given culture views and influ- ences proactive behaviors and different kinds of career goals. ORCID Adam Smale http://orcid.org/0000-0003-2051-9849 REFERENCES Abele, A. E., & Wiese, B. S. (2008). 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Criteria of career success among Chinese employees: Developing a multidimensional scale with qualitative and quantitative approaches. Journal of Career Assessment, 21(2), 265–277. AUTHOR BIOGRAPHIES Adam Smale is a Professor of Management at the University of Vaasa, Finland. His research interests lie in human resource management, talent management, and careers in multinational corporations. Silvia Bagdadli is Associate Professor of Human Resource Management at Bocconi University, Italy. Her research focuses on careers – individual and organizational perspective –, talent and HR management. Rick Cotton is Associate Professor of international Business and Service Management at the University of Victoria, Canada. His research interests include extraordinary career achievement, net- works, and talent management with a primary focus on how human, social, and positive psychological capital foster individual and collective success. Silvia Dello Russo is Assistant Professor of Organizational Behavior at ISCTE—Instituto Universitario de Lisboa (Portugal). Her research spans the interaction between the individual and the organizational context, workmotivation, andHRpractices for development, with a particular focus on multilevel and longitudinal dynamics. Michael Dickmann is Professor of International Human Resource Management at Cranfield University School of Management, UK. His research focuses on human resource strategies, structures, and processes of multinational organizations, cross‐cultural man- agement, international mobility, and global careers. SMALE ET AL. 121 Anders Dysvik is Professor of Organizational Behavior at the Department of Leadership and Organizational Behavior at BI Norwegian Business School, Norway. His research interests are in the intersections between HRM, leadership, and motivation. Martina Gianecchini is Associate Professor of Organizational Behavior and Human Resource Management at the University of Padova, Italy. Her research focuses on careers, entrepreneurship, and organizational development. Robert Kaše is Associate Professor of Management and Organiza- tion at the Faculty of Economics, University of Ljubljana, Slovenia. His research interests include human resource management, intra‐ organizational social networks, careers, and emergence in teams. Mila Lazarova is Associate Professor in International Business and Canada Research Chair in Global Workforce Management at the Beedie School of Business in Simon Fraser University, Canada. Her research interests include expatriate management, work/life balance issues related to assignments, global careers, and organi- zational career development and mobility practices. Astrid Reichel is Professor and Head of Human Resource Man- agement Group at the University of Salzburg, Austria. Her research focuses on power issues in HRM, international (compar- ative) HRM, creativity in organizations, and careers research, focusing on “new” forms of employment. Paula Rozo is a Professor in the Department of Management at Los Andes University, Columbia. Her research interests lie in the areas of public service motivation, the impact of contingent and noncontingent contracts on the psychological contract, the rela- tionship between subjective career success and career invest- ments, and performance management systems. Marijke Verbruggen is Associate Professor at the Faculty of Eco- nomics and Business and Head of the Research Centre for Work and Organization Studies at KU Leuven, Belgium. Her research focuses on careers, psychological mobility, employee develop- ment, and employability. How to cite this article: Smale A, Bagdadli S, Cotton R, et al. Proactive career behaviors and subjective career success: The moderating role of national culture. J Organ Behav. 2019;40: 105–122. https://doi.org/10.1002/job.2316 APPENDIX A ON BEHALF OF THE CROSS‐CULTURAL COLLABORATION ON CONTEMPORARY CAREERS (5C) RESEARCH COLLABORATIVE Ifedapo Adeleye, Lagos Business School, Nigeria; Maike Andresen, University of Bamberg, Germany; Eleni Apospori, Athens University of Economics and Business, Greece; Olusegun Babalola, Lagos Business School, Nigeria; Rhoda Bakuwa, University of Malawi. Jon P. Briscoe, Northern Illinois University, USA; Jong‐Seok Cha, Hansung University, South Korea; Katharina Chudzikowski, University of Bath, UK; Nicky Dries, KU Leuven, Belgium; Petra Eggenhofer‐Rehart, WU Vienna University of Economics and Business, Austria; Zhangfeng Fei, Donghua University, China; Martin Gubler, Schwyz University of Teacher Education, Switzerland; Douglas T. Hall, Boston University, USA; Svetlana Khapova, Vrije Universiteit Amsterdam, Netherlands; Najung Kim, Kookmin University, South Korea; Philip Lehmann, University of Bamberg, Germany; Evgenia Lysova, Vrije Universiteit Amsterdam, Netherlands; Sergio Madero, Tecnológico de Monterrey, Mexico; Debbie Mandel, Schwyz University of Teacher Education, Switzerland; Wolfgang Mayrhofer, WU Vienna University of Economics and Business, Austria; Biljana Bogićević Milikić, University of Belgrade, Serbia; Sushanta Kumar Mishra, Indian Institute of Management Indore, India; Chikae Naito, Waseda University, Japan; Ana Nikodijevic, University of Belgrade, Serbia; Emma Parry, Cranfield University, UK; Noreen Saher, International Islamic University, Pakistan; Richa Saxena, Institute of Management Technology, Ghaziabad, India; Nanni Schleicher, University of Hamburg, Germany; Florian Schramm, University of Hamburg, Germany; Yan Shen, University of Victoria, Canada; Pamela Suzanne, Universidad de San Andrés, Argentina; Mami Taniguchi, Waseda University, Japan; Julie Unite, Humber, Mundie & McClary, USA. Jelena Zikic, York University, Toronto, Canada. 122 SMALE ET AL.