Academics career success: the impact of organizational context and individual variables

Though managers cannot manage employee career success, as it is a characteristic related to each individual, it has in time proven to impact organizations in different ways: it influences employees’ turnover intention (Joo and Park, 2010) as it also influences their job performance (Karatepe, 2012). Career success is defined as the “positive psychological and work-related outcomes accumulated as a result of one’s work experiences” (Seibert and Kraimer, 2001) and not the ones related to a single organization. This concept received extensive attention from scholars in the past two decades (Santos, 2016). While quantitative studies mainly analyze determinants, content and outcomes of career success by the use of a division between subjective career success and objective career success (Ng et al., 2005; Spurk et al., 2019), qualitative studies mostly deal with the processual or dynamic character of the career success construction (Afiouni and Karam, 2014; Santos, 2016). Objective career success and subjective career success research have multiple gaps, as reviewed by Spurk et al. (2019): there are few studies, which consider both success categories or which make a differentiation between factors that influence only one category, as there are multiple contexts as universities which were less considered by researchers.

Academics careers have been studied mainly in Western contexts, the “publish or perish” paradigm guiding faculty performance concerning knowledge creation and dissemination (Baruch, 2013), academics career research itself is still considered an under-researched area (Santos, 2016; Van der Klink et al., 2014). There are few studies, which consider Eastern European academics careers (Bozionelos, 2014).

In response to the quest for studies, which investigate the impact of proximal environmental resources on both objective career success and subjective career success, but also for studies which look into differential mediation mechanisms for predicting objective career success versus subjective career success (Dries, 2011; Spurk et al., 2019), of studies which investigate the impact of context on career success (Dries, 2011) or the impact of different national, organizational contexts and cultures on academics’ careers (Bozionelos, 2014; Kaulisch and Enders, 2005), this paper proposes an investigation concerning academics career success in one of the largest Eastern European country, Romania, in its larger university, Babeș-Bolyai University (BBU). It is a quantitative analysis of how contextual factors, individual beliefs concerning work, individual motivation and demographic variables influence subjective career success and objective career success.

This paper first contributes to the academics’ career success research by including organizational context variables in quantitative analysis and observing their impact on career success. The inclusion of the “in-group” culture and the “publish or perish” strategy is one major advancement of this research, especially while considering the context of ex-communist countries where these two forces have shaped the evolution of higher education institutions (HEIs) governance. Second, it deepens the knowledge concerning teachers’ learning goal orientation in a university context, extending the data already existing in other fields (van Dierendonck and van der Gaast, 2013) and in non-tertiary education (Butler, 2007; Retelsdorf et al., 2010). Moreover, this study is an analysis of the mediating role of goal orientation and self-efficacy in specific work environmental conditions on subjective career success and objective career success (Spurk et al., 2019). Finally, by investigating the hypotheses concerning self-efficacy and goal orientation in a Romanian university, this study responds to calls to test the generalizability of Western results on career success in different international contexts. The results of this study can be further used by HEIs managers in establishing better human resources and organizational strategies.

The paper is structured in six parts. Section 2 presents the context of the research represented by BBU. Section 3 is a review of the four distinct strands of research on academics’ career success (“being part of the system” culture, “publish or perish,” goal orientation and self-efficacy) and the development of the appropriate hypotheses. This is followed by the methodology, including sample, procedure, measures and analysis in Section 4. Section 5 summarizes the analysis and research findings, based on hierarchical multiple regression analyzes. The discussion, limitations and future research opportunities are provided within Section 6.

The evolution of higher education institutions has followed in the past decades the tendencies which have previously dominated industry, as competition, massification, internationalization, globalization or diversification. For Eastern Europe universities, these changes have run parallel to national changes as the introduction of capitalism, European integration, the democratization of the society and also institutional changes, as the restoration of HEIs self-governance and autonomy, academic freedoms (Dobbins and Kwiek, 2017) or the Bologna Process (Dakowska, 2017). Eastern European HEIs governance has been modeled by two forces (Dakowska, 2017; Dobbins, 2017): isomorphism – imitation of Western best practices and building a more market-oriented, competitive and international university and historical institutionalism – adoption and adaptation of pre-communist Humboldtian logic of universities (Dakowska, 2017).

The Romania HEIs model has its historical roots before the Second World War in the French one, defined by strong state coordination (Dobbins, 2017). The communist system brought a more state-centered model (Dobbins, 2017), a long and slow process to the professor’s title and also a high degree of inbreeding (Majcher, 2005). After 1989, there is evidence that the collegial system is still an important part of the Eastern European university model (Dobbins and Kwiek, 2017). In an analysis concerning two decades of higher education reforms in Romania, Deca (2015) observes that Romanian academics have opted in all universities for a collegial governance system instead of a managerial one, though both alternatives are allowed by the 2011 Romanian Law on Education. One important observation is that after an initial 2000 more market and competitiveness oriented direction, Romanian universities are currently adopting the academic self-rule model, similar to Poland (Dobbins, 2017).

BBU is the largest Romanian HEI in terms of students and is the best-ranked Romanian HEI in international university ranking. However, its position in Times Higher Education Ranking has decreased from 501–600 (2016), 601–800 (2017 and 2018), to 801–1,000 (2019–2020), though it has adopted in the last years increasing requirements regarding research and has obtained better research results (from 11.3 scores for 2018 to 14.1 for 2020). According to the BBU rector’s report for 2018 (Pop, 2019), BBU has 1,489 teachers (most of them have permanent positions according to Romanian legislation), out of which 222 are professors, 445 associate professors, 670 lecturers and 152 teaching assistants. The Romanian system is one where inbreeding is at high levels, similar to the Portuguese or Polish systems (Horta, 2013; Majcher, 2005), the employment of external teachers being rather rare. Advancements are made by opening new positions at the departments’ level, these positions being usually proposed by those teachers who meet the requirements for that position. This is the area where BBU is more competitive than other Romanian universities by increasing with 25% the national requirements for each position, as is mentioned in the methodology concerning filling open positions at BBU (BBU, 2016). Most BBU colleges have adopted even more increased requirements than BBU requirements. The academic position is this way controlled by the department but also by university and colleges’ strategy for competitiveness.

A characteristic of Romanian HEIs governance and BBU implicitly is the system of elections which leads to a similar to political power and influence logic: departments’ heads and colleges’ representatives are elected by department members, the rector is elected by all teachers who have permanent positions (majority), colleges’ deans are validated by colleges’ representatives and further chosen by the rector (if more deans are validated by colleges’ representatives). This way, being the department head or having another management or representation position, can be associated with a better academic position.

Career success is usually approached in subjective career success and objective career success terms. Subjective career success, also referred as career satisfaction, is related to individuals’ perceptions, being harder to measure and depending more on individuals themselves (Joo and Ready, 2012), while objective career success is objective and related to attaining specific measurable targets by individuals such as promotions or salary levels (van Dierendonck and van der Gaast, 2013; Santos, 2016). The correlation between the two variables is rather low (Ng et al., 2005), this evidence supporting the idea that the two constructs are relatively independent. This paper is built by considering the model of emergent interactive agency proposed by Bandura (1989), where personal factors and environmental events operate as interacting determinants of career outcomes, in this case, career success.

Context is theorized as influencing careers in three ways (Cohen and Duberley, 2015): as ideology (it is related to culture and prescribes what is acceptable or unacceptable within organizations), as enduring structural features (they are temporal structural constraints defining what is possible considering resources) and as proximal events (unexpected challenges that arise at particular moments). This study deals with one ideological context variable (the “being part of the system culture,” typical for Eastern Europe) and one structural context variable (the temporary strategy adopted by the organization – “publish or perish”).

“Being part of the group” or “in-group” culture impact on career success has been analyzed for Greece by Bozionelos (2014), where the existence of “substantial social capital flowing through the medium-upper and top academic ranks of universities” is linked to the political and economic elite. The connect ties are found as related to “family and educational backgrounds, as well as interest and affiliation with politics,” while the material norms of the “in-group” members are based on trust and reciprocity. In time, social capital is linked to academic advancements, the existence of graduate programs, forcing doctoral students to work as professors’ secretaries and teach professors’ classes (Bozionelos, 2014). Objective career success is influenced by being part of the group: in-group academics can advance in an accelerated manner, while outsiders normally have a lengthier advancement path (Bozionelos, 2014).

One aspect linked to the “in-group” culture is the inbreeding system, one which has been observed both in Western (Santos, 2016) and Eastern (Majcher, 2005) Europe. Inbreeding means that academics hire their own doctoral students, this way the group blocks access for external candidates. While in the Eastern Europe context inbreeding is observed as part of the academic culture (Majcher, 2005), in the Portuguese context inbreeding has been associated with higher job insecurity among younger academics (Santos, 2016) and to low job insecurity among older academics. As job insecurity impacts subjective career success (Ngo and Li, 2015), it is obvious that being part of the system could also positively influence subjective career success.

Therefore, the following hypotheses are formulated:

The “publish or perish,” or the research competitiveness strategy is represented by the increased progression standards and expectations established for academics. The existence of this strategy is related to the management style adopted by universities (new public management), which is similar to the corporate sector (Barry et al., 2001). They affect academics’ success and the life: they are a barrier for Portuguese academics’ subjective career success (Santos, 2016) and they create an acceleration of UK academics life and affect their life balance (Vostal, 2015). Competitive pressure has been studied also in other contexts, being known as generating higher stress for employees, without visible impact on self-rated task performance (Fletcher et al., 2008).

To “catch up with the West” (Dobbins and Kwiek, 2017), few Romanian universities have adopted a performance-driven direction, BBU being one of them. This university is recognized as an early adopter of a research competitiveness strategy (Dobbins, 2017).

Consequently, the following hypothesis is formulated:

Goal orientations are individuals’ cognitive frames about competence, errors, success, ability and effort, within which individuals understand and respond to events, as they choose different forms of effect, cognition or actions (Ames and Archer, 1988). The three-goal orientations validated by scholars are mastery goal orientation (developing knowledge and skills), performance goal orientation (proving skills to others or achieving a specific goal) and performance-avoidance goal orientation (hiding low skills to others) (VandeWalle, 1997). There is relatively little research on teachers’ goal orientation (Han et al., 2015), this framework is used mainly to explain how non-university teachers’ goal orientations influence their teaching process (Butler, 2007; Han et al., 2015; Retelsdorf et al., 2010) and their psychological well-being (Han et al., 2016; Parker et al., 2012). For tertiary education, goal orientation has been confirmed as a determinant of teachers’ commitment to students and to institutions (Han et al., 2016) and teachers’ approaches to teaching (Han et al., 2015).

There are many studies, which analyze goal orientation’s impact on subjective career success. This way, it is expected that individuals with higher mastery goal orientation have a higher level of psychological and physical well-being and persons with a higher performance goal orientation have lower levels for these variables (Nitsche et al., 2013). For Greek teachers, Papaioannou and Christodoulidis (2007) revealed that mastery goal orientation is positively associated with subjective career success, performance goal orientation is unrelated to subjective career success and work avoidance has a negative impact on subjective career success. For Korean employees, Joo and Ready (2012) discovered that subjective career success is associated with performance goal orientation, while mastery goal orientation has no significant impact. For real estate professionals, subjective career success was found to be positively impacted by mastery goal orientation and to be not impacted by performance-avoidance goal orientation (Sims and Boytell, 2015).

The impact of goal orientation and self-efficacy on subjective career success and objective career success has been previously analyzed on 247 alumni (van Dierendonck and van der Gaast, 2013). The results are that mastery goal orientation is more beneficial for subjective career success than performance goal orientation and that objective career success, measured as salary growth, is not associated with any of the orientation goals. They conclude that goal orientation can be a better predictor than academic competencies or having a strong core self-efficacy, in relation to subjective career success.

Therefore, the following hypotheses are formulated:

Self-efficacy was developed by Bandura (1969) to describe human behavior and is defined as one’s perception regarding his/her own capabilities to successfully accomplish specific tasks. The impact of self-efficacy on career success has been analyzed in different contexts, though the relation between the two constructs can be in both directions (Spurk et al., 2019). One of the first studies, which associate subjective career success with self-efficacy is the one developed by Day and Allen (2004), who discover that career mentoring increases protégé self-efficacy, which later is associated with subjective career success. Abele and Spurk (2009) search for self-efficacy impact on subjective career success for 734 highly educated and full-time used professionals, confirming that occupational self-efficacy measured at career entry has a positive impact on subjective career success seven years later. While surveying managers and non-manager employees in Lebanon regarding their career commitment, self-efficacy and career success, Ballout (2009) find that career commitment predicted both subjective career success and objective career success only for employees with average to high self-efficacy, but not for those with low self-efficacy.

Consequently, the following hypotheses were formulated:

The control variables used in this study refer to different aspects of academics’ context. Gender is considered, as women academics have lower chances to attain tenure (Ooms et al., 2019) and women academics have more barriers and feel discriminated against attaining their career success (Afiouni and Karam, 2014; Santos, 2016). Age is also an important determinant of career success, being proved that younger academics feel higher pressure for publishing (Santos, 2016) and this pressure can be linked to lower career success (Fletcher et al., 2008).

Therefore, the following hypotheses are formulated:

An online survey was sent to all BBU academics who have teaching duties in different academic fields during the second semester of the 2017–2018 academic year. Teachers were informed about the goal of the survey and about their participation’s anonymity. Out of 1,950 academics (1,447 are permanent, while the rest are researchers with teaching responsibilities), 447 have responded to the survey, an adequate rate (22.92%) considering the context of the survey. In total, 447 complete responses were received. The respondents have the following positions: teaching assistant 8.50%, assistant professor 41.39%, associate professor 32.21% and full professor 17.90%. In total, 75.39% belong to social sciences, economics and business and 24.61% belong to experimental sciences, engineering and mathematics.

The questionnaire contained measures for all aspects previously mentioned and for each measure Romanian translations of scales developed and validated in previous studies were used. They were measured using a five-level Likert scale ranging from 1 to 5, except for control and other dummy variables further described:

• Subjective career success has been measured using the career satisfaction scale designed by Greenhaus et al. (1990) and used in other studies (Abele and Spurk, 2009; van Dierendonck and van der Gaast, 2013; Hagmaier et al., 2018). It consists of five items (e.g. “I am satisfied with the progress I have made toward meeting my overall career goals”). Responses were averaged to produce a total subjective career success score (Cronbach’s α = 0.81).

• Objective career success was measured considering the academic position, measured using a dummy variable (1 – teaching assistant or similar, 2 – lecturer, 3 – associate professor and 4 – professor).

• “Being part of the system” was measured using a single item concerning whether teachers have a management/representation function/position (1 if manager, 0 if not). It is relevant considering the election system existing at BBU.

• Research competitiveness pressure was measured considering a numerical attribute representing the number of years in the current position. Considering teacher’s promotion system, more years they spend in a position denotes the impossibility to meet upper position requirements.

• For goal orientation, the instrument advanced by VandeWalle (1997) was used. In total, 16 items were used: six for mastery goal orientation (e.g. “I prefer to work in situations that require a high level of ability and talent.”), five for performance goal orientation (e.g. “I prefer to work on projects where I can prove my ability to others.”) and five for performance-avoidance goal orientation (e.g. “I prefer to avoid situations at work where I might perform poorly.”). This measurement has been shown to be valid and reliable in multiple studies (Kunst et al., 2018). Internal reliabilities for performance, mastery and performance goal orientations, respectively, were Cronbach’s α = 0.76, Cronbach’s α = 0.78 and Cronbach’s α = 0.85.

• Similar to Van Daal et al. (2014), self-efficacy was measured using the short version of the Teachers’ Sense of Efficacy Scale, developed by Tschannen-Moran and Hoy (2001). The items correspond to the three efficacy dimensions identified by Tschannen-Moran and Hoy (2001): efficacy for instructional strategies (4 items), efficacy for classroom management (4 items) and efficacy for student engagement (4 items). A final self-efficacy score has been calculated as an average of all 12 items, similar to Van Daal et al. (2014). Internal reliability was Cronbach’s α = 0.86.

• There are specific measures for control variables: age – numerical attribute, gender – dummy variable (0 if female, 1 if male), seniority – numerical attribute representing the number of years of employment and academic teachers’ disciplines – dummy variable (1 if social sciences, business, economics, 0 if exact and natural sciences).

As subjective career success is measured using a continuous variable (Table 1), classical ordinary least squares (OLS) regressions with robust White correction for heteroskedasticity were used for estimating it. The academic position is measured using ordinal variables. Four ordered logit regressions were used to test the hypotheses, similar to the ones for subjective career success, as can be seen in Table 2. The first regressions (step 1) considered socio-demographic and context related variables, the next (step 2) included goal orientation, the third step (3) considered only socio-demographic variables and self-efficacy, while the fourth (4) considered self-efficacy, goal orientation and socio-demographic variables.

The results of this study are presented in two parts. First, the descriptive statistics and correlations of the variables included in the model are reported. Second, the hierarchical multiple regression models were tested and the results of the hypothesis testing are addressed. These analyzes were conducted using SPSS 16.0.

Table 1 provides means, standard deviations and correlations between study variables. The highest score is registered for mastery goal orientation, with an average of 3.80, while the lowest score is for performance-avoidance goal orientation, with an average of 2.10. Subjective career success, measured as career satisfaction, has an average of 3.68, while OCS, measured as academic position (four levels), has an average of 2.59. Self-efficacy has an average of 3.85 for the sample. Subjective career success is significantly positively correlated to objective career success (r = 0.31, p < 0.001), this correlation being similar to the levels previously identified (Ng et al., 2005) – (0.25–0.30). Subjective career success is also positively correlated to self-efficacy (r = 0.25, p < 0.001), moderately positively correlated to mastery goal orientation (r = 0.17, p < 0.05) and managing position (r = 0.11, p < 0.05) and moderately negatively correlated to performance-avoidance goal orientation (r = −0.11, p < 0.05). Objective career success, beside subjective career success, is significantly positively correlated to age (r = 0.63, p < 0.001), seniority (r = 0.62, p < 0.001), managing position (r = 0.35, p < 0.001) and gender (r = 0.25, p < 0.001) and moderately positively correlated to years in current position (r = 0.18, p < 0.001) and self-efficacy (r = 0.18, p < 0.001).

Table 2 illustrates the results of hierarchical multiple regressions for subjective career success (four OLS regressions) and objective career success (four ordered logit regressions).

SCS is positively influenced by owning management positions, performance goal orientation, mastery goal orientation and self-efficacy and negatively influenced by research competitiveness pressure (years in current position). Surprisingly, male academics have lower subjective career success. This way, H2 is accepted (being part of the system – owning a managing position – positively influences subjective career success), H3 is accepted (competitiveness pressure is a negative influence on subjective career success), H4 is accepted (mastery goal orientation positively impacts subjective career success), H5 is accepted (performance goal orientation is proven to have a positive influence on subjective career success instead of no influence expected) and H6 is accepted (performance-avoidance goal orientation has a weak influence on career success and does not have a convincing negative influence on the dependent variable). When self-efficacy is not included in the regression (step 2), performance-avoidance goal orientation is found to have a negative influence on career success, but when self-efficacy is included (step 4), this influence becomes non-significant). H8 is accepted (self-efficacy is a positive predictor of subjective career success), H11 is rejected (being a woman is surprisingly associated with higher subjective career success for BBU academics), H12 is rejected (age has no influence, in comparison to the expected negative influence) and H13 is accepted (academic discipline has no impact on subjective career success).

Objective career success is positively influenced by owning a managing position, self-efficacy, age and seniority and negatively influenced by research competitiveness pressure (years in current position). Considering the expectations, H1 is accepted (being part of the system – owning a managing position positively influences objective career success), H7 is accepted (goal orientation has no impact on objective career success), H9 is accepted (self-efficacy is a positive predictor of objective career success) and H10 is rejected (in this study gender is found to have no influence on academic position).

Concerning the first research area, which is related to the impact of in-group culture on subjective career success and objective career success, this study confirms the previous findings of Bozionelos (2014). Moreover, as in this study, the variable used for in-group culture is having or not a managing or representation position, it could be concluded that not only being part of the group but also owning a power position, increases the chances for increased subjective career success and objective career success.

Though research competitiveness pressure has been measured as the years in current position, this study confirms the negative impact of increased academic requirements observed in other studies (Barry et al., 2001; Santos, 2016) for other contexts. With no doubt, this competitiveness is mandatory for BBU given its position in HEIs rankings, but academics’ subjective career success and objective career success should be also considered.

Concerning goal orientation, this study reveals that mastery and performance goal orientations are two predictors for subjective career success. Concerning performance goal orientation, the study confirms the results of Joo and Ready (2012), but it contradicts the results of van Dierendonck and van der Gaast (2013) – they found no significant influence of performance goal orientation on subjective career success. By contrast, mastery goal orientation results are similar to those of van Dierendonck and van der Gaast (2013) but contradict the results of Joo and Ready (2012), who conclude that mastery goal orientation has no significant impact on subjective career success. In literature, there are mechanisms which explain the impact of both goal orientations as factors for subjective career success. For example, considering performance goal orientation’s positive impact on subjective career success, Joo and Ready (2012) argue that persons with higher performance goal orientation “are likely to set lower career goals and be satisfied with their current career they feel comfortable.” For mastery goal orientation, it is expected that individuals with higher mastery goal orientation will develop learning processes when facing problems and obstacles and this way to create strategies to become successful (García-Juan et al., 2019).

The results on self-efficacy are similar to those of Abele and Spurk (2009), Ballout (2009), van Dierendonck and van der Gaast (2013) – self-efficacy has a positive influence on subjective career success and objective career success. The impact of self-efficacy is higher than the one of goal orientation on subjective career success, considering its significance level. These results highlight the importance of self-efficacy on teachers’ well-being (described through job satisfaction, personal accomplishment and commitment), results confirmed in previous studies (Abele and Spurk, 2009; Ballout, 2009).

It was also a surprise to observe that female academics are more inclined to have higher subjective career success in comparison to male teachers. This is in contradiction to the studies that prove that women face multiple problems in academia and have lower subjective career success (Afiouni and Karam, 2014; Santos, 2016).

This paper contributes to research on career success in multiple ways. First, it brings evidence that the two major context variables specific to this university (Eastern European “in-group” culture and the organizational competitiveness strategy) impact both subjective career success and objective career success, proving that organizational turmoil affects academics career success. While being part of the system – measured as owning a managing/representation position – is used as a chance to increase both subjective career success and objective career success, academic pressure (measured as an extended period of having the same position) acts as an inhibitor for both subjective career success and objective career success. This complements the existing literature by proving that subjective career satisfaction has also organizational roots, in opposition to the previous results which associate subjective career success mainly to individuals’ perceptions (Joo and Ready, 2012). Moreover, the results of this paper prove that contextual variables also affect objective career success.

Second, this study is the first to analyze links between career success, goal orientation and self-efficacy in an education organization. In comparison to the study which has previously analyzed goal orientation and self-efficacy impact on subjective career success for an alumni sample (van Dierendonck and van der Gaast, 2013), this study provides valuable information on how these constructs are associated for university teachers. While self-efficacy is relevant for both subjective career success and objective career success, it is obvious that goal orientation is relevant only for subjective career success, proving that some variables are relevant for only one career success category (Spurk et al., 2019).

Finally, the results concerning gender impact on career satisfaction are intriguing. Women are more inclined to have higher career satisfaction in this organizational context, in opposition to the research performed in other contexts (Afiouni and Karam, 2014; Santos, 2016). One could speculate that this is related to Romanian culture or to the university culture or non-discriminating policies, but further data is needed to test new hypotheses.

The major practical implication is that academics career success is linked to university context, while their goal orientation and self-efficacy are important predeterminants of career satisfaction. Building a more equitable system concerning advancement in academic positions to attenuate the managing position advantage and providing increased career support for those who have spent many years in the same positions, are the two challenges for BBU. Given these challenges, leadership support should be increased, for academics to understand their role in the continuous change implemented by their institution, this factor being important in maintaining an adequate level for academics’ career success (Lee, 2017).

In addition to the theory that goal orientation is adaptive (Kunst et al., 2018), it is clear that for recruitment purposes profiles should be used, as teachers to be hired should have high levels for performance goal orientation, mastery goal orientation and self-efficacy. Moreover, creating an atmosphere that facilitates a mastery orientation, establishing interventions aimed at enhancing a proactive approach from teachers, could be also solutions for improving teachers’ goal orientation (Joo and Ready, 2012). Goal orientation can be also changed through facilitative coaching behavior (Kunst et al., 2018) and teacher education should emphasize the development of teachers’ self-efficacy concept (Ballout, 2009). Teachers should be self-aware of their goal orientation profile and their self-efficacy level. They should also manage their career satisfaction level, as not advancing in the academic hierarchy could have a negative impact on their well-being.

While an important strength of this study is the association between organizational context, goal orientation, self-efficacy and career success, this research has some limitations. First, as the assessment variables were self-reported in a single survey by volunteer participants, common method variance might have inflated correlations between variables. Second, for this study a limited convenience sample from a single university was used, which implies that some groups of teachers are slightly over or underrepresented at the respondent level, thereby limiting the validity of this article’s results. Third, the study had a narrow focus, while the emerging results raised new questions to be answered, as to why gender matters for teachers’ career satisfaction at this university?

The author thank all teachers who have participated in this study.