Employee's subjective-well-being and job discretion: Designing gendered happy jobs

Abstract

This paper analyses the influence of job discretion on employees’ subjective well-being (SWB) from a gender-based approach. Specifically, it explores whether the level of discretion given to employees in performing their jobs influences their SWB and whether this impact differs between women and men. Data from 20 European countries from Round 8 of the European Social Survey (ESS) are used to undertake an ordered probit analysis. Job discretion is approached through autonomy at work, supervision of other employees and influence on organisational policy decisions. Additionally, the individual's educational level is controlled to further explore gendered differences of job characteristics on SWB. The results show that job discretion does indeed affect SWB, and this effect is different for women and men. Moreover, the effect of job discretion on SWB is not homogeneous across different education levels.

1

Introduction

The happy-productive worker hypothesis (Diener, 2000; Wright et al., 2007) highlights that happy workers are not only more productive than less happy workers but also have greater career success, earn more, and are more disposed to help others at work (Boehm & Lyubomirsky, 2008; Oswald et al., 2015). Employees’ subjective well-being (SWB) can thus be important for organisational results (Salas-Vallina et al., 2018). This assumption seeded a growing research stream around how to improve job characteristics to enhance job satisfaction, on the assumption that job satisfaction and SWB are highly correlated (e.g., Frey & Stutzer, 2002; Rothmann, 2008). This approach has demonstrated that facets of jobs associated with enriched jobs—such as autonomy, self-control and skill utilisation—have a positive relationship to job satisfaction (Boxall & Macky, 2014; Guest, 2017; Wood & De Menezes, 2011; Wood et al., 2012).

This research seems, however, to consider job satisfaction as a driver for SWB, not a result in itself. Further, while some aspects of jobs have been explored in depth, others (such as job discretion and self-management) seem to have been considerably underestimated (Guest, 2017). Previous research has assumed that women and men react similarly to these drivers of satisfaction, but seminal evidence on some features of jobs (e.g., professional status, time devoted to work and full-time versus partial-time work) have different effects on women's and men's perceived well-being (WB) (Brockmann et al., 2018; Seiler & Wanzenried, 2019; Trzcinski & Holst, 2012).

This paper addresses these gaps by analysing how some variables of job design can impact its occupants’ WB differently, depending on the occupant's gender. We particularly focus on job discretion—also termed autonomy or control—understood as the freedom of choice individuals are given to decide how and when to perform their job (Moen et al., 2016). In so doing, we follow previous results that show job discretion to be an important mechanism of employees’ WB (Alfes et al., 2020; Boxall & Macky, 2014; Guest, 2017). More specifically, we explore how the level of discretion given to employees influences their WB and whether this impact differs between women and men.

To achieve these goals, we analyse data from the European Social Survey (ESS, 2018 ). We performed an ordered probit analysis to estimate the effect of level of job discretion on the occupants’ SWB. Our results show that job discretion affects SWB and that this impact differs between women and men. These results provide an integrative analysis of the gender-based implications of job design for employee SWB.

The remainder of the paper is organised as follows. Section 2 offers a brief theoretical background on gender differences in individual satisfaction, focusing on occupational variables that seem to impact men's and women's satisfaction in different ways. Section 3 develops the empirical analysis, presenting materials and method used. Section 4 presents the results. Section 5 discusses the study's main findings. Finally, Section 6 presents the conclusions.

2

Theoretical background

2.1

WB and SWB

WB has been attracting increasing interest in recent decades since quality of life was identified as a proxy to assess societies’ relative progress (Exton et al., 2015). Seminal research on this topic was performed under the label of “subjective well-being” (SWB) (see Diener (2009) for a summary of literature review). Diener et al. (2009) defined SWB as people's cognitive and emotional evaluations of their lives, both at present and for longer periods such as the past year. These evaluations are influenced by the individual´s psychological personality and include both cognitive judgments of life satisfaction and affective evaluations of mood and emotions. Veenhoven (2008, p.2) defines SWB in virtually the same way, as “overall judgement of life that draws on two sources of information: cognitive comparison with standards of the good life (contentment) and affective information on how one feels most of the time (hedonic level of affect)”.

With few exceptions, SWB has usually been measured through life satisfaction and happiness based on the (co-)relation between these terms (Ferrer-i-Carbonell & Ramox, 2015; Veenhoven, 2014). SWB is comprised of two factors: (1) presence/absence of positive/negative affective states, and (2) global life satisfaction. Happiness—or WB—is usually conceptualised as the judgments made about satisfaction with life (Diener, 2000; Diener et al., 2009; Fisher, 2010).

In the economics literature, WB, happiness and life satisfaction are often used interchangeably (Frey & Stutzer, 2002; Weziak-Bialowolska et al., 2020). From this theoretical perspective, research has analysed some economic factors that affect individual perceptions of SWB extensively (see Clark (2018) for a recent review in this issue). These studies include income (Ferrer-i-Carbonell, 2005), occupational status/unemployment (Binder & Coad, 2015) and social capital (Neira et al., 2018; 2019; Puntscher et al., 2015). Overall, these studies support the conclusion that external factors affect SWB.

2.2

SWB at work

SWB has been studied in depth in several research fields (e.g., psychological personality characteristics, health, variations across the lifespan, and genetics), although SWB at work has received less attention from academics. Since the emergence of the happy-productive worker hypothesis (Diener, 2000), scholars have been persuaded that “happy” workers perform better than “unhappy” workers, a relationship supported by subsequent studies and meta-analysis (e.g., Bowling et al., 2010; Salas-Vallina et al., 2020; Sender et al., 2021). SWB thus seems to be important at an organisational micro-level as well, because employees’ SWB can be important for organisational results.

Researchers have used several alternative constructs to measure SWB at work, including job satisfaction, job involvement and individuals’ engagement (Fisher, 2010; Salinas-Vallina et al., 2018; Sender et al., 2021; Wright et al., 2007). Within this approach, research has focused primarily on work environment as a driver of job satisfaction. This line of research includes studies on physical environment (e.g., ventilation, infrastructure, amenities) and psychological environment (e.g., fatigue, boredom, monotony, burn-out) that support the conclusion that work environment has both negative and positive effects on employees’ welfare (Bhanu & Babu, 2018).

This approach mainstreamed a long-standing tradition of studies on the relationship between job satisfaction and job characteristics that assumes that the type of work and functions individuals perform can impact their job satisfaction. For example, the well-known Job Characteristics Model (JCM) (Hackman & Oldham, 1976) states that five job characteristics—task identity, task importance or significance, skill variety, autonomy, and feedback— are positively related to job satisfaction (see Rai & Maheshawari, 2021 for a recent review in this relationship).

Subsequent studies extended the job characteristics that act as drivers of job satisfaction, addressing the importance of low levels of job demand (e.g., workload, Boxall & Macky, 2014) and high levels of job autonomy and social support; time autonomy (Janssen & Nachreiner, 2004; Moen et al., 2016); personal control (Nijp et al., 2012; 2016) and skill utilisation, task variety and job security (Böckerman et al., 2012; Wood, 2008; Wood & De Menezes, 2011). Another cluster of studies analysed the combined effect of some of these features under the label of high-performance work systems (Alfes et al., 2020). Takeuchi et al. (2009) focused on the additional dimension of support encompassing high-performance work systems (e.g., an organisational climate that encourages skill acquisition practices and a sense of caring about employees). These studies, which enhance the role of job autonomy amongst high-performance work systems, provide evidence of the positive effects of job discretion on job satisfaction.

As can be inferred, these studies focus primarily on job satisfaction, not on WB, since these concepts have been traditionally treated as synonymous (e.g., Frey & Stutzer, 2002). On the basis of this direct relationship, research has explored which job characteristics can improve job quality and, in turn, employees’ SWB (Boxall & Macky, 2014). Another broad, multidisciplinary literature has highlighted job-intrinsic characteristics that affect occupants’ WB. For example, some research supports the conclusion that low levels of job demand (workload, stress) and high levels of job responsibility have a negative effect on job satisfaction, while high levels of job control (autonomy) and social support (from colleagues and/or supervisors) are positive predictors of job satisfaction, which in turn affects SWB (Boxall & Macky, 2014; Nijp et al., 2016; Mateos Romero & Salinas-Jimenez, 2018). Research has also stressed the role of human resources management systems in increasing job satisfaction and their effect on employee WB (Alfes et al., 2020; Peccei & Van de Voorde, 2019; see also Guest, 2017 for a comprehensive review on this topic).

Subsequent studies have, however, found lower correlations between job satisfaction and satisfaction with life. They have also found the incremental validity of happiness (understood as a proxy of SWB) over job satisfaction when assessing job performance (Bowling et al., 2010). These results highlight the need to distinguish between WB and job satisfaction, as the constructs are related but are distinct. Thus, job satisfaction can be considered as a driver of employees’ SWB but not as a result in itself. Nevertheless, previous research has obtained inconclusive results. For example, some studies found a limited relationship between work effort and individual's SWB (Robone et al., 2011; Wood & De Menezes, 2011), whereas others related work effort to lower SWB (Avgoustaki & Frankort, 2019; Green et al., 2016) and other negative effects that could in turn reduce SWB, such as inferior work-life balance or negative psychological states (Boxall & Macky, 2014; Schieman et al., 2016). These mixed results suggest that more investigation is needed to explore the effects of job characteristics on SWB.

Another relevant question is whether these results are sensitive to gender differences. Seminal research on this issue suggests that job characteristics affect the individual's SWB differently depending on the occupant's gender. For example, in their research on working-family conflict amongst German managers, Trzcinski and Holst (2010) found that men scored higher in SWB since women must choose between career and family. Similarly, Booth and Van Ours (2009) found that part- and full-time work have different effects on the perceived SWB of men and women. Additionally, Salinas-Jiménez et al. (2013) found that variables such as participation in the workforce, part-time work, and professional status impact men's and women's satisfaction differently. Brockmann et al. (2018) found that women in managerial positions were less satisfied than men in these jobs due to biological differences. More recently, in their study on work-life balance (WLB) across occupations in Canada, Dimaghani and Tabvurna (2019) found that women in management had lower WLB satisfaction than their male counterparts. Another cluster of findings based on meta-analytic reviews show inconsistent results. Whereas Stevenson and Wolfers (2009) concluded that men had higher satisfaction with life than women, Wood and De Menezes (2011) found the opposite. Pinquart and Sörensen (2001), in turn, found that men had slightly higher levels of life satisfaction than women. Although these studies are based on the global gender inequalities index developed by the United Nations, the inconclusive results suggest that more research is needed on the issue.

Further, it seems that not only gender but also education level may influence the effects of work discretion on employees’ WB. On the one hand, education may have an indirect effect on SWB (Powdthavee, 2010) by promoting more opportunities on the labour market that involve better and more interesting types of employment (Salinas-Jiménez et al., 2013). In this regard, Verhofstadt et al. (2007) argued that highly educated people are associated with higher occupational positions, which provide higher autonomy and skill use, which in turn may affect their overall SWB. However, highly educated people have higher work expectations that are more difficult to fulfil and that may thus result in frustration, negatively affecting SWB.

2.3

Theoretical model and hypothesis

As aforementioned, previous research supports the conclusion that some job characteristics affect individuals’ job satisfaction at work, but the same characteristics showed mixed effects on SWB. Moreover, it seems obvious that men and women are not equally susceptible to these effects. Furthermore, education level may be relevant when measuring SWB at work, since it influences autonomy and skill use, which can have a positive effect on SWB, but also raises job expectations, which can undermine SWB at work. To shed light on these matters, the following section estimates whether and how job characteristics have a different effect on women's and men's WB and whether this effect depends on individuals’ education level.

Previous research has identified autonomy as a driver improving employee satisfaction (Batt & Valcour, 2003; Boxall & Macky, 2014). Greater autonomy may grant employees flexibility, reducing problems such as those associated with WLB and improving the individual's SWB (Glavin & Schieman, 2012; Wheatley, 2017). The possible effect that supervision and influence on decisions have on SWB has been largely neglected. Previous research has explored in depth the effects of supervision on subordinates, whether negative as a consequence of abusive supervision (i.e., Tepper, 2007) or positive as a result of supportive supervision (i.e., Van Dierendonck et al., 2004). However, little is known about the effect that being a supervisor has on individuals’ SWB. In the same line, while employees’ SWB may depend on organisational decisions, the possibility of influencing policy decision can affect SWB, although this effect requires further investigation. A meta-analysis by Chiaburu et al. (2014) affirmed an initial relationship, that participation has a positive effect on SWB. We thus propose that supervision and influence on decisions affect SWB at work, since both reinforce job autonomy. The job characteristics model (Hackman & Oldham, 1976) proposed that core job characteristics generate a sense of responsibility for outcomes, which in turn elicits job satisfaction, an indicator of SWB at work. Consistent with this idea, we expect these factors to affect SWB, since supervision and influence reinforce this responsibility.

Thus, this study treated SWB as a dependant variable, and autonomy, supervision and influence on policy decisions as independent variables. Other organisational variables (type and size of company), employment relationship, main occupation and educational level were also controlled in the analysis.

3

Materials and methods

3.1

Data and methodology

To test our theoretical model, we use data from the 8th wave (2018) of the European Social Survey (ESS, 2018). The ESS was designed to enable systematic study of European social and demographic trends.¹ Although the ESS data spanned 21 primarily European countries, problems of availability led us to analyse 37,629 individuals in 20 European countries.²

Our dependant variable is SWB. Following previous literature (Binder & Coad, 2015; Binder & Freytag, 2013; Neira et al., 2018, 2019; Puntscher et al., 2015), this paper uses individuals' responses to ESS questions about life satisfaction to measure well-being (ESS, 2018). The ESS provides information for life satisfaction based on the question, “All things considered, how satisfied are you with your life as a whole nowadays?” Answers range on a scale from zero (extremely dissatisfied) to ten (extremely satisfied).

Our main independent variable is job discretion. We assess job discretion through three proxies: perceived autonomy, supervision and influence on organisational policy decisions. As noted, autonomy refers to the freedom of choice given to individuals to decide how and when perform their job, including formal or informal working arrangements and delegation of tasks. The more autonomy on the work, the greater occupants’ capacity to decide how their daily work is organised. Supervision, in turn, refers to the capacity to take decisions about others’ jobs, as well as to control performance of tasks and results. Finally, the influence on organisational decisions indicates capacity to influence decisions about the organisation's activities and processes. We also used the ESS (2018) to measure these independent variables, specifically, the questions related to level of autonomy, responsibility for supervising other employees and influence on policy decisions at one's organisation. Table 1 presents the specific questions and answers recorded.

Table 1.

Measures for job discretion.

VARIABLE	ESS (2018) QUESTION	OPTIONS
AUTONOMY	How much does the management at your work allow you to decide how your daily work is organised?	Low influence Medium influence High influence
SUPERVISION	In your main job, do/did you have any responsibility for supervising the work of other employees?	Yes No
INFLUENCE ON POLICY DECISION	How much does the management at your work allow you to influence decisions about your organisation's activities?	Low influence  Medium influence High influence

Source. The authors, using data from the ESS (2018).

Following previous literature, we included other control variables, such as relationship to employer (Employee, Self-employed, Working for own family business), type of work (Public Sector, Private Sector, Self-employed), size of business and kind of activity (International Standard Classification of Activities, ISCO). We also included as control variables some individual circumstances of respondents, namely whether they had been unemployed during the past three months (Yes or No), their main activity (Paid work; Unemployed; Retired; Other) and if they were a member of trade union (Yes or Not).

Finally, we used education level to divide the sample and further explore its effects on individuals’ SWB. The variable education has been measured through the International Standard Classification of Education (ISCED), developed by UNESCO to organise educational levels and facilitate comparison of education statistics and indicators across countries on the basis of uniform and internationally agreed-upon definitions (European Commission, 2019).³ This classification uses different education levels, namely ISCED 0 (Early childhood education or ‘less than primary’ education), ISCED 1 (Primary education), ISCED 2 (Lower secondary education), ISCED 3 (Upper secondary education), ISCED 4 (Post-secondary non-tertiary education), ISCED 5 (Short-cycle tertiary education), ISCED 6 (Bachelor's or equivalent), ISCED 7 (Master's or equivalent) and ISCED 8 (Doctoral or equivalent). We used these levels to make a simplified classification to better understand people's behaviour based on education level. Our sample division thus differentiates between low, intermediate and high education levels, using the classifications primary and lower secondary education (ISCED 1&2), for low, secondary education (ISCED 3&4) for intermediate, and tertiary education (ISCED 5, 6, 7 & 8) for high education.

4

Results

Table 2 reports the results of the PROBIT analysis; columns 1 and 2 present the estimates of SWB by gender and columns 3 to 6 the same estimates based on respondent's educational level.

Table 2.

Estimates of job discretion on SWB by gender and educational level.

			ISCED
	MALE	FEMALE	1&2 MALE	1&2-FEMALE	3,4,5,6-MALE	3,4,5,6 - FEM
Age of respondent	−0.037^⁎⁎⁎[0.004]	−0.044^⁎⁎⁎[0.004]	−0.034^⁎⁎⁎[0.006]	−0.050^⁎⁎⁎[0.007]	−0.040^⁎⁎⁎[0.005]	−0.046^⁎⁎⁎[0.005]
Age of respondent (squared)	0.000^⁎⁎⁎[0.000]	0.000^⁎⁎⁎[0.000]	0.000^⁎⁎⁎[0.000]	0.000^⁎⁎⁎[0.000]	0.000^⁎⁎⁎[0.000]	0.000^⁎⁎⁎[0.000]
Autonomy
Medium influence	0.057[0.031]	0.020[0.028]	0.101[0.058]	0.028[0.053]	0.046[0.038]	0.012[0.033]
High influence	0.243^⁎⁎⁎[0.035]	0.241^⁎⁎⁎[0.031]	0.265^⁎⁎⁎[0.070]	0.199^⁎⁎[0.065]	0.234^⁎⁎⁎[0.041]	0.238^⁎⁎⁎[0.036]
Supervision
Yes	0.097^⁎⁎⁎[0.022]	0.028[0.023]	0.029[0.053]	0.000[0.058]	0.111^⁎⁎⁎[0.024]	0.028[0.025]
Influence on Policy Decisions
Medium influence	0.029[0.024]	0.057*[0.022]	−0.038[0.053]	0.005[0.051]	0.049[0.027]	0.069^⁎⁎[0.025]
High influence	0.186^⁎⁎⁎[0.032]	0.156^⁎⁎⁎[0.032]	0.035[0.076]	0.167*[0.081]	0.233^⁎⁎⁎[0.036]	0.163^⁎⁎⁎
OTHER WORK CHARACTERISTICS
EMPLOYMENT RELATIONSHIP
In your main job, are/were you….
Self-employed	−0.072[0.040]	−0.010[0.052]	0.141[0.085]	0.029[0.124]	−0.127^⁎⁎[0.046]	−0.028[0.057]
Working for own family's business	0.023[0.078]	0.208*[0.084]	0.110[0.148]	0.456^⁎⁎⁎[0.131]	−0.007[0.089]	0.092[0.105]
Type of organisation
Private firm	0.058*[0.029]	0.006[0.026]	0.083[0.062]	0.017[0.053]	0.069*[0.032]	0.028[0.029]
Self-employed	−0.014[0.049]	−0.148*[0.059]	−0.126[0.099]	−0.207[0.124]	0.038[0.057]	−0.104[0.067]
Size of company
10 to 24 employees	−0.053[0.030]	0.018[0.028]	−0.066[0.059]	0.074[0.059]	−0.053[0.035]	−0.005[0.032]
25 to 99 employees	−0.011[0.029]	0.001[0.027]	−0.089[0.062]	0.022[0.060]	0.001[0.034]	−0.022[0.030]
100 to 499 employees	0.031[0.032]	−0.057[0.031]	−0.014[0.071]	−0.060[0.068]	0.033[0.036]	−0.075*[0.035]
500 or more employees	0.113^⁎⁎[0.035]	0.034[0.037]	0.112[0.079]	0.049[0.092]	0.107^⁎⁎0.040]	0.015[0.041]
INCOME LEVEL
Medium	0.148^⁎⁎⁎[0.026]	0.129^⁎⁎⁎[0.024]	0.170^⁎⁎⁎[0.046]	0.136^⁎⁎[0.047]	0.135^⁎⁎⁎[0.031]	0.119^⁎⁎⁎[0.028]
High	0.264^⁎⁎⁎[0.030]	0.239^⁎⁎⁎[0.029]	0.313^⁎⁎⁎[0.068]	0.208^⁎⁎[0.071]	0.246^⁎⁎⁎[0.034]	0.235^⁎⁎⁎[0.033]
ISCO (International Standard Classification of Occupations)
Managers	0.104^⁎⁎[0.035]	0.077[0.042]	0.099[0.095]	0.188[0.168]	0.100^⁎⁎[0.037]	0.067[0.042]
Professionals	0.095^⁎⁎[0.033]	0.088^⁎⁎[0.030]	0.109[0.121]	−0.066[0.105]	0.090^⁎⁎[0.032]	0.096^⁎⁎[0.029]
Technicians and Associate Professionals	0.072*[0.029]	0.058*[0.027]	−0.107[0.080]	0.121[0.073]	0.105^⁎⁎⁎[0.030]	0.046[0.029]
Unemployment 3 months Yes	−0.345***[0.047]	−0.262***[0.051]	−0.106*[0.045]	−0.160***[0.047]	−0.203***[0.024]	−0.128***[0.023]

Standard errors in brackets.

Significant at * p < 0.05, ** p < 0.01, *** p < 0.001. Standardized β coefficients are reported.

The PROBIT analysis of job discretion (autonomy, supervision and influence on policy decisions) showed that these job characteristics are important in explaining employees’ SWB (p < 0.001) but that the significant relationship differs for women and men. The gender differences identified are that the influence of autonomy (β=0.243***), supervision (β=0.097***) and having strong influence on policy decisions (β=0.186***) are slightly more important for men than for women. As for autonomy, participants acknowledge that having a high level of autonomy at work has a positive effect on SWB, which is significant both for men (β=0.243***) and women (β=0.241***). The results on supervision show that having the capacity to control the accomplishment of others’ tasks and results and taking decisions about their jobs has a positive and statistically significant effect on employees’ SWB, but only for male respondents (β=0.097***). For women, the relationship is also positive but not significant (β=0.028). Finally, our results showed that having a strong influence on policy decisions at organisations has a positive and significant effect on SWB for men (β=0.186***) and women (β=0.156***), and that this influence is again higher for male employees.

Male respondents thus showed higher SWB, first, in jobs that gave them freedom to decide how to manage and organise their work, and, next, according to the degree of responsibility in supervision given and influence on policy decisions. Female participants had higher SWB in jobs with a high degree of autonomy and influence on policy decisions but lower SWB in jobs with supervision tasks.

Interrelations amongst these job characteristics and the participants’ education level are also presented in Table 2. A second PROBIT analysis was conducted to test whether SWB would vary with education. As Table 2 shows, control over one's work is positively associated with SWB for all workers, although the effect is stronger for well-educated individuals (β=0.238***). Further exploration of the results showed division along the lines of participants educational level, revealing that only men with a high educational level increase their SWB when supervising other employees (β=0.111***). Women, in contrast, do not enjoy these supervisory tasks, regardless of their educational level. However, women regardless of education level experience an increase in SWB when they can influence policy decisions about the activities at their organisation. Participating in decision making in the workplace is thus positive for women, independently of their education level. Influencing policy decisions has a positive and significant effect on men's SWB, but only amongst men with a high education level (β=0.233***).

Table 2 also presents the results for other control variables, namely type and size of company, occupation and type of employment. As the table shows, men showed higher SWB in private firms (β=0.058*) and large companies, particularly when they were highly-educated (β=0.069* and β=0.107**, respectively). Yet the opposite occurs with women. Female participants had higher SWB when they were working in a family business (β=0.208*), especially women with a low education level (β=0.456***). Finally, working as a manager had a positive and significant effect on men's SWB (β=0.104**). For women, SWB increased when they worked as professionals (β=0.088**) or technicians (β=0.058*). As can be expected, being unemployed had a significant and negative influence on SWB in all cases.

5

Discussion

This paper analyses the influence of job discretion on employees’ subjective well-being (SWB) from a gender-based approach. Specifically, it explores whether the level of discretion given to employees in performing their jobs influences their SWB and whether this impact differs between women and men. The results suggest that these factors indeed affect employees’ SWB, although linkages between them may have different effects depending on employees’ characteristics. Thus, participants report higher levels of SWB when their jobs provide them a high level of autonomy, as has been largely supported in previous research (i.e., Glavin & Schieman, 2012; Kalleberg, 2012; Wheatley, 2017). Studies by Alfes et al. (2000) also found that giving employees opportunities to participate is an important mechanism for achieving employees’ SWB. In fact, direct employee participation has been identified as one of the most-advocated interventions for influencing worker’ SWB (Humphrey et al., 2008). Additionally, control over task management and timing have been identified as paths to improve employee's SWB (Batt & Valcour, 2003; Kalleberg et al., 2009). Boxall and Macky (2014) also stress the importance of control. Their studies highlight that workers with greater control over their jobs registered a reduction in perceived job stress, thus increasing their SWB (Mackie et al., 2001).

As expected, the findings show gender differences for the effect of job-characteristics on SWB, with men scoring higher than women. Additionally, supervision seems not to affect female employees’ SWB, while it is important for males. The respondents’ education level was also important for both genders, as it introduces different effects. Participants expressed higher levels of SWB related to autonomy, supervision and influence on policy decisions as education level increased, with men scoring slightly higher than women. This finding accords with previous research, which found that education has an indirect effect on SWB through the promotion of interesting opportunities for employment and professional development. This effect is due to promotion of more opportunities on the labour market that involve better, more interesting types of employment (Salinas-Jiménez et al., 2013; Verhofstadt et al., 2007; Warr, 2007).

We also found that other work characteristics affect employees’ SWB by exploring the effect of occupational status on SWB. As different settings provide individuals with different opportunities and expectations (even in the same company), individuals’ SWB is likely to be heterogeneous (Bertrand, 2013). Our results on this point align with previous studies noting the positive effect of high-status occupations on SWB (i.e., Clark et al., 2008; Rollero et al., 2016; Salinas-Jiménez et al., 2013). Our analysis shows that working as a manager has a positive and significant impact on SWB for men, whereas women value being professionals or technicians. Further, working as a manager, technician or associate professional only affects SWB positively and significantly for highly educated men, while such work has no significant effect at lower education levels. SWB in managerial and professional jobs thus seems not to be independent of education level but rather to be highly determined by it.

The results also show that self-employment does not have a significant effect on SWB, nor does gender or education level. However, highly educated men experience lower SWB when they are self-employed. This analysis aligns with recent studies that show associations of job satisfaction with promotion and growth opportunities at work (Waddimba et al., 2019), as well as task contribution made at work (Kollmann et al., 2020). The opposite occurs when they work at private firms, where they experience higher SWB. In this line, working for a family business has a positive and significant effect on women's SWB—especially for women with a low education level. This suggests that unskilled women favour the collective and cooperative organizational climate that is specific of family businesses.

Findings also agree with previous research that shows that being unemployed has a negative and significant effect on SWB (Stam et al., 2015) and with previous studies that support a relationship between age and SWB (Kollman et al., 2020). Our results thus show a significant U-shaped relationship to SWB, meaning that young and old people tend to be happier than those in middle age. Married people seem to be happier than the divorced or widowed or those who never married. The results on place of residence show that living in a small town or in the countryside provides greater SWB than living in a big city, a result in line with Hudson (2006). Being unemployed and not currently being a trade union member has a negative and statistically significant effect on SWB. Finally, having a medium or high income has a positive and significant effect on individual SWB.

Our study thus makes important contributions to understanding how to design jobs to improve employees’ SWB. First, while unemployment negatively impacts SWB, job characteristics can indeed improve employee's SWB. This effect, as well as the effect of job characteristics on employees’ SWB, supports Fisher's (2010) assumption that happiness at work seems largely overlooked. Second, we explored the effect of discretion and responsibility on SWB in the workplace. A general view of our results shows that women's SWB seems to be more influenced by discretion, whereas men's SWB is positively associated to higher job responsibility. This result is important, since no research to date has explored the importance of these factors to SWB. Additionally, we found that some features that can be labelled job “power” or “status”—such as controlling others or being a manager— affect male employees’ SWB but do not have a significant effect on female employees. This finding is in line with the study by Trzcinski and Holst (2012) on individuals in management positions, which found that status on the labour market was associated with subjective life satisfaction but that women in leadership positions seem less satisfied than men in the same positions; nor does women's life satisfaction increase when they occupy top management positions (Brockmann et al., 2018; Trzcinski & Holst, 2012).

Education level is also important to employees’ SWB. The results suggest that the importance of expectations at work, since employees with high education levels could expect to obtain access to more prestigious occupations and have opportunities for promotion. Accomplishing these expectations would then affect employees’ SWB at work. In any case, this is a relationship that requires further testing.

Our findings have also managerial implications since they raise the question whether companies make implicit or explicit decisions that impact SWB in the workplace. A workplace that provides jobs with autonomy, supervision and influence in policy decisions can directly impact employees’ SWB and, in turn, their job satisfaction. The differences identified here by education level and gender suggest that highly-educated employees can experience specific problems in the workplace, and that there are gender differences in SWB. Thus, understanding the relationship between gender and job characteristics, as well as how this relationship differs by gender, is crucial to improving SWB. Theoretically, this result sheds light on how gender differences provide an in-depth framework for organising jobs and influencing their occupants’ SWB to encourage equality. This seminal result suggests the importance of further research on this topic, as well as of expanding the number of job characteristics to be considered.

This study contributes to existing knowledge of SWB at work by identifying gender differences and job characteristics that can improve organisational job design processes. The data suggest that high discretion and responsibility in the workplace are associated with high levels of SWB, but female respondents scored lower on both of these job-related characteristics than men. Further, well-educated employees are more affected by these features. Altogether, the results imply that these groups (female employees and well-educated individuals) may face specific problems that require particular attention when designing their jobs.

Some limitations should be mentioned. First, as we used official data, they were collected at a single point in time. Moreover, some distinctions that might be important for interpretations were not available, such as age intervals. Additionally, the data determine the context to which the results apply (European context) while highlighting no country differences. Thus, our results cannot be generalized to other cultural contexts without caution. Rather, future research should investigate the replicability of these findings in other countries.

Some specific suggestions for future research might increase the interest and contributions of this study. Specifically, additional qualitative studies can contribute to better examine the relationship of gender and work-related well-being. For example, the issue pertaining the less satisfaction of women in top management positions could be explicitly addressed, exploring whether women evaluate their work-related well-being on occupational positions. In addition, future studies should consider other job characteristics and extend insights by examining gendered workplaces.

6

Conclusions

The main result of our study is that jobs present structural constraints that can influence workers’ SWB. We show that some job characteristics—namely autonomy, supervision and influence on decisions— have a positive effect on employees’ SWB. As a whole, these results suggest that perception of individual control and power over the work environment is important for SWB. The presence of mechanisms to increase participation in turn fosters employees’ opportunity to improve their engagement, which leads ultimately to higher SWB. Designing jobs that give their holders discretion and responsibility is essential to improving individuals’ SWB. This result can, in turn, be associated with the job redesign movement and the concept of job enrichment. However, it agrees with Gibson et al.’s (2007) claim that the literature has become discrete in analysing the role of employee's involvement.

The results also show that the effect of these work-related variables (job discretion) on SWB is not homogeneous either across the different education levels analysed or at gender level. First, analysis of the differences by education level shows that autonomy correlates positively with well-being for men and women of all education levels. Second, having a strong influence on organisational decisions plays a positive role amongst employees with higher education levels only, regardless of gender.

The most significant differences between genders indicate that women managers who supervise other employees do not experience higher levels of SWB, even in the case of women with high education levels, which could have high job expectations. This finding is reinforced if we consider the type of employment, since male employees working in private firms with more than 500 individuals show more SWB as long as they are empowered with supervisory roles.

Overall, these results contribute to the debate over the reasons why it is difficult for women to obtain promotions in organizations. Our findings indicate that, in addition to exploring exogenous barriers in depth, individual preferences—such as the relationship of SWB to one's job— should also be considered. Women's SWB is not influenced by powerful positions, but by job discretion, and participation in decision-making processes increases women's SWB at work. Given that SWB influences performance, these effects can either undermine or favour women's options when they compete for managerial jobs. This issue should be addressed explicitly when designing promotion processes to foster organizations in which diversity and equality are pillars of the organizational culture.

Compliance with ethical standards

The authors declare that they have no conflict of interest.

Also, all the authors have contributed to the manuscript substantially and have agreed to the final submitted version.

Funding sources

This research was conducted as part of the project ref. RTI2018–101,722-B-I00 ‘Spanish Universities Involvement in Social Innovation Activities’ (SUISIA), funded by the National R&D Programme of the Spanish Ministry of Science, Innovation and Universities. The views expressed in this paper are not necessarily the views of that organization.

Acknowledgments

This research was conducted as part of the project ref. RTI2018–101722-B-I00 ‘Spanish Universities Involvement in Social Innovation Activities’ (SUISIA), funded by the National R&D Programme of the Spanish Ministry of Science, Innovation and Universities. The views expressed in this paper are not necessarily the views of that organization.

Also, the authors declare that they have no conflict of interest.