AUSTRIANS-
ARE THEY HAPPY AT WORK?
October, 2011
Sophie Martys
Student number: 1946250
Kliebergasse 1/Top 25, A-1050 Wien, AUSTRIA +43 650 434 8569
smartys@gmx.at
University of Groningen Faculty of Economics and Business Msc. Human Resource Management
“It is pretty hard to tell what does bring happiness; poverty and wealth have both failed”
Kin Hubbard, American Humorist
1 INTRODUCTION
Happiness is perceived as an ultimate goal of life which is virtually sought by everybody (Frey & Stutzer, 2002). Within the last decades the research on happiness has been intensified and, to date an extensive body of literature has been accumulated. Although, the happiness research is booming, little is known about the happiness of workers and the scientific community has only recently started to investigate in this matter. Hereof, it is known that employed persons are happier than nonworkers (Di Tella, MacCulloch & Oswald, 2001). For years, work has been viewed as a burden to bear to individuals, but research confirmed that being without a job, even when receiving the same income as during employment, people are more likely to become depressed, and thus, considerably less happy (Winkelmann & Winkelmann, 1998).
In contrast to job satisfaction (e.g. Herzberg, 1987; Hackman & Oldham, 1976), which has been intensively investigated by both sociologists and psychologists, the happiness of workers has only been recently addressed by researchers. Economists, for example, examined the level of workers’ happiness related to inflation (Di Tella et al., 2001), to the GDP per capita (Stanca, 2010) or institutional factors (Helliwell, 2001, as cited in Frey & Stutzer, 2002). The assumption that work itself and its characteristics provide some intrinsic value to happiness is rather new. As a consequence, this master thesis seeks to add value to the existing body of literature by examining the field of happiness based on the view that work itself is a source of happiness, thus, intrinsically rewarding and leading to both, higher levels of employee happiness and satisfaction
environment etc. Consequently, such work characteristics are expected to affect the relationship between work and happiness. At this, the question which of these factors actually contribute to higher levels of happiness arises.
This paper aims to investigate the level of happiness of the Austrian workforce by building on the study of van der Meer and Wielers (2011), which focused on the happiness of workers on a European wide basis. In their study, the happiness of the Austrian workers scored above average. However, according to the Austrian Chamber of Labour (Arbeiterkammer), both the level of contentedness as well as the level of the general life satisfaction of the Austrian workers has reached its bottom in 2010 since the beginning of the survey in 1997 (IT 1). Taking this issue as a starting point, this thesis seeks to examine what actually makes Austrian workers happy.
This study is one of the few addressing the happiness in Austria, which has so far only been investigated in cross-national contexts (e.g. Diener, Diener & Diener, 1995; Stanca, 2010) but rarely has been considered as a main research topic.
well-being, (job) satisfaction, as well as happiness and, thus, have been identified as important contextual and situational determinants for the Austrian workforce. In addition, considerable variations among gender regarding the determinants of happiness are expected to occur due to the different societal role men and women have and the consequential occupational segregation (Pugliesi, 1995). Therefore, gender has been decided on as a relevant socio-demographic determinant of happiness in this study.
These determinants of happiness will not only help to determine what makes workers happy or unhappy, but also give information about how to improve the current situation in Austria. In the end, some practical implications regarding what kind of actions should be taken by Austrian policymakers to increase the level of happiness will be given.
In the following, this set of research questions about happiness will be addressed: 1. What is the prevailing situation in Austria in terms of employee happiness?
2. What makes Austrian workers happy?
3. Are there any gender differences regarding the determinants of happiness?
2 THEORETICAL FRAMEWORK
Happiness at work
For a long time, happiness has been considered “as a purely personal issue” (Frey & Stutzer, 2001: VII) and researchers only recently have begun to acknowledge that happiness or subjective well-being is also strongly influenced by economic, institutional as well as situational and contextual factors (Frey & Stutzer, 2001).
(3) it is based on a holistic judgment rather than a narrowly-focused assessment of life. Happiness can refer to both, peace of mind and contentment as well as to fun and excitement (Freedman, 1978 as cited in Warr, 2007). People generally relate happiness to quality of life rather than prosperity (Diener, 2000). Moreover, people who consider themselves as happy also feel that that their lives have a greater meaning (King, Hicks, Krull & Del Gaiso, 2006).
Work plays a crucial role in the determination of people’s happiness: in order to attain genuine happiness in life, they must be happy with their job. A person who is unhappy at work can never be truly happy (Gavin & Mason, 2004). According to Fisher (2010: 385), happiness at work refers to “pleasant judgements (positive attitudes) or pleasant experiences (positive feelings, moods, emotions, flow states) at work.” Happiness at work relates to the enjoyment of and being strongly involved in one’s work while “experiencing a sense of significance, enthusiasm and challenge” (Bakker & Demerouti, 2008: 209). In a similar vein, Warr (1999, as cited in Sparr & Sonnentag, 2008) conceptualized job-specific well-being around three axes namely (1) displeasure – pleasure, (2) anxiety – comfort and (3) depression – enthusiasm, which are aligned on the two principal dimensions of pleasure and arousal (Warr, 1990 as cited in Mäkikangas, Feldt & Kinnunen, 2007; see Figure 1 below).
Figure 1: Job-specific Well-Being
feelings of attachment and belonging, have often been associated with happiness at work (Fisher, 2010).
Happiness, however, not only has important implications for individuals, but also for the workplace and the job performance. Evidence suggests that happy workers are productive workers (Zelenski, Murphy & Jenkins, 2008) and more helpful towards others (George, 1991). In addition, employees in positive moods look at problems in more flexible and creative ways and recognize coherences easier (Isen, Daubman, & Nowicki, 1987). There is ample support that happiness can create desirable outcomes for the working world and consequently, organizations should try hard to achieve high levels of employee happiness.
Happiness in Austria
So far, Austria has not received lot of attention in research as regards employee happiness or workers’ well-being since only few studies included this country in their analysis (e.g. van der Meer & Wielers, 2011; Swami, Stieger, Voracek, Dressler, Eisma & Furnham, 2009; Diener et al., 1995). Generally, individualistic countries like Austria report higher levels of well-being than collectivist countries (Diener, Diener & Diener, 1995), as individualists attach greater importance to personal achievements in both private and work areas, which form an integral part in the pursuit of happiness (Uchida, Norasakkunkit & Kitayama, 2004). In comparison to other European countries, Austrian workers scores above average in terms of happiness and life satisfaction (van der Meer & Wielers, 2011). Although these studies provide evidence that the Austrian workforce maintains higher levels of well-being, very little is known what actually makes them happy. Consequently, the aim of this paper is to apply the concept of happiness to Austria and seeks to investigate what makes Austrian workers happy.
Current Situation
satisfaction and the job satisfaction of the Austrian workforce have dropped sharply since 2008 (see Figure 2 & 3), whereas the latter achieved the lowest results since the beginning of the survey in 1997. This drop happened about at the same time with the global financial crisis, which brought along many layoffs, restructurings and company shutdowns in Austria.
Figure 2: Overall Job Satisfaction Index from 1997-2011
Although the Austrian economy begun to recuperate in the beginning of 2010, the job satisfaction of the Austrian workforce maintained at the same low level, whereas the life satisfaction curve (Figure 3) continued to decline. Consequently, the common view that the financial crisis is the main reason contributing to the low happiness of the workforce is challenged. Rather it is argued in this paper that other work-related factors largely determine the well-being of the workforce in Austria.
Determinants of happiness
As already mentioned earlier, this study will only discuss situational and contextual as well as socio-demographic determinants of happiness. The former mainly refer to employment, working and living conditions, health and personal relationships with co-workers or relatives and friends (Frey & Stutzer, 2001). Since this thesis is focusing on the happiness of the Austrian workforce, determinants related to employment and working conditions will be elaborated on. In the following, the three determinants of happiness chosen for this study will be defined and their relationship to happiness explored. In addition, justifications why these factors are considered relevant for this very topic will be given.
Job security
Job security is considered as the perceived likelihood to keep one’s job in a certain time spell. Furthermore it refers to the extent to which a person has the same job throughout his/her working life (Orio & Pagani, 2009).
Ample support has been found in research confirming that job insecurity has negative effects on health and contributes to burnout and feelings of exhaustion (Dekker & Schaufeli 1995), which eventually leads to both poor job-related and impaired well-being (De Witte, 1999; Cheng & Chan, 2008). If job insecurity significantly harms workers’ happiness, it can be inferred that job security should be able to advance subjective well-being.
Employees with higher job security feel more confident in their job (Kraimer, Wayne, Liden & Sparrowe, 2005), show lower levels of psychological distress (Dekker & Schaufeli, 1995) and are more satisfied with their current occupation (Theodossiou & Vasileiou, 2007). In addition, high levels of job security lead to a stronger commitment to and a feeling of belonging to the organization (Ashoford, Lee & Bobko, 1989). Both job satisfaction and this feeling of belonging, which emerge from a perception of job security, are important preconditions for achieving higher levels of happiness in both work-related and life areas.
Moreover, a person who views his future employment as secured feels in control in the determination of his/her future (Greenhalgh & Rosenblatt, 1984). Personal control is considered as an individual’s belief that he/she is able to behave in ways that enhance positive outcomes and diminish negative ones (Peterson, 1999, as cited in Sparr & Sonnentag, 2008), and is thus, very likely to result in happiness. In his book, Warr (2007) also related personal control to the three well-being axes mentioned above.
The above lines of reasoning imply the following hypothesis:
Hypothesis 1: Job security is positively related to workers’ happiness.
Work-life balance
work. Although the importance of WLB is widely acknowledged, few efforts have been made to implement the idea into practice (Leitner, Littig & Wroblewski, 2005). Similar to other European countries, in Austria the actual average working time differs significantly from the requested working hours (Eurofound, 2003). Since WLB is a vital feature of any occupation but still lacks realization in practice, it has been identified as an important determinant of the happiness of the Austrian workforce.
Ideally, WLB would mean sufficient time spent in both work and family domains irrespective of job or family demands, financial pressures or the family situation (Greenhaus, Collins & Shaw, 2003). A good balance refers to performing well at work and at home with little role conflict (Clark, 2000). Employees who perceive their organization as supportive in achieving an equilibrium between the time spent on work and on family, should thus experience greater levels of well-being.
Research showed that a work-family conflict significantly impairs both, job and life satisfaction while fostering unhappiness, stress and substance abuse (Greenhaus, Allen & Spector, 2006). On the other hand, when a conciliation between both areas is perceived, people tend to meet their respective needs and responsibilities more easier in work and family matters. Moreover, they experience fewer stress and obtain self-esteem from the competence in fulfilling their role expectations in working and family lives (Marks & MacDermid, 1996). Lower levels of stress positively affect greater well-being (Rego & Cunha, 2008) as well as self-esteem leads to life satisfaction (Joshanloo & Afshari, 2011), and thus to happiness.
Greenblatt (2002, as cited in as cited in Reiter, 2007: 278) describes WLB as “acceptable levels of conflict between work and nonwork demands”, which imply managing resources for competing demands. Once these resources are obtained and managed effectively, people can meet work-related and personal obligations, and hence, are able to fulfil their own needs as well as those from their direct environment. This feeling of fulfilment in both main areas of life is likely to result in higher levels of happiness.
The above lines of reasoning support the following hypothesis:
Development Opportunities
The third variable, which is expected to positively influence employees’ happiness, is development opportunities. However, development opportunities do not merely refer to career advancement but also to training, skill and competency development, and learning (Kuvaas & Dysvik, 2010). In Austria, further education and training is a relevant component of the professional life due to the steadily increasing work requirements (IT 4). Developing one’s competencies and skills does not only represent a good protection against job loss, but is also a critical success factor for the economic system (IT 5). In happiness research, development opportunities have proven to be a significant factor in determining employee happiness (Rego & Cunha, 2009), whereas besides few studies (e.g. Turner, Huemann & Keega, 2008; Demel & Mayrhofer, 2010) there is little evidence as related to Austria. In order to close this research gap, this thesis will investigate the effect of development opportunities on the happiness of the Austrian workforce.
Development opportunities do not merely refer to actual training programs, but also to the employees’ perception that the respective organization supports them in learning and enhancing their set of skills and abilities towards fully developing their potential (Rego & Cunha, 2009). This form of employee investment not only signals the workers that their contribution and efforts are acknowledged, but also that they are important and valuable to the organization (Lee & Bruvold, 2003). Thereby the workers’ feeling of doing something meaningful is likely to rise and eventually results in happiness and fulfilment.
Evidence in research suggests that development opportunities allow employees to satisfy their needs for learning and personal growth and thereby reinforce their sense of competence, determination and gratification (Kets de Vries, 2001), and consequently, is also likely to rise the feeling of happiness.
The above lines of reasoning support the following hypothesis:
Hypothesis 3: Development opportunities are positively related to workers’ happiness.
Gender
Due to the different social roles men and women hold in the professional world and society, some differences regarding the determinants of happiness are to be expected. The traditional role model of men who consider themselves as the “breadwinner” of the family (Bernard, 1981), whereas women regard their financial responsibility as secondary (Conger, Lorenz, Edler, Simons & Xiaojia, 1993), is still prevalent in Austria (Naderer, Sauer & Wieser, 2011). Due to this role allocation, men feel considerably more pressure regarding job security as they are aware of possible negative consequences of losing their job (De Witte, 1999). Moreover, De Witte (1999) found that job insecurity is negatively related to male workers’ well-being, which does not apply for female workers. Thus, the perception of job security is probably more a concern to men.
The above lines of reasoning lead to the following hypothesis:
Hypothesis 4: The impact job security has on happiness is greater for male workers than for female workers.
Peters, Dulk and van der Lippe (2009) in the Netherlands. Consequently, the perception of a good WLB should differ for men and women, i.e. what is balanced for men is not balanced for women since they would need more time than men for family matters. Moreover, in a study by Gimenez-Nadal and Sevilla-Sanz (2011) it was shown that women have a considerably higher free time deficit of five and a half hours per week in comparison to men, who only lack three hours.
The above lines of reasoning lead to the following hypothesis:
Hypothesis 5a: The perception of WLB differs considerably for men and women as such that a WLB for women comprises more time for family and housework than a men’s WLB.
Working females report lower levels of satisfaction with their amount of leisure time than working males (Gimenez-Nadal & Sevilla-Sanz , 2011), which could be explained by hypothesis 5a stating that a good WLB for women should include more family time. Since for women the WLB is more of a concern and is probably harder to achieve than for men, the effect WLB has on happiness should be larger for women than for men, which is leading to the following sub-hypothesis:
Hypothesis 5b: The impact WLB has on happiness is greater for female workers than for male workers.
receive further training and, thus, have considerably more development opportunities than women.
The above lines of reasoning support the following hypothesis:
Hypothesis 6a: Male workers have considerably more development opportunities than female workers.
Regarding the level of satisfaction with their development opportunities, the gender differences in Austria are significant: whereas 46% of the male workers are pleased with their chances of advancement, the same applies only for 32% of the female workers (IT 8). Based on hypothesis 6a, it is argued that inasmuch as women have fewer opportunities for development or career advancement, this effect on happiness will be lower than for men.
Hypothesis 6b: The impact development opportunities have on happiness is greater for male workers than for female workers.
3 METHOD
Sample and Procedures
To empirically examine the happiness of the Austrian workers, data from the European Social Survey (ESS), round 2, collected in 2004 has been used (IT 9). The ESS is an academically-driven survey carried out every two years, which covers more than 20 nations including Austria. Its aim is to monitor and interpret changing public attitudes and values as well as developing social and attitudinal indicators on a European wide basis. The questionnaire mainly focuses on family, work, economic morality, well-being and health.
Although more up to date data from round 3 (2006) and 4 (2008) would be available, round 2 is the only dataset which contains all variables employed in this study and therefore, has been identified as most suitable for the purpose of the paper.
working at least ten hours per week to be able to include the marginally employed workers into the analysis. Respondents were aged between 25 and 65, and had no missing values on the relevant variables of this study. 48.9% of the respondents were male and 51.1% referred to female workers employed in different industries ranging from agriculture, manufacturing, transportation and education to finance, research and the health sector. The mean age of the participants was measured for both men and women as 42 years. Most of the respondents completed a lower secondary education, which means that 44.8% graduated from a secondary modern school and followed an apprenticeship, whereas 22.7% attended a grammar school and 21.6% obtained a university degree. Furthermore, around 89% have an unlimited contract and only 11% of the respondents have a temporary or other type of employment contract. The majority of the participants work fulltime, whereas the proportion of men (91.3%) is considerably higher than for women (58.3%). Female workers represent the vast majority in part-time employment. Most of the respondents are married, consider themselves as healthy and cope well with the present income. Overall, the sample is a good reflection of the Austrian working population.
Measures
Happyfaction. The ESS contained two questions about life satisfaction and
happiness with detailed answer categories. It measured the two variables happiness (C1) (“Taking all things together, how happy would you say you are?”) and life satisfaction (B24) (“All things considered, how satisfied are you with your life as a whole nowadays?”) on a 11 point likert scale ranging respectively from extremely unhappy to extremely happy and extremely dissatisfied to extremely satisfied. Since both questions on happiness and life satisfaction relate to utility, they have been combined into a single measure called “happyfaction”, the average of these two variables. Just like in the preliminary study from van der Meer and Wieler (2011), a high correlation (.86) between happiness and life satisfaction has been obtained indicating a high reliability and internal consistency.
Job security. The first determinant of happiness was job security, which related to
“very true” and a item (G111) referring to the importance the respondents attached to job security. In order to see whether an interaction between these two variables exists, i.e. whether considered together, they have more of an effect on happiness than when they are considered separately, the variables have been splitted into low and high values. To see whether an interaction exists, an Anova analysis has been carried out.
Work-life balance. The 6 items related to WLB have been combined into a single
measure. These items included G71 “My job requires that I work very hard” and G72 “I never seem to have enough time to get everything done in my job” which are measured on a 5 point likert scale ranging from (1) agree strongly till (5) disagree strongly and had to be recoded for the sake of consistency. The remaining items referred to G86 “How often do you feel too tired after work to enjoy the things you would like to do at home?”, G87 “How often do you find that your job prevents you from giving the time you want to your partner or family?”, G89 “How often do you find that your partner or family gets fed up with the pressure of your job?”, and G90 “How often do you find it difficult to concentrate on work because of your family responsibilities?”. All of them are based on a 5 point likert scale and stretch from (1) never until (5) always. In avoidance of not considering respondents with no partner or family, they have been recoded into 0 indicating a very low score on the respective measures. Consequently, a high score on WLB implies a pour WLB and thus, unhappiness. The Crombach alpha amounted up to .75 revealing a high reliability of the combined items.
Development opportunities. Furthermore, the questions G64 “There is a lot of
variety in my work” and G65 “My job requires that I keep learning new things” both with a likert scale of 4 ranging from (1) not at all true and (5) very true represents the variable development opportunities. The Crombach alpha achieved was .69.
Controls. Control variables, which are known to have an effect on happiness and
has a temporary or permanent labour contract. For the control variables marital status (0 = married, single = 1) children (0 = no, 1 = yes) and contract type (0 = unlimited, 1= limited), dummy variables have been created to see the respective effects of their absence or presence.
Gender. To investigate whether there are some differences in gender, this variable
also has been transformed into a dummy, i.e. 0 = men and 1 = women.
To investigate the sub-hypothesis 5a, which stated that a WLB for women needs to contain more time for the family than a man’s WLB, 2 single items both on a 5 point scale namely G34 “There are so many things to do at home, I often run out of time before I get them all done”, ranging from (1) strongly agree till (5) strongly disagree and G115 “How important is it to have a job which allowed you to combine work and family responsibilities?” ranging from (1) not important at all till (5) very important have been chosen for the analysis. The first item had to be recoded.
Regarding the sub-hypothesis 6a claiming that men have more development opportunities than women, the item (G73) “My opportunities for advancement are good” has been included into the analysis.
Analysis
The analysis of the available dataset will be done by using SPSS. For the purpose of the study, the control variables as well as all three determinants of happiness have been standardized to eliminate potential inconsistencies that might arise from combining variables measured on different likert scales. Thereafter, a correlation test has been carried out to examine the relationships between the three job characteristics and “happyfaction”. At this, the control variables have been included as well. To test the proposed hypothesis, a series of regression analysis will be performed, which examine the effect of the independent variables, i.e. job security, WLB and development opportunities, on the dependant variable, i.e. happiness. Here, the standardized values of the respective variables have been used.
characteristics and happiness. For this, three interaction variables each relating to one of the three determinants of happiness have been created. Afterwards new regression analyses including the controls, the moderator gender as well as the interaction variables have been conducted. To see whether the effects of job security, WLB and development opportunities are different for men and women, another regression analysis comparing men and women has been carried out. To further investigate the sub-hypothesis, two Anova analyses have been conducted to compare mean values between men and women.
4 RESULTS
In order to investigate relationships between the above stated variables, first, a parametric correlations test has been carried out. The means, standard deviations and correlations between the variables are presented below in Table 1
TABLE 1
Means, Standard Deviations (SD), and Correlations
Variable Mean SD 1 2 3 4 5 6 7 8 9 10 11 12 1 Age 41.92 8.27 - 2. Marital Status .38 .49 3. Children .25 .43 4. Education 2.81 1.48 5. Income 3.29 .69 6. Health 4.17 .69 7. Contract Type 1.1 .31 8. Working Hours 39.10 10.38 9. Job Security 2.96 .91 10. WLB 2.39 0.74 11. Develop. Opp. 2.97 .82 12. Gender .51 .50 -.04 .05 .06 -.10* -.03 .00 -.02 -.36** .06 .00 -.06 13. Happyfaction 7.46 1.75 -.02 -.15** .06 -.02 .15** .32** -.05 -.02 .04 -.11** .07 .02
In here, the mean happyfaction of the Austrian workforce amounts up to 7.46 with a standard deviation 1.75, which indicates a moderate-high level of happiness. The mean value of women’s’ subjective well-being is slightly higher than the one of men (7.50 vs. 7.4), yet no significant difference was found (∆F (1, 632) = .29, p = n.s.).
As indicated in Table 1, job security neither seems to have a strong and significant relationship with happyfaction (r = .04, p= n.s.) nor with gender (r = .06, p = n.s.). The correlation between happyfaction and WLB (r = -.11,p < .001) is negative and of high significance, yet WLB is not significantly related to the moderating variable gender (r = .00, p = n.s.). Moreover, no significant correlation between development opportunities and happyfaction (r = .07, p = n.s.) or gender (r = -.06, p = n.s.) has been found. Also the correlation between happiness and gender did not produce any significant results (r = .02, p = n.s.). However, happyfaction seems to be positively associated with income (r = .15, p< .001) and health (r = .32, p < .001), whereas the correlation with marital status (r = -.15, p < .001) and WLB (r = -.11, p< .001) is of negative value.
In order to test the first three hypotheses, a series of step-wise regression analyses was performed. The results are presented below in Table 2.
TABLE 2
Results of the Regression Analysis I
Predicting Happyfaction
Variable R² change Total R² F change (df1, df2)
Step 1 .14*** .14 12.39*** (8, 625) Constant 7.46***(.07) Age -.02 (.07) Marital Status -.20** (.07) Children .02 (.07) Education -.08 (.07) Income .23*** (.07) Health .54*** (.07) Contract Type -.02 (.07) Working Hours -.04 (.07) Step 2 .00 .14 .08 (1, 624) Job Security .02 (.07) Step 3 .01*** .15 10.30*** (1, 623) WLB -.23*** (.07) Step 4 .01* .16 5.22* (1, 622) Develop. Opp. .16* (.07)
Note. N = 634. Unstandardized coefficients; standard errors are in parentheses.
* p < .05 ** p < .01 *** p < .001
Hypothesis 1 predicted that job security was positively related to employee happiness. The results of the regression analysis did not produce any significant results (b = .02, t = .27, ∆R² = .00, ∆F (1, 624) = .08, p = n.s.) indicating that job security is not a determinant of happiness at work and, thus, is not in support of Hypothesis 1. Furthermore, the Anova analysis did not reveal any significant interaction between job security and the importance thereof (∆F (1, 630) = .23, p = n.s.) For the SPSS output, see the Appendix.
happiness (b = -.23, t = -3.21, p < .001). Therefore, the results are in support of the hypothesis.
TABLE 3
Results of the Regression Analysis II Predicting Happyfaction
Model 1 Model 2 Model 3
Variable R² change Total R² F change (df1, df2) Variable R² change Total R² F change (df1, df2) Variable R² change Total R² F change (df1, df2) Step 1 .14*** .14 12.39*** (8, 625) .14*** .14 .14*** .14 Constant 7.46***(.07) Age -.02 (.07) Marital Status -.20** (.07) Children .02 (.07) Education -.08 (.07) Income .23*** (.07) Health .54*** (.07) Contract Type -.02 (.07) Work Hours -.04 (.07) Step 2 .00 .14 .15 (2, 623) .02** .15 5.64** (2, 623) .00 .14 1.59 (2, 623)
Job Security .02 (.07) WLB -.24*** (.07) Dev. Opp. .12 (.07)
Gender .03 (.07) Gender .07 (.07) Gender .03 (.07)
Step 3 .00 .14 1.04 (1, 622) .00 .15 .03 (1, 622) .00 .14 .01 (1, 622)
Interaction 1 -.07 (.07) Interaction 2 -.01 (.07) Interaction 3 -.01 (.07)
Note. N = 634. Unstandardized coefficients; standard errors are in parentheses.
TABLE 4
Results of the Regression Analysis III: Comparison of Men and Women
Predicting Happyfaction
Variable Men R² change Total R² F change
(df1, df2)
Women R² change Total
R² F change (df1, df2) Step 1 .13*** .13 5.60***(8, 301) .17*** .17 7.76*** (8, 315) Constant 7.41***(.10) 7.49*** (.10) Age .11 (.10) -.11 (.12) Marital Status .02 (.11) -.35*** (.10) Education -.08 (.09) -.05 (.11) Health .51*** (.10) , .56*** (.10) Income .20* (.10) .20* (.10) Children .15 (.10) -.08 (.11) Contract -.01 (.10) -.07 (.10) Work Hours .06 (.10) -.09 (.10) Step 2 .00 .13 1.19 (1, 300) .00 .17 .03 (1, 314) Job Security .10 (.09) -.06 (.10) Step 3r .01 .14 3.72 (1, 299) 02* .18 6.32*(1, 313) WLB -.20 (.10) -.26* (.10) . Step 4 .00 .15 1.30 (1, 298) .01* .19 4.17 (1, 312) Dev. Opp. .11 (.10) .21* (.10)
Note. N = 634. Unstandardized coefficients; standard errors are in parentheses.
* p < .05 ** p < .01 *** p < .001
The results of the regression analysis comparing men and women (see Table 4 above) revealed that being single has a significant negative effect on women (b = -.35, p < .001), implying that being married significantly contributes to women’s happiness and not to a man’s (b = .02, p = n.s.). Surprisingly, children did not have any significant effect on happiness. Health is an important determinant of happiness for both female and male workers, whereas the effect seems to be slightly larger for women (bw = .56. vs. bm = .51,
p < .001). Subjective income equally affects the well-being of men and women in a positive way (bw = .20 vs. bm = .20, p < .05).
significant moderator effect of gender (b = -.07, t = -1.02, ∆F (1, 622) = 1.04, p = n.s.), which means that gender does not have a significant effect on the relationship between job security and happiness. Nevertheless, a further regression was carried out to examine the effect sizes for both men and women in particular. When comparing the regression coefficient among men and women, the value for male workers (b = .10, p = n.s.) is higher than for female workers (b = -.06, p = n.s.), giving a very small indication that the effect of job security on happiness might be larger for men. Nevertheless, hypothesis 4 has to be rejected.
TABLE 5
Results of the Anova Analysis for WLB & Development Opportunities
Variable Sum of Squares df Mean Square Mean (m/f) F Sig.
Between Groups .00 1 .00 3.82/ 3.83 .00 n.s.
Within Groups 1711.56 632 2.71
Many things to do at home, often run out of time before I
get all done Total 1711.57 633
Between Groups .02 1 .02 4.35/ 4.35 .02 n.s.
Within Groups 608.25 632 .96
how important is it to combine work and family
responsibilities Total 608.27 633
Between Groups 12.66 1 12.66 2.83/2.55 10.21 p< .001
Within Groups 773.97 624 1.24
I have good advancement opportunities
Total 786.63 625
Hypothesis 5a claimed that a WLB for women comprises more time for family and household than a man’s WLB. The Anova analysis in Table 5 showed no significant differences between men and women (∆F1 (1, 632) = .00, ∆F2 (1, 632) = .02, p = n.s.),
which leads to the rejection of the hypothesis.
positive effect on women’s happiness, which is in support of the hypothesis. The results are presented above in Table 4.
Hypothesis 6a suggested that male workers have considerably more development opportunities than female workers. At this the Anova in Table 5 analysis showed that there are significant differences (∆F (1, 624) = 10.21, p < .001) between the mean values of male (2.83) and female worker (2.55), as such that men do have greater development opportunities. The result supports hypothesis 6a.
Hypothesis 6b claimed that the impact development opportunities have on happiness is greater for male workers than for female worker. The analysis in Table 4 again only yielded significant results for women (b = .21, ∆F (1, 312) = 4.17, p < .05) and none for men (b = .11, ∆F (1, 298) = 1.30, p = n.s.). Although, development opportunities have a positive effect on women’s happiness, the results are not in support of the hypothesis, which thus, has to be rejected.
5 DISCUSSION
Findings and Theoretical Implications
This paper sought to draw on a European-wide study from van der Meer and Wieler (2011) by focusing on and providing in depth-research on a small country like Austria, which has to date barely been considered as a main topic of investigation. The aim of this paper was to explore the level of happiness among Austrian workers, whereas the variable gender was argued to account for substantial differences between men and women. To this end, job characteristics which are assumed to have an influence on happiness have been considered.
Concerning the second research question investigating what actually affects Austrians’ happiness, the analysis showed that health is the major determinant of happiness for both men and women, followed by subjective income. Surprisingly, the factors children, age and education did not produce any significant outcome on happiness.
In view of Hypothesis 1, which stated that job security was positively related to workers’ happiness, no support has been found in the obtained results. Although previous research provides enough evidence that job insecurity elicits strong emotional responses and impairs the subjective well-being at work due to increased levels of stress and anxiety (Sverke, Hellgren & Näswall, 2002), the state of job security per se may not necessarily arouse such intense feelings and emotions but is rather perceived as a given. Therefore, it can be argued that unless job security is not at risk, it does not considerably affect the conscious state of mind and thus, will not anticipate happiness.
However, both WLB and ample development opportunities have been identified as important job-related features, which positively relate to happiness at work. Further characteristics such as the number of working hours or the type of contract (permanent or temporary) did not display significant effects on employee happiness.
The third research question was set up to determine whether there are any gender differences regarding the determinants of happiness.
Regarding the control variables, a remarkable finding was that being single had a negative influence on the well-being of women, whereas for men no effect was found. This implies that married women tend to be the happiest, whereas single women seem most unhappy.
well-being to a greater extend. Based on these mixed views, it can be argued that job security or insecurity probably equally impinges on the affective responses including the happiness of both male and female workers.
Hypothesis 5a claimed that a good WLB for women needs to comprise more time for family and household than for men, whereas the analysis showed no significant gender differences. An explanation at this might be that men are more inclined to perceive the division of household duties as equally distributed between them and their partners (Baxter, 2000). At this Baxter (2010) found that men take over the vast majority of outdoor tasks such as gardening, whereas women usually do more indoor tasks like cleaning or vacuuming. Despite the fact that women spent more time on household duties, men seemed to share the perception that housework was distributed fairly and thus, feel as strained as women when it comes to WLB.
However, as confirmed by Hypothesis 5b, having a good WLB enables women to experience higher levels of happiness whereas for men it seems redundant. This finding is rather surprising since both male and female workers feel equally challenged in finding a balance between private and working life, whereas succeeding only fosters women’s subjective well-being.
Practical Implications and Recommendations
As an overall goal, this study seeks to give some practical advice to firms and policymakers. The most striking findings of this paper are that subjective health, WLB and develop opportunities boost employee happiness in Austria. At the organizational level, one might consider implementing these determinants of happiness into the corporate culture or HR practices since previous research confirmed that happy workers are not merely successful in their work performance (Lyubomirsky, King & Diener, 2005), but enhance collaborative negotiation outcomes (Baron, Fortin, Frei, Hauver & Shack, 1990) and dispose of higher levels of motivation (George & Brief, 1996), creativity and proactivity (Fritz & Sonnentag, 2009).
Subjective health was found to be an important antecedent of well-being for both men and women. In this regard organizations can do more than creating a healthy and safe work environment, but boost the employees’ happiness by offering for example an medical insurance pool, short massages during working time to relax the muscles, the membership in a fitness centre, or even engaging a general practitioner come to the company for health checks on a regular basis.
Another approach for organizations to encourage the workers’ well-being, especially those of women, would be in providing more support to balance both family and professional responsibilities. The traditional family model with the spouse staying at home and taking care of the children, while the husband is the only provider has outlived. Women should not be faced with the decision to choose between family and career, but should be able to have both. At this, policymakers and companies should find ways together to increase the quality of life by providing for instance more daycare centres for children under the age of three. In the capital Vienna the infrastructure on childcare is quite progressive, whereas in more rural provinces improvements have to be made (Statistik Austria, 2011).
part-time concept, both policymakers and organizations would need to take action for instance by subsidizing company daycare centres or altering the corporate culture in terms of being more open to new models of working hours or simply having teams accepting that the superior is not always present.
A further implication is to provide employees, both male and female workers, with ample development opportunities such as seminars, on-the-job trainings, or cross-trainings to increase their performance at work. Such practices not merely improve the level of motivation, reduce turnover or improve financial performance (Fisher, 2010), but also encourage the subjective well-being as shown in this study.
Limitations and Future Research
Although the data used in this study is highly representative of the Austrian working population in terms of occupation, age as well as education and is thus, well generalisable, it has its limitations.
First, the survey was carried out in 2004 and within the past few years the labour market experienced some changes which might have influence the attitudes of the respondents. Unfortunately, no other relevant data has been available during the time the research was conducted. It would be up to scholars to reinvestigate the happiness of the Austrian workforce with more up-to date information order to see whether the results would change considerably. A further shortcoming here might be the rather small number of respondents, which slightly weakens the representativeness of the sample.
As it is the case with the majority of happiness-related studies, the measurements solely rely on self-report. Unfortunately, this method hardly shows a comprehensive picture of the respondents’ emotional live since mainly the cognitive components of affect are assessed (Diener, 1994).
This paper focused on three work-related characteristics, namely job security, WLB and development opportunities, yet there are many more to investigate. In order to increase the practical relevance, future researchers may wish to build on the study and identify further job-related determinants of happiness.
differences namely subjective health, martial status, WLB and development opportunities have been found, whereas no significant results for the gender-interaction have been obtained. In order to shed more light on this matter, it would be interesting to see whether the same holds for other relationship constructs, with happiness as the dependent variable.
Conclusion
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APPENDIX
Univariate Analysis of Variance
Between-Subjects Factors N 1,00 437 splitjobsec 2,00 197 1,00 314 splitimpjobsec 2,00 320
Tests of Between-Subjects Effects
Dependent Variable:happyfaction
Source Type III Sum of Squares df Mean Square F Sig.
