In this chapter, the researcher reveals the findings of the study with a detailed highlight of the analysis processes used as well as the demographics of the population studied. In a later part emphasis is made on discussions and implications as well as limitations of this study.
Descriptive Statistics Sample Characteristics
For the study a total of 342 questionnaires were collected. 187 were collected in France at Auchan and Super U and 155 in Japan at Aeon and MaxValu. Out of those 342 questionnaires 298 were validated for analysis.
Table 4.1 Demographics
Variable Category Frequency France % Frequency Japan %
Age 18-25 37 23.12 19 13.77
26-40 66 41.25 55 39.85
Above 40 57 35.63 64 46.38
Gender Female 137 85.62 132 95.65
Male 23 14.38 6 4.35
Contract Full time 160 88.89 138 95.17
Part time 13 7.22 7 4.83
Student 7 3.89 0 0
Tenure Less than 1 year 7 3.74 10 7.25
1-3 years 56 29.95 27 19.57
3-10 years 76 40.64 44 31.88
Above 10 years 48 26.67 57 41.30
In order to better analyze the stress and burnout perceived by cashiers in both France and Japan and how these ones might have a negative impact on wellbeing we removed data collected for part time cashiers, students contracts and cashiers who worked less than one year. Following the above criteria, the total number of validated questionnaires was 160 for France and 138 for Japan.
Descriptive Statistic of the Different Dimensions
In this section, the mean and standard deviation of each item is examined. The questionnaire uses some reverse-coding questions that were recoded while analyzing on SPSS. Those questions are marked with an asterisk. All the variables were measured using a 5 points Likert scale.
Descriptive statistics for Work Related Stress Risk Factors
Table 4.2 represents the mean comparison between Japan and France. We can observe that STR1 has the highest mean for France, which indicates that most of French cashiers agree with the fact that they felt highly stressed during the past month. If we compare it with Japan, we can also say that most of them felt a high stress during the past month, however it did not seem as drastic as the stress felt by French cashiers.
Table 4.2
Descriptive Statistics for Mean Comparison of Stress
Code Item Mean
STR2 In the last month you felt upset because of something that
Table 4.2 (continued) cope with all the things you have to do felt difficulties were piling up so high that you could not overcome them
3.08 1.02 3.13 1.15
N (France) = 160 | N (Japan) = 138 The items with * were recoded in SPSS
Descriptive statistics for Burnout
In the table 4.3 we can observe that French cashiers feel physical pain at the end of their working day (BUR8, M=3.87). This could be explained by the heavy loadings found in Europe compared to Japan. On the other hand we can observe that Japanese cashiers tend to be exhausted before their day of work (BUR5, M=3.57). Working in Japan is very demanding, from every aspect, which could explain this higher mean score.
Table 4.3
Descriptive Statistics for Mean Comparison of Burnout
Code Item Mean
Table 4.3 (continued)
Descriptive statistics of mean comparison for Management Standards
In this part we observed several factors that can contribute to stress of employees within an organization. Several differences have to be pointed out between France and Japan. The major one is the length of work. Item WSD1 represents the inequality between the two countries. Most of Japanese cashiers who responded to the questionnaire agreed that they are pressured to work very long hours (M=3.98) compared to French cashiers who comply by the French regulation of 35h of work per week (M=2.97). The other main difference found below that can be pointed out is the differences in relationships between colleagues. Working relations appear to be more tensed in France compared to Japan. Item WSRE24 highlights the fact that most French cashiers rather agree with the fact that there are tensions between colleagues (M=2.83) whereas Japan, that really puts the emphasis on the group effort and the relations between colleagues
Table 4.4
Descriptive Statistics For Mean Comparison Of Management Standards
Code Item Mean
WSD7 I am unable to take sufficient breaks
Table 4.4 (continued) manager to help me out with a work problem
3.50 1.11 3.85 0.97
WSSM17 I can talk to my line manager about something that has upset or annoyed me about work
WSSM19 My line manager encourages me
Table 4.4 (continued)
WSSC23 My colleagues are willing to listen to my work-related
Table 4.4 (continued) am clear how they will work out in practice
2.51 1.16 3.55 1.25
N (France) = 160 N (Japan) = 138
Descriptive statistics of mean comparison for Wellbeing
The analysis of our last variable ”wellbeing” revealed several major differences between France and Japan. The major one is item WWS5 “I feel connected to the organizations’ values”. French cashiers seen a lot less connected (M=2.63) to their organization’s values compared to Japanese cashiers (M=3.49). This can be explained by exacerbated consumerism in France that may not connect with the cashiers’ philosophy.
Table 4.5
Descriptive Statistics Of Mean Comparison For Wellbeing
Code Item Mean
Table 4.5 (continued)
WOR8 People at my work believe in the worth of the organization
Intrusion of work into private life
WIW12 After work do you find it
Mean Comparison
Independent T-testThis test is an inferential statistical test that determines whether there is a statistically significant difference between the means in two unrelated groups. In the case of this study the researcher is seeking for differences in mean between French and Japanese cashiers. According to the result, Stress, Work-Related Stress Risk Factors and Wellbeing have significantly different means, whereas Burnout is not significant between France and Japan. The results are listed below:
Table 4.6
Independent T-test
Variable France (N = 160) Japan (N=138)
Mean Std. Dev. Mean Std. Dev. Sig. t-ratio
Stress 3.41 0.65 3.15 0.48 0.002*** 3.86
Burnout 3.37 0.60 3.40 0.63 0.709 -0.44
WRSRF 3.02 0.27 3.35 0.28 0.486*** -10.33
Wellbeing 3.15 0.35 3.51 0.37 0.113*** -8.61
***p<0.001 N France = 160 N Japan = 138
Reliability Analysis
Cronbach’s alpha was used to measure the internal consistency of the study.
Internal consistency is typically a measure based on the correlations between different items on the same test (or the same subscale on a larger test). It measures whether several items that propose to measure the same general construct produce similar scores. All of the Cronbach’s alpha were above .70, meaning all the questionnaire was usable.
Table 4.7
Cronbach’s Alpha Analysis
Variables Items Cronbach’s Alpha
France
Correlation is a statistical technique that can show whether and how strongly pairs of variables are related. In the study, the researcher aims at finding relations between work related stress risk factors, stress, burnout and wellbeing.
We can observe on table 4.8 below, that wellbeing has a negative correlation with Burnout, Stress and Work Related Stress Risk Factors. In other words this means that if the levels of stress of an employee are high, then this employee wellbeing will lower down. The contrary is also applicable. If an employee has very high wellbeing, this means that this employee burnout levels are low.
Table 4.8
Pearson Correlation Analysis Of French Cashiers CORRELATIONS
Stress Burnout WRSF Wellbeing
Stress 1
Burnout .371** 1
WRSRF .230** .221** 1
Wellbeing -0.139 -0.088 -0.088 1
** Correlation is significant at the 0.01 level WRSRF = Work Related Stress Risk Factors N = 160
(2-tailed).
We can observe that the data are similar with French cashiers. Wellbeing has a negative relation with all the other variables. Stress, Burnout, and Stress Related Work Risk Factors are strongly correlated.
Table 4.9
Correlation Analysis Of Japanese Cashiers
CORRELATIONS
Stress Burnout WRSF Wellbeing
Stress 1
Burnout .498** 1
WRSRF .341** .206* 1
Wellbeing -.199* -.042 -.095 1
* Correlation is significant at the 0.05 level (2-tailed).
** Correlation is significant at the 0.01 level WRSRF = Work Related Stress Risk Factors N = 138
(2-tailed).
Hypothesis Tests
A. France
In addition to the previous analysis, the researcher has conducted linear and multiple regression analysis to test the effect of Work Related Stress Risk Factors on both Stress and Burnout, the influence those two have on Wellbeing, the impact Stress has on Burnout as well as the mediator effect of Stress and Burnout.
H1: Work Related Stress Risk Factors is significantly related to Stress
According to the analysis below, Work Related Stress Risk Factors account for 5.3% of the variation of Stress. The F value explains that the relation between those two variables is significant.
Table 4.10
Linear Regression Analysis of Work Related Stress Risk Factors and Stress for French cashiers
Model Unstand.
Coefficients
Stand.
Coefficients
t Sig. F Sig.
B Beta
1 (Constant) 1.722 3.017 .003
8.847
WorkStress .560 .230** 2.974 .003 .003
Dependent Variable: Stress R square = .053
Adjusted R square = .047
** p < .01
According to the results below, only two items have a significant impact on Stress.
Those two sub dimensions are “Demands” and “Relationships”.
Table 4.11
Linear Regression Analysis Of Work Related Stress Risk Factors Sub Dimensions And Stress For French Cashiers
Model Unstandardized
Coefficients
Standardized
Coefficients t Sig.
B Std.
Error
Beta
1 (Constant) 1.835 .568 3.228 .002
Demands .355 .076 .357*** 4.675 .000
Control .003 .071 .003 .047 .963
Support (manager) -.042 .060 -.052 -.703 .483 Support (colleague) -.001 .058 -.002 -.023 .982
Relationships .176 .074 .182* 2.37 .019
Role .043 .069 .047 .623 .534
Change .012 .050 .018 .238 .812
Dependent Variable: Stress R square: .185
Adjusted R Square: .147
*** p < .001
** p < .01
* p < .05
H2: Work Related Stress Risk Factor is significantly related to Burnout According to the analysis below, Work Related Stress Risk Factors account for 4.9% of the variation of Burnout. The F value explains that the relation between those two variables is significant.
Table 4.12 Burnout. Those two sub dimensions are “Demands” and “Relationships”.
Table 4.13
Linear Regression Analysis Of Work Related Stress Risk Factors Sub Dimensions And Burnout For French Cashiers
Table 4.13 (continued) Dependent Variable: Burnout R Square: .154
Adjusted R Square .116
*** p < .001
** p < .01
* p < .05
H3: Stress has a significant negative effect on Wellbeing
According to the analysis below, Stress is not significant to the variation of Wellbeing because of its .080 significance value. However Stress has a negative impact on Wellbeing because of its negative t-value of (-1.764).
Table 4.14
Linear Regression Analysis of Wellbeing and Stress for French cashiers
Model Unstand.
Coefficients
Stand.
Coefficients
t Sig. F Sig.
B Beta
1 (Constant) 3.406 23.132 .000
3.111
Stress -.075 -.139 -1.764 .080 .080
Dependent Variable: Wellbeing R square = .019
Adjusted R square = .013
H4: Burnout has a significant negative effect on Wellbeing
According to the analysis below, Burnout is not significant to the variation of Wellbeing because of its 0.269 significance value. However Burnout has a negative impact on Wellbeing because of its negative t-value of (-1.109).
Table 4.15
Linear Regression Analysis Of Wellbeing And Burnout For French Cashiers
Model Unstand.
H5: Stress mediates the relationship between Work Related Risk factor and Wellbeing
In the first model, Work Related Stress Risk Factors is not significant of the variance of wellbeing. In the second model, Stress was put as mediator. However Stress is also not significant. This indicates that Stress does not mediate the relation between Work Related Stress Risk Factors and Wellbeing.
Table 4.16
Mediation Effect Of Stress For Work Related Stress Risk Factors And Wellbeing Model 1
H6: Burnout mediates the relationship between Work Related Risk factor and Wellbeing
In the first model, Work Related Stress Risk Factors is not significant of the variance of wellbeing. In the second model, Burnout was put as mediator. However Burnout is also not significant. This indicates that Burnout does not mediate the relation between Work Related Stress Risk Factors and Wellbeing.
Table 4.17
Mediation Effect Of Burnout For Work Related Stress Risk Factors And Wellbeing
Model 1 Sig Model 2 Sig
Beta Beta
Independent Variable
-.088 .266 -.073 .374
Work Related Stress Risk Factors
Mediator
- -.072 .378
Burnout
Dependent variable: Wellbeing
B. Japan
In addition to the previous analysis, the researcher has conducted linear and multiple regression analysis to test the effect of Work Related Stress Risk Factors on both Stress and Burnout, the influence those two have on Wellbeing, the impact Stress has on Burnout as well as the mediator effect of Stress and Burnout.
H1: Work Related Stress Risk Factors is significantly related to Stress
According to the analysis below, Work Related Stress Risk Factors account for 1.16% of the variation of Burnout. The F value explains that the relation between those two variables is significant only with Demands.
Table 4.18
According to the results below, only two items have a significant impact on stress.
Those two sub dimensions are “Demands” and “Role”.
Table 4.19
Linear Regression Analysis Of Work Related Stress Risk Factors Sub Dimensions And Stress For Japanese Cashiers
Table 4.19 (continued) Dependent Variable: Stress R Square: .228
Adjusted R Square: .193
*** p < .001
* p < .05
H2: Work Related Stress Risk Factor is significantly related to Burnout According to the analysis below, Work Related Stress Risk Factors account for 4.3% of the variation of Burnout. The F value explains that the relation between those two variables is significant only with Demands.
Table 4.20
Linear Regression Analysis Of Work Related Stress Risk Factors And Burnout For Japanese Cashiers
Model Unstand.
Coefficients
Stand.
Coefficients
t Sig. F Sig.
B Beta
1 (Constant) 1.866 2.973 .003
6.050
WorkStress .459 .206* 2.460 .015 .015
Dependent Variable: Burnout R square = .043
Adjusted R square = .036
* p < .05
According to the results below (table 4.21), only one item have a significant impact on Burnout. This sub dimension is “Demands”.
Table 4.21
H3: Stress has a significant negative effect on Wellbeing
According to the analysis below, Burnout is significant to the variation of Wellbeing because of its 0.019 significance value. However Burnout has a negative impact on Wellbeing because of its negative t-value of (-2.371).
Table 4.22
Linear Regression Analysis of Wellbeing and Stress for Japanese cashiers
Model Unstand.
Table 4.22 (continued)
Dependent Variable: Wellbeing R square = .040
Adjusted R square = .033
* p < 0.5
H4: Burnout has a significant negative effect on Wellbeing
According to the analysis below, Burnout is not significant to the variation of Wellbeing because of its 0.625 significance value. However Burnout has a negative impact on Wellbeing because of its negative t-value of (-.490).
Table 4.23
Linear Regression Analysis Of Wellbeing And Burnout For Japanese Cashiers
Model Unstand.
Coefficients
Stand.
Coefficients
t Sig. F Sig.
B Beta
1 (Constant) 3.596 20.522 .000
.240
Burnout -.025 -.042 -.490 .625 .625
Dependent Variable: Wellbeing R square = .002
Adjusted R square = -.006
H5: Stress mediates the relationship between Work Related Risk factor and Wellbeing
In the first model, Work Related Stress Risk Factors is not significant of the variance of wellbeing. In the second model, Stress was put as mediator. However Stress is also not significant. This indicates that Stress does not mediate the relation between Work Related Stress Risk Factors and Wellbeing.
Table 4.24
Mediation Effect Of Stress For Work Related Stress Risk Factors And Wellbeing
Model 1 Sig Model 2 Sig
Beta Beta
Independent Variable
-0.095 0.27 -0.03 0.738
Work Related Stress Risk Factors
Mediator
- -0.189 0.037
Stress
Dependent variable: Wellbeing
H6: Burnout mediates the relationship between Work Related Risk factor and Wellbeing
In the first model, Work Related Stress Risk Factors is not significant of the variance of wellbeing. In the second model, Burnout was put as mediator. However Burnout is also not significant. This indicates that Burnout does not mediate the relation between Work Related Stress Risk Factors and Wellbeing.
Table 4.25
Mediation Effect Of Burnout For Work Related Stress Risk Factors And Wellbeing
Model 1 Sig Model 2 Sig
B B
Independent Variable
-0.095 0.27 -0.09 -0.09
Work Related Stress Risk Factors
Mediator
- -0.023 0.789
Burnout
Dependent variable: Wellbeing
Summary of the Analysis Results
The results of the analysis revealed mixed findings. Some hypothesis were accepted as a whole but not all the components were accepted, therefore they are listed as
“Yes but”. The other hypotheses were rejected.
Table 4.26
Results of the study
Hypotheses FRANCE JAPAN
Accepted Rejected Accepted Rejected H1: Work Related Stress Risk
negative effect on Wellbeing X X
H4: Burnout has a significant
negative effect on Wellbeing X X
H5: Stress mediates the
Note: for the H1 and H2, the overall hypotheses are accepted, however not all the sub dimensions of Work Related Stress Risk Factors are significantly related to Stress and Burnout.
Discussion of the Results
The results did not support all the hypotheses of the study. Risk factors of stress at work have a significant impact on both the levels of stress and burnout felt by the employees. A study conducted in 2003 already supported this idea that work related stress risk factors have a negative impact on stress felt by employees and causes problems such as increased absenteeism from the workplace (Jones, Huxtable, Hodgson, & Price, 2003). Concerning burnout, some people already tried to prevent it from being affected by work related stress risk factors. This is the case of France where a new law has passed forbidding an employer to contact his employees outside the working hours (Huffington Post, 2016). However, when breaking down the several dimensions composing stress and burnout, the impact was not significant on all the dimensions. For French cashiers, the dimensions demands and relations were significant to the relation with stress, whereas the other dimensions did not support this relation. As for Japan, the demand dimension was effectively related with stress supporting the whole relation between work stress risk factors and stress when the other dimensions alone did not support the relation.
In 2008, a study supported the idea that a very high level of stress has a negative impact on employees that may end up starting to live with different behaviors to try to block it, leading them to lower wellbeing levels (Whitaker, 2008). Wellbeing was identified in a previous study as “the diminution of personal accomplishment at work. In this component the individual feels not worthy of his job, unable to achieve what he would want and starts expressing a feeling of uselessness.” (Anact & INRS & Ministère du travail, 2015) That dimension brings the employees to experience lower self-esteem by being unable to cope with work-related situations, bringing their wellbeing down.
However, an Australian study revealed that stress did not necessarily have an impact on wellbeing. Rather, what played a major difference in wellbeing was the level of education as well as the income (Casey & Mathews, 2011). The findings revealed that there were no significant relation between stress and burnout, and wellbeing, however stress and burnout still have a negative impact on wellbeing. Concluding from the existing literature above and the results of the study, stress and burnout do not mediate the relationship between work related stress risk factors and wellbeing.