Enhancing the Sustainability and Satisfaction of Leisure Life for Regular and Non-Regular Workers
1
Department of Recreation and Leisure Sports, College of Sport Science, Dankook University, Cheonan-si 31116, Republic of Korea
2
Department of English Language, College of Foreign Languages, Dankook University, Cheonan-si 31116, Republic of Korea
*
Authors to whom correspondence should be addressed.
Sustainability 2024, 16(14), 5914; https://doi.org/10.3390/su16145914
Submission received: 13 June 2024
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Revised: 5 July 2024
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Accepted: 9 July 2024
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Published: 11 July 2024
Abstract
:Research background: Many studies have shown that there are differences in income, health, and quality of life between regular and non-regular workers. However, relatively little is known about the leisure lives of regular and non-regular workers. Purpose of research: The purpose of this study was to provide an empirical basis, in terms of social and policy-level aspects, to enhance the sustainability and satisfaction of leisure life for regular and non-regular workers in Korea by identifying the factors affecting leisure satisfaction according to the employment type of workers and their relative influence. Research method: To this end, data on 3627 regular and non-regular workers were analyzed using the raw data from the ‘National Leisure Activity Survey’, which is statistically representative at the national level. For the data analysis, SPSS version 23.0 was used. A descriptive statistical analysis was performed to identify the characteristics of the analysis variables, and a hierarchical regression analysis was conducted to identify the major factors and their relative influences on leisure satisfaction. Results: The analysis revealed that the relative influence of factors affecting the leisure satisfaction of regular workers was found in the following order: leisure time on weekdays, marital status, number of vacation days used, implementation of a five-day workweek system, income, leisure time on holidays, regional scale, and working hours. For non-regular workers, the factors influencing leisure satisfaction in order of relative influence were as follows: leisure time on weekdays, leisure expenses, marital status, working hours, and income. Implication: Based on the results of the study, practical measures and policy-level proposals were made to increase the sustainability and satisfaction of leisure life for both regular and non-regular workers.
1. Introduction
The increase in non-regular workers is not exclusive to a specific country. On the contrary, it is a becoming increasingly common within many advanced countries around the world. Particularly in Korea, the number of non-regular workers has increased ever since the financial crisis, and the increase in the number of these types of workers and conditions under which they work is recognized as the biggest problem in our society. The proportion of non-regular workers in Korea is 36.3%, accounting for one-third of all wage earners [1], and the proportion of temporary workers with less than one year of employment is also 24.4%, double the OECD average of 11.8%. According to OECD (2020), it is likely even higher than officially reported [2]. This shows that the employment environment of Korea’s labor market is quite unstable compared to other OECD countries.
The concept of non-regular workers does not have a uniform definition internationally and is used in various ways according to the history and conditions of each country [3]. The European Union defines it based on objective forms of employment, while the United States centers its definition around employment instability. Australia’s definition hinges on the presence of legal protection for workers, and Japan’s definition focuses on intra-company treatment, with an emphasis on discrimination in working conditions [4]. Looking at the dictionary definition in Korea, non-regular workers are defined as positions or jobs that do not receive guarantees that regular workers receive in terms of working methods, duration, and continuity of employment, and refer to contract workers, temporary workers, and daily workers. In this dictionary sense, regular workers can be defined as workers who work full-time, have an unlimited contract period, and have stable employment, whereas a non-regular worker can be defined as a worker who works for a short time, has a finite labor contract, and has unstable employment.
Temporary workers are more likely to receive lower wages than regular workers, and they are more likely to have unstable earnings due to the flexible working contract period [5]. According to Statistics Korea (2020) data [1], the average monthly wage of domestic workers by employment type is 3.23 million won for regular workers and 1.71 million won for non-regular workers, showing significant differences between groups. There is also a difference in working hours. According to data from the Ministry of Employment and Labor (2020) [6], the average monthly working hours by employment type is reported to be 165 h for regular workers and 112 h for non-regular workers. This gap can directly or indirectly lead to a difference in the leisure life of both types of workers and is expected to affect leisure life satisfaction.
For workers, leisure is very important for the reproduction of the workforce. Lack of leisure and an unsatisfactory leisure life not only lead to an accumulation of fatigue at work and reduced productivity, but are highly likely to lower the quality of life. According to a number of previous studies, it was found that satisfaction with leisure life acts as a major antecedent factor in enhancing self-efficacy and job satisfaction, enhancing happiness, and improving quality of life [7,8,9,10,11]. These facts show that leisure life satisfaction plays an important role in an individual’s life.
On the other hand, it is reported that leisure life satisfaction is affected by various factors such as individual demographic factors, workplace factors, and leisure resource factors. Sevin, Koyuncu, and Baldiran (2020) [12] found that there was a difference in leisure satisfaction according to gender and age. In the case of gender, females were more satisfied with leisure than males, and, for those in their 40s, 30s, 20s, and 50s, leisure satisfaction was higher in that order. A study by Yasartürk, Akyüz, and Gönülates (2019) [13] found that leisure satisfaction increased with increasing income. In addition, the higher the education level, the higher the satisfaction with leisure [14], and the group with a spouse showed higher satisfaction with leisure [15]. These study results show that demographic factors influence leisure life satisfaction, suggesting the need to control demographic characteristics in a research model that explains leisure life satisfaction.
Occupational types, length of service, and working hours have been reported as workplace factors affecting leisure life satisfaction. Kang Eun-Na (2016) [14] revealed that there is a difference in leisure satisfaction according to the type of job and working hours. In the case of occupation, it was found that office workers had higher leisure satisfaction than non-office workers, and, as working hours decreased, leisure satisfaction was higher. In the study of Choi Seund-Mook (2020) [16], it was found that the group working fewer than 40 h a week had higher leisure satisfaction than the group working more than 40 h a week in comparison to the leisure satisfaction difference between the groups who worked fewer than 52 h and those who worked over 52 h. In addition, the higher the job security, the higher the satisfaction with leisure [17], and the length of service [18] and the degree of work–leisure balance [19] made a difference in leisure satisfaction.
Leisure time and leisure expenses are reported as leisure resource factors that affect leisure life satisfaction. Kim Soo-Ah and Kim Nam-Jo (2020) [20] revealed that leisure satisfaction increases as more leisure time is available on weekdays and spending on leisure life activities increases. In the study of Jong-Soon Kim, Se-Sook Oh, and So-Young Yoon (2016) [21], it was found that, with the greater amount of leisure time on weekdays, the more leisure time perceived, and the higher the satisfaction with leisure expenses one was spending, the higher the satisfaction with leisure. In the study by Ji-Myung Yang, Young-Geum Jung, and So-Young Yoon (2017) [22], it was also found that the more one perceived that one’s leisure time and leisure expenses were sufficient, the higher the leisure satisfaction was. In addition, leisure life satisfaction is closely related to psychological factors such as serious leisure, leisure motivation, leisure attitude, and leisure constraints [23,24,25,26,27].
In summary, the above studies are meaningful in that they revealed factors affecting leisure life satisfaction from various perspectives. However, although there are many studies on specific age groups such as millennials, the middle-aged, and the elderly [14,15,20,22,28], research on workers is relatively scarce, and, in particular, it is difficult to find a study analyzing the factors affecting leisure life satisfaction according to the employment type of workers.
Therefore, this study intends to analyze the factors affecting workers’ satisfaction with leisure life. In particular, based on a previous study [29], there is a difference in participation in leisure activities according to employment type; regular and non-regular workers are used as comparative groups to analyze factors affecting leisure life satisfaction. Specifically, the purpose of this study is to set demographic characteristics such as gender, age, education level, income, marital status, etc. as control variables, and to examine their relative influence on leisure life satisfaction, including workplace factors and leisure resource factors. These efforts are expected to provide empirical evidence in terms of social and policy-level aspects to enhance the sustainability and satisfaction of leisure life for regular and non-regular workers in Korea by identifying the factors affecting leisure satisfaction according to the employment type of workers and their relative influence. Based on the trends of the studies presented so far, this study set the following research questions:
First, what are the main factors affecting the leisure life satisfaction of regular workers and their relative influence?
Second, what are the main factors affecting the leisure life satisfaction of non-regular workers and their relative influence?
2. Research Method
2.1. Research Design
This study is a prospective study on leisure life satisfaction of regular and non-regular workers. The specific research design is shown in Figure 1.
2.2. Research Structure and Subjects
The data used in the analysis of this study are from the ‘2019 National Leisure Activities Survey’ conducted from 9 September 2019 to 14 November 2019 by the Ministry of Culture, Sports and Tourism and the Korea Culture and Tourism Institute [30]. The statistics were approved by the National Statistics Office (Approval Number: No. 113014). The ‘National Leisure Activity Survey’ provides nationally representative statistical data that comprehensively measures diverse variables related to leisure activities for households across the country. The ‘2019 National Leisure Activities Survey’ surveyed 10,060 men and women aged 15 and over in 17 cities and provinces nationwide. As a survey method, household visit interviews were conducted by surveyors who visited selected households and completed the questionnaire. The 17 cities and provinces were stratified into large urban cities and rural regions, which were further subdivided into Eup and Myeon (i.e., small towns and villages) to capture the distinct features of both urban and rural areas. In this study, a total of 3627 regular and non-regular workers were selected as final research subjects.
Weight Calculation
Final weight calculation: Design weight × Nonresponse adjustment coefficient × (1/In-household extraction rate) × Population information adjusted coefficient.
2.3. Analysis Variables
Through a review of previous studies and discussions between researchers, the variables shown in Table 1 were included in the analysis. Specific information on the variables included in the analysis is shown in Table 1.
2.3.1. Demographic Factors (Control Variables)
Gender, age, final educational background, income, marital status, number of household members living together, and demographic factors of regional size were set as control variables. Gender was treated as a dummy, as ‘0 = Female, 1 = Male’, and the response value, which is a continuous variable, was used as is. The final academic background was coded as ‘1 = No education, 2 = Elementary school, 3 = Middle school, 4 = High school, 5 = University (less than 4 years), 6 = University (4 years or more), 7 = Graduate master’s program, 8 = Graduate doctoral program’. Income was coded as ‘1 = No income, 2 = Monthly average less than 1 million won (i.e., unit: Korean won—1 US dollar is equivalent to approximately 1344.07 Korean won; thus, 1 million Korean won is equivalent to approximately 744.01 US dollars [31]), 3 = Monthly average between 1 and 2 million won, 4 = Monthly average between than 2 and 3 million won, 5 = Monthly average between 3 and 4 million won, 6 = Monthly average between 4 and 5 million won, 7 = Monthly average between 5 and 6 million won, 8 = Monthly average between 6 and 7 million won, 9 = Monthly average between 7 and 8 million won, 10 = Monthly average between 8 and 9 million won, 11 = Monthly average between 9 and 10 million won, 12 = More than 10 million won per month’. Marital status was treated as a dummy, as ‘0 = Unmarried, 1 = With a spouse’, and the response value, which is a continuous variable, was used for the number of household members living together. As for the regional scale, it was coded as ‘0 = Small town/Eup and Myeon area, 1 = Large city’ and was treated as a dummy.
2.3.2. Independent Variables
Workplace Factors
The workplace factors set as independent variables are whether a five-day workweek from Monday to Friday is implemented, working hours, and the number of days of vacation, that is, and the total number of days of vacation per year. Whether or not the five-day workweek system was implemented was treated as a dummy, as ‘0 = Not implemented, 1 = Implemented’, and the response values, which are continuous variables, were used as the average working hours per week and the number of days of vacation.
Leisure Resource Factors
The leisure resource factors set as independent variables are the average monthly leisure cost, the average daily leisure time on weekdays, and the average daily leisure time on holidays. The response values, which are continuous variables, were used as is for leisure expenses, weekday leisure time, and holiday leisure time.
2.3.3. Dependent Variable
‘Overall leisure satisfaction’ acted as a dependent variable in analyses. The overall leisure satisfaction was measured using the questionnaire ‘Are you satisfied with your overall leisure life?’. The questionnaire consists of responses on a 7-point scale (1 = ‘Very dissatisfied’, 4 = ‘Average’, 7 = ‘Very satisfied’). The descriptive statistical analysis results for the above analysis variables are presented in Table 2 and Table 3.
2.4. Analysis Method
The detailed data analysis method of this study is as follows. First, correlation analysis (Pearson’s moment correlation coefficient) was performed to determine the relationship between the analysis variables. The range of the correlation coefficient has a value between −1.0 and 1.0, and it can be interpreted that, the closer it is to the absolute value 1, the higher the correlation is [32]. Second, hierarchical regression analysis was performed to determine the relative influence of demographic factors (control variables), workplace factors, and leisure resource factors on leisure satisfaction. Hierarchical regression analysis is an analysis method to find out the relative influence size of each independent variable in order when there are several independent variables. In other words, hierarchical regression analysis is used to determine the relative magnitude of influence of independent variables, such as the independent variable having the greatest influence on the dependent variable and the independent variable having the second greatest influence, in order [33,34]. Diagnosis of the suitability of the regression model was conducted through the review of tolerance which can measure multi-collinearity between independent variables and the Durbin–Watson statistic values which can measure the joint independence between variance inflation factor (VIF) and the residuals. When both tolerance and VIF are close to 1, it is judged that there is no multi-collinearity, and, in the case of VIF, it is considered that there is multi-collinearity when it is 10 or more. Durbin–Watson statistic values close to 0 indicate positive correlation, values close to 4 indicate negative correlation, and values close to 2 are mutually independent [32]. The evaluation of the relative influence of the hierarchical regression analysis was based on the final model (three-step model), and was judged based on the beta (B) value, which is the standardization coefficient. For data analysis, the SPSS 23.0 program was used, and the statistical significance level was set to 0.05.
3. Results
3.1. Correlation Analysis
The results of the correlation analysis between the analysis variables are shown in Table 4. As a result of the analysis, the correlation coefficient ranged from −0.618 to 0.591, and no excessive correlation between variables was found.
3.2. Factors Affecting Leisure Life Satisfaction of Regular Workers
Table 5 shows the results of a hierarchical regression analysis of the factors affecting the leisure life satisfaction of regular workers. As a result of the statistical significance test for the regression model (Model 1) including demographic factors, the F statistical value was 8.088 and the probability of significance was 0.000, the independent variable included in Model 1 significantly explains the satisfaction of leisure life, and the explanatory power of satisfaction was found to be 2%. Factors significantly affecting leisure life satisfaction in the first-stage model were education level (t = 3.644, p = 0.000), income (t = 3.384, p = 0.001), marital status (t = 3.029, p = 0.002), and regional size (t = 2.558, p = 0.011). As a result of the statistical significance test for the regression model (Model 2) including demographic characteristics and workplace characteristics factors, the F statistical value was 11.066 and the probability of significance was 0.000, and the explanatory power of leisure life satisfaction was 3.8%. In Model 2, factors that had a significant effect on leisure life satisfaction were whether a five-day workweek was implemented (t = 4.28, p = 0.000), working hours (t = −2.204, p = 0.028), and the number of days of vacation use (t = 4.304, p = 0.000). As a result of the statistical significance test for the regression model (Model 3) including demographic characteristics, workplace characteristics, and leisure resource characteristics factors, the F statistical value was 10.198, and the probability of significance was 0.000, so the independent variable included in Model 3 was meaningful in terms of satisfaction with leisure life. The explanatory power of leisure life satisfaction was found to be 4.5%. In Model 3, factors significantly affecting leisure life satisfaction were weekday leisure time (t = 4.314, p = 0.000) and holiday leisure time (t = −2.512, p = 0.012).
The evaluation of relative influence, the most important factor that can be tested in a hierarchical regression analysis, is based on the final model. According to standardized coefficients indicating the relative influence of independent variables, weekday leisure time (0.1), marital status (0.086), number of days used on vacation (0.081), whether a five-day workweek system was implemented (0.081), and income (0.064), holiday leisure time (0.059), regional size (0.051), and working hours (−0.043) have an effect on leisure life satisfaction. When looking at the tolerance and variance inflation factor (VIF), it is judged that there is no multicollinearity between the independent variables, and the Durbin–Watson statistic is also close to 2, so it can be said that the residuals are mutually independent. Figure 2 shows the standardized residuals of regular workers.
3.3. Factors Affecting Leisure Life Satisfaction of Non-Regular Workers
Table 6 shows the results of a hierarchical regression analysis of factors affecting the leisure life satisfaction of non-regular workers. As a result of the statistical significance test for the regression model (Model 1) including demographic factors, the F statistical value was 1.207 and the probability of significance was 0.297, indicating that the regression model was not statistically significant, and the explanatory power of leisure life satisfaction was. It was found to be 1.6%. Marital status (t = 2.129, p = 0.034) was found to have a significant influence on leisure life satisfaction in the first-stage model. As a result of the statistical significance test for the regression model (Model 2) including demographic characteristics and workplace characteristics factors, the F statistical value was 3.039 and the probability of significance was 0.001, and the explanatory power of leisure life satisfaction was 5.5%. In Model 2, factors significantly affecting leisure satisfaction were found to be working hours (t = −3.219, p = 0.001) and the number of days of vacation use (t = 2.192, p = 0.029). As a result of the statistical significance test for the regression model (Model 3) including demographic characteristics, workplace characteristics, and leisure resource characteristics factors, the F statistical value was 5.864 and the probability of significance was 0.000. The explanatory power of leisure life satisfaction was found to be 12.8%. In Model 3, factors significantly affecting leisure satisfaction were found to be leisure expenses (t = 4.360, p = 0.000) and weekday leisure time (t = 4.330, p = 0.000).
The evaluation of relative influence, the most important factor that can be tested in a hierarchical regression analysis, is based on the final model. According to the standardized coefficient indicating the relative influence of the independent variable, leisure time on weekdays (0.238), leisure expenses (0.192), marital status (0.149), working hours (−0.122), and income (0.115) were the factors affecting leisure life satisfaction in that order. When looking at the tolerance and variance inflation factor (VIF), it is judged that there is no multicollinearity between the independent variables, and the Durbin–Watson statistic is also close to 2, so it can be said that the residuals are mutually independent. Figure 3 shows the standardized residuals of non-regular workers.
3.4. Factors Affecting Leisure Satisfaction of Regular and Non-Regular Workers
Table 7 shows the results of comparing factors affecting leisure satisfaction between regular and non-regular workers. Variables that show a significant correlation with the leisure satisfaction of regular workers include age, education level, income, marital status, regional size, five-day workweek, working hours, number of vacation days, leisure costs, weekday leisure time, and holiday leisure time. For non-regular workers, variables that show a significant correlation with the leisure satisfaction include the five-day workweek system, working hours, number of vacation days, leisure costs, weekday leisure time, and holiday leisure time. As a result of analyzing significant factors and their relative influence on the leisure satisfaction of regular workers, the factors were found to be, in order: weekday leisure time, marital status, number of vacation days used, implementation of a five-day workweek, income, holiday leisure time, regional scale, and working hours. For non-regular workers, the factors were found to be, in order: weekday leisure time, leisure costs, marital status, working hours, and income.
4. Discussion
The objective of this study is to provide an empirical basis, in terms of social and policy-level aspects, to enhance the sustainability and satisfaction of leisure life for regular and non-regular workers in Korea by identifying the factors affecting leisure satisfaction according to the employment type of workers and their relative influence. To this end, using national statistical data from the ‘2019 National Leisure Activities Survey’, the demographic factors, workplace factors, and leisure resource factors of respondents were sequentially inputted, a model was constructed, and a hierarchical regression analysis was performed. The discussion of the research results is as follows.
First, the demographic factors that had a significant effect on leisure life satisfaction for both regular and non-regular workers were marital status and income. This result supports a previous study that older people with a spouse have higher leisure satisfaction [14], and it is in line with a study that, the higher the income, the higher the leisure satisfaction [12]. Among the workplace factors, working hours were found to act as an influencing factor on leisure life satisfaction, and, as working hours decreased, leisure life satisfaction increased. These results show that the working hours of middle-aged and elderly people participating in economic activities have a negative (−) effect on leisure satisfaction [13], and the group working 40 h or less per week was compared with the group working more than 40 h and less than 52 h per week. This supports the study of Choi Seung-Mook (2020) [16] who observed higher leisure satisfaction compared to the 52 h overtime group. In the leisure resource factor, it was found that weekday leisure time had a significant effect on leisure life satisfaction, and, as the weekday leisure time increased, leisure life satisfaction increased. These research results support previous studies [19,20] that revealed the positive relationship between leisure time on weekdays and leisure satisfaction. As described above, there are great social implications implicit in how marital status, income, working hours, and leisure time on weekdays act as influence factors on the leisure life satisfaction of regular and non-regular workers. In particular, it seems that policy efforts are needed to increase the leisure life satisfaction of low-wage workers and long-time workers.
Second, the factor that had the greatest influence on the leisure life satisfaction of regular and non-regular workers was the leisure resource factor. The leisure resource factor increases or decreases satisfaction with leisure life depending on the level of time and cost for leisure life. Weekday leisure time was found to be the most influential variable affecting leisure life satisfaction. This shows the possibility of weekday leisure time as a variable that most representatively explains the leisure life satisfaction of regular and non-regular workers. Kim Jong-Soon, Oh Se-Suk, and Yoon So-Young (2016) [21] also support the results of this study by reporting that, among the leisure resource factors such as weekday leisure time, desired weekday leisure time, holiday leisure time, desired holiday leisure time, average monthly leisure cost, and desired average monthly leisure cost, weekday leisure time has the greatest impact on leisure life satisfaction. On the other hand, it can be seen that this result is organically linked with the result that working hours act as a significant variable for both regular and non-regular workers among the workplace factors. Therefore, in order to increase the satisfaction of Korean workers with their leisure life, above all, social and policy-level efforts are needed to guarantee leisure time on weekdays through a reduction in working hours and flexible working hours.
Recently, various efforts are being made in Korean society to guarantee workers’ leisure time and create a healthy leisure society. In 2015, the National Leisure Activation Framework Act was enacted to legally recognize people’s right to leisure activities [35], and the Labor Standards Act was revised in 2018 to gradually implement the 52 h workweek system. As a result of these policy efforts, positive changes are being observed in workers’ leisure lives [36].
The second most influential variable on leisure life satisfaction after weekday leisure time was the number of days used for vacation in the case of regular employees. Moreover, in the case of non-regular workers, the second most influential variable was leisure expenses, and it was found that leisure life satisfaction increased as leisure expenses increased. This means that, in the case of regular workers, the work environment rather than material resources is a big variable affecting leisure life satisfaction, whereas, in the case of non-regular workers, physical resources have a greater influence. Therefore, in order to increase the satisfaction of regular workers with their leisure life, companies need to actively encourage the use of vacation time and create a work environment in which they can freely use their vacation time. Relevant policies, such as support, will be needed.
5. Conclusions
This study empirically analyzed which factors affect the leisure life satisfaction of regular and non-regular workers in Korea, and which of those factors are relatively important, and the following conclusions were drawn.
First, the determinants of the leisure life satisfaction of Korean regular workers are weekday leisure time, number of days used for vacation, whether the five-day workweek is implemented, leisure time on holidays, and working hours.
Second, the determinants of the leisure life satisfaction of Korean non-regular workers are weekday leisure time, leisure expenses, and working hours.
Finally, we would like to clarify the limitations of this study. The ‘National Leisure Activity Survey’ comprises data collected from households across the country, and, although it comprises nationally representative data, there is a limit to generalizing the research results to all regular and non-regular workers. In addition, this study examined the factors affecting the leisure life satisfaction of regular and non-regular workers through a cross-sectional data analysis. In a follow-up study, if we analyze how factors affecting leisure life satisfaction change with the passage of time through a longitudinal study, this would clearly have great significance in relation to the work being carried out in this field of research. In addition, there remains a limitation to this study in that there was no choice but to select limited variables due to the limitations of panel data. Ultimately, there is the possibility of variables which exist that can better explain disparities in leisure life satisfaction that have not been included in this analysis. Therefore, it is clear that a follow-up study which considers other variables as factors influencing leisure life satisfaction is necessary.
Author Contributions
Conceptualization, E.-J.K. and H.-W.K.; methodology, E.-J.K.; validation, E.-J.K. and H.-W.K.; formal analysis, E.-J.K.; investigation, E.-J.K. and H.-W.K.; data curation, E.-J.K. and H.-W.K.; writing—original draft preparation, E.-J.K. and H.-W.K.; writing—review and editing, S.-M.P.; visualization, E.-J.K.; supervision, H.-W.K.; project administration, H.-W.K. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Conflicts of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Figure 1.
Research design.
Figure 2.
Standardized residuals (regular workers).
Figure 3.
Standardized residuals (non-regular workers).
Table 1.
Information on the variables included in the analysis.
| Variable | Variable Type | Description |
|---|---|---|
| Gender | Categorical | Gender (1 = Male, 2 = Female) |
| Age | Continuous | Age (Years) |
| Education | Categorical | Highest education level (1 = No education, 2 = Elementary school, 3 = Middle school, 4 = High school, 5 = College (less than 4 years), 6 = University (4 years or more), 7 = Master’s program, 8 = Doctoral program) |
| Income | Categorical | Average monthly income before taxes for the past year (1 = No income, 2 = Less than 1 million won, 3 = Between 1 and 2 million won, 4 = Between 2 and 3 million won, 5 = Between 3 and 4 million won, 6 = Between 4 and 5 million won, 7 = Between 5 and 6 million won, 8 = Between 6 and 7 million won, 9 = Between 7 and 8 million won, 10 = Between 8 and 9 million won, 11 = Between 9 and 10 million won, 12 = More than 10 million won) |
| Marital status | Categorical | Marital status (1 = Unmarried, 2 = Married, 3 = Bereavement/Divorce/Etc.) |
| Number of household members | Continuous | Number of household members living together |
| Region | Categorical | Regional scale (1 = large cities, 2 = Small and medium-sized cities, 3 = Small towns/Eup and Myeon areas) |
| Five-day workweek | Categorical | Whether to implement a five-day workweek system (1 = Yes, 2 = No) |
| Working hours | Continuous | Working hours (hours) |
| Vacation use | Continuous | Number of vacation days (days) |
| Leisure cost | Continuous | Average monthly spending on leisure activities (Korean won) |
| Weekday leisure time | Continuous | Average leisure time per day on weekdays (hours) |
| Holiday leisure time | Continuous | Average leisure time per day on holidays (hours) |
| Leisure satisfaction | Continuous | Satisfaction with leisure life (1 = very dissatisfied, 4 = average, 7 = very satisfied) |
Table 2.
Descriptive statistical analysis results for the analysis variables: unit—N (%).
| Variable | Category | Regular | Non-Regular | Total | |
|---|---|---|---|---|---|
| Demographic factor | Gender | Female | 1019 (34.4) | 362 (54.7) | 1381 (38.1) |
| Male | 1946 (65.6) | 300 (45.3) | 2246 (61.9) | ||
| Education | No education | 0 (0.0) | 16 (2.4) | 16 (0.4) | |
| Elementary school | 21 (0.7) | 68 (10.3) | 89 (2.5) | ||
| Middle school | 51 (1.7) | 99 (15.0) | 150 (4.1) | ||
| High school | 980 (33.1) | 287 (43.4) | 1267 (34.9) | ||
| College (less than 4 years) | 534 (18.0) | 80 (12.1) | 614 (16.9) | ||
| University (4 years or more) | 1315 (44.4) | 109 (16.5) | 1424 (39.3) | ||
| Master’s program | 53 (1.8) | 3 (0.5) | 56 (1.5) | ||
| Doctoral program | 11 (0.4) | 0 (0.0) | 11 (0.3) | ||
| Monthly income | No income | 1 (0.0) | 2 (0.3) | 3 (0.1) | |
| Less than 1 million won | 22 (0.7) | 162 (24.5) | 184 (5.1) | ||
| Between 1 and 2 million won | 451 (15.2) | 308 (46.5) | 759 (20.9) | ||
| Between 2 and 3 million won | 1134 (38.2) | 153 (23.1) | 1287 (35.5) | ||
| Between 3 and 4 million won | 892 (30.1) | 26 (3.9) | 918 (25.3) | ||
| Between 4 and 5 million won | 293 (9.9) | 7 (1.1) | 300 (8.3) | ||
| Between 5 and 6 million won | 107 (3.6) | 4 (0.6) | 111 (3.1) | ||
| Between 6 and 7 million on | 30 (1.0) | 0 (0.0) | 30 (0.8) | ||
| Between 7 and 8 million won | 14 (0.5) | 0 (0.0) | 14 (0.4) | ||
| Between 8 and 9 million won | 8 (0.3) | 0 (0.0) | 8 (0.2) | ||
| Between 9 and 10 million won | 8 (0.3) | 0 (0.0) | 8 (0.2) | ||
| More than 10 million won | 5 (0.2) | 0 (0.0) | 5 (0.1) | ||
| Marital status | Unmarried | 1037 (35.0) | 213 (32.2) | 1250 (34.5) | |
| With a spouse | 1767 (59.6) | 321 (48.5) | 2088 (57.6) | ||
| Bereavement/Divorce/ETC | 161 (5.4) | 128 (19.3) | 289 (8.0) | ||
| Regional Scale | Small towns/Eup and Myeon areas | 1732 (58.4) | 382 (57.7) | 2114 (58.3) | |
| Large cities | 1233 (41.6) | 280 (42.3) | 1513 (41.7) | ||
| Workplace factor | Whether to implement a five-day workweek system | Implemented | 738 (24.9) | 379 (57.3) | 1117 (30.8) |
| Not implemented | 2227 (75.1) | 283 (42.7) | 2510 (69.2) | ||
| Total | 2965 (100.0) | 662 (100.0) | 3627 (100.0) | ||
Table 3.
Descriptive statistical analysis results for the analysis variables.
| Variable | Minimum | Maximum | Mean | SD | ||
|---|---|---|---|---|---|---|
| Demographic factor | Age | Regular | 18 | 82 | 41.09 | 11.74 |
| Non-regular | 18 | 87 | 48.87 | 17.70 | ||
| Number of household members living together | Regular | 1 | 7 | 2.83 | 1.20 | |
| Non-regular | 1 | 7 | 2.49 | 1.25 | ||
| Workplace factor | Average working hours per week | Regular | 3 | 98 | 43.83 | 9.53 |
| Non-regular | 1 | 98 | 36.52 | 15.70 | ||
| Number of days of vacation | Regular | 0 | 50 | 4.46 | 4.95 | |
| Non-regular | 0 | 60 | 2.73 | 5.82 | ||
| Leisure resource factor | Leisure cost (Unit: Korean won) | Regular | 0 | 3,000,000 | 184,965.20 | 170,287.10 |
| Non-regular | 0 | 1,000,000 | 127,874.62 | 123,841.73 | ||
| Weekday leisure time | Regular | 1 | 10 | 3.05 | 1.31 | |
| Non-regular | 1 | 12 | 3.36 | 1.69 | ||
| Holiday leisure time | Regular | 1 | 16 | 5.56 | 2.78 | |
| Non-regular | 1 | 14 | 5.50 | 2.76 | ||
| Leisure life satisfaction | Regular | 1 | 7 | 4.69 | 1.05 | |
| Non-regular | 1 | 7 | 4.43 | 1.20 | ||
Table 4.
Correlation analysis.
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Gender | 1 | |||||||||||||
| Age | 0.013 | 1 | ||||||||||||
| Education | 0.078 ** | −0.437 ** | 1 | |||||||||||
| Income | 0.418 ** | 0.001 | 0.368 ** | 1 | ||||||||||
| Marital status | −0.007 | −0.618 ** | 0.093 ** | −0.201 ** | 1 | |||||||||
| Number of household members | −0.042 * | −0.120 ** | 0.203 ** | 0.105 ** | −0.329 ** | 1 | ||||||||
| Regional scale | 0.042 * | −0.033 * | 0.076 ** | 0.036 * | 0.014 | 0.035 * | 1 | |||||||
| Five-day workweek | 0.003 | −0.071 ** | 0.292 ** | 0.181 ** | −0.055 ** | 0.071 ** | 0.054 ** | 1 | ||||||
| Working hours | 0.168 ** | −0.132 ** | 0.112 ** | 0.234 ** | 0.051 ** | 0.014 | 0.070 ** | −0.142 ** | 1 | |||||
| Number of days of vacation | 0.005 | −0.131 ** | 0.265 ** | 0.169 ** | −0.017 | 0.112 ** | −0.03 | 0.166 ** | −0.006 | 1 | ||||
| Leisure cost | 0.130 ** | −0.080 ** | 0.171 ** | 0.251 ** | 0.02 | 0.028 | 0.079 ** | 0.063 ** | 0.089 ** | 0.190 ** | 1 | |||
| Weekday leisure time | 0.009 | 0.055 ** | −0.117 ** | −0.125 ** | 0.109 ** | −0.116 ** | 0.087 ** | 0.016 | −0.097 ** | 0.039 * | 0.146 ** | 1 | ||
| Holiday leisure time | 0.072 ** | −0.059 ** | 0.034 * | −0.008 | 0.152 ** | −0.077 ** | 0.111 ** | 0.023 | 0.009 | 0.141 ** | 0.233 ** | 0.591 ** | 1 | |
| Leisure satisfaction | 0.037 * | −0.046 ** | 0.107 ** | 0.095 ** | 0.063 ** | −0.014 | 0.052 ** | 0.140 ** | −0.064 ** | 0.113 ** | 0.097 ** | 0.102 ** | 0.047 ** | 1 |
* p < 0.05, ** p < 0.01.
Table 5.
Factors affecting the leisure life satisfaction of regular workers.
| Variable | Model 1 | Model 2 | Model 3 | Collinearity | ||||
|---|---|---|---|---|---|---|---|---|
| B | t | B | t | B | t | Tolerance | VIF | |
| <Demographic factor> | ||||||||
| Gender | −0.035 | −10.672 | −0.021 | −0.999 | −0.021 | −0.997 | 0.789 | 1.268 |
| Age | 0.014 | 0.554 | 0.017 | 0.693 | 0.013 | 0.523 | 0.542 | 1.846 |
| Education | 0.075 | 3.644 *** | 0.032 | 1.518 | 0.038 | 1.784 | 0.755 | 1.325 |
| Income | 0.076 | 3.384 ** | 0.064 | 2.857 ** | 0.064 | 2.8 ** | 0.659 | 1.518 |
| Marital status | 0.08 | 3.029 ** | 0.091 | 3.478 ** | 0.086 | 3.263 ** | 0.493 | 2.028 |
| Number of household members | −0.014 | −0.698 | −0.015 | −0.751 | −0.013 | −0.631 | 0.813 | 1.23 |
| Regional scale | 0.048 | 2.558 * | 0.055 | 2.914 ** | 0.051 | 2.689 ** | 0.962 | 1.04 |
| <Workplace factor> | ||||||||
| Five-day workweek | 0.087 | 4.28 *** | 0.081 | 4.007 *** | 0.836 | 1.196 | ||
| Working hours | −0.043 | −2.204 * | −0.043 | −2.214 * | 0.894 | 1.119 | ||
| Number of days used on vacation | 0.083 | 4.304 *** | 0.081 | 4.114 *** | 0.88 | 1.136 | ||
| <Leisure resource factor> | ||||||||
| Leisure cost | 0.024 | 1.228 | 0.872 | 1.147 | ||||
| Weekday leisure time | 0.1 | 4.314 *** | 0.636 | 1.572 | ||||
| Holiday leisure time | −0.059 | −2.512 * | 0.61 | 1.639 | ||||
| R2 | 0.02 | 0.038 | 0.045 | |||||
| Adjusted R2 | 0.017 | 0.035 | 0.041 | |||||
| F(p) | 8.088 *** | 11.066 *** | 10.198 *** | |||||
| Durbin-Watson | 1.908 | |||||||
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table 6.
Factors affecting the leisure life satisfaction of non-regular workers.
| Variable | Model 1 | Model 2 | Model 3 | Collinearity | ||||
|---|---|---|---|---|---|---|---|---|
| B | t | B | t | B | t | Tolerance | VIF | |
| <Demographic factor> | ||||||||
| Gender | 0.023 | 0.475 | 0.046 | 0.951 | 0.016 | 0.346 | 0.764 | 1.309 |
| Age | 0.156 | 1.899 | 0.113 | 1.373 | 0.147 | 1.850 | 0.264 | 3.787 |
| Education | 0.075 | 1.292 | 0.032 | 0.560 | 0.039 | 0.702 | 0.534 | 1.874 |
| Income | 0.027 | 0.594 | 0.095 | 1.934 | 0.115 | 2.375 * | 0.715 | 1.398 |
| Marital status | 0.155 | 2.129 * | 0.136 | 1.900 | 0.149 | 2.143 * | 0.346 | 2.888 |
| Number of household members | 0.038 | 0.776 | 0.021 | 0.435 | 0.045 | 0.963 | 0.781 | 1.280 |
| Regional scale | 0.029 | 0.660 | 0.026 | 0.603 | −0.003 | −0.067 | 0.950 | 1.053 |
| <Workplace factor> | ||||||||
| Five-day workweek | 0.076 | 1.745 | 0.079 | 1.885 | 0.955 | 1.047 | ||
| Working hours | −0.154 | −3.219 ** | −0.122 | −2.635 ** | 0.779 | 1.283 | ||
| Number of days used on vacation | 0.097 | 2.192 * | 0.064 | 1.471 | 0.899 | 1.112 | ||
| <Leisure resource factor> | ||||||||
| Leisure cost | 0.192 | 4.360 *** | 0.866 | 1.155 | ||||
| Weekday leisure time | 0.238 | 4.330 *** | 0.555 | 1.803 | ||||
| Holiday leisure time | −0.096 | −1.771 | 0.574 | 1.741 | ||||
| R2 | 0.016 | 0.055 | 0.128 | |||||
| Adjusted R2 | 0.003 | 0.037 | 0.106 | |||||
| F(p) | 1.207 | 3.039 | 5.864 | |||||
| Durbin-Watson | 1.922 | |||||||
* p < 0.05, ** p < 0.01, *** p < 0.001.
Table 7.
Comparison of factors affecting leisure life satisfaction between regular and non-regular workers.
Table 7.
Comparison of factors affecting leisure life satisfaction between regular and non-regular workers.
| Variable | Total Workers | Regular Workers | Non-Regular Workers | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| r | m1 | m2 | m3 | r | m1 | m2 | m3 | r | m1 | m2 | m3 | |
| B | B | B | B | B | B | B | B | B | ||||
| 1.1 | 0.037 * | −0.021 | −0.005 | −0.008 | 0.015 | −0.035 | −0.021 | −0.021 | 0.049 | 0.023 | 0.046 | 0.016 |
| 1.2 | −0.046 ** | 0.033 | 0.031 | 0.025 | −0.042 * | 0.014 | 0.017 | 0.013 | 0.014 | 0.156 | 0.113 | 0.147 |
| 1.3 | 0.107 ** | 0.083 *** | 0.037 | 0.044 * | 0.103 ** | 0.075 *** | 0.032 | 0.038 | 0.003 | 0.075 | 0.032 | 0.039 |
| 1.4 | 0.095 ** | 0.086 *** | 0.080 *** | 0.081 *** | 0.071 ** | 0.076 ** | 0.064 ** | 0.064 ** | 0.02 | 0.027 | 0.095 | 0.115 * |
| 1.5 | 0.063 ** | 0.090 *** | 0.101 *** | 0.092 *** | 0.064 ** | 0.08 ** | 0.091 ** | 0.086 ** | 0.073 | 0.155 * | 0.136 | 0.149 * |
| 1.6 | −0.014 | −0.007 | −0.010 | −0.006 | −0.026 | −0.014 | −0.015 | −0.013 | −0.013 | 0.038 | 0.021 | 0.045 |
| 1.7 | 0.052 ** | 0.041 * | 0.046 ** | 0.038 * | 0.059 ** | 0.048 * | 0.055 ** | 0.051 ** | 0.028 | 0.029 | 0.026 | −0.003 |
| 2.1 | 0.140 ** | 0.095 *** | 0.091 *** | 0.126 ** | 0.087 *** | 0.081 *** | 0.099 * | 0.076 | 0.079 | |||
| 2.2 | −0.064 ** | −0.062 *** | −0.057 *** | −0.066 ** | −0.043 * | −0.043 * | −0.152 ** | −0.154 ** | −0.122 ** | |||
| 2.3 | 0.113 ** | 0.085 *** | 0.076 *** | 0.102 ** | 0.083 *** | 0.081 *** | 0.102 ** | 0.097 * | 0.064 | |||
| 3.1 | 0.097 ** | 0.045 * | 0.066 ** | 0.024 | 0.197 ** | 0.192 *** | ||||||
| 3.2 | 0.102 ** | 0.126 *** | 0.090 ** | 0.1 *** | 0.178 ** | 0.238 *** | ||||||
| 3.3 | 0.047 ** | −0.064 ** | 0.037 * | −0.059 * | 0.081 * | −0.096 | ||||||
| R2 | - | 0.023 | 0.045 | 0.057 | - | 0.02 | 0.038 | 0.045 | - | 0.016 | 0.055 | 0.128 |
| R2(ad) | - | 0.021 | 0.042 | 0.054 | - | 0.017 | 0.035 | 0.041 | - | 0.003 | 0.037 | 0.106 |
| F(p) | - | 11.005 *** | 15.553 *** | 15.585 *** | - | 8.088 *** | 11.066 *** | 10.198 *** | - | 1.207 | 3.039 *** | 5.864 *** |
1.1 Gender, 1.2 Age, 1.3 Education level, 1.4 Income, 1.5 Marital status, 1.6 Number of household members living together, 1.7 Regional scale. 2.1 Five-day workweek, 2.2 Working hours, 2.3 Number of days used on vacation. 3.1 Leisure cost, 3.2 Weekday leisure time, 3.3 Holiday leisure time. * p < 0.05, ** p < 0.01, *** p < 0.001.
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MDPI and ACS Style
Kim, E.-J.; Kang, H.-W.; Park, S.-M. Enhancing the Sustainability and Satisfaction of Leisure Life for Regular and Non-Regular Workers. Sustainability 2024, 16, 5914. https://doi.org/10.3390/su16145914
AMA Style
Kim E-J, Kang H-W, Park S-M. Enhancing the Sustainability and Satisfaction of Leisure Life for Regular and Non-Regular Workers. Sustainability. 2024; 16(14):5914. https://doi.org/10.3390/su16145914
Chicago/Turabian StyleKim, Eui-Jae, Hyun-Wook Kang, and Seong-Man Park. 2024. "Enhancing the Sustainability and Satisfaction of Leisure Life for Regular and Non-Regular Workers" Sustainability 16, no. 14: 5914. https://doi.org/10.3390/su16145914
APA StyleKim, E. -J., Kang, H. -W., & Park, S. -M. (2024). Enhancing the Sustainability and Satisfaction of Leisure Life for Regular and Non-Regular Workers. Sustainability, 16(14), 5914. https://doi.org/10.3390/su16145914
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