Comparison of Job Quality Indices Affecting Work–Life Balance in South Korea According to Employee Gender
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design
2.2. Study Population
2.3. Measures
2.3.1. Occupational Characteristics
2.3.2. Job Quality Indices
2.3.3. Work–Life Balance
2.4. Statistical Analyses
3. Results
3.1. Comparison of Occupational Characteristics According to Gender
3.2. Comparison of Job Quality Indices According to Gender
3.3. Comparison of Work–Life Balance According to Gender
3.4. Associations between Job Quality Indices and Work–Life Balance According to Gender
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Twenge, J.M.; Campbell, S.M.; Hoffman, B.J.; Lance, C.E. Generational differences in work values: Leisure and extrinsic values increasing, social and intrinsic values decreasing. J. Manag. 2010, 36, 1117–1142. [Google Scholar] [CrossRef]
- Kim, N.D.; Jeon, M.Y.; Lee, H.Y.; Lee, J.Y.; Kim, S.Y.; Choi, J.H.; Lee, S.J.; Seo, Y.H. Trend Korea 2018; Miraebook Publishing Co.: Seoul, Korea, 2017. [Google Scholar]
- Organization for Economic Co-operation and Development (OECD). Working hours in Korea were long for both men and women in 2014. In OECD Economic Surveys: Korea 2016; OECD Publishing: Paris, France, 2016. [Google Scholar] [CrossRef]
- Hsu, Y.Y.; Bai, C.H.; Yang, C.M.; Huang, Y.C.; Lin, T.T.; Lin, C.H. Long hours’ effects on work-life balance and satisfaction. Biomed. Res. Int. 2019, 1, 1–8. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chung, H.; Van der Lippe, T. Flexible working, work–life balance, and gender equality: Introduction. Soc. Indic. Res. 2018, 1–17. [Google Scholar] [CrossRef] [Green Version]
- Dilmaghani, M.; Tabvuma, V. The gender gap in work–life balance satisfaction across occupations. Gend. Manag. 2019, 34, 398–428. [Google Scholar] [CrossRef]
- Emslie, C.; Hunt, K.; Macintyre, S. Gender, work-home conflict, and morbidity amongst white-collar bank employees in the United Kingdom. Int. J. Behav. Med. 2004, 11, 127–134. [Google Scholar] [CrossRef]
- Frankenhaeuser, M.; Lundberg, U.; Fredrikson, M.; Melin, B.; Tuomisto, M.; Myrsten, A.L.; Hedman, M.; Bergman-Losman, B.; Wallin, L. Stress on and off the job as related to sex and occupational status in white-collar workers. J. Organ. Behav. 1989, 10, 321–346. [Google Scholar] [CrossRef]
- Lundberg, U.; Mårdberg, B.; Frankenhaeuser, M. The total workload of male and female white collar workers as related to age, occupational level, and number of children. Scand. J. Psychol. 1994, 35, 315–327. [Google Scholar] [CrossRef]
- Swanson, V.; Power, K.G.; Simpson, R.J. Occupational stress and family life: A comparison of male and female doctors. J. Occup. Organ. Psychol. 1998, 71, 237–260. [Google Scholar] [CrossRef]
- Turesky, M.; Warner, M.E. Gender dynamics in the planning workplace: The importance of women in management. J. Am. Plan. Assoc. 2020, 86, 1–14. [Google Scholar] [CrossRef]
- Bosak, J.; Sczesny, S.; Eagly, A.H. The impact of social roles on trait judgments: A critical reexamination. Pers. Soc. Psychol. Bull. 2012, 38, 429–440. [Google Scholar] [CrossRef]
- Kim, K.J. Human resource management system for nurses: Challenges and research directions. Korean J. Health Serv. Manag. 2012, 6, 247–258. [Google Scholar] [CrossRef]
- McKinsey & Company. Women Matter: Time to Accelerate Ten Years of Insights into Gender Diversity; McKinsey & Company: New York, NY, USA, 2017. [Google Scholar]
- Bettio, F.; Verashchagina, A. Gender Segregation in the Labour Market. Root Causes, Implications and Policy Responses in the EU; European Commission’s Expert Group on Gender and Employment; European Commission: Brussels, Belgium, 2009. [Google Scholar]
- Gonäs, L.; Wikman, A.; Vaez, M.; Alexanderson, K.; Gustafsson, K. Gender segregation of occupations and sustainable employment: A prospective population-based cohort study. Scand. J. Public Health 2019, 47, 348–356. [Google Scholar] [CrossRef] [PubMed]
- Sung, N.; Lee, H.; Jo, D. Regional unbalance in sex ratio and marriage rate: Empirical analysis. Korea Rev. Appl. Econ. 2012, 14, 187–220. [Google Scholar]
- Elahi, E.; Weijun, C.; Jha, S.K.; Zhang, H. Estimation of realistic renewable and non-renewable energy use targets for livestock production systems utilising an artificial neural network method: A step towards livestock sustainability. Energy 2019, 183, 191–204. [Google Scholar] [CrossRef]
- Elahi, E.; Weijun, C.; Zhang, H.; Abid, M. Use of artificial neural networks to rescue agrochemical-based health hazards: A resource optimisation method for cleaner crop production. J. Clean. Prod. 2019, 238, 117900. [Google Scholar] [CrossRef]
- Elahi, E.; Khalid, Z.; Weijun, C.; Zhang, H. The public policy of agricultural land allotment to agrarians and its impact on crop productivity in Punjab province of Pakistan. Land Use Policy 2020, 90, 104324. [Google Scholar] [CrossRef]
- Elahi, E.; Abid, M.; Zhang, L.; ul Haq, S.; Sahito, J.G.M. Agricultural advisory and financial services; farm level access, outreach and impact in a mixed cropping district of Punjab, Pakistan. Land Use Policy 2018, 71, 249–260. [Google Scholar] [CrossRef]
- Camerino, D.; Sandri, M.; Sartori, S.; Conway, P.M.; Campanini, P.; Costa, G. Shiftwork, work-family conflict among Italian nurses, and prevention efficacy. Chronobiol. Int. 2010, 27, 1105–1123. [Google Scholar] [CrossRef]
- Kim, H.D.; Kim, M.H. The effect of confucian philosophy and gender egalitarian ideology on the work-family balance of married working women-husband and working conditions as partners. Women’s Stud. 2011, 81, 33–67. [Google Scholar]
- Kim, J.K.; Yang, J.S. Analysis of the factors influencing work-family balance: A focus on the impact of social support. Korean J. Public Adm. 2012, 50, 251–280. [Google Scholar]
- Lee, Y.S.; Jang, S.J. The effects of work-family conflicts, organizational culture, and supervisor support, on the mental and physical health of married nurses. Health Soc. Welf. Rev. 2013, 33, 397–418. [Google Scholar]
- Wang, M.L.; Tsai, L.J. Work-family conflict and job performance in nurses: The moderating effects of social support. J. Nurs. Res. 2014, 22, 200–207. [Google Scholar] [CrossRef] [PubMed]
- Zhang, J.; Liu, Y. Antecedents of work-family conflict: Review and prospect. Int. J. Bus. Manag. 2011, 6, 89–103. [Google Scholar] [CrossRef] [Green Version]
- Bender, K.A.; Donohue, S.M.; Heywood, J.S. Job satisfaction and gender segregation. Oxf. Econ. Pap. 2005, 57, 479–496. [Google Scholar] [CrossRef]
- Lingard, H.; Brown, K.; Bradley, L.; Bailey, C.; Townsend, K.L. Improving employees’ work-life balance in the construction industry: Project alliance case study. J. Constr. Eng. Manag. 2007, 133, 807–815. [Google Scholar] [CrossRef]
- European Foundation for the Improvement of Living and Working Conditions. Sixth European Working Conditions Survey—Overview Report; Publications Office of the European Union: Brussels, Belgium, 2016.
- Brown, J.D. Likert items and scales of measurement. Statistics 2011, 15, 10–14. [Google Scholar]
- Leinonen, T.; Viikari-Juntura, E.; Husgafvel-Pursiainen, K.; Virta, L.J.; Laaksonen, M.; Autti-Rämö, I.; Solovieva, S. Labour market segregation and gender differences in sickness absence: Trends in 2005–2013 in Finland. Ann. Work. Expo. Health 2018, 62, 438–449. [Google Scholar] [CrossRef]
- Jung, J.; Kim, G.; Kim, K.; Paek, D.; Cho, S.I. Association between working time quality and self-perceived health: Analysis of the 3rd Korean working conditions survey (2011). Ann. Occup. Environ. Med. 2017, 29, 55. [Google Scholar] [CrossRef]
- Kim, H.; Moon, C.G. Empirical analysis of work-life balance: Using the 4th and 5th Korean working conditions surveys. Korean Soc. Secur. Stud. 2019, 35, 167–206. [Google Scholar]
- Theorell, T.; Hammarström, A.; Gustafsson, P.E.; Hanson, L.M.; Janlert, U.; Westerlund, H. Job strain and depressive symptoms in men and women: A prospective study of the working population in Sweden. J. Epidemiol. Community Health 2014, 68, 78–82. [Google Scholar] [CrossRef]
- De Jonge, J.; Bosma, H.; Peter, R.; Siegrist, J. Job strain, effort-reward imbalance and employee well-being: A large-scale cross-sectional study. Soc. Sci. Med. 2000, 50, 1317–1327. [Google Scholar] [CrossRef]
- Chavalitsakulchai, P.; Shahnavaz, H. Musculoskeletal disorders of female workers and ergonomics problems in five different industries of a developing country. J. Hum. Ergol. 1993, 22, 29–43. [Google Scholar]
- Hämmig, O.; Knecht, M.; Läubli, T.; Bauer, G.F. Work-life conflict and musculoskeletal disorders: A cross-sectional study of an unexplored association. BMC Musculoskelet. Disord. 2011, 12, 60. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Holmgren, K.; Löve, J.; Mårdby, A.C.; Hensing, G. Remain in work--what work-related factors are associated with sustainable work attendance: A general population-based study of women and men. J. Occup. Environ. Med. 2014, 56, 235–242. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Variable | Category | Male | Female | X2 | p | ||
---|---|---|---|---|---|---|---|
n (%) | n (%) | ||||||
Age | 15–19 | 233 | (1.1) | 172 | (1.1) | 406.402 | <0.001 |
20–29 | 3103 | (14.6) | 3513 | (21.7) | |||
30–39 | 5736 | (27.1) | 3469 | (21.5) | |||
40–49 | 5547 | (26.2) | 3884 | (24.0) | |||
50–59 | 4305 | (20.3) | 3203 | (19.8) | |||
≥60 | 2260 | (10.7) | 1912 | (11.8) | |||
N = 21,184 | N = 16,153 | ||||||
Occupation | Managers | 205 | (1.0) | 23 | (0.1) | 4664.509 | <0.001 |
Professionals | 4273 | (20.2) | 4355 | (27.0) | |||
Clerks | 5143 | (24.3) | 3927 | (24.3) | |||
Service workers | 1060 | (5.0) | 2663 | (16.5) | |||
Sales workers | 1608 | (7.6) | 2216 | (13.7) | |||
Agricultural workers | 121 | (0.6) | 28 | (0.2) | |||
Crafts workers | 2869 | (13.5) | 445 | (2.8) | |||
Plant or machine operators | 3482 | (16.4) | 512 | (3.2) | |||
Elementary workers | 2309 | (10.9) | 1980 | (12.3) | |||
Armed forces | 113 | (0.5) | 6 | (0.0) | |||
N = 21,183 | N = 16,155 | ||||||
Sector | Agriculture | 97 | (0.5) | 56 | (0.3) | 6566.438 | <0.001 |
Industry | 5578 | (26.3) | 2114 | (13.1) | |||
Construction | 2667 | (12.6) | 225 | (1.4) | |||
Commerce and hospitality | 2947 | (13.9) | 3764 | (23.3) | |||
Transport | 1606 | (7.6) | 220 | (1.4) | |||
Financial services | 1092 | (5.2) | 1065 | (6.6) | |||
Public administration | 1265 | (6.0) | 789 | (4.9) | |||
Education | 1031 | (4.9) | 2100 | (13) | |||
Health | 588 | (2.8) | 2946 | (18.2) | |||
Other services | 4318 | (20.4) | 2874 | (17.8) | |||
N = 21,183 | N = 16,153 | ||||||
Number of employees | 1–9 | 6557 | (31.2) | 7834 | (48.9) | 1408.591 | <0.001 |
10–249 | 11,811 | (56.2) | 7312 | (45.6) | |||
≥250 | 2643 | (12.6) | 880 | (5.5) | |||
N = 21,011 | N = 16,026 | ||||||
Monthly income | <100 | 853 | (4.1) | 2151 | (13.4) | 7505.939 | <0.001 |
(10,000 won) | 100–199 | 2871 | (13.7) | 6611 | (41.3) | ||
200–299 | 5736 | (27.4) | 4806 | (30.0) | |||
300–399 | 6226 | (29.7) | 1573 | (9.8) | |||
400–499 | 3090 | (14.7) | 508 | (3.2) | |||
≥500 | 2177 | (10.4) | 369 | (2.3) | |||
N = 20,953 | N = 16,018 |
Indices | Male (n = 21,183) | Female (n = 16,154) | t | p |
---|---|---|---|---|
M ± SD | M ± SD | |||
Physical environment | 75.20 ± 12.80 | 79.33 ± 10.21 | −35.037 | <0.001 |
Work intensity (reversed) | 69.25 ± 14.41 | 70.60 ± 13.28 | −9.415 | <0.001 |
Working time quality | 73.09 ± 17.57 | 78.73 ± 14.45 | −34.000 | <0.001 |
Social environment | 82.10 ± 7.58 | 81.38 ± 7.54 | 9.151 | <0.001 |
Skills and discretion | 43.43 ± 18.52 | 37.96 ± 17.88 | 28.877 | <0.001 |
Prospects | 76.44 ± 14.00 | 74.57 ± 13.94 | 12.808 | <0.001 |
Variables | Male | Female | X2 | p |
---|---|---|---|---|
n (%) | n (%) | |||
Positive | ||||
My working hours fit in well or very well with family/social commitments outside work | 15,611 (73.8) | 12,811 (79.4) | 159.039 | <0.001 |
N = 21,150 | N = 16,131 | |||
Negative 1 | ||||
Worry about work when not working | 1693 (8.2) | 1267 (8.1) | 0.027 | 0.869 |
N = 20,679 | N = 15,567 | |||
Too tired after work to do household tasks | 2370 (11.5) | 1671 (10.5) | 8.254 | 0.004 |
N = 20,634 | N = 15,863 | |||
Job prevents spending time with family | 2743 (13.4) | 1856 (11.9) | 17.743 | <0.001 |
N = 20,540 | N = 15,642 | |||
Family prevents spending time working | 1574 (7.6) | 1343 (8.6) | 10.615 | 0.001 |
N = 20,640 | N = 15,682 | |||
Hard to concentrate on job because of my family responsibilities | 1654 (8.1) | 1370 (8.8) | 6.271 | 0.012 |
N = 20,474 | N = 15,538 |
Job Quality Indices | Positive | Negative | ||||
---|---|---|---|---|---|---|
Good Fit between Working Time and Non-Working Time | Worry about Work | Tired after Work | Job Affects Family Time | Family Affects Job Time | Concentration Problems Due to Family Issues | |
OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | OR (95% CI) | |
Male | ||||||
Physical environment | 1.011 (1.008–1.013) | 0.995 (0.993–0.998) | 0.980 (0.978–0.983) | 0.983 (0.980–0.985) | 0.984 (0.982–0.987) | 0.983 (0.980–0.985) |
Work intensity (reversed) | 1.002 (0.999–1.004) | 0.981 (0.979–0.983) | 0.976 (0.974–0.978) | 0.981 (0.979–0.983) | 0.979 (0.976–0.981) | 0.978 (0.976–0.980) |
Working time quality | 1.038 (1.036–1.040) | 0.989 (0.987–0.990) | 0.975 (0.973–0.977) | 0.968 (0.966–0.969) | 0.991 (0.990–0.993) | 0.993 (0.991–0.995) |
Social environment | 1.028 (1.024–1.032) | 0.994 (0.991–0.998) | 0.982 (0.978–0.985) | 0.988 (0.984–0.992) | 0.989 (0.986–0.993) | 0.985 (0.981–0.989) |
Skills and discretion | 1.008 (1.006–1.010) | 1.017 (1.015–1.018) | 1.001 (1.000–1.003) | 1.001 (0.999–1.003) | 1.002 (1.001–1.004) | 1.002 (1.001–1.004) |
Prospects | 1.008 (1.006–1.011) | 0.986 (0.984–0.989) | 0.985 (0.983–0.987) | 0.988 (0.985–0.990) | 0.985 (0.983–0.987) | 0.986 (0.984–0.988) |
N = 20,961 | N = 20,499 | N = 20,446 | N = 20,396 | N = 20,477 | N = 20,319 | |
Female | ||||||
Physical environment | 1.014 (1.010–1.018) | 0.986 (0.983–0.989) | 0.975 (0.972–0.978) | 0.976 (0.972–0.979) | 0.974 (0.971–0.977) | 0.970 (0.967–0.974) |
Work intensity (reversed) | 1.007 (1.004–1.010) | 0.978 (0.975–0.980) | 0.969 (0.966–0.971) | 0.974 (0.971–0.976) | 0.975 (0.972–0.977) | 0.976 (0.974–0.979) |
Working time quality | 1.045 (1.042–1.048) | 0.989 (0.986–0.991) | 0.969 (0.967–0.972) | 0.965 (0.963–0.968) | 0.986 (0.983–0.988) | 0.988 (0.986–0.991) |
Social environment | 1.025 (1.020–1.030) | 0.989 (0.985–0.993) | 0.985 (0.981–0.989) | 0.992 (0.987–0.996) | 0.987 (0.983–0.992) | 0.990 (0.986–0.995) |
Skills and discretion | 1.007 (1.005–1.009) | 1.017 (1.015–1.019) | 1.005 (1.003–1.007) | 1.003 (1.001–1.005) | 1.006 (1.004–1.008) | 1.005 (1.003–1.007) |
Prospects | 1.001 (0.998–1.004) | 0.983 (0.981–0.986) | 0.990 (0.998–0.993) | 0.989 (0.986–0.991) | 0.985 (0.983–0.988) | 0.984 (0.982–0.987) |
N = 15,658 | N = 15,129 | N = 15,406 | N = 15,255 | N = 15,262 | N = 15,153 |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Choi, S.-H.; Choi, E.Y.; Lee, H. Comparison of Job Quality Indices Affecting Work–Life Balance in South Korea According to Employee Gender. Int. J. Environ. Res. Public Health 2020, 17, 4819. https://doi.org/10.3390/ijerph17134819
Choi S-H, Choi EY, Lee H. Comparison of Job Quality Indices Affecting Work–Life Balance in South Korea According to Employee Gender. International Journal of Environmental Research and Public Health. 2020; 17(13):4819. https://doi.org/10.3390/ijerph17134819
Chicago/Turabian StyleChoi, Seung-Hye, Eun Young Choi, and Haeyoung Lee. 2020. "Comparison of Job Quality Indices Affecting Work–Life Balance in South Korea According to Employee Gender" International Journal of Environmental Research and Public Health 17, no. 13: 4819. https://doi.org/10.3390/ijerph17134819