Mesai Sürelerini Etkileyen Faktörler: TÜİK Verileri Üzerine Ampirik Bir Araştırma

Yıl 2018, Sayı: 74, 33 - 49, 12.07.2018

Tekin Akgeyik

Öz

Bu araştırmanın amacı, TÜİK 2016 Hane Halkı İşgücü İstatistikleri veri seti kapsamında mesai sürelerini etkileyen değişkenleri analiz etmektir. Hiyerarşik regresyon analizinin sonuçları, cinsiyet, yaş, medeni durum, eğitim düzeyi ve deneyim süresi gibi bireysel değişkenlerin mesai süreleri üzerinde etkili değişkenler olduğunu göstermektedir. Ayrıca çalışan sayısı, kayıtlı istihdam ve ücret düzeyi gibi işle ilgili değişkenler de mesai sürelerinin diğer açıklayıcı değişkenleri olarak tespit edilmiştir. Tüm değişkenler bir arada haftalık mesai sürelerindeki değişimi %10,7 oranında açıklayabilmektedir. Araştırmanın bir diğer sonucu, mesai süresi ile çalışan sayısı, eğitim düzeyi, kayıtlı istihdam ve ücret düzeyi arasında görece daha yüksek korelasyon ilişkisi olduğu yönündedir. Nihayet, istatistiksel analizler mesai süreleri açısından cinsiyet farklılığı olduğunu göstermiştir. Bulgular erkeklerin kadınlara oranla daha uzun süreli mesailer (%6) yaptığına işaret etmektedir. 

Anahtar Kelimeler

Mesai süresi, Bireysel değişkenler, İşle ilişkili değişkenler

Factors Affecting the Number of Hours Worked (An Empirical Study on TSI Data)

Öz

This paper investigates factors affecting the number of hours worked per week based on a sample from the Turkish Statistic Institute’s (TSI) 2016 labor force statistics. Overall, the results of the hierarchical multiple regression analysis revealed that individual variables including gender, age, marital status, education and job experience are significant predictors of the number of hours worked. Moreover, the number of workers, amount of formal work and income as a job-related factor are observed to predict the number of hours worked. These predictors account for 10.7 percent of the variance in the number of hours worked. In addition, the results of correlation analysis indicate that the number of hours worked is negatively and significantly correlated with gender, education, job experience, the number of workers and income but is positively and significantly related to marital status, position and formal work. Finally, a significant difference in gender was found with respect to the number of hours worked, with male employees having a higher number of working hours compared to female employees (6%). 

Anahtar Kelimeler

Working hours, Individual variables, Job-related factors

Kaynakça

• Abhayaratna, J., Andrews, L., Nuch, H., & Podbury, T. (2008). Part time employment: The Australian experience. Melbourne: Productivity Commission Staff Working Paper.
• Beccue, B. B. (1977). Determinants of the number of hours worked by the gainfully-employed married woman (Doctoral dissertation, University of Illinois, Illinois).
• Benham, L. (1971). The labor market for registered nurses: A three-equation model. The Review of Economics and Statistics, 53(3), 246‒252.
• Buerhaus, P. I. (1990). Economic and work satisfaction determinants of the annual number of hours worked by registered nurses (Doctoral dissertation, Wayne State University, Michigan). Retrieved from http://urn.kb.se/resolve?urn:nbn:se:kth:diva-3029
• Eymen, U. E. (2007). Spss kullanma klavuzu (E-basım). İstanbul: İstatistik Merkezi. van Hassel, D., van der Velden, L., de Bakker, D., & Batenburg, R. (2017). Age-related differences in working hours among male and female GPS: An SMS based time use study. Human Resources for Health, 15(84), 1‒8.
• Hogan, V., Hogan, M., Hodgins, M., Kinman, G., & Bunting, B. (2015). An examination of gender differences in the impact of individual and organizational factors on work hours, work-life conflict and psychological strain in academics. The Irish Journal of Psychology, 35(2-3), 133‒150.
• International Labour Organization. (2014). Wages and working hours in the textiles. Clothing, Leather and Footwear Industries, GDFTCLI/2014, Geneva. Lu, L. (2011). Working hours and personal preference among Taiwanese employees. International Journal of Workplace Health Management, 4(3), 244‒256.
• Major, V. S., Klein, K. J., & Erhart, M. G. (2002). Work time, work interference with family and psychological distress. Journal of Applied Psychology, 87(3), 427‒436.
• McKay, J. C., Ahmad, A., Shaw, J. L., Rashid, F., Clancy, A., David, C. … Quiñonez, C. (2016). Gender differences and predictors of work hours in a sample of Ontario dentists. Journal of the Canadian Dental Association, 82(26), 1‒11.
• Mishra, V., & Smyth, R. (2013). Working hours in Chinese enterprises: evidence from matched employer–employee data. Industrial Relations Journal, 44(1), 57‒77.
• Nagamachi, R., & Yugami, K. (2015). The consistency of Japan’s statistics on working hours, and an analysis of household working hours. Policy Research Institute, Ministry of Finance, Japan, Public Policy Review, 11(4), 623‒655.
• Organisation for Economic Co-operation and Development. (2018). Hours worked: 2016. Retrieved from www.oecd.org
• Organisation for Economic Co-operation and Development. (2016). OECD Employment Outlook 2017. Paris: Author.
• Organisation for Economic Co-operation and Development. (1998). OECD Employment Outlook 1998: June. Paris: Author.
• Shields, M. (1999). Long working hours and health. Health Reports, 11(2), 49‒56.
• Wallace, J. E. (1999). Work-to-nonwork conflict among married male and female lawyers. Journal of Organizational Behavior, 20(6), 797‒816.