Impact of Human Capital and Weak Ties in Social Networks on Employability

Yıl 2023, , 254 - 274, 31.10.2023

Mahmut Özer

https://doi.org/10.46778/goputeb.1351495

Öz

Countries attach special importance to improving the quality of their human capital to sustain their development processes and enhance their competitive strength. The most effective instrument for achieving this goal is education. For this reason, countries allocate substantial budgets to ensure universality in their education systems, aiming to enable the participation of all citizens in education. This process has led to massification in education and, therefore, has brought a heated debate about what needs to be done in the education system and the labor market to ensure a smooth transition from school to work. In these discussions, the problems related to the transition from school to work are often primarily associated with deficiencies in the education system. However, this trend overlooks many hidden social networks and actual employment dynamics in this transition. Thus, the current study addresses employability based on the Granovetter network model, which has played a pioneering role in understanding employment dynamics and continues to be relevant. The study explores the Granovetter model and the significance of weak ties, the relationship between the Granovetter model and new network models, and the Matthew Effect in the Granovetter model. Furthermore, it emphasizes that acting based on the insights from this model in the transition from school to work is as crucial as human capital.

Anahtar Kelimeler

Human Capital, Granovetter Network, Weak Link, Matta Effect, School-to-Work Transition, Employment

Beşerî Sermaye ve Sosyal Ağlarda Zayıf Bağların İstihdam Edilebilirliğe Etkisi

Öz

Ülkeler kalkınma süreçlerini sürekli kılmak ve rekabet güçlerini artırmak için beşerî sermayelerinin niteliğini artırmaya özel önem vermektedir. Bu amaca yönelik en etkin enstrüman eğitimdir. Bu nedenle ülkeler eğitim sistemlerinde evrenselleşmeyi sağlamak için, yani tüm vatandaşlarının eğitime katılımını sağlamak için devasa bütçeler kullanmaktadır. Bu süreç eğitimde kitleselleşmeye yol açmış ve okuldan-işe sorunsuz geçiş sağlayabilmek için eğitim sistemi ve işgücü piyasasında yapılması gerekenler sıcak tartışma gündemine taşınmıştır. Bu kapsamdaki tartışmalarda okuldan-işe geçişteki sorunların çoğunlukla eğitim sistemindeki eksikliklerle ilişkilendirildiği görülmektedir. Ancak bu eğilim okuldan-işe geçişte toplumlarda görünmez sosyal ağların ve işe alımdaki gerçek dinamiklerin çoğunu göz ardı etmektedir. Bu nedenle bu çalışmada istihdam dinamiklerinin anlaşılmasında öncü rol oynayan ve halen geçerliliğini koruyan Granovetter ağ modeline dayalı olarak istihdam edilebilirlik ele alınmaktadır. Granovetter modeli ve zayıf bağların önemi, Granovetter modelinin yeni ağ modelleri ile ilişkisi ve Granovetter modelinde Matta etkisi irdelenmektedir. Ayrıca, okuldan işe geçişte bu model bilgisine göre hareket etmenin beşerî sermaye kadar önemli olduğu vurgulanmaktadır.

Anahtar Kelimeler

Beşerî Sermaye, Granovetter Ağı, Zayıf Bağ, Matta Etkisi, Okuldan İşe Geçiş, İstihdam

Kaynakça

• Arrow, K. J., & Borzekowski, R. (2004). Limited network connections and the distribution of wages. U.S. Federal Reserve Board, Finance and Economics Discussion Series, No.2004-41. http://dx.doi.org/10.2139/ssrn.632321
• Barabasi, A. L., Albert, R., & Jeong, H. (1999). Mean-field theory for scale-free random networks. Physica A, 272, 173-187. https://doi.org/10.1016/S0378-4371(99)00291-5
• Barabasi, A. L., & Bonabeau, E. (2003). Scale-free networks. Scientific American, 288(5), 60-69. https://doi.org/10.1038/scientificamerican0503-60
• Barabasi, A. L. (2022). Formül: Başarının evrensel kuralları. [Formula: Universal rules of success]. İstanbul Bilgi University Publishing.
• Becker, G. S. (1962). Investment in human capital: A theoretical analysis. J Polit Econ, 70, 9-49.
• Becker, G. S. (1964). Human capital: A theoretical and empirical analysis with special reference to education. Columbia University Press.
• Bolibar, M., Verd, J. M., & Barranco, O. (2019). The downward spiral of youth unemployment: An approach considering social networks and family background. Work, Employment and Society, 33(3), 401-421. https://doi.org/10.1177/0950017018822918
• Burks, S. V., Cowgill, B., Hoffman, M., & Housman, M. (2015). The value of hiring through employee referrals. Querterly Journal of Economics, 130(2), 805-839. https://doi.org/10.1093/qje/qjv010
• Calvo-Armengol, A. (2006). Social networks and labour market outcomes. Els Opuscles del CREI, Universitat Pompeu Fabra, No.17.
• Calvo-Armengol, A., & Jackson, M. O. (2004). The effects of social networks on employment and inequality. The American Economic Review, 94(3), 426-454. https://doi.org/10.1257/0002828041464542
• Campbell, K. E., & Marsden, P. V. (1990). Recruitment and selection process: The organizational side of job searches. In R. L. Breiger (Ed.). Social mobility and social structure (pp. 59-79). Cambridge University Press.
• Erdi, P. (2020). Ranking: The unwritten rules of the social game we all play. Oxford University Press.
• Erkaymaz, O., Özer, M., & Yumuşak, N. (2014). Impact of small-world topology on the performance of a feed-forward artificial neural network based on 2 different real-life problems. Turkish Journal of Electrical Engineering and Computer Sciences, 22(3), 708-718. https://doi.org/10.3906/elk-1202-89
• Erkaymaz, O., & Özer, M. (2016). Impact of small-world network topology on the conventional feed-forward artificial neural network for the diagnosis of diabetes. Chaos, Solitons & Fractals, 83, 178-185. https://doi.org/10.1016/j.chaos.2015.11.029
• Erkaymaz, O., Özer, M., & Perc, M. (2017). Performance of small-world feedforward neural networks for the diagnosis of diabetes. Applied Matematics and Computation, 311, 22-28. https://doi.org/10.1016/j.amc.2017.05.010
• Gee, L. K., Jones, J., & Burke, M. (2017). Social networks and labor markets: How strong ties relate to job finding on Facebook’s social networks. Journal of Labor Market, 35(2), 485-518. https://doi.org/10.1086/686225
• Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78, 1360-1380.
• Granovetter, M. S. (1974). Getting a job: A study of contacts and careers. Harvard University Press.
• Granovetter, M. S. (1982). The strength of weak ties: A network theory revisited. In P. V. Marsden & N. Lin (Eds.). Social structure and network analysis (pp. 105-130). Sage Publishing.
• Granovetter, M. S. (1985). Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91, 481-510.
• Hurst, J. M. (2016). The impact of networks on unemployment. Palgrave Macmillan: Springer Nature.
• Katz, L. F., & Autor, D. H. (1999). Changes in the wage structure and earnings inequality. In O. Ashenfelter & D. Card. (Eds.) Handbook of labor economics (pp. 1463-1555). Elsevier Science.
• Kramarz, F., & Skans, O. N. (2014). When strong ties are strong: Networks and youth labour market entry. Review of Economic Studies, 81(3), 1164-1200. https://doi.org/10.1093/restud/rdt049
• Llyod, C., & Payne, J. (2016). Skills in the age of over-qualification: Comparing service sector work in Europe. Oxford University Press.
• Maccabe, R. (2023). A narrative inquiry into the formation and deployment of graduate capitals by first-generation graduates over time. [Unpublished PhD Thesis]. Lancaster University.
• MacMillan, L., Tyler, C., & Vignoles, A. (2015). Who gets the top jobs? The role of family background and networks in recent graduates’ access to high-status professions. Journal of Social Policy, 44(3), 487-515. https://doi.org/10.1017/S0047279414000634
• Merton, R. K. (1968). The Matthew effect in science. Science, 159, 53-63. https://doi.org/10.1126/science.159.3810.56
• Merton, R. K. (1973). The sociology of science: Theoretical and empirical investigations. University of Chicago Press.
• Montgomery, J. D. (1991). Social networks and labor-market outcomes: Towards and economic analysis. American Economic Review, 81(5), 1408-1418.
• Montgomery, J. D. (1994). Weak ties, employment, and inequality: An equilibrium analysis. American Journal of Sociology, 99(5), 1212-1236. https://doi.org/10.1086/230410
• Myers, C. A., & Shultz, G. P. (1951). The dynamics of a labor market. Prentice-Hall.
• Ost, B., Pan, W., & Webber, D. (2023). College networks and re-employment of displaced workers. Finance and Economics Discussion Series 2023-043. Board of Governors of the Federal Reserve System. https://doi.org/10.17016/FEDS.2023.043
• Özer, M., & Suna, H. E. (2019). Future of vocational and technical education in Turkey: Solid steps taken after Education Vision 2023. Journal of Education and Humanities, 10(20), 165–192.
• Özer, M., & Suna, H. E. (2020). The linkage between vocational education and labor market in Turkey: Employability and skill mismatch. Kastamonu Education Journal, 28(2), 558–569. https://doi.org/10.24106/kefdergi.704878
• Özer, M. (2020a). The new factors affecting the school to-work transition for vocational education and training: New trends in global transformation. The Journal of Humanity and Society, 10(3), 1-27. https://doi.org/10.12658/M0534
• Özer, M. (2020b). The conflict between individualist vs structural approaches for issues in the transition from school-to-work. Bartın University Journal of Faculty of Economics and Administrative Sciences, 11(22), 330–345. https://doi.org/10.47129/bartiniibf.759157
• Özer, M., & Perc, M. (2020). Dreams and realities of school tracking and vocational education. Palgrave Communications, 6, 34. https://doi.org/10.1057/s41599-020-0409-4
• Özer, M (2021). Eğitim politikalarında sistemik uyum. [Systemic coherence in education policies]. Maltepe Üniversitesi Yayınları.
• Özer, M., & Perc, M. (2021). Impact of social networks on the labor market inequalities and school-to-work transitions. Journal of Higher Education, 11(1), 38–50. https://doi.org/10.2399/yod.21.868353
• Özer, M. (2023). Türkiye’de eğitimin geleceği: Eşit, kapsayıcı ve kaliteli. [The future of education in Turkey: Equal, inclusive, and quality]. VakıfBank Kültür Yayınları.
• Park, P. S., Blumenstock, J. E., & Macy, M. W. (2018). The strength of long-range ties in population-scale social networks. Science, 362(6421), 1410–13. https://doi.org/10.1126/science.aau9735
• Perc, M. (2014). The Matthew effect in empirical data. Journal of Royal Soc Interface, 11, 20140378. https://doi.org/10.1098/rsif.2014.0378
• Rajkumar, K., Saint-Jacques, G., Bojinov, I., Brynjolfsson, E., & Aral, S. (2022). A causal test of the strength of weak ties. Science, 377(6612), 1304-1310. https://doi.org/10.1126/science.abl4476
• Rees, A. (1966). Information networks in labor markets. American Economic Review, 56, 559-566.
• Rees, A., & Shultz, G. P. (1970). Worker in an urban labor market. University of Chicago Press.
• Reschly, A. (2010). Reading and school completion: Critical connections and Matta effects. Reading & Writing Quarterly, 26, 67-90. https://doi.org/10.1080/10573560903397023
• Simard, D., Nadeau, L., & Kroger, H. (2005). Fastest learning in small-world neural networks. Phys. Lett. A, 336, 8–15. https://doi.org/10.1016/j.physleta.2004.12.078
• Suna, H. E., Tanberkan, H., Gür, B. S., & Özer, M. (2020). Socioeconomic status and school type as predictors of academic achievement. Journal of Economy Culture and Society, 61(1), 41-64. https://doi.org/10.26650/JECS2020-0034
• Stanovich, K. E. (2009). Matthew effect in reading: Some consequences of individual differences in acquisition of literacy. Journal of Education, 189, 23-55. https://doi.org/10.1177/0022057409189001-204
• Van der Leij, M., & Goyal, S. (2011). Strong ties in a small world. Review of Network Economics, 10(2), 1-20. https://doi.org/10.2202/1446-9022.1278
• Walberg, H. J., & Tsai, S. L. (1983). Matthew effects in education. American Educational Research Journal, 20(3), 359-373. https://doi.org/10.3102/00028312020003359
• Wang, D., & Uzzi, B. (2022). Weak ties, failed tries, and success. Science, 377(6612), 1256-1258. https://doi.org/10.1126/science.add0692
• Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of ‘small-‘world’ networks. Nature, 393, 440-442. https://doi.org/10.1038/30918
• Wheelahan, L., Moddie, G., & Doughney, J. (2022). Challenging the skills fetish. British Journal of Sociology of Education, 43(3), 475-494. https://doi.org/10.1080/01425692.2022.2045186
• Zenou, Y. (2013). Spatial versus social mismatch. Journal of Urban Economics, 74, 113-132. https://doi.org/10.1016/j.jue.2012.11.002
• Zenou, Y. (2015). A dynamic model of weak and strong ties in the labor market. Journal of Labor Economics, 33(4), 891-932. https://doi.org/10.1086/681098