The ecosystem view is a fascinating perspective which provides management scholars with innovative conceptual tools to investigate the functioning of complex service systems. The purpose of this paper is to focus on the “mega” level of the education service ecosystem in an attempt to explain the relationships between education attainments and income disparities across Europe.
Data were collected from the European Union Statistics on Income and Living Conditions. Data trends over the time period (2007-2010) were investigated, involving 27 European countries. Unobserved time-invariant heterogeneity was controlled and dynamics over time were investigated. A random effects model was estimated for each country. The semi-log functional form is informed by Mincer’s (1974) human capital models.
Education levels were found to be a predictor of income inequality in all the countries included in this research, i.e. higher education level leads to higher income and vice versa. However, the effect of education attainments on individual earnings was irregular. Eastern European countries, inter alia, revealed a strong relationship between education attainments and individual earnings, whereas Scandinavian countries showed a weak link between education levels and income.
Education has the potential to affect income inequalities in Europe. Policy makers should develop tailored strategies to deal with the consequences of education levels on individual earnings. Both education services’ quality and the interaction between education and moderating socio-demographic variables may influence income inequality in European countries.
This is one of the first attempts to investigate the relationship between education and income inequalities drawing on the service ecosystem perspective. Further conceptual and practical developments are needed to better explain the effects of education attainments on income inequality.
Manna, R., Ciasullo, M.V., Cosimato, S. and Palumbo, R. (2018), "Interplaying ecosystems: a mega-level analysis of education and labour ecosystems", The TQM Journal, Vol. 30 No. 5, pp. 572-588. https://doi.org/10.1108/TQM-11-2017-0139
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