Abstract
The fear of job loss due to the labour-saving technological changes is not a new phenomenon, dating back to the 19th century Luddites in Britain. Recently, similar fear has reawakened due to the rapid expansion of the increasingly cheap and capable computers (digitisation). According to the empirical experience of the European Working Condition Surveys (EWCS 2005 and 2015), every second workplace belongs to the category of ‘creative work’, which is less threatened by automation; and every fourth worker carries out ’routine’ tasks, which will be easily replaced by computers. However, important country group differences exist: creative jobs higher than EU-27 average characterise the Nordic, Continental and Anglo-Saxon countries. By contrast, the highest rate of routine tasks prevails in the Mediterranean and Central and Eastern European countries. Among the post-socialist countries Hungary lags behind the European average and the trends of the previous years on the job loss are alarming, meaning concerns of automatization are a valid concern for unskilled workers.
Highlights
For more than half a century, many business organizations and national policies have embraced Drucker’s declaration that organizations only have two basic functions: marketing and innovation (Mohr, 2009)
On the basis of cluster analysis we intend to answer three main research questions: i) to what extent are European labor markets susceptible to automation, ii) to what extent do EU Member States differ in this regard, and iii) what trends can be identified with respect to this phenomenon over time? Our paper reviews the history of automation and the most relevant literature in the field, presents our own conceptual framework in the second section, describes the methodology and the data sources used in the empirical analysis, summarizes results, and raises some research questions and challenges for the future
To describe labor markets in the Member States of the European Union from the perspective of the possible impact of current and future waves of automation and digitalization, we draw upon the theoretical basis elaborated by Frey and Osborne (2017), who distinguished three major job characteristics – perception and manipulation, creative intelligence, and social intelligence – that may inhibit the substitution of human labour by computers
Summary
For more than half a century, many business organizations and national policies have embraced Drucker’s declaration that organizations only have two basic functions: marketing and innovation (Mohr, 2009). The ten-year strategy of the European Union, accepted in 2010, placed smart, inclusive, and sustainable growth at the center of development policy (European Commission, 2010). Of these objectives, ‘smart’ has almost become synonymous with most modern technological development, ‘inclusive’ with the risk of widening social inequalities, while ‘sustainability’ draws attention to the long-term environmental and socio-economic impacts of human activity. Our study describes the complex social impacts of technological innovation through the example of automation by using American, European, and Hungarian quantitative analyses. Our paper reviews the history of automation and the most relevant literature in the field, presents our own conceptual framework, describes the methodology and the data sources used in the empirical analysis, summarizes results, and raises some research questions and challenges for the future On the basis of cluster analysis we intend to answer three main research questions: i) to what extent are European labor markets susceptible to automation, ii) to what extent do EU Member States differ in this regard, and iii) what trends can be identified with respect to this phenomenon over time (i.e., between 2005 and 2015)? Our paper reviews the history of automation and the most relevant literature in the field, presents our own conceptual framework in the second section, describes the methodology and the data sources used in the empirical analysis, summarizes results, and raises some research questions and challenges for the future
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