Suchergebnisse

Smart Working (SW) is a new form of work based on the use of digital devices allowing people to work anywhere and anytime, which has developed in the last decades, but only recently has become the object of studies, discussions, and attention of several organizations, companies and governments. SW rises from the digitalization of the work and the spread of mobile technologies, but is more than flexible working or teleworking. It reorganizes completely the world of work and shapes the private life of the workers. The present study is aimed at giving a theoretical background, and through an empirical analysis, studying the possible implications of the use of ICTs and the degree of mobility of the workers on their working conditions and wellbeing conditions. Despite the increasing interest in this topic, there are only few empirical studies that address the above issue. Therefore, this study tries to contribute to fill this gap through an analysis of secondary data from the 6th European Working Conditions Survey (EWCS, EC 2015), on a sample of more than 43.000 European workers. The first part of this work is a review of the literature on the digitalization of the work, its impact and consequences on the world of work and on the new forms of work. Then, SW is described and the analysis covers the traits, the advantages and the drawbacks for the smart workers, the roots and the levers of this new form of work, the fields of adoption, and finally an eye to the future. In the second part of this study, the research hypotheses are tested through the analysis of data from the 6th EWCS. In particular, the sample is divided in five groups of workers based on the intensity of the use of ICT and on their degree of mobility. For each group descriptive statistics are computed in order to describe them. Then, on the whole sample, measures of association are produced to find relationships between ICT use intensity and degree of mobility, and between these and working conditions and wellbeing conditions. Finally, regression analyses are computed in order to find some predictors able to explain the consequences of the adoption of SW. In the final part of the study, the implications of the main findings are discussed.