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Existing research suggests that the competitive advantage provided by technological development depends to a large extent on the speed and coordination of the technology’s implementation, and on how adoptable the technological applications are considered. While accepting this argument, the authors consider the explanatory model to be inadequate. This study aims to contribute to the theoretical discussion by analysing institutionalised industrial relations and other organisation-level factors, which are important for workplace restructuring and societal change.

The analysis is based on a representative nation-wide work and working conditions survey (N = 4,100) from Finland, which includes a variety of themes, including practices, changes and well-being at work. Changes are understood as organisational changes, focusing on modern technologies such as robotisation and digitalisation.

The results indicate that occupational division at workplace (low-skilled vs high-skilled occupations) affects job insecurity and acceptance of technologies at work. The characteristics of workplaces, such as the employees’ participation and involvement in the development of the organisation, play a significant part in both the acceptance and the implementation and outcomes of the technological transformations in the workplace.

The research provides new and interesting insights into working life practices. Furthermore, it reveals how technology acceptance and employment perspectives relate to working conditions and lessons learned from past reforms.

The authors consider current theories such as technology acceptance model at the micro level and that way rationalise the need for this study. This study shows the importance of individual, organisational and wider contextual factors in technology acceptance.

This paper aims to examine how input from the digital restructuring of the workplace and productivity affects the risk of job loss and unemployment.

Relying on the concepts of technological unemployment and the productivity paradox as well as the theory of skills-biased technological change, the analysis incorporated micro-level individual determinants of job loss, macro-level economic determinants of input and the contribution from traditional (machinery and equipment) vs innovative (ICT) factors of production. The model has been also controlled for “traditional” indicators of “outsiderness” in the labour market. The Quality of Work Life Survey, which is a broad-based national interview survey produced by Statistics Finland, for 2018, the latest year available (N = 4,110) has been used in the analysis. Binomial logistic regression has been applied in order to estimate the effects of individual- and macro-level factors on the risk of job loss.

The results support arguments for the divergence between effects from labour- vs total-factor productivity on the risks of job loss, as well as the divergence between effects for temporary (layoff) vs permanent job loss (dismissal or unemployment). While the contribution from “traditional” factors of production to labour productivity potentially decreases the risk of permanent job loss, input from “innovative” factors of production on total-factor productivity potentially causes adverse effects (e.g. growing risks of permanent job loss).

The paper contributes to the theoretical discussion about technological unemployment and productivity by means of including two different concepts into a single econometric model, thus enabling examination of the research problem in an innovative way.