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This research considers the question of whether unemployment insurance benefit and labour-market activation measures induce the likelihood of re-employment and whether this effect differs for natives and immigrants.

Statistical processing was carried out on the European Union Statistics on Income and Living Conditions cross-sectional data for Finland for the period 2004 to 2016. Propensity score matching analysis was undertaken to investigate whether a treatment effect (unemployment insurance benefit) was a predictor of success in increasing re-employment rates, when controlling for participation in labour-market policy measures, subsidized employment and personal background characteristics.

We find that the probability of re-employment for recipients of unemployment benefits is half that of non-recipients of benefits. Due to the influence of subsidized employment, subsequent employment income decreases for recipients of unemployment benefits and especially for immigrants. Finally, we find that due to the influence of subsidized employment, time spent as a full-time employee decreases for recipients of unemployment benefits and especially for immigrants.

Although our results indicate that benefit determination has a marked impact on re-employment probabilities, unobserved variables turn to play a significant role in selection of labour-market activation measures. In this respect, we find the treatment assignment to activation policy measures depends on influence of unobserved variables and this effect is more important for the re-employment rates of natives than it is for immigrants.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2019-0668.

The purpose of this paper is to outline the study to determine whether the dual earner model better offsets the actual risk of unemployment compared to other household models.

The authors linked the partner effect (household type) with macroeconomic institutional settings, such as employment protection, the active labour market policy, economic growth rate and globalisation, to study how these micro- and macro-level factors influence the unemployment risk of individuals.

Using European Labour Force Survey (EU-LFS) microdata for Finland from 2005 to 2013 and a multilevel modelling technique, the authors found that the partner effect is an important regulator of unemployment risks, but the effect is modified by institutional factors. Dual earners and breadwinners experience a less significant effect from employment protection legislation regulation and other external factors on the increase or decrease in unemployment risk compared to singles. The authors also found that unemployed singles are more exposed and vulnerable to fluctuations caused by economic events.

In this way, this paper contributes to the sociological theory of labour markets and a better understanding of how different household types buffer and mediate the risks of unemployment. The authors used the EU-LFS and novel multilevel analysis statistical solutions to determine the impact of macro- and micro-level factors. The case of Finland may also be of broader interest to researchers and policy-makers because of the long and strong tradition of the dual earner employment pattern and strong macro-economic fluctuations.

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.