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The purpose of this paper is to present some scenarios about a possible future evolution of the labour market in the knowledge economy.

The author used the literature to describe the historical evolution of the technology unemployment.

Digital technology does not directly generate unemployment, as the balance between jobs destroyed and created has historically always been positive. Indeed, technological unemployment in such a context can manifest itself in the form of frictional unemployment.

The study enriches the literature on the relationship between digital technologies and unemployment rate.

This paper seeks to connect changes in the structure of wages at the occupation level to measures of the task content of jobs. We first present a simple model where skills are used to produce tasks, and changes in task prices are the underlying source of change in occupational wages. Using Current Population Survey (CPS) wage data and task measures from the O*NET, we document large changes in both the within and between dimensions of occupational wages over time, and find that these changes are well explained by changes in task prices likely induced by technological change and offshoring.

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.

The authors illustrate that there are significant differences in the wage performance across companies in relation to the digital content of their production and training activities.

Using company-level data from three waves of the Continuing Vocational Training Survey (2005, 2010 and 2015), this paper provides an overview on European firms implementing training and the magnitude of their training effort.

The authors conduct a regression analysis documenting that a wage premium of 9% is associated with companies undertaking training and that an additional 8% is paid by firms arranging training for IT skills-intensive workers. The latter effect is pervasive across sectors and is not strictly related to industry exposure to the digital transformation.

The authors assess the wage effect of training, in relation to the digital content of firm production or job tasks, using a large set of European companies (112,000), from countries with different degree of specialisation and institutional setting. The analysis covers a significant period of time of the last wave of digitalisation (2005, 2010, 2015).

A prominent labour market feature in recent decades has been the increase in abstract and service jobs, while the demand for routine work has declined. This article examines whether the components of Type A behaviour predict workers' selection into non-routine abstract, non-routine service and routine jobs.

Building on the work by Barrick et al. (2013), this article first presents how the theory of purposeful work behaviour can be used to explain how individuals with different levels of Type A components sort into abstract, service and routine jobs. Then, using longitudinal data, it examines whether the components of Type A behaviour predict occupational sorting. Estimations were performed based on the linear regression method.

The results show that the Type A dimension “leadership” was associated with a higher level of abstract and service job tasks in occupation. High eagerness-energy and responsibility were also positively linked with occupation's level of abstract tasks. These results suggest that workers sort into jobs that allow them to pursue higher-order implicit goals.

Job market polarisation towards low-routine jobs has had a pervasive influence on the labour market during the past few decades. Based on high-quality data that combine prime working-age register information on occupational attainment with information about personality characteristics, the findings contribute to our knowledge of how personality characteristics contribute to occupational sorting in terms of this important job aspect.

This work analyses how the adoption of technological innovations correlates with workers' perceived levels of job insecurity, and what factors moderate such relationship.

The study makes use of the 2018 wave of the Participation, Labour, Unemployment Survey (PLUS) from Inapp. The richness of the survey and the representativeness of the underlying sample (including 13,837 employed workers) allow employing various empirical specifications where it is possible to control and moderate for many socio-demographic features of the worker, including her occupation and industry of employment, thereby accounting for various potential confounding factors.

The results of this ordered logit estimations show that workers' perception of job insecurity is affected by many subjective, firm-related and even macroeconomic factors. This study demonstrates that the adoption of technological innovations by companies is associated with lower levels of job insecurity perceived by their workers. In fact, the adoption of technological innovations by a company is perceived by surviving workers (those who remain in the same firm even after the introduction of such innovations) as a signal of the firm's health and its commitment to preserving the activity. Individual- and occupation-specific moderating factors play a limited role.

This study estimates how perceived job insecurity relates to the technological innovations adopted by the firms in which the interviewees are employed rather than analyzing their general concerns about job insecurity. In addition, this study identifies different types of innovations, such as product and process innovation, automation and other types of innovations.

This study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.

Our method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.

The study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.

Our study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.

The polarisation of employment is a specific structural change in the labour market when the share of high and low-skilled workers increases and, simultaneously, the share of middle-skilled workers decreases. The chapter analyses the effect of polarisation in Czechia and other Central European countries and describes how employment has changed from the perspective of skills regarding gender. The analysis is based on observing the changes in the share of high, middle and low-skilled workers evaluated on the basis of occupational classification over time. Results imply (with a few exceptions) polarisation of employment across all countries during the period between 1998 and 2021, even if we consider the distinction between males and females. Results confirm that employment polarisation has also become a prevalent phenomenon in Central European countries during the last two decades. Finally, this chapter also summarises the economic motivation for studying polarisation phenomenon.