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The study investigates the influence of ChatGPT on the labor market dynamics, aiming to provide a structured understanding of the changes induced by generative AI technologies.

An analysis of existing literature serves as the foundation for understanding the impact, while the supply and demand model helps assess the effects of ChatGPT. A text-mining approach is utilized to analyze the International Standard Occupation Classification, identifying occupations most susceptible to disruption by ChatGPT.

The study reveals that 32.8% of occupations could be fully impacted by ChatGPT, while 36.5% might experience a partial impact and 30.7% are likely to remain unaffected.

While this study offers insights into the potential influence of ChatGPT and other generative AI services on the labor market, it is essential to note that these findings represent potential implications rather than realized labor market effects. Further research is needed to track actual changes in employment patterns and job market dynamics where these AI services are widely adopted.

This paper contributes to the field by systematically categorizing the level of impact on different occupations, providing a nuanced perspective on the short- and long-term implications of ChatGPT and similar generative AI services on the labor market.

The purpose of this study is to investigate the evolving perceptions and human resource (HR) responses of owners and HR managers of Chinese small and medium-sized enterprises (SMEs) towards local labour markets in the context of the impact of the coronavirus disease 2019 (COVID-19) pandemic.

This study adopts a two-stage longitudinal qualitative approach involving 52 interviews with owners and HR managers of Chinese SMEs in the pre- and post-pandemic time periods.

The findings reveal a shift from the perceptions of a general labour shortage to perceptions of specialised talent shortages and increasing geographical disparities in local labour markets. They further reveal that SMEs are increasingly likely to adopt efficiency-oriented, flexibility-enhancing HR practices in the face of high uncertainty.

The findings provide insights into the nature of the constraints of SMEs' sustainable development that need to be addressed by policymakers, SME owners and HR managers when they devise and implement policies relating to structure optimisation, labour market integration and mobility enhancement.

In contrast to extant literature that has examined the labour market at the national level, this study explores the views of SMEs (the demand side) by taking a localised perspective on how SMEs have responded to change through their HR practices.

The Covid-19 pandemic appears to have engendered heterogeneous effects on individuals’ labour market prospects. This paper focuses on two possible sources of a heterogeneous exposition to labour market risks associated with the pandemic outbreak: the routine task content of the job and the teleworkability. To evaluate whether these dimensions played a crucial role in amplifying employment and wage gaps among workers, we focus on the case of Italy, the first EU country hit by Covid-19.

Investigating the actual effect of the pandemic on workers employed in jobs with a different degree of teleworkability and routinization, using real microdata, is currently unfeasible. This is because longitudinal datasets collecting annual earnings and the detailed information about occupations needed to capture a job’s routine task content and teleworkability are not presently available. To simulate changes in the wage distribution for the year 2020, we have employed a static microsimulation model. This model is built on data from the Statistics on Income and Living Conditions (IT-SILC) survey, which has been enriched with administrative data and aligned with monthly observed labour market dynamics by industries and regions.

We measure the degree of job teleworkability and routinization with the teleworkability index (TWA) built by Sostero et al. (2020) and the routine-task-intensity index (RTI) developed by Cirillo et al. (2021), respectively. We find that RTI and TWA are negatively and positively associated with wages, respectively, and they are correlated with higher (respectively lower) risks of a large labour income drop due to the pandemic. Our evidence suggests that labour market risks related to the pandemic – and the associated new types of earnings inequality that may derive – are shaped by various factors (including TWA and RTI) instead of by a single dimension. However, differences in income drop risks for workers in jobs with varying degrees of teleworkability and routinization largely reduce when income support measures are considered, thus suggesting that the redistributive effect of the emergency measures implemented by the Italian government was rather effective.

No studies have so far investigated the effect of the pandemic on workers employed in jobs with a different degree of routinization and teleworkability in Italy. We thus investigate whether income drop risks in Italy in 2020 – before and after income support measures – differed among workers whose jobs are characterized by a different degree of RTI and TWA.

While the effect of the minimum wage (MW) on employment has been widely studied, less is known about its impact on hirings and separations. Whereas the adverse effects of MW on hiring are quite familiar, results of studies indicating reductions in separations are less expected. This study aims to bridge the gap between theory and practice by performing a meta-analysis, which allows for understanding the real effect of MW on employment's two components: hirings and separations.

Since mixed results cloud understanding of the issue, a meta-regression analysis was conducted. This technique permits understanding the effect of MW on labor market transitions and offers additional explanations for controversial results.

Despite the evidence that MW increasing the turnover and reducing permanence could negatively affect employment, findings from meta-regression analysis pointed out that increases in MW reduce hirings but also separations offsetting the negative effect on employment. Overall, the results imply that the standard finding that MW changes have little or no impact on employment rates reflects offsetting reductions in hiring and separations. Evidence of negative publication bias is also found.

The results emphasize the importance of looking beyond employment rates to understand the impacts of MW. Overall, the evidence implies that the standard finding that MW changes have little or no impact on employment rates reflects offsetting reductions in hiring and layoffs. In addition, the results suggest that MW tends to have a much larger impact on employment flows than on employment levels. This finding has to be considered by policymakers when they make decisions about increasing the MW. These analyses assist in clarifying debates about the effects of MW on the labor market in the changing economic environment and conduct a labor policy in the right direction.

The meta-regression analysis (MRA) conducted in this study emphasizes the importance of looking beyond employment rates to understand the impacts of MW (Brochu and Green, 2013). Overall, the evidence implies that the standard finding that MW changes have little or no impact on employment rates reflects offsetting reductions in hiring and layoffs. Therefore, the evidence from the performed MRA is consistent with those previous meta-analysis studies that found little or no evidence about MW adversely affecting employment and, at the same time, provide additional explanation for these findings. In addition, the results suggest that MW tends to have a much larger impact on employment flows than on employment levels (Dube et al., 2016).

Even though hirings are reduced due to MW, this evidence could not necessarily imply a negative effect of MW on the labor market since job searching or matching is improved. Additionally, the increases in MW could improve the quality of the job and the job attachment, which are consistent with a recruitment-retention model (Dube et al., 2007). The evidence from this MRA, which is consistent with little or no impact of MW on employment, also could imply that although the MW is set relatively high to balance the supply and demand of labor, their level is close to optimal. Setting the right level is also associated with compliance with MW. This issue deserves attention since any adverse employment effects of MW could be strengthened by incomplete coverage. The effectiveness of the entire process of developing, putting into practice and enforcing MW rules hinges on compliance.

As prior meta-regression analysis did not have the same objective, the results of this article move current research forward. Based on the analysis, future research lines are delineated, and some public policy implications are assessed.

An increasing number of international immigrant workers enter the EU labour market to fill the gap in many key economic sectors. Labour migration often implies a process of family adaptation and, in some cases, a breakdown in the community structure and networks. This study aims to provide insights into the dynamics of transnational families, focusing on changes in the redefinition of roles within family members and children care arrangements.

The study was based on the analysis of 12 biographical interviews conducted using semi-structured interviews between November 2018 and December 2019 among Romanian women who worked as caregivers in families in an Italian metropolitan city and the surrounding urban area.

Despite the economic dimension being essential, psychological well-being increasingly burdens workers’ migratory experience and that of their family members. Findings suggest including employers and children among the actively involved actors of the family decision-making process; working and contractual conditions as factors that significantly impact the opportunities and capability of workers to provide and receive care, mainly if the latter are employed in the informal market.

The study makes it possible to highlight that the dynamics in decision-making processes in transnational families change in the different phases of the migration project and involve numerous actors. These processes are not always rational and are strongly influenced by the labour market structure in which migrants are employed.

Purpose: This chapter addresses the skills shortages in Kosovo’s labour market, emphasising the service sector. The labour market economy is very dynamic, and Kosovo, with the youngest population in Europe, also has the highest unemployment level among youths. Therefore, we aim to analyse the mismatches of the skills demand in the labour market.

Methodology: The scientific methods used in this chapter are quantitative methods applying analytical and critical approaches based on economic theory. In this chapter, we analysed secondary data from Labour Force Surveys (LFS) and official reports such as the World Bank and UNDP. We have also conducted primary research with the employees of SMEs in the service sector, with specifically related questionnaires for descriptive issues.

Findings: The logit model used in this research has shown goodness of fit and yielded significant results. Based on the empirical findings, we have found a need for some main soft skills such as communication skills, language skills, ICT skills, and additional training to help gain employability skills. These findings suggest that there is a need for more skills in the service sector, significantly impacting the employees’ job performance and the job seeker’s level of employability.

Significance: Noticeably, countries that are still in the transition process face inequalities in the labour market and have a very high level of unemployment. The findings can be used in analysing demand-side management of the labour market and mismatching of skills in transition economies by policy makers.

The growing use of internet communication technology has led to increased economic growth across the world, and this chapter seeks to assess the case of Czechia. The study also examines the changing employment distribution in the labour market with the growing influence of information and communication technology (ICT). The multiple indicators and multiple causes model as well as changes in employment or earnings shares of occupations are used for the analysis. The findings show that increased use of ICT contributes to growth in GDP and employment. It also shows that ICT has contributed to rising labour and factor productivity through increased innovation. There is also increased demand for highly educated labour leading to growth in employment in high skill occupations, while the share of low and middle skill occupations declines. The situation, however, does not indicate job polarisation in the labour market and total employment is still increasing. The study also finds that investment and use of ICT has led to progressive development in the human development index of the Czech Republic and a decline in the gender inequality index.

The study maps workplace stakeholders’ perceptions of living wage (LW) impacts in New Zealand. Empirical findings inform an inaugural model of LW impacts and contingent factors at individual, organisation, sector/industry and national levels.

Data from a national employee survey, semi-structured interviews with business sector representatives, and staff in two LW organisation cases were subjected to thematic content analysis.

Informants emphasised anticipated LW impacts amid complex workplace and regulatory dynamics. Employers/managers stressed its cost effects. However, employees, human resource (HR) advocates and other LW proponents highlighted employee “investment” impacts that improve worker productivity and societal circumstances.

This study highlights the need for further context-sensitive LW analysis. An initial model of LW impacts provides a framework for comparative and longitudinal work in other national contexts.

The proposed model categorises perceived LW effects and can inform policy development. Findings also stress a need for cross-agency initiatives to address LW concerns, including a key role for HR.

The findings highlight perceptions of a LW impacting within and beyond the workplace. Whilst higher-quality management is seen to encourage better-informed decisions about “going living wage”, a LW's positive socio-economic impacts require multi-lateral initiatives, suggesting that those initiatives are is part of wider obligations for policy makers to encourage decent living standards.

This study provides a much-needed and inaugural focus on the intertwined workplace and wider impacts of a LW, extending extant econometric analyses. The paper also synthesizes different data sources to develop an inaugural, context-sensitive model of perceived LW effects.

This paper aims to identify the disproportionate impacts of the COVID-19 pandemic on labor markets.

The authors conduct a large-scale survey on 16,000 firms from 82 industries in Ho Chi Minh City, Vietnam, and analyze the data set by using different machine-learning methods.

First, job loss and reduction in state-owned enterprises have been significantly larger than in other types of organizations. Second, employees of foreign direct investment enterprises suffer a significantly lower labor income than those of other groups. Third, the adverse effects of the COVID-19 pandemic on the labor market are heterogeneous across industries and geographies. Finally, firms with high revenue in 2019 are more likely to adopt preventive measures, including the reduction of labor forces. The authors also find a significant correlation between firms' revenue and labor reduction as traditional econometrics and machine-learning techniques suggest.

This study has two main policy implications. First, although government support through taxes has been provided, the authors highlight evidence that there may be some additional benefit from targeting firms that have characteristics associated with layoffs or other negative labor responses. Second, the authors provide information that shows which firm characteristics are associated with particular labor market responses such as layoffs, which may help target stimulus packages. Although the COVID-19 pandemic affects most industries and occupations, heterogeneous firm responses suggest that there could be several varieties of targeted policies-targeting firms that are likely to reduce labor forces or firms likely to face reduced revenue. In this paper, the authors outline several industries and firm characteristics which appear to more directly be reducing employee counts or having negative labor responses which may lead to more cost–effect stimulus.

On the basis of labor economics theories, this study examines how adjustment in human capital accounts for labor cost stickiness.

This study makes use of employee education level as a measure of the quality of human capital and relies on data from Chinese public firms to conduct the empirical test. This study focuses on two important components of labor cost changes: one corresponding to the adjustment in the number of employees (capacity adjustment) and another corresponding to the adjustment in the mix of employee education levels (quality adjustment).

This study reveals that labor cost changes driven by the adjustment of employee education level are sticky. This stickiness cannot be explained by the standard adjustment cost theory. This further shows that firms that actively adjust their employee quality during downturns experience improved future performance. The findings are robust to alternative measures and specifications.

This study provides new evidence for and insights into the cost behavior literature. Previous studies treat input resources in a homogenous way and focus on the effect of capacity adjustment. This study considers the heterogeneity of resources and examines three dimensions of salary cost adjustment: capacity, structure, and unit cost. In line with the economic theory of sticky costs proposed by Banker et al. (2013a), the study’s evidence sheds light on the additional underlying economic mechanisms driving cost stickiness behavior. Specifically, managers asymmetrically adjust both employee structure and average salaries, in addition to employee number. This study also adds to the existing knowledge of the consequences of managers' actions regarding cost behavior.