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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.

In this research, we explore the dynamics among measures of income inequality in the USA, male and female unemployment rates, and growth in government transfer using time series data.

This research adopts a macro-econometric approach to estimate a structural VAR model using time series data.

Our structural impulse responses found that growth in government transfer increases unemployment rates for both males and females. Female income inequality declines with increased government transfer. When the female income ratio rises, we observe that government transfer outlays fall over the forecast horizon. Variance decomposition finds that growth in government transfers is impacted by the male unemployment rate relatively more than the female unemployment rate. This research, therefore, suggests gender-specific government transfers to reduce income inequality. This, in effect, may reduce government transfer outlays over time.

This research, therefore, suggests gender-specific government transfers to reduce income inequality. This, in effect, may reduce government transfer outlays over time.

This research investigates the dynamics among income inequality, government transfer, and unemployment rates. There is a dearth of research articles that adopt a macro-econometric in this area.

This study assesses the probability of an OECD member country exhibiting high persistence in unemployment duration, considering income inequality, productivity, accumulation of human capital and labor income share in Gross Domestic Product (GDP) between the years 2013–2019.

To achieve the purpose of the study, a probabilistic analysis with panel data is employed, focusing on 20 OECD countries segmented into two groups: those with high persistence and low persistence in unemployment duration. Probit and Logit models are estimated, marginal changes are analyzed and the models are evaluated in terms of their classification accuracy. Finally, trends in probabilities over time are examined.

This paper exhibits that countries with higher human capital index, greater labor income share in GDP, and more relevant productivity for well-being reduce their probabilities of experiencing high persistence in unemployment duration. It is observed that Mexico (MEX), Greece (GRC), Italy (ITA), and Turkey (TUR) have elevated probabilities of experiencing high persistence in unemployment duration in the future, while Costa Rica (CRI), Estonia (EST), Slovakia (SVK), Czech Republic (CZE), Lithuania (LTU), Poland (POL), and Israel (ISR) show a marked downward trend in these probabilities. Lastly, countries like the United Kingdom (GBR), Denmark (DNK), Sweden (SWE), Norway (NOR), Netherlands (NLD), Germany (DEU), United States (USA), and Canada (CAN) present minimal risk of experiencing high persistence in unemployment duration in the future.

The measurement of the relationship between development outcomes and persistence in unemployment duration has been scarce. Generally, the literature has focused on the analysis of development and unemployment without delving into the duration of unemployment, let alone persistence in duration.

This paper provides a solid foundation for the formulation of policies aimed at promoting sustainable employment and inclusive economic growth.

Based on the findings of the study, two key development policies are proposed. Firstly, the implementation of investment programs in Human Capital to increase productivity is recommended. Resources should be directed towards initiatives that improve the necessary skills and competencies in the labor markets of OECD countries, especially in strategic economic sectors with higher production linkages. Additionally, incentivizing the application of active labor policies is proposed. This entails prioritizing policies aimed at increasing the labor income share in GDP through progressive fiscal reforms that strengthen social safety nets and ensure fair labor standards. Implementing employment programs targeted at vulnerable groups, such as long-term unemployed individuals, youth, female heads of households and marginalized communities, is also recommended to eliminate structural barriers to labor market participation and reduce disparities in unemployment persistence. Adopting these policies can help mitigate the risk of high unemployment duration persistence and foster sustainable and inclusive long-term economic growth.

This is the first study to analyze the probabilities of both developing and developed countries experiencing high persistence in unemployment duration. It specifically evaluates these probabilities over a period of time and also estimates potential outcomes if real investments were made to enhance their human capital, productivity and employability.

We enquire whether short-time work (STW) avoids firings as intended by policymakers and is associated with unintended side effects by subsidising some establishments and locking in some employees. Additionally, where it was feasible, establishments used working from home (WFH) to continue working without risking an increase in COVID-19 infections and allowing employed parents to care for children attending closed schools.

Using 21 waves of German high-frequency establishment panel data collected during the COVID-19 crisis, we investigate how STW and WFH are associated with hirings, firings, resignations and excess labour turnover (or churning).

Our results show the important influences of STW and working from home on employment dynamics during the pandemic. By means of STW, establishments are able to avoid an increase in involuntary layoffs and hiring decreases significantly. In contrast, WFH is associated with a rise in resignations, as can be expected from a theoretical perspective.

While most of the literature on STW and WFH is unrelated and remains descriptive, we consider them in conjunction and conduct panel data analyses. We apply data and methods that allow for the dynamic pattern of STW and working from home during the pandemic. Furthermore, our data include relevant establishment-level variables, such as the existence of a works council, employee qualifications, establishment size, the degree to which the establishment was affected by the COVID-19 crisis, industry affiliation and a wave indicator for the period the survey was conducted.

The aim of this paper is to empirically investigate whether social contacts can mediate the way in which current unemployment impacts future unemployment.

We use 2006–2017 data from the Household Income and Labour Dynamics in Australia (HILDA) survey and a dynamic random-effects model to describe the evolution of individual unemployment status over time.

Once controlled for the local context where individuals live and create friendships, we find that above-average social contacts reduce unemployment persistence. However, social contacts seem to be slightly less effective in deprived neighborhoods. These findings are consistent with the idea that individuals obtain information about job opportunities through a network of social contacts, and unemployment may lead to a decay of social capital, making it more difficult to find employment in future periods. Our results also show that neighborhood deprivation increases individual unemployment risk, while above-average neighborhood cohesion reduces the probability of unemployment in deprived neighborhoods.

Although many studies have been published on unemployment persistence, to the best of the author's knowledge, this is the first study quantifying the impact of social contacts on unemployment persistence. The study also offers fresh empirical evidence on the impact of neighborhood characteristics on unemployment risk.

This study explores job search dynamics among employed individuals. We focus on factors related to employees initiating their job searches and changing its intensity.

We conducted a qualitative study with 41 employed job seekers using semi-structured interviews.

Our analysis reveals six catalysts that initiate employee job searches and nine modulators that influence fluctuations in job search effort. We highlight the significant roles of social actors, resource dynamics, and personal, professional, and environmental factors in shaping employees’ job searches.

The diverse sample strengthens theory building but may not represent all employed job seekers. Future research would benefit from longitudinal designs.

This study underscores the influence of social actors on employee job search processes. Our findings offer valuable insights for policymakers and employers seeking to support employed job seekers and proactively manage voluntary turnover.

This research advances our understanding of employee job search beyond its traditional role in voluntary turnover. By integrating Conservation of Resources (COR) theory, we provide a framework for understanding employee job search initiation and modulation.

The implementation of BIM in the construction industry requires the coevolution of the various aspects of the BIM ecosystem. The human dimension is a very important dimension of the ecosystem necessary for BIM implementation. It is imperative to study this aspect of the BIM ecosystem both from the employer perspective and employee availability to provide insights for stakeholders (job seekers, employers, students, researchers, policymakers, higher education institutions, career advisors and curriculum developers) interested in the labour market dynamics.

To understand the BIM actor roles through the employer lens and the actual BIM actors in the construction industry, this study employed data mining of job adverts from LinkedIn and Mncjobs website. Content analysis was employed to gain insights into the data collected. Also, through a quantitative approach, the existing BIM actor roles were identified.

The study identified the employers' expectations of BIM actors; however, it is noted that the BIM actor recruitment space is still a loose one as recruiters put out open advertisements to get a large pool of applicants. From the data analysed, it is concluded that the BIM actor role is not an entirely new profession. However, it simply exists as construction industry professionals with BIM tool skills. Also, the professional development route is not well defined yet.

This study presents a realistic angle to BIM actor roles hence enhancing BIM implementation from the human perspective. The findings present an insight into the preferred against the actual.

This study aims to analyze the relationship between global value chain (GVC) participation and poverty levels. Additionally, it investigates the impact of education levels, specifically analyzing literacy rates and tertiary education rates, on the correlation between GVC participation and poverty in Organization for Economic Co-operation and Development (OECD) and Association of Southeast Asian Nations (ASEAN) countries.

Fixed effect and random effect models will be employed to quantify the relationships between the dependent and independent variables. The Hausman test is applied to determine the appropriate estimator between fixed and random effects. Also, in the model, time-fixed effect or two-way fixed effect has been used to control for unobserved heterogeneity both across entities and over time in panel data analysis.

The findings demonstrate that engagement in GVCs presents a promising avenue for stimulating development, advancing income per capita growth and facilitating job creation. Notably, the results illuminate that the poverty-alleviating impacts of GVC participation are most conspicuous in nations boasting elevated levels of educational attainment among their populace.

This research aims to promote a better understanding of the connection between GVC participation and the level of poverty, with GVC participation decomposed into forward participation and backward participation.

This study employs the social ecology model to comprehensively explore the complex challenges young Black men face in South Africa and aims to highlight the importance of collaboration in addressing these multifaceted issues.

A multidisciplinary approach combines insights from sociology, education and the health literature with regard to government reports and academic data, and provides a holistic analysis of challenges faced by young Black men. Furthermore, it emphasises formal and informal learning, social and environmental influences and health disparities.

Young Black men in South Africa encounter complex challenges throughout their developmental journey, including limited family support, educational barriers, financial constraints, societal expectations and health disparities. Therefore, collaboration among stakeholders is essential for creating an equitable and inclusive environment that supports their development.

This research provides a comprehensive understanding of the challenges faced by young Black men in South Africa by emphasising the interconnectedness of informal education, economic empowerment and healthcare. Future research should focus on longitudinal studies, cultural influences and international comparisons, informing evidence-based interventions for a more equitable society.

This study aims to examine the effect of marketing agility of startup companies on their new product creativity and new product performance while examining the moderating role of technological turbulence.

Data were collected from 319 South Korean startups and empirically analyzed using structural equations modeling technique.

First, marketing agility is a potent catalyst that positively influences the novelty and meaningfulness of new products, thereby enhancing new product creativity. Second, marketing agility contributes significantly to new product performance across multiple dimensions, including market, financial, and customer performances. Third, this study underscores the pivotal role of new product creativity, with both novelty and meaningfulness proving to be key drivers of improved new product performance. Technological turbulence is revealed as a moderating force, amplifying the positive relationship between new product novelty and performance. However, while it substantiates some moderating effects, the study does not find significant support for the role of technological turbulence in moderating the relationships among new product meaningfulness, marketing agility, and new product performance.

To the best of our knowledge, this study is the first to analyze the effect of startups’ marketing agility on new product creativity and performance considering the moderating effect of technological turbulence, especially in the South Korean context. This study offers practical insights emphasizing the indispensability of marketing agility for startups operating in rapidly evolving markets. Additionally, it advocates a strategic emphasis on novelty in high-tech turbulence scenarios to bolster new product performance.