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The purpose of this paper is to understand the impending relationship between the impact of the US–China trade war on Taiwanese firms' spending on R&D and their offshore investment in technologically advanced countries (TAC), the authors examined if changes in these firms' R&D ratios and the growing presence of skilled workers in Taiwan's labour market during the trade war have affected their offshore investments in TAC.

Using a model built on pooled cross-sectional time-series data from 2012–2019, the authors examined whether a change in R&D ratios of domestic firms in Taiwan and the growing presence of skilled workers in Taiwan's labour market have affected the offshore investment by these firms during the trade war. Using data from the Manpower Utilisation Survey, the authors applied differences–in–differences–in–differences and differences–in–differences–in–differences–in–differences estimation methods and found that the trade war indeed gave a boost to Taiwan's job market, particularly for skilled workers.

From the estimation results, the authors noticed a rise in employment opportunities alongside a decline in the earnings of skilled workers in industries where more firms have spent on R&D as well as invested in offshore operations. However, firms in Taiwan that had not heavily spent on R&D from industries where investment in foreign operations was otherwise high have also attracted skilled workers during the trade war.

An in-depth analysis of the impact of the trade war on domestic firms' spending on R&D and their investment in offshore operations in TAC should be helpful to policymakers interested in understanding the effects of the trade war and subsequent changes in firms' spending on R&D on labour market outcomes. If changes in the R&D ratios and a steady supply of skilled workers influenced the outflow of Foreign Direct Investment (FDI) to TAC, this insight could be helpful for those devising policies and measures to curb the impact of the trade war on domestic spending on R&D.

The study findings not only provide broad lessons to policymakers in Taiwan, but the country case study can guide growing economies that are equally careful while perceiving trade war as a significant deterrent to domestic R&D spending and the outflow of FDI.

This study aims to examine the impact of China's “Manufacturing and Internet Integration Development Pilot Demonstration Project” (MIP) policy on the digital transformation (DT) and labor structure optimization (LSU) of manufacturing enterprises, reveal the relationship between DT and LSU at the micro level and investigate the mechanism between them.

This study employs MIP as a quasi-natural experiment and develops a time-varying difference-in-difference (DID) model based on a sample of 2,445 Chinese A-share listed manufacturing enterprises in the Shanghai and Shenzhen markets from 2013 to 2021.

The implementation of MIP significantly increases DT by 0.4366 and optimizes LSU by 0.0507. By enhancing the two mediated variables of organizational learning inputs (SI) and employees' personal digital cognition (PDC), DT can optimize the LSU of pilot enterprises by 0.035 and 0.034, according to the results of the mechanism analysis. The study also reveals that the impact of MIP on LSU is highly heterogeneous. With effects of 0.0691 and 0.0632, the optimization effect is more pronounced in state-owned firms and firms with low ownership concentration, respectively.

This study demonstrates the dual effects of the MIP pilot on DT and LSU. In addition, this study pioneers research on the significance of optimizing the labor structure through SI and PDC on the basis of DT, which provides an empirical foundation for the Chinese Government to expand the scope of MIP pilots and revise policy content, as well as for manufacturing enterprises to upgrade the labor structure.

The purpose of this paper is to test the impact of selected characteristics of jobseekers on employers’ decisions regarding potential hires (direct and probabilistic signals). The main focus of the study is to test the impact of jobseekers’ participation in selected active labour market programmes on employers’ hiring decisions for three positions: unskilled worker, skilled worker and administrative employee. Other characteristics tested include age, gender, presence of children in the household, state of health, experience of short- and long-term unemployment and indebtedness.

This study analyses data from a representative survey of employers with five or more employees in the Czech Republic. The survey was conducted in December 2020 using stratified random sampling, combining online questionnaires and personal interviews. The study includes 1,040 employers and uses the factorial survey experiment (FSE) design.

The results of the FSE suggest that the perceived positive impact of completing one of the activation programmes depends on the position for which the candidate is being recruited. While for the unskilled job category, the completion of any of the tested schemes (training, subsidised jobs or public works) had a positive effect; for the skilled job category, only the training and subsidised jobs schemes had a positive effect; and for the administrative job category, public works programme even had a negative effect.

A somewhat limiting factor in the context of this study seems to be the definitions of the positions tested (unskilled and skilled workers and administrative staff). The decision-making of the respondents was somewhat restricted by such broadly defined categories. Typically, studies with FSE designs have a focus on a specific sector of the economy, which allows for a better definition of the positions or jobs under test. The relationship between position and the impact of individual characteristics is clearly a matter for further research.

The results of the study confirm that completion of the activation programme, as well as other candidate characteristics, constitute differentiating signals for employers that influence their hiring decisions. At the same time, there is evidence that the training programme and the subsidised jobs programme are effective in terms of increasing participants’ chances of employment.

The demand side should be included in the evaluation of activation policies. The design of the FSE provides an appropriate way to test the impact of activation measures on the decision-making of employers.

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.

A new round of technological revolution is impacting various aspects of society. However, the importance of technology adoption in fostering firm innovation is underexplored. Therefore, this study aims to investigate whether robot adoption affects technological innovation and how human capital plays a role in this relationship in the era of circular economy.

Based on the robot adoption data from the International Federation of Robotics (IFR) and panel data of China's listed manufacturing firms from 2011 to 2020, this study uses regression models to test the impact of industrial robots on firm innovation and the mediating role of human capital.

The results demonstrate that the adoption of industrial robots can significantly promote high-quality innovation. Specifically, a one-unit increase in the number of robots per 100 employees is associated with a 13.52% increase in the number of invention patent applications in the following year. The mechanism tests show that industrial robots drive firm innovation by accumulating more highly educated workers and allocating more workers to R&D jobs. The findings are more significant for firms in industries with low market concentration, in labor-intensive industries and in regions with a shortage of high-end talent.

Due to data limitations, the sample of this study is limited to listed manufacturing firms, so the impact of industrial robots on promoting innovation may be underestimated. In addition, this study cannot observe the dynamic process of human capital management by firms after adopting robots.

The Chinese government should continue to promote the intelligent upgrading of the manufacturing industry and facilitate the promotion of robots in innovation. This implication can also be applied to developing countries that hope to learn from China's experience. In addition, this study emphasizes the role of human capital in the innovation-promoting process of robots. This highlights the importance of firms to strengthen employee education and training.

The adoption of industrial robots has profoundly influenced the production and lifestyle of human society. This study finds that the adoption of robots contributes to firm innovation, which helps people gain a deeper understanding of the positive impacts brought about by industrial intelligence.

By exploring the impact of industrial robots on firm innovation, this study offers crucial evidence at the firm level to comprehend the economic implications of robot adoption based on circular economy and human perspectives. Moreover, this study reveals that human capital is an important factor in how industrial robots affect firm innovation, providing an important complement to previous studies.

Small and medium-sized contractors are critical to micro and macroeconomic performance. These contractors in South Africa have long been confronted with the problem of business failure because of a plethora of factors, including poor productivity. The purpose of this study is to investigate salient issues undermining the productivity of small and medium-sized contractors in South Africa. This study proposes alternative possibilities to engender productivity improvement.

Qualitative data were collected using semi-structured interviews with 15 contractors in Gauteng Province, South Africa. The research data were analysed using content and causal layered analyses.

Challenges to contractors’ productivity were associated with inadequately skilled workers, management competence and political factors. Skills development, construction business and political factors were dominant stakeholders’ perceptions. Metaphors for construction labour productivity are presented and reconstructed as alternative directions for productivity improvement.

Contractors lose a substantial amount of South African Rand to poor productivity. Alternative directions provided in this study can be leveraged to increase profitability in construction organizations, enhance the social well-being of South Africans and ultimately improve the contribution of contractors to the South African economy.

The causal layered analysis (CLA) applied in this study is novel to construction labour productivity research. The four connected layers of CLA, which make a greater depth of inquiry possible, were explored to investigate labour productivity in construction organizations.

At the beginning of the 21st century, a new class of information workers, the “information have-less” has risen. This class of workers alleviates the influence of information and communication technologies (ICTs) revolution on poverty and unemployment. The purpose of this study is to investigate the presence of this class of workers in Egypt and assess the size and potential growth of this category of workers.

The study clarifies the conceptual framework of the new division of labor, in the information age. The Central Agency for Public Mobilization and Statistics, American Chamber of Commerce in Egypt, Ministry of Communications and Information Technology and Information and Decision Support Center websites provided secondary data for this study. These data are used to assess the size of “the information have less” in Egypt.

The division of work and class, in the 21st century, depends on the level of skills possessed to work with ICTs. So, class and labor nowadays could be divided into self-programmable labor (Innovators). Information have-less labor class, adding value to the economy by learning skills and presenting repetitive work. Generic labor class, who cannot work with ICTs, and work in jobs, that do not need computers or other ICTs. The study has shown that the “information have-less” labor class is present in Egypt since the beginning of the 21st century, in all its categories; entrepreneurism, the service sector and the manufacturing sector. There are approximately 50% of this labor class in the service sector and only 13% of the information have-less works in manufacturing sector despite the great opportunities that Egypt has to expand manufacturing to absorb more employment. The inclusion of information technology (IT), in all domains, has not decreased employment in Western countries but has reallocated information have-less employment toward the service sector, and there would probably be the same effect in Egypt.

The study highlights the need for Egyptian policymakers to encourage the manufacturing and service sectors to provide huge working opportunities. The Egyptian government has to change the educational policies, at all stages, to include digital learning skills so IT can be incorporated in a wide range of economic activities. Further research includes: conducting a survey to measure the contribution of the entrepreneurial part of the information have-less employment in Egypt. In addition, a model may be developed, by the researcher to examine the reallocation of employees in Egypt.

Studying employment, in Egypt, using the conceptual framework of the information age is rarely being done.

Studies highlight that poor labour supervision and inadequate labour training facilities are the primary factors that result in labour skill shortages and productivity-related challenges among construction firms. This study aims to assess the construction supervisors’ abilities in providing work-based training elements and evaluating labour skills in construction.

A construction supervisory training programme was newly designed with a set of labour training exercises using comprehensive approaches. A total of 64 construction supervisors were trained to deliver the labour training components for more than 250 labourers working on 23 construction projects in Sri Lanka. The supervisors’ competencies were assessed using a detailed marking guide developed through expert discussions and literature reviews.

The results show the detailed cross-section of a wide range of competencies of the construction supervisors in providing labour training elements with the levels of standards/descriptions. The generalisability of the study applications and the reliability of the results were ensured using statistical tests and expert reviews. The findings further describe the impacts of the well-improved competencies of construction supervisors on labour working patterns and work outputs.

Though the study findings were limited to the Sri Lankan construction sector, the study applications can have a considerable impact on the current/future practices of the construction sector in developing countries as well as other developing industries.

The study outcomes may contribute to a rapid increase in the number of construction supervisors becoming certified assessors of National Vocational Qualifications up to certain levels. This paper describes the further extensive implications and future scopes of the study elaborately.

The study adds new characteristics and values to construction supervision practices that can be remarkable in achieving higher levels of performance and productivity in labour operations. Importantly, the study contributes to adorning the job role of construction supervisors with the title of “labour training expert”.

This paper aims to develop a vision for the future identifying how digital nomadism affects the labor markets in the tourism industry.

The qualitative research method was used. The research data were collected using a semistructured interview form developed by the researcher. The sample consists of twenty people working in the tourism industry as tour guides, travel agency owners, accommodation sector employees and professional managers. The content analysis method was used to analyze the data.

It was found that employees in the tourism industry are familiar with digital nomadism, interact with employees working as digital nomads and may prefer the digital nomad way of working, while employees in the accommodation sector cannot work as digital nomads due to the nature of their work. It is shown that digital nomadism can be applied to tour guides and travel agency owners.

The data was collected from employees of the accommodation sector, travel agencies, tour guides and employees of the Turkish tourism labor market. It is recommended that the tourism labor markets adapt to the digitalized world and adjust their working models in this context.

This is one of the first studies on the impact of digital nomadism on the tourism labor markets.

The present study aims to investigate the reasons for the gap between academic education and the required skills of the labor market in Iran.

For this purpose, the authors adopted a thematic analysis method. The participants in the study were connoisseurs from universities and research institutes in Iran, who were selected with purposeful sampling methods of snowball type. To collect the data, the authors used a semi-structured interview and performed a thematic analysis for data analysis.

The findings showed that the views and perceptions of the connoisseurs participating in the study about the reasons for the gap between academic education and the skills required in the labor market in Iran can be classified into four main themes including lack of attention to labor market needs in the academic curricula, lack of attention to practical and entrepreneurial skills in the academic curricula, the weak link between universities and industry and society, and shortage of academic resources and equipment in some academic disciplines.

The present study had three implications. First, the human capital theory, the social closure theory, the positional conflict theory and the labor market segmentation theory are more compatible with the labor market of Iranian graduates, compared to other theories of the labor market. Second, the lack of coordination between academic education and the required skills in the labor market has weakened the Iranian economy. Third, the absence of practical and entrepreneurial skills in academic graduates has led to increased unemployment in Iranian society.