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This study aims to investigate the effect of the tourism sector on employment in 13 Mediterranean countries. In addition, the impact of economic growth and inflation rate, which are included in the analysis as control variables, on the employment rate are investigated.

For this study, data from 1995 to 2018 and the ratio of the employed population, the number of international tourist arrivals, the annual growth rate of real gross domestic product (GDP) and the annual percentage change in the Consumer Price Index (CPI) were used. First, the authors investigated the relationship between variables using the Autoregressive Distributed Lag (ARDL) Bounds Test with Sharp and Smooth Breaks. Then, after determining the significant cointegration relationship, the long-term and short-term coefficients were also estimated.

The results show a cointegration relationship for Cyprus, Greece, Israel, Malta and Tunisia. Tourism demand has a positive effect on all these countries and economic growth positively affects the employment rate only in Greece, Israel and Tunisia. Besides, the inflation rate has a negative effect in Israel and Tunisia and a positive effect in Malta. Overall, the authors' results provide important policy suggestions, such as the training of the employees in the tourism sector should be improved to keep up with the requirements of the times.

The impact of the tourism sector on total employment varies from country to country. In particular, the employment creation policies of the sector need to be changed by taking technological changes into consideration.

Since tourism is a labor-intensive sector, tourism's impact on employment is an important research topic. However, whether this effect applies to all countries is debatable. Furthermore, the development of technology can also reduce employment in labor-intensive sectors. Therefore, this research can be regarded as important as this research addresses such a critical current issue and suggests a novel econometric method such as the ARDL Bounds Test with Sharp and Smooth Breaks.

This study aims to empirically analyze the impact of technological innovation on the quantity and quality of employment in the hospitality industry.

Using the data of 30 provinces in China from 2010 to 2020, this paper makes an empirical analysis through the fixed effect model.

The results show that process innovation has a significant positive impact on employment quantity, while product innovation has a significant negative impact on employment quantity. The creative effect of process innovation and the substitution effect of product innovation offset each other, so in the long run, the impact of technological innovation on employment quantity is not significant. However, technological innovation has significantly improved the employment quality of the hospitality industry.

Because technological innovation has replaced part of the labor force, hospitality could guide the labor force in a positive direction. To promote innovation and retain talents, hotels should train employees’ digital thinking and attract high-skilled talents.

This research is unique in using process innovation and product innovation as the main measurement indicators of technological innovation, unlike previous studies that often relied on technological progress to conclude.

A lack of sufficient gainful employment opportunities in developing countries means that those at the bottom of the income ladder resort to self-employment for survival. While self-employment equalises inequality by providing earning opportunities to such individuals due to the ease of entry, it also creates a competitive environment among the self-employed, consequently widening inequality. In light of this, the study aims to determine the optimal level at which self-employment narrows inequality.

Five-yearly average data from 72 developing countries covering 2000–2019 is used. Inequality measures include Gini, and self-employment includes total, male and female participation levels. The empirical analysis is based on the dynamic two-step system Generalized Method of Moments (GMM) estimation approach, two-stage instrumental variables (2 SLS IV) approach and Sasabuchi (1980) and Lind and Mehlum (2010) test. Several robustness checks are used to validate the findings.

Prima facie, the study's findings suggest that self-employment equalises inequality in developing countries. The income-equalising effect can be seen, however, when the total, male and female self-employment levels are below the optimal of 54.22% of total employment, 52.50% of male employment and 54.19% of female employment, respectively. Inequality widens when self-employment exceeds these optimal levels. Further, the income-narrowing effect of self-employment is larger than its income-widening effect. When self-employment is below its optimal level, it reduces inequality 80 times more effectively than when it widens above the optimal levels. The corresponding figures for male and female self-employment are 90 and 52, respectively. Second, the income-equalising effects of self-employment are gender-specific.

Developing countries striving to achieve SDG 10 should limit self-employment to the above-mentioned levels. To this end, an inclusive approach to reducing inequality requires these countries to use selective and targeted policy interventions to create gainful employment opportunities for those above the identified optimal levels and eventually assist them in utilising these opportunities.

To the best of the author’s knowledge, this is the first study to determine the optimal levels at which self-employment equalises income in developing countries. As such, it makes novel contributions to both labour and development economics.

The main purpose of this study is to investigate the symmetric and asymmetric effects of exchange rate uncertainty on employment in South Africa’s manufacturing sector over the period 1985Q1–2019Q2.

Jorda’s (2005) local projection method is employed and following Koop et al. (1996); generalized impulse response functions are generated to see the effect of exchange rate uncertainty on employment in South Africa’s manufacturing sector.

The results show that exchange rate uncertainty affects negatively and significantly employment in South Africa’s manufacturing sector. Employment also responds negatively and significantly to export shock. Inflation and output shocks, however, positively and significantly affect employment on impact. Asymmetric responses of employment to exchange rate uncertainty are also found in this study. While high exchange rate uncertainty leads to a reduction in employment, low exchange rate uncertainty brings an increase in employment in South Africa’s manufacturing sector.

This research adds to the scarce empirical literature on the effect of exchange rate uncertainty on employment in South Africa’s manufacturing sector by incorporating mainly non-linearities into the model.

The farm sector is crucial for rural poverty alleviation, alongside the non-farm sector, which contributes to mitigating risks associated with crop failures. This paper investigates the effects of public policies on productive employment within both the farm and non-farm sectors in sub-Saharan Africa.

A meta-analysis is conducted exclusively on the results of the Partnership for Economic Policy (PEP)-funded studies under the Policy Analysis on Growth and Employment (PAGE II) initiative. Selected studies focused on the impact of public policies on productive employment in rural farm and non-farm sectors, encompassing a total of nine sub-Saharan Africa countries in: Benin, Burkina Faso, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Lesotho, Nigeria, Senegal and South Africa.

The results indicate that public investments in rural areas and public policies that facilitate access to productive resources are likely to enhance productive employment. The overall effect size is positive and significant, ranging from 2% to 10% increases in productive employment. Sources of variation include the sector of activity and the policy instrument. In addition, the policy effects are gender-sensitive and seem more consistent in the non-farm sector.

Although the selected working papers addressed several aspects of productive employment, other aspects warrant further investigation. Policies involving restrictions or regulations have received little attention in the impact analysis. Researches to fill this gap would be important. Another suggestion for further research is the analysis of the relative importance of non-farm employment in rural areas in developing countries. It is always assumed that rural households depend heavily on agriculture for their subsistence.

The contribution of the paper lies in the comparative analysis of numerous public policies implemented in nine distinct countries. By consolidating data from fourteen 14 different experiences into a single study, the paper offers valuable insights on factors that determine policy effectiveness and contribute to understanding what worked for whom and why.

High levels of youth unemployment in Africa, the difficulty of accessing salaried jobs, and the weakness of public institutions in charge of employment issues push youths towards informal channels that can help them find jobs. Among these informal channels, religion has been playing an increasingly important role. Thus, this study aimed to analyse the effects of religion on youths' access to self-employment.

This study used data from the survey on the improvement of youth employment policies in Francophone Africa—conducted in 2018 by the Laboratory for Economic and Social Research and Studies (LARES) of Marien Ngouabi University—to estimate the effects of religion on access to self-employment. The econometric model employed is a two-stage model. Conditional mixed process developed by Roodman (2011) was used to verify the model's robustness.

The results indicate that religion exhibits a positive and significant effect on access to self-employment. This effect is stronger for youths from Muslim communities than for those from other religious communities, compared to youths who do not engage in religious communities.

Based on the current dynamics observed in numerous African countries with respect to employment access, these results imply that religious denominations should be considered when developing policies and programs related to employment, particularly for youths.

The approach followed in this study contributes to the literature predominantly by demonstrating how the network theory approach helps explain, to some extent, the link between religion and access to employment in general and access to self-employment, particularly in developing economies—mainly in sub-Saharan Africa, where the recourse to informal channels of access to self-employment constitutes a significant solution approach for youths.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2023-0097

This study aims to identify articles examining human-robot interaction and the effects of robotic systems on employment.

In this research, electronic searches were performed for articles published between 2000 and 2022 in Emerald, Springer, PubMed, Science Direct, Wiley and Google Scholar. In the searches of robotic systems with keywords such as “motivation, job satisfaction, job loss, performance, job giving,” 5 quantitative and 5 qualitative studies were included in the systematic review. The selected research was conducted using the Johanna Briggs Analytical Cross-Sectional Studies Checklist from the Joanna Briggs Institute (JBI) critical evaluation lists and the JBI Critical Appraisal Checklist for Qualitative Research, depending on their type. The included studies are mostly on employee-robot collaboration.

Although the majority of the articles examined in this study are included in keywords or titles, it is determined that there is a gap in descriptive quantitative studies in the literature on the effects of employee-robot collaboration, robotic systems and robotic systems on variables such as motivation, job satisfaction, job loss, performance and employment, although they do not mention a framework that directly investigates human-robot interaction and the effects of robotic systems on employment.

There are several limitations in this study. One of them is that, although the databases are comprehensively scanned, only studies published in English between 2000 and 2022 are included in the systematic review. Another limitation is the heterogeneity between studies.

As a result of the authors’ findings, the practical effects of the research are reflected as follows: It serves as a guide for future studies to fill the gap in the field, especially for academics and researchers working in the field of social sciences on robotic systems and intelligent automations. In addition to the qualitative studies on this subject, there is a need for the use of robotic systems in the field of human resources and management and quantitative studies with more sample sizes, especially at the corporate (firms) and individual (employees) level. Considering that the number of studies on this subject is very insufficient, this research is important in terms of shedding light on future studies.

The authors believe that the impact of robotic systems on employment is one of the few conceptual articles that systematically examines 6 dimensions (job satisfaction, performance, job loss, employment, motivation, employment).

This study aims to examine the effects of vocational training programs for people with disabilities on their income.

It conducted a multinomial regression analysis of 10,469 survey responses from 31 provincial administrative areas in mainland China.

It finds the following antecedents all influence the trainees’ self-reported income, including their perception of the quality of the program, the training subject, the degree of consistency between their current job and this subject, their employment sector, their motivation and access to training resources and the geographical location of the program.

The findings are not representative of people with disabilities across mainland China because the respondents were not randomly sampled.

The findings suggest that to increase the income of people with disabilities, the training can be designed according to the needs of employers by teaching subjects relevant to the needs of the labor market, reaching out to motivated trainees and enhancing the quality of training. Training institutions, employers and governments are recommended to work together to integrate class-based learning with workplace-based learning and practices. More training resources can be devoted to the self-employed people with disabilities or those who operate in the informal sector and are in less-developed areas.

The improvement of employment opportunities and income of people with disabilities supports the safeguarding of their social economic rights and the building of an inclusive society.

Few studies have empirically explored and explained the effects of vocational training programs on people with disabilities’ income. This article fills this gap by assessing the performance of China's vocational training programs funded by the Federation of Disabled Persons at all levels.

This paper documents a robust empirical regularity: higher trade openness is associated with a lower unemployment rate. This paper also examines whether or not the effects of trade liberalisation depend on countries' income levels. Further, the dynamic causation between trade openness and unemployment is also examined.

In order to obtain insight into the openness–unemployment nexus, following empirical methods were utilised - static panel models, dynamic panel models and a novel panel Granger causality approach proposed by Juodis et al. (2021).

Results suggest that openness negatively affects unemployment; the extent to which trade liberalisation affects unemployment depends on the income level of each country. The Juodis, Karavias, and Sarafidis (JKS) test confirmed that the past values of trade openness, inflation, foreign direct investment and gross domestic product per capita contain information that helps to predict unemployment in a more robust manner. To simply put, opening upto trade may eventually become a requirement for creating more job opportunities, but this alone may not be enough. The extent to which nations benefit from trade liberalisation is largely dependent on the overall economic conditions and their capability to move up the income scale.

A major difference between this study and those performed previously is that this study does not only examine the impact of trade openness on unemployment, but also investigates whether the unemployment effect of liberalisation is affected by countries' income levels – an issue that has received little attention in the past. Additionally, the unique panel non-causality approach put forth by Juodis et al. (2021) is used in the first instance to look into the causal link between trade openness and unemployment. This method has advantages in that the method enables capturing Granger-causality in homogeneous or heterogeneous panels amongst multiple variables.

Financial inclusion can be proxied by banking status. The purpose of this study is to investigate the potential effects of financial capability on the financial fragility of US adults with various banking statuses during the COVID-19 pandemic.

This study utilized the 2021 National Financial Capability Study (NFCS) dataset to investigate the relationship between financial capability and financial fragility among consumers with different banking statuses. The analysis controlled for employment shocks, health shocks and other consumer characteristics. Banking statuses included fully banked, under-banked (utilizing both banking and alternative financial services) and unbanked individuals. Logistic regression analyses were conducted on both the entire sample and subsamples based on banking statuses.

The results showed that financial capability was negatively associated with financial fragility. The magnitude of the potential negative effect of financial capability was the greatest among the fully banked group, followed by the underbanked and unbanked groups. Respondents who were underbanked or unbanked were more likely to experience financial fragility than those who were fully banked. Additionally, respondents who were laid off or furloughed during the pandemic were more likely to experience financial fragility than those without employment shocks. The effect size of financial capability factors was greater than that of COVID-19 shock factors. These results suggest that higher levels of both financial capability and financial inclusion may be effective in reducing the risk of financial fragility.

This study represents one of the first attempts to examine the potential effects of financial capability on financial fragility among consumers with various banking statuses during the COVID-19 pandemic. Furthermore, this study offers new evidence to determine whether COVID-19 shocks, as measured by health and employment status, are associated with financial fragility. Additionally, the effect size of financial capability factors is greater than that of COVID-19 shock factors. The results from the 2021 NFCS dataset provide valuable insights for banking professionals and public policymakers on how to enhance consumer financial wellbeing.