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This study aims to investigate whether the increasing robot adoption will affect employment rate and wages to contribute to the economic cycle and sustainable development in the world.

The authors introduce a two-way fixed effect model and ordinary least-squares (OLS) model to evaluate the influence based on relevant data of the eighteen countries with the largest robot stocks and robot densities in the world from 2006 to 2019 to test the influences and do the robustness test and endogeneity test by using empirical models.

The authors’ research findings suggest that increasing robot adoption can cause strong negative impacts on employment for both males and females in these economies. Second, the effect of robots on reducing job opportunities has penetrated different industries. It means that this negative impact of robots is comprehensive for the industry. Third, robot adoption can have a strong positive influence on wages and increase workers' incomes.

The limitations of the study are that the influence of industrial intelligence technologies on the circular economy is diversities in different countries. Thus, this study should consider the development levels of different economies to do additional confirmatory studies.

This study makes out the correlations between industrial robots and the employment market from the circular economy perspective. The result proves the existence of this influence relationship, and the authors propose some suggestions to promote sustainable economic development.

This paper addresses the activity of industrial intelligence technologies in the labor market. The employment market is an important part of the circular economy, and it will benefit social development if the government provides appropriate guidance for social investment and industrial layout.

This study is one of the few studies which considered the impact of industrial robots on employment and wages from the perspective of different industries, and this is very important for the circular economy in the world. The results of this paper provide an instructive reference for government policymakers and other countries to stabilize the labor market and optimize human resources for sustainable economic development.

This research aims to find which components of Decent Work are associated with Subjective Well-Being.

With data from 2021 from the states of Mexico, econometric models are carried out.

It is found that disposable income and satisfaction with leisure time have a significant positive relationship with employees' Subjective Well-Being. Likewise, the rate of critical occupancy conditions and informality rate have a significant negative relationship with Subjective Well-Being. The research suggests that influencing the Decent Work conditions of the population in Mexico could favour their Subjective Well-Being.

Share guidelines that enable employers and governments to establish strategies and policies that promote Decent Work to increase the Subjective Well-being of employees.

This article evaluates different variables that make up the Decent Work construct in their level of influence on Subjective Well-being. These relationships and variables considered have not been identified in previous studies as a whole.

This paper evaluates the short-term impact of childcare centres' closures, due to COVID-19 restrictions, on Brazilian mothers' labour force participation and employment rates.

Formal education is non-mandatory according to Brazilian law until the age of four, allowing the identification of children that attend childcare centres and of those that do not attend. Using data from the Brazilian Household Survey, PNAD Contínua/IBGE, the authors construct a two-period panel with women sampled in the second quarter of 2019 and 2020. The authors apply propensity score matching and differences-in-differences methods to control selection into treatment.

The results show a negative impact in terms of employment for mothers whose children attended a childcare centre before the COVID-19 pandemic. But there was no impact in terms of labour force participation rates. Investigating heterogeneous effects associated with childcare centres' closures, the authors find that women with fewer years of schooling, with children aged two or three years old and located in urban areas, suffered greater penalties in the labour market due to the closure of childcare centres.

Few studies could distinguish the pandemic effects directly associated with childcare centres' closures. The paper is the first to analyse the Brazilian case, undertaking an original approach to handle the problem of selection bias. The results help identify the most vulnerable groups of women in the labour market, shedding light on the importance of childcare centres on women's labour supply and of compensating mechanisms to serve as protection during the crisis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2022-0748.

This study aims to contribute to the literature by examining the gender gap effects of childcare restrictions. Specifically, not using professional childcare services due to issues like access, quality or costs. Additionally, we explore the long-run consequences of extended work interruptions for childcare.

Using a specialized cross-sectional module from the 2018 Spanish Labor Force Survey, we estimated a set of linear regression models to capture the short and long run effects of childcare restrictions in labor market outcomes.

We identify substantial gender gaps in labor force, employment, full-time employment and hours worked among parents facing childcare constraints. In contrast, parents without such restrictions experience much lower gender gaps. The long-run analysis reveals that mainly career breaks lasting 2 years or more significantly diminish the labor supply and employment rates of mothers.

Our study goes beyond examining the effects of childcare restrictions on mothers’ labor market behavior and explicitly studies the gender disparities related to these restrictions. Moreover, our database includes information on work flexibility for childcare, allowing us to explore whether such flexibility can help mitigate these gender gaps. Additionally, we assess the long-term effects of work interruptions due to childcare responsibilities on women’s labor outcomes.

This paper examines the determinants of children’s schooling under imperfect credit market conditions in Cameroon, with a particular focus on the role of monetary and non-monetary shocks.

The study uses microeconomic data from the fourth Cameroonian Household Survey (ECAM IV) conducted in 2014 by the National Institute of Statistics (INS) and an instrumental variable Probit model to demonstrate its point.

The results show that uncertainty about household income as measured by transitory income and declining household income decreases the probability of children attending school in Cameroon. The same is true for increasing household size. Nevertheless, access to the credit market is a factor in household resilience to shocks.

The purpose of this article is to contribute to the identification of the determinants of children’s schooling in Cameroon in a situation of credit market imperfection. The aim is to examine the influence of different household vulnerability factors and not only income shocks, which have long been considered the dominant factor.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2024-0028

As a new research interest, robots have surpassed human performance across several aspects. In this research, the authors wish to investigate whether robot adopters perform better than non-adopters in terms of export behavior, especially when distinguishing between different types of firms.

The authors try a new strategy to identify the extent of robot adoption by import data and compare the export trajectories of robot adopters and non-adopters by employing the propensity score matching-difference in difference (PSM-DID) method.

The authors find that robot adopters are more likely to enter export markets and improve subsequent export performance, as the gains from doing so can spread the reduction in variable production costs to a larger customer base abroad. But this rule does not always seem to work; for large-scale firms, robot adoption makes it easier to win export competition and increase market share, while small and medium-sized enterprises (SMEs) do not seem to enjoy any benefits from adoption. More importantly, robot adoption also leads to the fiercer market competition when improving the productivity of firms, which will threaten smaller non-adopters.

The findings provide new evidence for the scale bias of robotics and offer new insights into whether exporters or future exporters ought to adopt robots in production.

1. First, distinguishing from existing research, we explain the controversial results of previous work on robotics by providing evidence from export markets and using the concept of size bias, which helps to update the theoretical interpretation of robotics and provides new insights for current and future exporters to evaluate their robot adoption decisions.

2. Second, we extend previous research by further considering the potential robotics threats faced by non-adopters, especially we record that export gains of robot adopters are partially at the expense of smaller non-adopters, which provides new evidence for the rationale of SME protection policies and supplements robotics theory with new knowledge, such as the competitive game of firms related to robot adoption.

3. Third, to our knowledge, prior research tended to examine the economic effects of robotics through industry data provided by the IFR, this may lead to systematic bias due to the inability to distinguish the robot adoption intentions of different firms. In this respect, we try a new strategy through robot import data and further distinguish between robot adopters and non-adopters in the sample, which helps to mitigate the potential bias in the findings and provide a complement to the recently developed literature related to robotics.

4. Finally, as we pointed out earlier, robot adoption could be an interesting research work for the Chinese export market, which helps us to obtain some special findings, such as in assessing whether the benefits of robots are equally appropriate for economies that previously had an advantage in terms of labor.

First, distinguishing from existing research, we explain the controversial results of previous work on robotics by providing evidence from export markets and using the concept of size bias, which helps to update the theoretical interpretation of robotics and provides new insights for current and future exporters to evaluate their robot adoption decisions.

Second, we extend previous research by further considering the potential robotics threats faced by non-adopters, especially we record that export gains of robot adopters are partially at the expense of smaller non-adopters, which provides new evidence for the rationale of SME protection policies and supplements robotics theory with new knowledge, such as the competitive game of firms related to robot adoption.

Third, to our knowledge, prior research tended to examine the economic effects of robotics through industry data provided by the IFR, this may lead to systematic bias due to the inability to distinguish the robot adoption intentions of different firms. In this respect, we try a new strategy through robot import data and further distinguish between robot adopters and non-adopters in the sample, which helps to mitigate the potential bias in the findings and provide a complement to the recently developed literature related to robotics.

Finally, as we pointed out earlier, robot adoption could be an interesting research work for the Chinese export market, which helps us to obtain some special findings, such as in assessing whether the benefits of robots are equally appropriate for economies that previously had an advantage in terms of labor.

This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.

Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.

In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).

Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.

This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.

To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.

Robots are widely used in industrial manufacturing and service industries around the world. However, most of the previous studies on industrial robots use data at the national or industry level in the context of developed countries. This study examines the impact of imported industrial robots on firm innovation at the firm level in China.

Drawing on a large dataset of more than three million records in China, including non-publicly traded small and medium firms, the authors adopt a difference-in-differences method to investigate the impact and channels of industrial robots on firm innovation.

The authors find that the application of industrial robots increases firm innovation. Two possible channels are identified through which robots promote innovation: alleviation of financial constraints and the improvement of human capital. Further analysis shows that the effect of robots on innovation is more pronounced for firms that are highly dependent on external financing, belong to high-tech industries, import high-end robots, have insufficient supply of skilled labor and private firms (non-SOEs). The authors also find that industrial robots increase the firms' innovation quality and the marginal contribution of innovation to firms' total factor productivity.

This study provides big data evidence of the unintended positive consequences of industrial robots on firm innovation. The results are helpful to clarify the controversy of industrial robots. It also has important implications for government industrial policy making, firm innovation and human resource management.

The methodology discussed in this chapter is extracted from a qualitative analysis that explored the entrepreneurship of Mexicans in three cities in the province of Quebec using the conceptualising categories inspired by grounded theory as an analytical tool. The main contribution of the chapter lies in the fact that the methodological decisions that were taken to answer the research question about the process of business creation by immigrants of Mexican origin are explicitly given in detail. The use and limits of the grounded theory methodology in entrepreneurship studies are discussed. The data collection procedures, the corpus of information that was analysed, the characteristics of the people who participated in the study, as well as the instruments and techniques used to understand the data are described. The chapter details the prior considerations for the selection of the study territory and the particular limits of the research. This is rarely done in studies of immigrant entrepreneurship.

Since the 1970s and 1980s, subsequent waves of so-called ‘new immigration’ have arrived in the United States and Europe. In the United States, this immigration started with the arrival of immigrants and asylum-seekers from Mexico, Central America and Asia. In Europe, the trend began with the influx of Turkish and Moroccan immigrants and continues today with the ongoing refugee crisis. Anti-immigrant politicians on both sides of the Atlantic have adopted exclusionary and often xenophobic rhetoric to further their policies, arguing that these new immigrants and their children cannot assimilate into Western society. A literature review reveals why the classical linear theory of second-generation assimilation is no longer relevant and proposes the contemporary segmented assimilation and comparative integration context theories developed by US and European researchers. A presentation of the findings of two state-of-the-art studies – the CILS project for the United States context and the TIES project for the European context – provides empirical evidence that, despite undeniable obstacles, the new second generation can assimilate into Western education systems and labour markets. Nonetheless, gaps in the existing literature also suggest the need for further research to create a more generalisable theory of second-generation assimilation before appropriate policy measures can be implemented.