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Whether by direct or indirect action (or by inaction), multinational enterprises (MNEs) can have both a positive and a negative effect on within-country social and economic inequality. This paper aims to comment on this multifaceted relationship between MNEs and within-country inequality.

Given the absence of either robust theory or evidence in the neglected realm of MNEs and within-countries inequalities, this paper offers some general observations, highlights some of the key issues and illustrates possible avenues for future research studies.

The capacity of MNEs to upgrade economic activity in the host country is a key policy objective. MNEs have arguably contributed to reducing income inequalities between countries. However, the limited evidence available suggests that the gains of FDI are rarely evenly distributed within recipient countries, and many of the underlying dynamics need further investigation.

The authors broaden the engagement with inequality beyond income levels, as this is just one aspect of inequality that shapes or impedes human development. They believe it is necessary – for both MNEs and policymakers – to have a more nuanced understanding of how, and under what circumstances, the presence of MNEs affects inequality in host economies.

This paper relates the large literature on inequality (going beyond the mainstream focus on income inequality) to the mainstream understanding of MNE-assisted development.

Cross-country studies have shown that higher costs to starting a business tend to reduce entrepreneurship (Chambers and Munemo, 2019) and that an unfavorable environment for business can increase poverty and income inequality (Chambers et al., 2019a; Djankov et al., 2018). Building on the current literature, the authors test whether barriers to starting a business at the state and city level in the USA are associated with changes in entrepreneurship and income inequality.

Measures of entrepreneurship (establishment entry rate and exit rate) are regressed on measures of barriers to entry in a cross-section of 50 states as well as a cross-section of 73 cities in the USA. Further, the authors regress measures of income inequality on measures of barriers to entry using the same two cross-sections. State level data on barriers to entry are from Teague (2016), published in the Journal of Entrepreneurship and Public Policy. City level data on barriers to starting a business are from the Doing Business in North America (DBNA) dataset.

Results show that there is a negative and significant association between barriers to starting a business and the rate of firm exit. A standard deviation increase in barriers to entry is associated with a five percent decrease in the firm exit rate at the state level. The authors find only limited evidence that barriers to entry are associated with income inequality.

Despite a large volume of scholarship on how regulation and barriers to entry influence entrepreneurship, no study (to the authors’ knowledge) has investigated how general entry regulation affects the entry or exit rate of establishments at the state or municipal level in the USA.

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.

This paper explores intergenerational perceptions of kindness in the context of Black Lives Matter (BLM) movement and the COVID-19 global pandemic. The purpose of this exploratory study is to investigate perceptions of kindness in the context of traumatic events and its potential value in authentic allyship in organizational environments.

Authors interviewed 65 individuals (31 self-identifying as non-racialized and 34 self-identifying as Black, Indigenous and People of Colour aka BIPOC). Participants included Generation Z (Gen Z; born between 1997–2012/5) and Generation Y (Gen Y; also referred to as Millennials, born between 1981 and 1994/6) across North American, Europe and Africa. Millennials currently represent the largest generation in the workplace and are taking on leadership roles, whereas Gen Z are emerging entrants into the workplace and new organizational actors.

The paper offers insights into how to talk about BLM in organizations, how to engage in authentic vs performative allyship and how to support BIPOC in the workplace. The study also reveals the durability of systemic racism in generations that may be otherwise considered more enlightened and progressive.

The authors expand on kindness literature and contribute theoretically and methodologically to critical race theory and intertextual analysis in race scholarship.

The study contributes to the understanding of how pro-social behaviours like kindness (with intention) can contribute to a more inclusive discourse on racism and authentic allyship.

Authors reveal the potential for kindness as a pro-social behaviour in organizational environments to inform authentic allyship praxis.

This study aims to answer two research questions: first, to what extent can workplace bullying be explained by ageism? And second, does the likelihood of workplace bullying increase when age interacts with gender and ethnic minority?

The authors report results from a survey carried out in 11 organizations in Estonia (N = 1,614) using the Negative Acts Questionnaire-Revised (Einarsen et al., 2009).

The results show that ageism does not explain bullying in Estonia. As in some earlier studies, older age correlates negatively with negative acts, and women report less work-related bullying than men. These findings were unexpected because Estonia's post-socialist background and the highest gender wage gap in Europe suggested otherwise. However, there is gendered ageism in work-related bullying such that older women report more negative acts in their workplace. Respondents from ethnic minority groups do not experience more bullying in general, nor in combination with age. Surprisingly, managers reported both person- and work-related bullying more than employees with no subordinates.

The study contributes to intersectionality literature with a view to workplace bullying in post-socialist study context.

This paper places what has happened to income inequality in rich countries over recent decades alongside trends in median and low incomes in real terms, taken as incomplete but valuable indicators of the evolution of living standards for “ordinary working families” and the poor. The findings demonstrate first just how varied country experiences have been, with some much more successful than others in generating rising real incomes around the middle and toward the bottom of the distribution. This variation is seen to be only modestly related to the extent to which income inequality rose, which itself is more varied across the rich countries than is often appreciated. The extent to which economic growth is transmitted to the middle and lower parts of the distribution is seen to depend on a range of factors of which inequality is only one. Sources of real income growth around the middle have also varied across countries, though transfers are consistently key toward the bottom. The diversity of rich country experiences should serve as an important corrective to a now-common “grand narrative” about inequality and stagnation based on the experience of the USA.

This study aims to analyse the impact of digital divide (DD) on income inequality in sub-Saharan Africa over the period 2004–2016.

In applying a finite mixture model (FMM) to a sample of 35 sub-Saharan African (SSA) countries, this study posits that DD affects income inequality differently.

The findings show that the effect of DD on income inequality varies across two distinct groups of countries, which differ according to their level of globalization. In addition, the study shows that most globalized countries are more inclined to be in the group where the effect of DD on income inequality is negative. The results are consistent with several robustness checks, including alternative measures of income inequality and additional control variables.

This study complements that extant literature by assessing linkages among the DD, globalization and income inequality in sub-Saharan African countries contingent on cross-country heterogeneity.