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Public health measures implemented early in the COVID-19 pandemic brought the idea of essential work into the public discourse, as the public reflected upon what types of work are essential for society to function, who performs that work, and how the labour of essential workers is rewarded. This chapter focusses on the rewards associated with essential work. The authors develop an intersectional lens on work that was officially deemed essential in 2020 to highlight longstanding patterns of devaluation among essential workers, including those undergirded by systemic racism in employment and labour law. The authors use quantitative data from the CPS-MORG to examine earnings differences between essential and non-essential workers and investigate whether the essential worker wage gap changed from month to month in 2020. The authors find that patterns of valuation among essential workers cannot be explained by human capital or other standard labour market characteristics. Rather, intersectional wage inequalities in 2020 reflect historical patterns that are highly durable and did not abate in the first year of the global pandemic.

This paper intervenes in the consequences of a myth propagated in academic discourse about the dancesport world, according to which half of the men in Latin dancesport are gay. I challenge two assumptions that surround this myth: that cisgender gay men do not contribute to the reification of the heteronormative gender binary, and that the dancesport scene is inclusive of gay people. These assumptions are based on a blatant lack of understanding of the position of gay men within the dancesport world – that is, the ways in which subjects are constituted through the effects of power.

This work is based on empirical research I conducted in the dancesport community, including ethnographic and autoethnographic fieldwork, extant documents (e.g. books, blogs, Judging Regulations) and interviews with experts and participants of the dancesport scene (2021/2022). To analyse the data, I relied on the principles of dispositive analysis, grounded theory and dance analysis.

I show that gay dancers have turned to assimilation as their only available strategy. I discuss the negative consequences of assimilation as a political strategy and how it impacted queer dancers – between invisibilisation, residual shame and a failure to challenge the heteronormative gender binary. This led gay dancers to rationalise and perpetrate harm based on the systems of oppression they had internalised.

I conclude the paper by highlighting a way beyond assimilation for queer dancers.

This paper addresses a critical gap in research on LGBT + inclusion in dancesport.

The present study aimed to examine the effect of received remittance inflows on the price level ratio of the purchasing power parity conversion factor to the market exchange rate in 36 developed and developing countries from 2004 to 2020.

The panel data conducted a comparative analysis and used panel least squares, regression with Driscoll-Kraay standard errors of fixed effect, random effect, feasible generalised least squares and maximum likelihood robust least squares to overcome the heterogeneity issue. Furthermore, the two-step difference generalised method of moments to overcome the endogeneity issue. Diagnostic tests were used to increase robustness.

In the studied countries, there was a statistically significant negative relationship between received remittance inflows and the price-level ratio of the purchasing power parity conversion factor to the market exchange rate. This relationship explains why remittance flows depreciate the real exchange rate. The study’s results also indicated that attracting investments can improve the quality of institutions despite high tax rates, leading to low tax revenue.

The current study findings enrich the understanding of policies of how governments should minimise tariff rates on capital imports and introduce export-oriented incentive programmes. The study also revealed that Dutch disease can occur due to differences in the demand structure and manufacturing development policy.

This study aims to explore Augmented Language Models (ALMs) for synthetic data generation in services marketing and research. It evaluates ALMs' potential in mirroring human responses and behaviors in service scenarios through comparative analysis with five empirical studies.

The study uses ALM-based agents to conduct a comparative analysis, leveraging SurveyLM (Bickley et al., 2023) to generate synthetic responses to the scenario-based experiment in Söderlund and Oikarinen (2018) and four more recent studies from the Journal of Services Marketing. The main focus was to assess the alignment of ALM responses with original study manipulations and hypotheses.

Overall, our comparative analysis reveals both strengths and limitations of using synthetic agents to mimic human-based participants in services research. Specifically, the model struggled with scenarios requiring high levels of visual context, such as those involving images or physical settings, as in the Dootson et al. (2023) and Srivastava et al. (2022) studies. Conversely, studies like Tariq et al. (2023) showed better alignment, highlighting the model's effectiveness in more textually driven scenarios.

To the best of the authors’ knowledge, this research is among the first to systematically use ALMs in services marketing, providing new methods and insights for using synthetic data in service research. It underscores the challenges and potential of interpreting ALM versus human responses, marking a significant step in exploring AI capabilities in empirical research.

In recent years we have seen major technological advancements including the launch of large language models such as ChatGPT and the popularity of the digital transformation topic among professionals and academics. Despite this, the pace of digital transformation is surprisingly slow. We aimed to identify behavioral antecedents of an organization’s sluggish digital transformation.

We adopted the organizational level of analysis, which differs from prior analyses of technological revolutions that looked at the phenomenon from an aggregate labor market or society level of analysis.

We identified dehumanization as a key construct useful in examining the behavioral impediments to digital transformation. We indicated that the traditionally dual understanding of dehumanization needs to incorporate the actual involvement of non-human agents in operational and decision-making processes in organizations.

We complemented the predominant approach of digital transformation, which focuses on technology and related business model development, with a behavioral approach. We considered digital transformation as an extreme degree of change, similar to the Industrial Revolution. We paved the way for the conceptual development of dehumanization in the digital world and for developing managerial practices useful in alleviating concerns that impede the pace of digital transformation.