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The increasing relevance of environmental, social and governance (ESG) engagement has attracted interest in its drivers and effects on business outcomes under different organizational settings. By focusing on family firms (FFs), we deepen both the role of business ethics as a predictor of enhanced ESG engagement and the link with improved corporate financial performance (CFP). In this way, we aim to provide new insights into the impact of business ethics and ESG engagement on FFs competitiveness.

Based on a worldwide panel of 335 FFs covering the 2002–2020 time horizon, this study adopts a two-stage Heckman model (1979) to empirically address two research questions: (RQ1) Do business ethics predict greater ESG engagement in FFs? (RQ2) Does ESG engagement positively affect the corporate financial performance (CFP) of FFs?

The results of the current study are twofold. First, we demonstrate that an ethical approach to business drives greater ESG engagement. Second, we show that higher levels of ESG engagement lead to improved financial performance in FFs.

Our study contributes to filling the knowledge gaps regarding the drivers and effects of ESG engagement in FFs. On the one hand, we demonstrate the positive connection between dimensions that have their own identity, such as business ethics and ESG constructs. On the other hand, by shedding light on the impact of ESG engagement on improved CFP, we contribute to solving the trade-off between economic and noneconomic FF goals.

Artificial intelligence (AI) is poised to reshape mental health practices, policies and research in the coming decade. Simultaneously, mental health inequalities persist globally, imposing considerable costs on individuals, communities and economies. This study aims to investigate the impact of AI technologies on future citizenship for individuals with mental health challenges (MHCs).

This research used a community-based participatory approach, engaging peer researchers to explore the perspectives of adults with MHCs from a peer-led mental health organisation. This study evaluated potential threats and opportunities presented by AI technologies for future citizenship through a co-created film, depicting a news broadcast set in 2042. Data were gathered via semi-structured interviews and focus groups and were analysed using a reflexive thematic approach.

The analysis identified four key themes: Who holds the power? The divide, What it means to be human, and Having a voice. The findings indicate that adults with living experiences of MHCs are eager to influence the development of AI technologies that affect their lives. Participants emphasised the importance of activism and co-production while expressing concerns about further marginalisation.

This study provides new insights into the intersection of AI, technology and citizenship, highlighting the critical need for inclusive practices in technological advancement. By incorporating the perspectives of individuals with living experiences, this study advocates for participatory approaches in shaping AI technologies in mental health. This includes the co-creation of machine learning algorithms and fostering citizen engagement to ensure that advancements are equitable and empowering for people with MHCs.

Retailers increasingly endeavour to implement artificial intelligence (AI) innovations, such as humanoid social robots (HSRs), to enhance customer experience. This paper investigates the interactive effect of HSR intelligence and consumers' speciesism on their perceptions of retail robots as sales assistants.

Three online experiments testing the effects of HSRs' intellectual intelligence on individuals' perceived competence and, consequently, their decision to shop at a retail store that uses HSRs as sales assistants are reported. Furthermore, the authors examine whether speciesism attenuates these effects such that a mediation effect is likely to be observed for individuals low in speciesism but not for those with high levels of speciesism. Data for all studies were collected on Prolific and analysed with SPSS to perform a logistic regression and PROCESS 4.0 (Hayes, 2022) for the mediation and moderated-mediation analysis.

The findings show that the level of speciesism moderates the relationship between HSR intellectual intelligence and perceived competence such that an effect is found for low but not for high HSR intelligence. When HSR intellectual intelligence is low, individuals with higher levels of speciesism (vs low) rate the HSR as less competent and display lower HSR acceptance (i.e. customers' decision to shop using retail robots as sales assistants).

This research responds to calls in research to adopt a human-like perspective to understand the compatibility between humans and robots and determine how personality traits, such as a person's level of speciesism, may affect the acceptance of AI technologies replicating human characteristics (Schmitt, 2019). To the best of the authors' knowledge, the present research is the first to examine the moderating role of speciesism on customer perceptions of non-human retail assistants (i.e. human-like and intelligent service robots). This study is the first to showcase that speciesism, normally considered a negative social behaviour, can positively influence individuals' decisions to engage with HSRs.

Recent research has proposed a specific female phenotype within autism spectrum disorder (ASD). It suggests females exhibit differences in social communication styles with higher levels of camouflaging and compensatory strategies, as well as variance in restrictive repetitive behaviours (RRBs); however, many existing studies have been based on either small, disproportionate or child and adolescent samples, leaving questions about the specific phenotype. This study aims to explore the sex difference and phenotype in a clinic sample of individuals diagnosed with autism.

A service evaluation of sex/ gender differences on 150 historical ASD assessment reports (75 males, 75 females) using a 103-item questionnaire developed from a quantitative review of existing literature was undertaken.

Females camouflaged more significantly than males in five different areas (thinking how to act next, preparing conversation in advance, making lists of prompts/social responses, wearing a mask/acting, less monotone voice); however, these were not maintained in post-analysis correction.

This study points the evidence towards a different phenotype of Autism that is more common in women than men rather than a unique female phenotype.