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The purpose of this paper is to present a register‐based index that could provide a practical tool for gathering information and increasing our knowledge on gender equality at organizational level.

Based on Swedish gender policy and information available in public registers, six variables were chosen. For each variable, a gender gap was calculated as the ratio between the sexes, with the larger figure always treated as numerator. The study population consisted of 11,471 persons in 46 companies working in the computer sector, and 32,151 individuals in 77 companies employed in the grocery production sector.

The results show indices of 1.43‐2.09 for the computer sector and of 1.13‐2.14 for the grocery production sector, both with a normal distribution (one is considered fully gender equal and three least gender equal). Added together, the selected variables provide results that are sufficiently different to enable ranking. The variables vary in importance in the two sectors compared. The smallest index variation was for education and salaries; the largest was for parental leave and the number of men and women employed at the companies.

The index is based on public registers, treats men and women symmetrically, and the results generated by the index are easy to communicate to all stakeholders. This research could provide a useful tool for investigating the extent to which men and women differ in certain variables at company level.

The advent of technology has propelled audit firms to incorporate AI-based audit services, bringing the relationship between audit clients and firms into sharper focus. Nonetheless, the understanding of how AI-based audit services affect this relationship remains sparse. This study strives to probe how an audit client's satisfaction with AI-based audit services influences their trust in audit firms. Identifying the variables affecting this trust, the research aspires to gain a deeper comprehension of the implications of AI-based audit services on the auditor-client relationship, ultimately aiming to boost client satisfaction and cultivate trust.

A conceptual framework has been devised, grounded in the client-company relationship model, to delineate the relationship between perceived quality, perceived value, attitude and satisfaction with AI-based audit services and their subsequent impact on trust in audit firms. The research entailed an empirical investigation employing Facebook ads, gathering 288 valid responses for evaluation. The structural equation method, utilized in conjunction with SPSS and Amos statistical applications, verified the reliability and overarching structure of the scales employed to measure these elements. A hybrid multi-analytical technique of structural equation modeling and artificial neural networks (SEM-ANN) was deployed to empirically validate the collated data.

The research unveiled a significant and positive relationship between perceived value and client satisfaction, trust and attitude towards AI-based audit services, along with the link between perceived quality and client satisfaction. The findings suggest that a favorable attitude and perceived quality of AI-based audit services could enhance satisfaction, subsequently augmenting perceived value and client trust. By focusing on the delivery of superior-quality services that fulfill clients' value expectations, firms may amplify client satisfaction and trust.

Further inquiries are required to appraise the influence of advanced technology adoption within audit firms on client trust-building mechanisms. Moreover, an understanding of why the impact of perceived quality on perceived value proves ineffectual in the context of audit client trust-building warrants further exploration. In interpreting the findings of this study, one should consider the inherent limitations of the empirical analysis, inclusive of the utilization of Facebook ads as a data-gathering tool.

The research yielded insightful theoretical and practical implications that can bolster audit clients' trust in audit firms amid technological advancements within the audit landscape. The results imply that audit firms should contemplate implementing trust-building mechanisms by creating value and influencing clients' stance towards AI-based audit services to establish trust, particularly when vying with competing firms. As technological evolutions impinge on trustworthiness, audit firms must prioritize clients' perceived value and satisfaction.

To the researcher's best knowledge, no previous study has scrutinized the impact of satisfaction with AI-based audit services on cultivating audit client trust in audit firms, in contrast to past research that has focused on the auditors' trust in the audit client. To bridge these gaps, this study employs a comprehensive and integrative theoretical model.

The purpose of this study is to provide information on how citizens in nine countries across Europe perceive egg product quality and the importance of a product's sustainability attributes (animal welfare, country of origin and production method) in egg purchases.

The data were gathered in 2021 via an online survey in nine European countries (Finland, the United Kingdom, France, Italy, Belgium, Germany, the Netherlands, Romania and Denmark). A total of 3,601 responses were collected. As methods of analysis, exploratory factor analysis (EFA), independent samples t-test, paired samples t-test and one-way analysis of variance (ANOVA) were conducted when investigating the quality dimensions of egg products and the differences amongst the sociodemographic groups.

Citizens in European countries considered animal welfare aspects, production method and country of origin important when purchasing egg products. Citizens' perceived quality of egg products was related to two dimensions (i.e. product properties and responsible production), and there were differences in perceptions by sociodemographic groups (i.e. age, gender, education and country of residence). Responsible production was most valued by younger women with higher education. Also in the Netherlands and Romania, citizens had stronger preferences for product properties compared to responsible production, whilst in Germany, responsible production was appreciated more than product properties.

The study provides new information on citizens' perceived egg product quality and the role of a product's sustainability attributes in egg purchases. Furthermore, the results bring novel insights on the differences in perceptions amongst citizens living in nine European countries.

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The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

This study aims to establish a comprehensive understanding of the intricacies of how individuals engage with deepfakes, focusing on limiting adverse effects and capitalizing on their benefits.

This study conducted a meta-synthesis of qualitative studies on deepfakes, incorporating study-specific analysis followed by a cross-study synthesis.

Based on the meta-synthesis, the study developed an integrated conceptual framework based on the perspectives from the social shaping of technology theory embedding deepfake-related assertions, motivations, the subtleties of digital platforms, and deepfake-related repercussions.

The study offers crucial insights into the evolving nature of deepfakes as a socio-technical phenomenon and the significance of platform dynamics in deepfake production. It enables researchers to comprehend the cascading effects of deepfakes and positions them to evaluate deepfake-related risks and associated mitigation mechanisms.

The framework that emerges from the study illustrates the influence of platforms on the evolution of deepfakes and assists platform stakeholders in introducing effective platform governance structures to combat the relentless proliferation of deepfakes and their consequences, as well as providing guidance for governments and policymakers to collaborate with platform leaders to set guardrails for deepfake engagement.

Deepfakes have been extensively contested for both their beneficial and negative applications and have been accused of heralding an imminent epistemic threat that has been downplayed by some quarters. This diversity of viewpoints necessitates a comprehensive understanding of the phenomenon. In responding to this call, this is one of the first to establish a comprehensive, theoretically informed perspective on how individuals produce, process, and engage with deepfakes through a meta-synthesis of qualitative literature on deepfakes.

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NOTWITHSTANDING the fact that there exists a considerable amount of literature published in various forms on the subject of brittle lacquers and their applications to a multitude of diverse problems a brief resume of some of the general principles involved would seem not to be out of place.