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The goal of this study is to propose and test a model of the effect of the socio-cultural context on the disability inclusion climate of organizations. The model has implications of hiring people with disabilities.

To test the model, we conducted a cross-sectional study across four countries with very different socio-cultural contexts. Data were gathered from 266 managers with hiring responsibilities in Canada, China, Norway and France. Participants responded to an online survey that measured the effect of societal based variables on the disability inclusion climate of organizations.

Results indicated support for the theoretical model, which proposed that the socio-cultural context influenced the disability inclusion climate of organizations through two distinct but related paths; manager’s value orientations and their perception of the legitimacy of legislation regarding people with disabilities.

The vast majority of research regarding employment of people with disabilities has focused on supply side factors that involve characteristics of the people with disabilities. In contrast, this research focuses on the less researched demand side issue of the socio-cultural context. In addition, it responds to the “limited systematic research examining and comparing how country-related factors shape the treatment of persons with disability” (Beatty et al., 2019, p. 122).

Online gaming has emerged as a popular activity providing a social outlet for millions. However, implications of online game networks for mental health remain disputed. Concepts of bridging social capital and bonding social capital may help characterize protective factors within social networks. This study aims to examine the associations between social capital derived from online versus in-person networks and mental health indicators among gamers.

Online gamers (n = 301) completed an online survey assessing their social networks (both in-person and through online gaming) and mental health indicators (depressive symptoms, anxiety, social isolation, perceived social support). Social network analysis was used to analyze bridging (network size, effective size, heterogeneity, weak ties) and bonding (closeness, frequent contact, confiding, connection quality) social capital. Separate linear regression models evaluated associations between bridging and bonding social capital for both online and in-person networks and depressive symptoms, anxiety, social support and social isolation.

In-person network characteristics showed the strongest associations with mental health outcomes. Greater average closeness and frequent confiding in the in-person network predicted lower isolation and fewer depressive symptoms. More diverse relationship types also correlated with lower depression. For online networks, closeness and confiding ties associated only with less isolation and greater support, not depressive symptoms, or anxiety.

While online gaming networks provide some degree of social support, in-person social capital exhibited stronger associations with mental health. This reinforces the importance of face-to-face relationships for emotional well-being. Findings suggest helping gamers cultivate close bonds offline. However, online connections still matter and should not be discounted.

This paper aims to discuss the practical dilemmas of institutional change to tackle the climate crisis in a UK university, identifying key assumptions and issues that block meaningful change. The research was part of an initiative to define a theory of change (ToC) to meet the university’s institutional climate commitments.

The findings are based on interviews with members of an inter-disciplinary ToC working group, a staff–student climate coalition and student representatives at the university. Interviewees were purposively selected to gain insights into assumptions about the nature of the university and its role in tackling the climate crisis, which must be addressed for the university to effectively implement its climate plan.

This paper identified tensions between the university’s role as a public and commercial institution, a lack of clarity over decision-making processes and the difficulties in balancing (and being transparent about) actions with commitments to tackle the climate crisis. A democratic and flexible approach to change is essential to mitigate these issues, providing an opportunity to reflect on the diversity of the university community and openly debate goals and commitments.

In setting out the initial steps of a ToC in a UK university, this paper offers practical insights for higher education institutions looking to change practices. By highlighting assumptions at a particular institution, this paper also contributes a level of granularity to a growing field of research on efforts in higher education institutions to tackle the climate crisis.

The aim of this paper is to explore how multi-national corporations (MNCs) can effectively adopt artificial intelligence (AI) into their talent acquisition (TA) practices. While the potential of AI to address emerging challenges, such as talent shortages and applicant surges in specific regions, has been anecdotally highlighted, there is limited empirical evidence regarding its effective deployment and adoption in TA. As a result, this paper endeavors to develop a theoretical model that delineates the motives, barriers, procedural steps and critical factors that can aid in the effective adoption of AI in TA within MNCs.

Given the scant empirical literature on our research objective, we utilized a qualitative methodology, encompassing a multiple-case study (consisting of 19 cases across seven industries) and a grounded theory approach.

Our proposed framework, termed the Framework on Effective Adoption of AI in TA, contextualizes the motives, barriers, procedural steps and critical success factors essential for the effective adoption of AI in TA.

This paper contributes to literature on effective adoption of AI in TA and adoption theory.

Additionally, it provides guidance to TA managers seeking effective AI implementation and adoption strategies, especially in the face of emerging challenges.

To the best of the authors' knowledge, this study is unparalleled, being both grounded in theory and based on an expansive dataset that spans firms from various regions and industries. The research delves deeply into corporations' underlying motives and processes concerning the effective adoption of AI in TA.

Key to transnational higher education (HE) cooperation is building trust to allow for seamless recognition of studies. Building on the Tuning Educational Structures initiative (2001) and lessons learnt from the Organisation for Economic Cooperation and Development (OECD)-Assessment of Learning Outcomes in Higher Education (AHELO) feasibility study, this paper offers a sophisticated approach developed by the European Union (EU)-co-financed project Measuring and Comparing Achievements of Learning Outcomes in Europe (CALOHEE). These evidence the quality and relevance of learning by applying transparent and reliable indicators at the overarching and disciplinary levels. The model results allow for transnational diagnostic assessments to identify the strength and weaknesses of degree programmes.

The materials presented have been developed from 2016 to 2023, applying a bottom-up approach involving approximately 150 academics from 20+ European countries, reflecting the full spectrum of academic fields. Based on intensive face-to-face debate and consultation of stakeholders and anchored in academic literature and wide experience.

As a result, general (overarching) state-of-the-art reference frameworks have been prepared for the associated degree, bachelor, master and doctorate, as well as aligned qualifications reference frameworks and more detailed learning outcomes/assessment frameworks for 11 subject areas, offering a sound basis for quality assurance. As a follow-up, actual assessment formats for five academic fields have been developed to allow for measuring the actual level of learning at the institutional level from a comparative perspective.

Frameworks as well as assessment models and items are highly innovative, content-wise as in the strategy of development, involving renown academics finding common ground. Its value is not limited to Europe but has global significance. The model developed, is also relevant for micro-credentials in defining levels of mastery.

This study, a theoretical article, aims to introduce new institutionalism as a framework through which business and management researchers can explore the significance of artificial intelligence (AI) in organizations. Although the new institutional theory is a fully established research program, the neo-institutional literature on AI is almost non-existent. There is, therefore, a need to develop a deeper understanding of AI as both the product of institutional forces and as an institutional force in its own right.

The authors follow the top-down approach. Accordingly, the authors first briefly describe the new institutionalism, trace its historical development and introduce its fundamental concepts: institutional legitimacy, environment and isomorphism. Then, the authors use those as the basis for the queries to perform a scoping review on the institutional role of AI in organizations.

The findings reveal that a comprehensive theory on AI is largely absent from business and management literature. The new institutionalism is only one of many possible theoretical perspectives (both contextually novel and insightful) from which researchers can study AI in organizational settings.

The authors use the insights from new institutionalism to illustrate how a particular social theory can fit into the larger theoretical framework for AI in organizations. The authors also formulate four broad research questions to guide researchers interested in studying the institutional significance of AI. Finally, the authors include a section providing concrete examples of how to study AI-related institutional dynamics in business and management.