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This study aims to focus on key approaches to education for sustainability (EfS) leadership development in the context of Malaysian and Japanese universities. The authors identify key indicators of effective EfS leadership development approaches using both descriptive and inferential analyses, identify and compare the preferred leadership learning methods of academics and examine the impact of marital status, country of residence and administrative position on the three EfS leadership development approaches.

The study is quantitative in approach and survey in design. Data were collected from 664 academics and analysed using the efficient partial least squares (PLSe2) methodology. To provide higher education researchers with more analytical insights, the authors re-estimated the models based on the maximum likelihood methodology and compared the results across the two methods.

The inferential results underscored the significance of four EfS leadership learning methods, namely, “Involvement in professional leadership groups or associations, including those concerned with EfS”, “Being involved in a formal mentoring/coaching program”, “Completing formal leadership programs provided by my institution” and “Participating in higher education leadership seminars”. Additionally, the authors noted a significant impact of country of residence on the three approaches to EfS leadership development. Furthermore, although marital status emerged as a predictor for self-managed learning and formal leadership development (with little practical relevance), administrative position did not exhibit any influence on the three approaches.

In addition to the theoretical and methodological implications drawn from the findings, the authors emphasize a number of practical implications, namely, exploring the applicability of the results to other East Asian countries, the adaptation of current higher education leadership development programmes focused on the key challenges faced by successful leaders in similar roles, and the consideration of a range of independent variables including marital status, administrative position and country of residence in the formulation of policies related to EfS leadership development.

This study represents an inaugural international comparative analysis that specifically examines EfS leadership learning methods. The investigation uses the research approach and conceptual framework used in the international Turnaround Leadership for Sustainability in Higher Education initiative and uses the PLSe2 methodology to inferentially pinpoint key learning methods and test the formulated hypotheses.

This study aims to investigate the contribution of higher education institutions (HEIs) to the sustainable development goals (SDGs) and propose strategies to cultivate a culture centred on the SDGs in HEIs.

The methodology used encompassed an integrative literature review, combining bibliographic analysis on how HEIs incorporate the SDGs into their practices, adopting a qualitative approach for the analysis and categorization of the results.

The multifaceted contributions of HEIs in promoting the SDGs stand out, through their roles in teaching, research, management and integration and communication between university and society.

While influencing policies at various levels, HEIs encounter challenges in the effective integration of SDGs into their strategies. This underscores the need for contextualized governance, understanding students’ perspectives on sustainability and active external collaboration in policy formulation.

There is an urgent need to integrate SDGs into academic programmes, emphasizing the importance of redesigning curricula, actively involving teachers, researchers and students, establishing partnerships and promoting research applied to SDGs.

The social relevance of the study lies in the emphasis on an SDG-centred culture, involving teaching, research, outreach, community engagement and governance practices.

The study’s uniqueness lies in identifying persistent challenges during the transition to an SDG-centred culture, necessitating multisectoral collaboration and educational programmes that integrate sustainability principles into the strategy of HEIs.

The purpose of this paper is to open a debate on the interrelationship between categorisation, labelling, disclosure and enforcement. The extant literature on the accounting reporting environment explores the provision of both mandated and voluntary disclosures. Often disclosure is defined in a less than rigorous manner, mislabelled, misclassified and uses a strict dichotomy that limits information fineness.

The authors advance a non-dichotomous continuum of disclosure from voluntary and innovative at one end of the spectrum, to mandatory at the other, that helps reduce mislabelling and miscategorisation.

Firms’ voluntary disclosures cannot be properly interpreted without reviewing their interrelationship with mandatory disclosures and vice versa. Definitions of voluntary disclosure that have been used in empirical studies are examined, including the mislabelling and misclassification of voluntary disclosures and the authors provide examples of truly voluntary and innovative disclosures by companies.

This paper constructs, and provides evidence consistent with, a reporting continuum rather than the dichotomous disclosure measure that dominates decades of prior literature.

This paper aims to respond to the need for “socially sustainable settlements for all” and the need for successful integration within the settlements through building strong social constructs among the settlers.

Mixed methods were used in this study. A sample size of 332 households in Pagirinya Refugee Settlement was used. The settlement is divided into six blocks, each block is subdivided into clusters. Each cluster comprises of 100 households. Due to variations in the number of households in each settlement block, the authors used a proportional sampling approach to determine the number of respondent households in each settlement block. Data was collected through questionnaires, interviews and focus group discussions. Chi-square and an interdependent multivariate statistical analysis were performed to establish the relationship between housing and social sustainability.

The study finds a significant relationship between housing and social sustainability when considered jointly on the variables of roofs of buildings and how often the refugee respondents meet with neighbours (p = 0.018) and when considered jointly on the variables of the width of access roads and how knowledgeable the refugee respondents are about their neighbours (p = 0.018). The study also finds a significant relationship between housing and social sustainability when considered jointly on the variables of the number of direct access roads to the households and the number of friends of the refugee respondents (p = 0.019).

With limited literature, this is a novel approach. To the best of the authors’ knowledge, no previous studies focused on the specifics of a building and analysed its relationship with the social dynamics, especially in settlement studies.

The study aims to evaluate PubMed publications on ChatGPT or artificial intelligence (AI) involvement in scientific or medical writing and investigate whether ChatGPT or AI was used to create these articles or listed as authors.

This scoping review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. A PubMed database search was performed for articles published between January 1 and November 29, 2023, using appropriate search terms; both authors performed screening and selection independently.

From the initial search results of 127 articles, 41 were eligible for final analysis. Articles were published in 34 journals. Editorials were the most common article type, with 15 (36.6%) articles. Authors originated from 27 countries, and authors from the USA contributed the most, with 14 (34.1%) articles. The most discussed topic was AI tools and writing capabilities in 19 (46.3%) articles. AI or ChatGPT was involved in manuscript preparation in 31 (75.6%) articles. None of the articles listed AI or ChatGPT as an author, and in 19 (46.3%) articles, the authors acknowledged utilizing AI or ChatGPT.

Researchers worldwide are concerned with AI or ChatGPT involvement in scientific research, specifically the writing process. The authors believe that precise and mature regulations will be developed soon by journals, publishers and editors, which will pave the way for the best usage of these tools.

This scoping review expressed data published on using AI or ChatGPT in various scientific research and writing aspects, besides alluding to the advantages, disadvantages and implications of their usage.

Information systems (IS) research in general and health IS studies, in particular, are prone to a positivity bias – largely focusing on upside gains rather than the potential misuse practices. This paper aims to explore failures in health IS use and shortcomings in data privacy and cybersecurity and to provide an explanatory model for health record misuse.

This research is based on four data sets that we collected through a longitudinal project studying digital health (implementation, use and evaluation), interviews with experts (cybersecurity and digital health) and healthcare stakeholders (health professionals and managers). We applied qualitative analysis to explain health records misuse from a sociotechnical perspective.

We propose a contextualized model of “health records misuse” with two overarching dimensions: data misfit and improper data processing. We explain sub-categories of data misfit: availability misfit, meaning misfit and place misfit, as well as sub-categories of improper data processing: improper interaction and improper use-related actions. Our findings demonstrate how health records misuse can emerge in sociotechnical health systems and impact health service delivery and patient safety.

Through contextualizing system misuse in healthcare, this research advances the understanding of ineffective use and failures in health data protection practices. Our proposed theoretical model provides explanations for unique patterns of IS misuse in healthcare, where data protection failures are consequential for healthcare organizations and patient safety.