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During the last decade, several areas in the biomedical and social sciences experienced a reproducibility crisis, where mounting empirical evidence indicated that many published findings could not be successfully replicated. This crisis resulted in considerable introspection within the field of statistics because the null hypothesis statistical testing (NHST) paradigm is acknowledged as one of its root causes based on widespread agreement that it is deeply flawed. However, unlike in many other areas, there has yet to be a concerted effort within the discipline of accounting to acknowledge these developments, let alone steps taken to improve practice. This essay aims to spark discussion and debate on the validity of the NHST paradigm by presenting a comprehensive case, incorporating the latest arguments and findings, that demonstrates why the paradigm needs to be abandoned, especially in fields where statistical model misspecification looms large and statistical power is low, such as in management accounting. In so doing, the analysis exposes why obtaining robust knowledge in management accounting has proved elusive. Additionally, it offers a new perspective on the reproducibility crisis and critical insights for improving statistical practice.

Global leadership research, like general leadership studies, is conceptually agnostic and amoral. This tendency can result in a limited understanding of how followers are affected by global leadership behavior and processes, ultimately restricting scholarly rigor and relevance. We identify two contemporary leadership theories that adopt a relational perspective: system leadership and complexity leadership. From these, we derive what leaders should do to enable system solutions to complex challenges. Interpreting both theories through a normative lens, we put forth that some of the key ethical principles underpinning system leaders are truth, care, and trust, incorporated within cycles of action and reflection. Principles of diversity, respect, dignity, compassion, and voice underpin the process of emergence relevant from the perspective of complexity leadership. Based on our deliberations, we suggest implications for global leadership research.

Since the COVID-19 pandemic had a significant impact on all facets of civilisation around the world, including food safety, this study aimed to determine and compare the pre-COVID and post-COVID food safety knowledge of Bangladeshi consumers and their association with sociodemographic variables.

The current study performed a cross-sectional survey of 503 consumers who prepared food at least 2–4 times per week through a validated questionnaire, selected through convenience sampling from two metropolitan cities and two rural districts in Bangladesh. The non-parametric Wilcoxon signed-rank test, Mann–Whitney U tests, Kruskal–Wallis H and binary logistic regression were used for statistical analysis.

Although an increased percentage of consumers showed a better level of overall food safety knowledge in the post-pandemic (38.2%) than the pre-pandemic (28.8%), there is a low level of awareness of the appropriate duration of handwashing, foodborne pathogens, consuming raw milk or eggs, safe storage and temperature control of food. University graduates, families with few children and urban consumers had a good understanding of food safety both pre- and post-pandemic.

This study compares consumers’ pre- and post-COVID-19 food safety knowledge previously unknown in Bangladesh. The findings have significantly contributed to existing food safety knowledge in Bangladesh to adopt policies and structure training programmes for consumers in the country.

This paper investigates the impact of ex-ante cybersecurity risks on stock market liquidity at the firm level.

Using a US sample of 10,719 firm-year observations from 2007 to 2018, we employ fixed effects regressions, an innovative ex-ante cybersecurity risks measure and control for various market microstructure and firm-specific characteristics to examine the research question. To address endogeneity concerns, a two-stage least squares regression analysis with instrument variables and a propensity-matched sample is utilized to validate the findings.

Our results show that ex-ante cybersecurity risks reduce stock liquidity in the form of higher bid-ask spreads and lower trading turnover. The findings are economically significant and accentuate the importance of cybersecurity risks to stakeholders, as a 1-standard deviation rise in cyber risks can increase bid-ask spreads by 15.55–31.20% and reduce trading turnover by 2.97%.

We provide empirical evidence on the important differences between the instrument choice of ex-ante versus ex-post cybersecurity risks for market microstructure studies. Prior research suggests ex-post cybersecurity breaches lead to lower bid-ask spreads and increased trading volumes. These findings are counterintuitive. Our study contributes a missing piece to this puzzle by showing that increases in ex-ante cybersecurity risks lead to wider bid-ask spreads and lower trading turnover, possibly due to heightened information asymmetry. Furthermore, we show that during periods of elevated market uncertainty, these cyber-risk effects may be “overlooked” as market participants may be preoccupied with greater concerns at the macroeconomic level.

This study aims to explore the strategies for implementing research data management (RDM) services in Tanzania’s higher education institutions (HEIs).

The study drew upon the technology, organization, people and environment (TOPE) framework. Using a qualitative case study approach, data was collected through semistructured interviews with librarians, lecturers, information and communication technologies (ICT) and research and innovation staff. Data was thematically analyzed.

Numerous participants recognized the importance of RDM services, such as creating data management plans, enhancing the retrieval and reuse of research data and offering support for data curation and preservation. The study also identified organizational support, including developing policies and guidelines, providing financial assistance and ensuring data security. Furthermore, the study highlighted the importance of ICT infrastructure, including servers, software and hardware. A lack of ICT infrastructure and limited skills and knowledge among those responsible for implementing RDM services were among the challenges identified.

This study used the TOPE framework, along with relevant literature, to guide the formulation of research objectives and questions. While the TOPE framework offers a comprehensive view through its four dimensions, there is a need to integrate additional models, such as data curation, to achieve a more holistic understanding.

This study provides valuable insights into strategies for implementing RDM services in HEIs. It highlights the importance of professional development for stakeholders, enabling them to develop and enforce effective strategies supporting a data-driven research agenda.

This study contributes original insights by outlining the necessary strategies for HEIs to consider when implementing RDM services. The study adds value to understanding effective RDM implementation requirements in an academic setting by identifying various strategies for developing RDM activities.

Focusing on the social influence processes in the context of massively multiplayer online role-playing games (MMORPGs), this study aims to investigate the nomological network of social influence factors, a topic seldom explicitly articulated in the literature in this unique context.

This study adopts a mixed-methods approach to develop and test a context-specific model of social influence processes in MMORPGs. First, the authors conducted qualitative interviews with MMORPG players to identify the drivers shaping players' perceptions of social influences. Second, the authors formulated and tested a research model with quantitative data collected from 450 respondents of an online survey.

Through the qualitative study, the authors identify leader enthusiasm, social support and social presence as the critical drivers of social influence factors. The result of the quantitative study validates the influences of the critical drivers and demonstrates the impact of social influences on MMORPG players' we-intention to continue playing games.

This research extends the social influence theory by identifying contextualized drivers that shape MMORPG players' perception of social influences determining their we-intention to continue playing games. MMORPG service providers can draw on these drivers to leverage social influences to increase players' we-intention of continuance.

Mega-infrastructure development plans pave the way for policies to upgrade the infrastructure, environmental management and different aspects of locals’ well-being. These developmental dynamics can positively affect rural tourism including heritage sites destinations. The quality of life of local people can be linked to this positive developmental change through long-term and sustainable economic revitalization projects. In terms of this process, developing large-scale infrastructure and incorporating tourism sustainability can improve the quality of life-related to different dimensions that are critical to the community's well-being. Therefore, researchers have attempted to address this issue.

Data were collected between September and October 2020. The study sample size was the residents of Zhabagly village, including Zhabagaly, Abaiyl and 115 Railway settlements. Moreover, the residents were older than 18 years. A systematic random sampling technique was utilised to reach the targeted sample size and the researchers received 243 responses from the locals. Structural equation modelling (SEM) was used for analysis.

The findings from the structural equation modelling suggest that sustainable tourism increases due to the positive effect of mega-infrastructure development and positively impacts the locals' quality of life. Notably, no direct effect of mega-infrastructure development on quality of life reveals the pivotal role of sustainable tourism. Therefore, during the COVID-19 period, the dimensions of sustainable tourism – economic, market, socio-cultural and environmental – played a role in securing the positive impact of mega-infrastructure development on the locals’ quality of life.

This research highlighted the fact that when infrastructure projects are implemented to their full potential, they will generate sustainable tourism activities, provide eco-adventure activities, relax, treat signatories and boost the economy of all stakeholders. The study used AMOS to test the hypotheses. Qualitative research methods, including interviews with citizens, government officials and tourism managers, require further study.

The infrastructural development on a mega-scale means building an upscaling tourism ecosystem. This ecosystem is marked by the availability of drinking water, waste and energy management facilities that support the elevation of living material, community, health, safety and emotional well-being. It reflects the policy-level implications for future Belt and Road initiatives (BRIs). The tourism industry's resilience during COVID-19 has practical lessons for other industries.

Large-scale infrastructure construction must create favourable conditions for the rapid development of tourism. The availability of clean water, waste and energy management facilities contributes to the food production, social cohesion, physical and mental health and general well-being of the ecosystem. This is one of the few studies that used sustainable tourism as a mediator between the impact of large infrastructure projects and their impact on the quality of life of locals during the COVID-19 pandemic. Aksu-Zhabagly, a World Heritage Site in Kazakhstan, was the site of this field study.

Artificial intelligence (AI) has the potential to address significant challenges in education, innovate learning and teaching practices and achieve SDG 4. However, existing literature often overlooks the behavioural aspects of students regarding AI in education, focusing predominantly on technical and pedagogical dimensions. Hence, this study aims to explore the significant relationships among AI literacy, AI usage, learning outcomes and academic performance of generation Z students in the Indian educational context.

The study used structural equation modelling (SEM) on Gen Z students born in the years 1997–2012 as a sample population for the research in the north Indian states like Punjab, Haryana, Himachal and regions like Chandigarh and N.C.R. Delhi.

The results established significant positive relationships between AI literacy, AI usage, AI learning outcomes and academic performance. Specifically, higher levels of AI literacy were associated with increased engagement with AI technologies and tools for learning purposes, leading to better learning outcomes and academic performance. The findings demonstrated that AI literacy plays a crucial role in providing effective learning experiences and fostering skills such as problem-solving and critical thinking among Gen Z students.

The implications of the study include the significance of integrating AI education initiatives into curricula, prioritising professional development programmes for educators and making sure that every student has equitable access to AI technologies.

The study introduces a novel perspective by examining variables such as AI literacy, AI usage, AI learning outcomes and academic performance and developing a model that has not been previously studied. It provides a new discourse and proposes a framework uniquely combining AI-infused curriculum design, educator empowerment, robust assessment mechanisms and sustainable practices.