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This study is a theory-building effort to extend the risk perception attitude (RPA) framework by considering an organization-related factor. Specifically, this study examined how an organization-related factor, namely safety climate, and individual-related factors, namely risk perception and efficacy belief, jointly influence flight attendants’ occupational health and safety (OHS) information seeking intent.

About 486 flight attendants from an international air carrier, based in Hong Kong, participated in an online survey. Hierarchical regression was employed to examine the three-way interaction of risk perception, efficacy belief, and safety climate.

Results showed that safety climate moderated the effect of efficacy belief on the relationship between risk perception and OHS information seeking intent. For flight attendants who perceived a high safety climate, those who felt more efficacious had a higher intent for OHS information seeking than those who felt less efficacious. In contrast, for flight attendants who perceived a low safety climate, when they perceived a high level of risk, those with low efficacy had a higher information seeking intent than those with high efficacy.

Although the RPA framework has shown its potential to explicate how individual employees engage in OHS information seeking behavior, the framework has largely overlooked the importance of organization-related factors as an influential shaping force of individual employees’ behavior. To fill this research gap, this study extends the RPA framework by examining how safety climate moderates the relationship between risk perception and efficacy belief on flight attendants’ OHS information seeking intent. Safety climate also plays an important role in segmenting audience groups for OHS promotion.

In this introductory chapter, we collaborate on how digital transformation (DT) supports a value-driven educational approach, emphasizing the need for regular assessments of stakeholder needs, enhancing students' abilities to solve complex problems, applying learned knowledge effectively, nurturing creativity, and boosting employment prospects through skill development. Strategic considerations for implementing DT include creating a shared vision through collaborative strategy development, establishing clear objectives, designing a detailed action plan for DT initiatives, encouraging active participation from all educational community members, and maintaining the DT strategy through continuous evaluation and adaptation. By interweaving DT with these strategic educational priorities, higher education institutions can not only improve the learning experience but also equip students to succeed in a rapidly evolving future.

The evolution of Artificial Intelligence (AI) in higher education marks a paradigm shift, driving significant changes in pedagogical approaches and learning methodologies. With the rise of generative AI and artificial general intelligence (AGI), institutions have witnessed a transformative era where traditional content creation and delivery are being redefined. Start-ups like OpenAI and Anthropic have been at the forefront, offering tools like ChatGPT and Claude-3, which reshape natural language processing and forecast a future where AI integrations are seamless and pervasive. This chapter provides a critical overview of the current AI-driven applications enhancing personalized learning, content generation, and remote learning. Tools such as Mainstay, CourseGenie, and AIDES demonstrate AI's capacity to improve student engagement and success rates, while Degreed and Gnowbe showcase the broadening horizons of AI in skills building and microlearning experiences. Furthermore, platforms like Elicit and Research Rabbit exemplify the transformation in research and academic writing, albeit not without raising ethical concerns. In conclusion, AI's permanence in the educational landscape is unquestionable, calling for strategic frameworks that empower educators and students to harness its benefits effectively. The imminent expansion of the AI tool ecosystem necessitates preparedness for substantial shifts in educational practices, where ethical considerations and value-based strategies become paramount. Higher education institutions must align with this technological momentum, ensuring AI's potential is maximized in an ethical, inclusive, and impactful manner.

The dawn of Artificial Intelligence (AI) in higher education (HE) is not just on the horizon; it's here, promising a transformative leap forward. This shift is not simply about adopting new technologies; it's about redefining educational paradigms to meet specific challenges – from enhancing support and critical thinking to improving outcomes and fostering teamwork. This chapter outlines a comprehensive strategy to integrate AI into HE, spotlighting personalized learning, content generation, and remote learning, among others, as key domains ripe for AI's influence. An effective AI strategy will foster excellence and enable HE institutions to unlock the potential of technology for students and faculty alike. At its core, the proposed AI development strategy targets five critical areas: training, career growth, skill enhancement, learning, and team building. These areas ensure that all HE community members are well-equipped to navigate the AI-enhanced landscape of future jobs and challenges. However, realizing the full benefits of AI transcends the deployment of tools and systems; it requires strategic planning, investment in people, and policy changes. HE must cultivate champions to spearhead this transformation, emphasizing that success is not just measured in output but in the cultivation of socially responsible citizens. To harness AI's full capacity, we must transcend outdated stereotypes and metrics, fostering an educational environment that prepares students for the future. The ultimate goal is not just to integrate AI into HE but to use it as a catalyst for growth, innovation, and a better future for all.

This chapter delves into the pivotal role of digital transformation (DT) strategies in fostering educational innovation, particularly through the lens of transformative learning (TL). By outlining a five-stage TL model, we explore how DT strategies can not only support but also significantly enhance educational reforms. Actions and multipliers, constituting the core elements of this model, interact dynamically to advance TL within academic institutions. Actions, such as strategic initiatives and the development of learning environments, account for the tangible steps toward transformation. Meanwhile, multipliers amplify these efforts, emphasizing the importance of strategy, commitment and the sustainable impact of educational transformations. We also highlight the emerging influence of artificial intelligence (AI) in reshaping learning contexts, demonstrating its capacity to personalize learning experiences and foster problem-solving skills. Additionally, we envision the future trajectory of higher education (HE) toward 2035, emphasizing the integration of AI and DT in creating a responsive and adaptive educational ecosystem. This chapter argues that DT is not just a tool but also a catalyst for active and transformative learning, proposing a holistic approach to integrating technology in education that addresses current challenges and anticipates future needs.

This study examines the moderating role of female directors on the relationship between the firms’ characteristics and tax avoidance in an emerging economy.

This study employs the second-generation unit root test and the generalised method of moments (GMM) techniques. The Kao residual cointegration test corroborates a long-run cointegration among variables.

Female directors demonstrate mixed and unusual findings. No significant impact of female directors on tax avoidance is found. In addition, the presence of female directors does not show any negative or significant moderating impacts on the relationship between leverage, firm age, board size and tax avoidance. However, having more female directors can negatively and significantly moderate the relationship between more profitable firms, larger firms and tax avoidance. These findings show that the board of directors could use the presence of female directors to maximise their opportunistic behaviour, such as to avoid tax.

Research limitations – The study is limited by considering only 62 listed firms. The scope could be extended to include non-listed firms.

Research implications – There is increasing pressure for female directors on boards from diverse stakeholders, such as the European Commission, national governments, politicians, employer lobby groups, shareholders, and Fortune and Financial Times Stock Exchange (FTSE) rankings. This study provides input to decision-makers putting gender quota laws into practice. Our findings can help policy-makers adopt regulatory reforms to control tax avoidance practices and enhance organisational legitimacy. Policymakers can change their policy to include female directors up to the threshold suggested by the critical mass theory.

This is the first attempt in Bangladesh to explore the role of female directors in the relationship between the firms' characteristics and tax avoidance. The current study has significant ramifications for bringing gender diversity into practice as a component of good corporate governance.

The transtheoretical model (TTM) has been applied to varying areas of physical health, e.g. diabetes. However, research into its applicability to psychotherapy is mixed. The TTM is applied through the University of Rhode Island Change Assessment (URICA). Investigating the utility of the URICA is needed to improve patient care and outcomes. This study aims to assess whether the URICA scores relate to patient outcomes; patient attendance; practitioner ratings of patient readiness, appropriateness, insight, motivation and potential for improvement; and to explore practitioner’s perspectives on the URICA.

Correlational methods were used to assess the relationship between the URICA and therapeutic outcome, attendance and practitioner-rated areas. Content analysis was used to analyse practitioner qualitative data.

The URICA did not correlate with either therapeutic outcome or attendance. A significant negative correlation was found between the URICA and practitioner-rated appropriateness of the referral. This means practitioners perceived individuals with lower URICA scores to be a more appropriate referral, despite the score indicating a reduced readiness to change. Qualitative categories included positive views, negative views, ambivalence and changes to measure and process. To conclude, the URICA does not explain a patient’s outcome or attendance. The URICA may not be appropriate to use in its current format in mental health services; therefore, assessing the TTM verbally may be more helpful.

This study provides research into suitability of using the URICA to assess the TTM and its applicability to attendance and outcome in psychological therapies.

Using an international sample of firms affiliated with a business group, this paper aims to investigate the audit quality of common auditors, i.e. auditors shared by multiple firms affiliated with the same business group.

This paper utilizes a large sample of group-affiliated firms from 35 regions. Following the frameworks of DeFond and Zhang (2014) and Fung et al. (2017), this paper measures audit quality using the absolute value of abnormal accruals and modified audit opinions. Ordinary least squares (OLS) regression is used to address the research question.

The findings demonstrate that audit quality improves for firms that share the same auditor with other group members. Importantly, cross-country analyses reveal that this relationship is stronger when auditors operate in countries with stricter local auditor inspection programs and an overall opaque information environment. Additionally, the impact of common auditors on audit quality is more pronounced for group affiliates that have a more opaque firm-level information environment and are monitored by heightened institutional ownership.

While affiliates are more likely to select the same audit firms as common auditors, the evidence regarding the effects of common auditors is mixed. The results of this study provide further insights into auditor choices for group-affiliated firms and offer a potential avenue for better protecting shareholders' interests.

The results of this study add to the ongoing debates regarding the costs and benefits of common auditor choice for group affiliates. To the best of the authors’ knowledge, this study is the first to demonstrate that the effects of common auditors may vary in different external environments.

Introduction: Political stability is an essential source of stock market dynamics. Investors are confident about countries that have higher political stability. Political stability in an economy enables investors to develop their ability to predict the future and thus to tend towards longer-term and permanent economic and financial activities.

Purpose: The study aimed to investigate the impact of political instability in BRICS countries and Türkiye on their stock market volatilities.

Methodology: The study analysed the univariate exponential generalised autoregressive conditional heteroskedasticity (EGARCH) Model. The model employed the credit default swap (CDS) 5-year USD Bond data of the BRICS countries and Türkiye to represent political instability. The daily stock exchange index return data from 1 January 2015 to 15 January 2023 was used for model estimation.

Findings: The results of the EGARCH model indicate that political instability is a crucial factor in stock market volatility. The coefficients suggest that when CDS increases in BRICS countries and Türkiye, the volatility of stock returns also increases. The analysis shows that the impact of political instability on the stock market of BRICS countries and Türkiye is not uniform. However, the significant effect of political instability on volatility is higher for Türkiye than for BRICS countries. This indicates that investors perceive the political risk of Türkiye to be greater than that of BRICS countries when investing in the stock market of Türkiye.

This study examines the impact of profitability, firm size and leverage on corporate tax avoidance in Bangladesh, an emerging South Asian economy.

A balanced panel data of 62 firms from Dhaka and Chittagong stock exchanges in Bangladesh from 2009 to 2020 were used to run the regression. This study employed the fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to examine the hypotheses.

The findings show that large firms positively impact corporate tax avoidance. Similarly, profitability and leverage are positively associated with tax avoidance, and the results are significant. Furthermore, the study conducts robustness tests that confirm the findings.

The use of cash effective tax rate (ETR) to investigate firms’ tax avoidance practices poses some limitations, and the results should be interpreted cautiously.

The current study may help policymakers better enhance tax collection from business firms. The findings could serve as a valuable input for effectively monitoring tax collection from large profit-earning firms.

To the authors' best knowledge, this is the first historical attempt in Bangladesh to use panel data to examine the relationship between the firm’s level characteristics and corporate tax avoidance. Panel data often provides greater flexibility with large data, simplifying calculation and statistical analysis.