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As the today's world is leading toward the digital dependency and after the world pandemic of COVID-19, the dependency of students and the university is completely through a digital medium, in context with that the higher education according to the demand of the generation is leading towards digital transformation. The digital transformation in the sector of education is the road map for the sustainable management and development of education. The digital transformation is the new pillar of education in which the students are mostly reliable. The digitalization in the field of education will lead to simple and clarified as well as multiple way for acquiring the knowledge. As the integration of the new model of education system is applied and implemented throughout the globe, the digital medium plays a significant role for the smooth and the systemic development of the model. In this chapter, the pathway for the development of the well-stable and well-developed strategies is considered in which the integration of the essential requirements, proper guidance, and advantages of the model is dependent for the transformation to digital medium of the higher education that will be leading to the development of the management and the education system. The foundation of that transformation model is detailed in the paper for the digitalization of higher education.

Criminological research, particularly in the Anglo-Saxon academic realm, has extensively examined the sharp increase in incarceration rates since the mid-1970s. Referred to as the “sociologies of the punitive turn” (Carrier, 2010), these studies argue that this surge reflects a sudden and harsh transformation in the logic governing penal practices and discourse. Some findings even suggest that this punitive shift has a global reach, impacting regions like Latin America. This broader narrative prompts an inquiry into whether a similar punitive turn occurred in Ecuador, a South American nation. Examination of prison demographics and legal frameworks in this country reveals a notable increase in incarceration rates during the 1990s, closely linked to drug trafficking control policies led by the United States. Consequently, I suggest that while the influence of neoliberal rationality, characteristic of the punitive turn, is evident, it’s more aptly described as a manifestation of punitive imperialism. Thus, it is imperative to analyze shifts in punishment trends within the framework of imperial dynamics, particularly considering the economic dependency of peripheral countries.

Nanosensors have a wide range of applications because of their high sensitivity, selectivity and specificity. In the past decade, extensive and pervasive research related to nanosensors has led to significant progress in diverse fields, such as biomedicine, environmental monitoring and industrial process control. This led to better and more efficient detection and monitoring of physical and chemical properties at better resolution, opening new horizons in the development of novel technologies and applications for improved human health, environment protection, enhanced industrial processes, etc.

In this paper, the authors discuss the application of citation network analysis in the field of nanosensor research and development. Cluster analysis was carried out using papers published in the field of nanomaterial-based sensor research, and an in-depth analysis was carried out to identify significant clusters. The purpose of this study is to provide researchers to identify a pathway to the emerging areas in the field of nanosensor research. The authors have illustrated the knowledge base, knowledge domain and knowledge progression of nanosensor research using the citation analysis based on 3,636 Science Citation Index papers published during the period 2011 to 2021.

Among these papers, the bibliographic study identified 809 significant research publications, 11 clusters, 556 research sector keywords, 1,296 main authors, 139 referenced authors, 63 nations, 206 organizations and 42 journals. The authors have identified single quantum dot (QD)-based nanosensor for biological applications, carbon dot-based nanosensors, self-powered triboelectric nanogenerator-based nanosensor and genetically encoded nanosensor as the significant research hotspots that came to the fore in recent years. The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

The future trend in nanosensor research might focus on the development of efficient and cost-effective designs for the detection of numerous environmental pollutants and biological molecules using mesostructured materials and QDs. It is also possible to optimize the detection methods using theoretical models, and generalized gradient approximation has great scope in sensor development.

This is a novel bibliometric analysis in the area of “nanomaterial based sensor,” which is carried out in CiteSpace software.

Introduction: Why companies pay dividends and the determinants of dividend policy are considered an unresolved dividend puzzle. To reach a consensus over the puzzle, researchers must investigate the factors affecting dividend policy by incorporating all the determinants into a single research effort.

Purpose: We examine the dividend policy determinants of Sri Lankan firms, explicitly focusing on the banking, finance, and insurance (BFI) sectors.

Methodology: This study uses the quantitative approach applying the Generalized Method of Moments (GMM) system to examine the dividend policy determinants by obtaining secondary data from 51 listed BFI organisations in Sri Lanka.

Findings: The analysis disclosed that the variables of changes in revenues, firm size, liquidity, corporate tax, business risk, and profitability have a positive relationship with dividend yield, whereas investment opportunities, leverage, change in revenues, corporate tax, and firm size impact positively on the propensity to pay dividends in BFI organisations in Sri Lanka. Our findings opine that managers in the BFI industries should prioritise changing their dividend policies by paying close attention to factors, such as dividend yield, changes in revenue, firm size, liquidity, corporate tax ratio, business risk, and profitability because the dividend policy is critical to retaining current investors and luring new ones.

Effective voice behavior in healthcare workers is critical for patient safety, quality improvement and workforce well-being. A review of the literature on voice behavior in healthcare highlights that little is known about the voice behaviors of new graduates in allied health and that current theory, from medical and nursing research, does not adequately apply to this sector. New knowledge about voice behavior for this sector of the workforce will support education and healthcare institutions in building and sustaining a healthy voice behavior culture.

This paper reports on phase two of a two-phase study looking at the voice behavior experiences of new allied health graduates over one year. Using a realist perspective and narrative analysis, we uncover and illustrate what works, with whom and under what conditions.

Four synthesized narratives outline the contexts and mechanisms that result in different voice behavior outcomes – speaking up effectively, speaking up with unmet expectations, not speaking up and a reduction in speaking up over time. Experiences of positive interprofessional collaboration and reflective supervision supported effective voice behavior.

This study used a case study approach, focusing on healthcare providers within a large New Zealand city and a cohort of 10 participants. Some researchers argue that small numbers limit the generalization of findings to different populations. Realists argue that, given the way in which knowledge is developed using realist methodologies, the resultant theory is portable. Interviews were conducted online during the COVID-19 pandemic. This may have impacted the connection between the interviewer and interviewee, causing the interviewees to not express their true thoughts. However, the interviewer did take time to connect with the interviewees and build trust over the three interviews over one year. Participants did not capture the diversity in the allied health workforce – most identified as female and none identified as Māori/Indigenous. And finally, participants could inhibit or exaggerate information due to the influence of social desirability. This does not appear to be a significant limitation in this study, given the many examples shared by the participants highlighted their challenges.

This study provides an in-depth exploration of how new graduates in allied health experience speaking up. Our findings enrich the knowledge of speaking up by using synthesized narratives to provide insights into what factors can enable a healthy speaking up culture within the new graduate allied health workforce. This is new knowledge that will be of interest at the individual, team and organizational levels of healthcare. The findings will support curriculum design and new graduate support frameworks for the education and health sectors. Highlighted in this study are the importance of the following factors in supporting speaking up for allied health new graduates: the employment of reflective supervision, purposeful facilitation of team belonging and interprofessional collaboration and tailored speaking up training for allied health new graduates and leaders in healthcare.

By taking a realist perspective and using narrative analysis, we gain an understanding of the voice behavior experiences of new graduates in allied health and the contextual factors and mechanisms that activate effective voice behavior in sub-acute and rehabilitation settings. These findings differ from nursing and medicine and highlight the benefits of reflective supervision and interprofessional collaborative practice.

The response of the receiver to a voiced patient safety concern is frequently cited as a barrier to health professionals speaking up. The authors describe a novel Receiver Mindset Framework (RMF) to help health professionals understand the importance of their response when spoken up to.

The framework draws on the broader receiver-focussed literature and integrates innovative findings from a series of empirical studies. These studies examined different receiver behaviour within vignettes, retrospective descriptions of real interactions and behaviour in a simulated interaction.

The authors' findings indicated that speaking up is an intergroup interaction where social identities, context and speaker stance intersect, directly influencing both perceptions of and responses to the message. The authors' studies demonstrated that when spoken up to, health professionals poorly manage their emotions and ineffectively clarify the speaker's concerns. Currently, targeted training for receivers is overwhelmingly absent from speaking-up programmes. The receiver mindset framework provides an evidence-based, healthcare specific, receiver-focussed framework to inform programmes.

Grounded in communication accommodation theory (CAT), the resulting framework shifts speaking up training from being only speaker skill focussed, to training that recognises speaking up as a mutual negotiation between the healthcare speaker and receiver. This framework provides healthcare professionals with a novel approach to use in response to speaking up that enhances their ability to listen, understand and engage in point-of-care negotiations to ensure the physical and psychological safety of patients and staff.

Factor investment is booming in global asset management, especially environmental, social, and governance (ESG), dividend yield, and volatility factors. In this chapter, we use data from the US securities market from 2003 to 2019 to predict dividends and volatility factors through machine learning and historical data–based methods. After that, we utilize particle swarm optimization to construct the Markowitz portfolio with limits on the number of assets and weight restrictions. The empirical results show that that the prediction ability using XGBoost is superior to the historical factor investment method. Moreover, the investment performance of our portfolio with ESG, high-yield, and low-volatility factors outperforms baseline methods, especially the S&P 500 ETF.

Our aim in this study is to investigate the relative importance of the economic policy uncertainty and of the geopolitical risk on U.S. REITs (Real Estate Investment Trusts) returns with a special focus on the different real estate sectors.

We use an augmented Fama-French (1993)’s asset pricing model, including economic policy uncertainty indices (EPU), introduced by Baker et al. (2016), and geopolitical risk indices (GPR) recently developed by Caldara and Iacoviello (2022), to price the potential risk factors for U.S. Nareit indices returns. To obtain robust economic results, we correct for the problems of errors-in-variables in linear asset pricing models; we advocate the use of higher moments estimators as instruments in a generalized method of moments (GMM) framework.

Our results report that economic policy uncertainty (EPU), and geopolitical risk (GPR) are priced for the different Nareit sectors for the last three decades. The GPR index stands as a relevant risk factor. The coefficient estimates are low compared to Fama-French risk factors. They are higher for Shopping Centers, Retail and Region Malls and lower for Health Care and Lodging/Resorts. EPU indices are also priced and less statistically significant. Health Care sector, followed by Shopping Centers and Retail are the most policy-sensitive sectors.

In their “2023–2024 Top Ten Issues Affecting Real Estate” “political unrest and global economic health” is ranked 1 issue by the Counselors of Real Estate. Our results report that economic policy uncertainty and geopolitical risk are priced for the different Nareit sectors. They suggest implications for investors, insurers, bankers, policymakers and other stakeholders. The geopolitical risk index (GPR) stands as a relevant and significant risk factor for REITs returns.

Based on parsimonious robust asset pricing models, the results shed a new light on the relative importance of geopolitical risk and economic policy uncertainty in the real estate sector, with a special focus on the different U.S. REITs sectors. They suggest possible implications for investors, insurers, bankers, policymakers and other stakeholders in a context marked by higher uncertainty shocks and geopolitical risks.

This study aims to explore how artificial intelligence (AI) tools influence the academic success and adaptation of international students in higher education. It examines the benefits, challenges and ethical considerations including academic integrity of integrating AI in learning environments.

An exploratory qualitative research approach was employed, utilising semi-structured interviews with postgraduate international students from diverse backgrounds.

The findings suggest that AI tools enhance academic performance by offering personalised learning, immediate feedback and efficient assessment. However, concerns about ethical use, over-reliance and the potential impact on critical thinking and academic integrity were prominent in the contexts of assessments and learning experiences.

The research offers unique insights by focusing on postgraduate international students, an often-underrepresented group in AI education studies. Their distinctive challenges, including adapting to new academic environments and overcoming language barriers, make them a particularly valuable sample for understanding the role of AI in higher education. This focus allows the study to contribute new perspectives on how generative AI (GenAI) tools like Grammarly and ChatGPT facilitate academic performance improvement, especially in enhancing writing proficiency and managing academic expectations. These findings extend the discussion by specifically addressing the experiences of international students in postgraduate studies, a demographic where AI’s impact has been less explored.

Purpose: This study focuses on the business case of Environmental, Social and Governance (ESG), namely its economic benefits and long-term value creation by attracting environmental-friendly and socially responsible investors.

Methodology: The central result of the von Neumann–Morgenstern (VNM) expected utility theory is that the optimal strategy under uncertainty is given by maximising the expected utility. The study introduces a second utility function to represent externalities. Total utility can be derived by a sum of the two functions where h is a scalar value which indicates to what degree the actor is interested in maximising the utility of externalities. The payouts could be set by ESG scores for the given companies, then the whole equation can be solved for simple cases such as the normal case.

Findings: By extending the traditional risk/return MPT framework to account for the additional utility of contributing towards externalities (in this case specifically ESG goals) the utility maximisation algorithm can be applied to the ESG dimension in a holistic manner and not as a separate filter on the investment universe nor a synthetic boost to expected returns.

Implications: Portfolio and asset managers can more efficiently optimise for consumer risk, return and sustainability preferences, allowing access to the widest possible investment universe while at the same time delivering an optimal bespoke solution for the specific sustainability preferences of the investors.

Future research: How to measure investment’s sustainability impact and what is the best way to estimate that. How to determine monetary impact of damages and externalities. Estimation of Hamilton’s coefficient.