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The global non-attainment of the Sustainable Development Goal (SDG) 5 indicates the issue of rising gender inequality. Educated women shying away from the labor force is worsening it. The labor market dynamics might shape the female labor force participation (FLFP). The present study recommends a policy framework by analyzing this dynamism across 125 countries over 1990–2020.

The Two-step System Generalized Method of Moments is used to address endogeneity bias. Dynamism in policy environment is captured by relaxing the Ceteris Paribus condition in the empirical model.

Results show that the moderation of labor market factors has increased with the attainment of Secondary and Tertiary Education. Results also highlight that these factors promote FLFP through prospective opportunities but also hinder female participation through employer’s discrimination despite educational attainment.

Studies have examined the role of education on FLFP. However, prior research has not investigated the role of labor market factors in influencing the impact of education on FLFP. The consideration of these factors will help in addressing the global policy lacuna by recommending a policy framework for enhancing FLFP through internalization of the externalities exerted by the labor market factors, and thereby, help the countries attaining the SDG 5 objectives.

COVID-19 has affected the economies adversely from all sides. The sudden halt in production has impacted both the supply and demand sides. It calls for analysis to quantify the impact of the reduction in economic activity on the economy-wide variables so that appropriate steps can be taken. This study aims to evaluate the sensitivity of various sectors of the Indian economy to this dual shock.

The eight-sector open economy general equilibrium Global Trade Analysis Project (GTAP) model has been simulated to evaluate the sector-specific effects of a fall in economic activity due to COVID-19. This model uses an economy-wide accounting framework to quantify the impact of a shock on the given equilibrium economy and report the post-simulation new equilibrium values.

The empirical results state that welfare for the Indian economy falls to the tune of 7.70% due to output shock. Because of demand–supply linkages, it also impacts the inter- and intra-industry flows, demand for factors of production and imports. There is a momentous fall in the demand for factor endowments from all sectors. Among those, the trade-hotel-transport and manufacturing sectors are in the first two positions from the top. The study recommends an immediate revival of the manufacturing and trade-hotel-transport sectors to get the Indian economy back on track.

The present study has modified the existing GTAP model accounting framework through unemployment and output closures to account for the impact of change in sectoral output due to COVID-19 on the level of employment and other macroeconomic variables.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.

Despite the unique features and potential applications in various industries, widespread blockchain adoption is hindered for several reasons. One of them is the lack of government regulations regarding blockchain and cryptocurrencies. However, a deliberate preliminary analysis of the policy initiatives by various jurisdictions proved otherwise, and a lack of sound academic literature on the policy initiatives on blockchain worldwide was evident. Addressing this gap, this study aims to summarize the policy initiatives of jurisdictions around the world, assessing if governments do not enact many regulations.

A systematic literature review was adopted in this study, in which the authors shortlisted a set of research papers and policy reports using several selection criteria and a screening process.

It was found that numerous policy initiatives have been enacted by governments worldwide, and blockchain applications are also being piloted or practiced successfully in several nations. It was also evident that governments are reluctant to accept cryptocurrencies as legal tender while embracing their underlying technology, blockchain.

To the best of the authors’ knowledge, this paper appears to be one of the first attempts to summarize the blockchain policy initiatives contributing to the body of knowledge on blockchain adoption.

This study aims to address the existing knowledge gap by investigating teachers’ adoption of ChatGPT for educational purposes. The study specifically focuses on identifying the factors that motivate and inhibit teachers in adoption of ChatGPT in higher education institutions (HEIs).

This research has used interpretative phenomenological analysis – a qualitative approach. Through in-depth interviews among the teachers, data was collected to identify the motivating and inhibiting factors that impacted teachers’ willingness to adopt ChatGPT. The data was collected from 48 teachers working across HEIs of Uttarakhand region in India.

The analysis revealed seven themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purposes. These include time factor, tool for competitive edge, learning enhancement tool for students, research facilitator, benefits in educational settings, troubleshooter and easy to use. On the other hand, inhibiting factors comprise five themes, which include technical difficulties, limited features for educational and research purposes, tool for handicapping innovation and creativity, lack of personal touch and ethical considerations.

The findings will be valuable for HEIs in establishing policies that promote the appropriate and effective use of ChatGPT. Moreover, the study provides recommendations to ChatGPT solution providers for improving ChatGPT services for effective adoption of ChatGPT among teachers and implementation at HEIs. Further, it contributes to the body of literature by filling a knowledge gap about teacher adoption of ChatGPT in the HEIs. Through qualitative research, the study has pinpointed specific motivating and inhibiting factors that affect teacher adoption of ChatGPT.

Unlike previous studies that primarily explored the potential advantages and drawbacks of ChatGPT in education, this research study delves deeper into the topic. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers by identifying distinct factors that either motivate or inhibit teachers from adopting ChatGPT for job related purposes. The study provides novel insights that were previously mislaid, thereby introducing a fresh perspective to the existing literature

Improving health outcomes requires a robust health-care service model that delivers cost-efficient services and increase customer patronage. The purpose of this study is to examine how service quality and convenience influence perceived value, satisfaction and customer patronage of health insurance policyholders. Based on contemporary research, this study further investigates the moderating role of trust, inertia, insurer type and word-of-mouth (WOM) on relationship between satisfaction and customer patronage.

This study conceptualized the dimensions of SERVQUAL and SERVCON as drivers of perceived value leading to satisfaction and finally customer patronage in presence of four moderators. To test the hypotheses, data from 500 consumers who had a running health insurance policy was collected and analyzed using partial least square path modeling.

The results of this study showed service quality and convenience dimensions significantly affected perceived value. Perceived value strongly influenced satisfaction and customer patronage intentions. Satisfaction had a significant positive effect on patronage. WOM and trust moderated the satisfaction–patronage relationship for recommendation intention but not repurchase intention. The moderators had an indirect bearing on customer patronage.

Such an engagement ecosystem can be considered to be a revolution, as it will change the way businesses are conducted and how stakeholders interact with one another.

This study adapts and integrates the SERVQUAL and SERVCON models to health insurance domain. Second, this study conceptualizes a modified view of post-benefit convenience relevant for health insurance as policy renewal intention rather than returns/exchanges. This addresses a gap in the SERVCON scale's applicability to insurance services. This study also makes a novel attempt of examining implication of WOM and trust in health insurance domain.

The need to enhance student support is evident in higher education (HE) curricula. In addition to the complications created by the COVID-19 pandemic, the current strategies used in academia are criticised for their lack of appropriate student support in HE. The study focused on the themes under Section 4 of the National Student Survey (NSS): availability to contact tutors, receiving good advice and guidance and availability of good advice. The study aimed to provide recommendations for enhancing academic support by developing drivers that need implementation during course delivery.

A documental analysis and a qualitative survey were adopted for this study. A documental analysis of 334 mid-module reviews (MMRs) from levels three to six students in the built environment (BE) discipline. Critical themes identified from the MMRs were fed forward in developing a questionnaire for academics. A sample of 23 academics, including a Head of school, a Principal lecturer, Subject leads and Lecturers, participated in the questionnaire survey. Content analysis is adopted through questionnaire data to develop drivers to enhance academic support in BE. These drivers are then modelled by interpretive structural modelling (ISM) to identify their correlation to NSS Section 4 themes. A level partition analysis establishes how influential they are in enhancing academic support.

The study identified nine drivers, where two drivers were categorised as fundamental, two as significant, four as important, and one insignificant in enhancing academic support in HE. Module leaders’/tutors’ improving awareness and detailing how academic support is provided were identified as fundamental. Differentiating roles in giving advice and the importance of one-to-one meetings were identified as significant. A level partitioning diagram was developed from the nine drivers to illustrate how these drivers need to be implemented to promote the best practices in academic support in HE.

The identified drivers and their categories can be used to set prioritised guidelines for academics and other educational institutions to improve students’ overall satisfaction.

Novelty from the study will be the developed drivers and the level partitioning diagram to assist academics and academic institutions in successfully integrating academic support into HE curricula.

Internal workplace coaches are employees who, in addition to their main job, volunteer to provide coaching to work colleagues who are not their direct reports. The purpose of this paper is to explore what motivates these individuals to volunteer to be an internal workplace coach and to continue carrying out the role.

To explore the experiences of internal coaches, a questionnaire was devised and issued; it attracted 484 responses – the largest survey response to date from this population. Following analysis of the questionnaire data, semi-structured interviews were carried out with 20 internal coaches from private, public and not-for-profit UK organisations. The responses were analysed in relation to motivation theory, principally self-determination theory.

Individuals were motivated to volunteer for the role, and to continue to practise as coaches, in the most part to satisfy intrinsic needs for competence, relatedness and autonomy. The research presents rich information about how coaches perceived these needs were satisfied by coaching. In general, there were only moderate or poor levels of support and recognition for individual coaches within their organisation, indicating limited extrinsic motivation.

The practical implications are that organisations can draw on the findings from this study to motivate individuals to volunteer to be internal coaches and to continue to act in that role.

Many organisations use internal coaches, but there is very little research into what motivates these volunteers.

In this study, the authors propose a novel digital twinning approach specifically designed for controlling transient thermal systems. The purpose of this study is to harness the combined power of deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical system.

To achieve this goal, we introduce a deep neural network (DNN) as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is used to address the challenges of controlling an unsteady heat transfer problem with an integrated feedback loop.

The results of our study demonstrate the effectiveness of the proposed digital twinning approach in regulating the maximum temperature within the system under varying and unsteady heat flux conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful evaluations should be conducted if such a training approach, based on steady-state data, is applied to completely different transient heat transfer problems.

The present work represents one of the first examples of a comprehensive digital twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this approach is its robustness. Adopting a training based on dimensionless data, the approach can seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for retraining.

The Scottish Government hope to pilot judge only rape trials to increase the woefully low rape conviction rates in Scotland. The reasoning is that by removing jurors, the court will be attenuating the role that rape myths and other cognitive and social biases have on conviction rates. However, a plethora of research from cognitive and social psychology, legal literature and decision-making science has shown that experts, including judges and other legal professionals, may be no less biased than laypeople. This paper aims to outline the research highlighting that experts may also be biased, why biases in judges can be elicited, and potential alternative recommendations (i.e. deselecting jurors who score highly on rape myths and providing training/education for jurors). Furthermore, piloting with real judges, in real trials, may not be best practice. Therefore, the authors recommend that any piloting is preceded by experimental research.

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Furthermore, piloting with real judges, in real trials, may not be best practice; therefore, the authors recommend that any piloting is preceded by experimental research.

To the best of the authors’ knowledge, this research is the first of its kind to directly compared the decision-making of jurors and judges within the current Scottish legal context.