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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.

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

This research paper investigates the theoretical frameworks encompassing a nuanced analysis of the digital divide in the Indian educational context, recognising that it is not merely a matter of technology access but also the ability to effectively use the resource for enhancing learning outcomes. This research provides valuable insights for fostering a more equitable and digitally inclusive learning environment by integrating conceptual insights with empirical evidence. The New Education Policy (NEP), India 2020 firmly emphasises the appropriate integration of technology into the teaching-learning process to develop relevant competencies. The pertinent question is, for India to conquer the second digital divide challenge, is the pace of technology accessibility and skill development sufficient?

The paper is a desk research, using secondary data from the Unified District Information System for Education (UDISE+), the Indian Government database of schools. A structured dataset has been created for all years, where states are grouped in descending ranking order of availability of infrastructure and teachers trained. A colour key segregates the States into three zones demonstrating their different levels of performance – high (green), moderate (blue) and low (yellow). The purpose is to identify state/s that have moved from one zone to another and, thereafter, analyse the reasons behind the movement.

Almost all states remained in the same digital resource availability zone for the four years studied, except for a limited few. Despite government interventions through higher budget allocation and targeted policies, growth rates of teacher training in computer usage slowed down post-COVID-19. A high positive correlation between Teachers' training in computer usage and the availability of computer and Internet facilities in schools indicates that an increase in digital infrastructure in schools is highly linked to teachers' training in computer usage and would ultimately translate into better use of digital resources to impart equitable education opportunities.

Primary data collection through interviews might have added to the critical findings. Therefore, researchers are encouraged to test the proposed propositions further on a case-by-case basis for any state under consideration.

Enhancing digital infrastructure in schools and building digital competence in teachers must be understood in the context of the learning organisation and the beneficiaries' attitudes at the meso-level to expand stakeholder motivation towards digital internalisation. This requires continuous engagement with education institutions as professional learning organisations, which will thereby help develop a decentralised context for teacher competency building. Collaboration, continuous monitoring of the outcomes of professional development programs, and sharing best practices are crucial in improving teacher readiness for digital education.

Access to tangible resources, such as computers, Internet connectivity and educational software, and developing intangible resources, such as teacher digital competencies, will play a pivotal role in shaping students' learning experiences. By studying the discrepancies in digital resource accessibility and teacher technology adoption, this research endeavours to add to the efforts towards enhancing the educational landscape.

This paper seeks to address a critical issue in the Indian education system and contribute to the ongoing effort to prevent the widening of the second and third digital divide in schools, and help achieve UN SDG Goals 4 and 10.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

The purpose of this paper is to scrutinise the effectiveness of four derivative exchanges’ enforcement efforts since 2007. These exchanges include the Commodity Exchange Inc. and ICE Futures US from the United States and ICE Futures Europe and the London Metal Exchange from the UK.

The paper examines 799 enforcement notices published by four exchanges through a behavioural science lens: HUMANS conceived by Hunt (2023) in Humanizing Rules: Bringing Behavioural Science to Ethics and Compliance.

The paper finds the effectiveness of the exchanges’ enforcement efforts to be a mixed picture as financial markets transition from the digital to artificial intelligence era. Humans remain a key cog in the wheel of market participants’ trading operations, albeit their roles have changed. Despite this, some elements of exchanges’ enforcement regimes have not kept pace with the move from floor to remote trading. However, in other respects, their efforts are or should be, effective, at least in behavioural terms.

The paper’s findings are arguably limited to exchanges based in Anglophone jurisdictions. The information published by the exchanges is variable, making “like-for-like” comparisons difficult in some areas.

The paper makes several recommendations that, if adopted, could help exchanges to increase the potency of their enforcement programmes.

A key aim of the paper is to shift the lens through which the debate concerning the efficacy of exchange-level oversight is conducted. Hitherto, a legal lens has been used, whereas this paper uses a behavioural lens.

This chapter provides a comprehensive exploration of global demographic trends and challenges, specifically focusing on Asian countries and the demographic landscape of Bangladesh. This chapter highlights the implications of rapid population growth, aging populations, and urbanization, analyzing their socioeconomic impacts on education, healthcare, and employment. By contextualizing these trends within the broader framework of sustainable development, this chapter sets the stage for understanding the intricate relationship between population dynamics and the empowerment of marginalized communities through family planning strategies.

Emotional labour (EL) is a complex phenomenon that has received increasing attention in recent years due to its impact on employee’s well-being and job satisfaction. For a comprehensive understanding of the evolving field of EL, it is important to extract different research trends, new developments and research directions in this domain. The study aims to reveal 13 prominent research topics based on the topic modelling analysis.

Using latent Dirichlet allocation (LDA) method, topic modelling is done on 1,462 journal research papers published between 1999 and 2023, extracted from the Scopus database using the keyword “EL”.

The analysis identifies several emerging trends in EL research, including emotional regulation training and job redesign. Similarly, the topics like EL strategies, cultural differences and EL, EL in hospitality, organizational support and EL, EL and gender and psychological well-being of nursing workers are popular research topics in this domain.

The findings provide valuable insights into the current state of EL research and can provide a direction for future research as well as assist organizations to design practices aimed at improving working conditions for employees in various industries.

Topic modelling on emotional labor is done. The paper identifies specific topics or clusters related to emotional labor, quantifies these topics using topic modeling, adds empirical rigor, and allows for comparisons across different contexts.

Technology advancement has changed how banks operate. Modernizing technology has, on the one hand, made it simpler for banks to do their daily business, but it has also increased cyberattacks. The purpose of the study is to to determine the factors that have the most effects on online fraud detection and to evaluate the advantages of AI and human psychology research in preventing online transaction fraud. Artificial intelligence has been used to create new techniques for both detecting and preventing cybercrimes. Fraud has also been facilitated in some organizations via employee participation.

The main objective of the research approach is to guide the researcher at every stage to realize the main objectives of the study. This quantitative study used a survey-based methodology. Because it allows for both unbiased analysis of the relationship between components and prediction, a quantitative approach was adopted. The study of the body of literature, the design of research questions and the development of instruments and procedures for data collection, analysis and modeling are all part of the research process. The study evaluated the data using Matlab and a structured model analysis method. For reliability analysis and descriptive statistics, IBM SPSS Statistics was used. Reliability and validity were assessed using the measurement model, and the postulated relationship was investigated using the structural model.

There is a risk in scaling at a fast pace, 3D secure is used payer authentication has a maximum mean of 3.830 with SD of 0.7587 and 0.7638, and (CE2).

This study focused on investigating the benefits of artificial intelligence and human personality study in online transaction fraud and to determine the factors that affect something most strongly on online fraud detection. Artificial intelligence and human personality in the Indian banking industry have been emphasized by the current research. The study revealed the benefits of artificial intelligence and human personality like awareness, subjective norms, faster and more efficient detection and cost-effectiveness significantly impact (accept) online fraud detection in the Indian banking industry. Also, security measures and better prediction do not significantly impact (reject) online fraud detection in the Indian banking industry.

In 2022, the Baltimore professional development school (PDS) partner schools, John Ruhruh Elementary/Middle School (JREMS) and Notre Dame of Maryland University (NDMU) received funds through a Maryland Educational Emergency Revitalization (MEER) grant to determine (a) to what extent additional resources and professional development would increase JREMS teachers’ efficacy in technology integration and (b) to what extent NDMU professional development in the form of workshops and self-paced computer science modules would result in greater use of technology in the JREMS K-8 classrooms. Results indicated a statistically significant improvement in both teacher comfort with technology and integrated use of technology in instruction.

Survey data were collected on teacher-stated comfort with technology before and after grant implementation. Teachers’ use of technology was also measured by unannounced classroom visits by administration before and after the grant implementation and through artifacts teachers submitted during NDMU professional development modules.

Results showing significant increases in self-efficacy with technology along with teacher integration of technology exemplify the benefits of a PDS partnership.

This initiative was original in its approach to teacher development by replacing required teacher professional development with an invitation to participate and an incentive for participation (a personal MacBook) that met the stated needs of teachers. Teacher motivation was strong because teammates in a strong PDS partnership provided the necessary supports to induce changes in teacher self-efficacy.