Global journal of Business and Integral Security

Systematic Literature Review of Applications of Data Science Techniques in the Domain of Indian Stock Markets With a Focus on Identifying Investor Opportunities

Sulekha Aloorravi, Vijayakumar Varadarajan — Wed, 23 Apr 2025 00:00:00 +0000

Any investment model relies on capital for the investment to grow. The investment model such as Indian stock market relies on public to invest their savings and the investments thus acts as a source for the growth of both the individual investor and the country’s economy. In India, a very small proportion of the population invests in stock markets while there is a large proportion with capital and do not invest due to the lack of adequate knowledge or due to the lack of adequate understanding on how to utilize the public information available on the markets. In this study, the scope is to perform a systematic literature review to understand what level of analytics and applications of data science are available for individuals to understand how publicly available data can be used along with data science techniques on stock markets.

Keywords: Opportunity Cost, Stock Market, Machine Learning, Deep Learning.

A Study On Advanced Frameworks For Enhancing Personal Identity Protection And Information Security In Digital Environment

Siggy Simon — Thu, 17 Apr 2025 00:00:00 +0000

This study investigates advanced frameworks for enhancing personal identity protection and information security within digital environments, addressing the growing risks associated with data breaches, identity theft, and cyber-attacks. As digital interactions proliferate, traditional security frameworks struggle to keep up with increasingly sophisticated threats, highlighting the need for proactive, adaptive, and technology-driven solutions. This research explores the potential of integrating advanced technologies such as artificial intelligence (AI), machine learning (ML), and blockchain to improve real-time threat detection, enhance data
integrity, and create flexible security systems capable of evolving alongside emerging threats.
Using a qualitative methodology, data was gathered from 138 respondents, reaching sample saturation, and analyzed through thematic analysis to identify key themes, including the limitations of existing frameworks, the role of user education, and the significance of global best practices. Findings reveal that implementing Privacy-by-Design, adopting predictive analytics, and developing modular security frameworks can address current security gaps.
Additionally, user education and adherence to global standards like GDPR and NIST are essential in fostering a secure, user-centered approach to digital interactions.
This study contributes to the field of cybersecurity by proposing actionable recommendations for organizations, policymakers, and technology developers, emphasizing a multi-layered approach to identity protection and information security. The insights from this research offer a pathway toward building resilient digital security frameworks that safeguard personal data while adapting to the dynamic landscape of modern cyber threats.

Oversight Methodologies for Artificial Intelligence Implementation in the Energy Sector

Cedric Alwyn Worthmann — Thu, 17 Apr 2025 00:00:00 +0000

Humankind has been intrigued by Artificial Intelligence (AI) for decades (Fenwick and Molnar, 2022) as it is foreseen as a tool to improve efficiencies, further organizational interests, and improve societal well-being. Over the past years, there have been advancements in developing and deploying AI systems and tools in many critical services sectors, influencing organizations and people with a mixed level of benefits, successes, and risks.
The research aimed to understand the current knowledge base and gaps concerning the compliance oversight for the safe development, deployment, implementation, and use of AI systems within critical infrastructure services, specifically focusing on the energy or electricity sector. The driving factor for this research is that within the critical infrastructure and services sectors, incorrect decisions influence more than financial returns but can cause severe equipment damage, premature failure, and harm to people.
The outcome of this research is a unique AI compliance audit framework development procedure, AI compliance audit framework, and AI audit process, which is a fit-for-purpose compliance solution driven from a senior executive management level, integrated into specific existing compliance or governance processes, which is more advanced than the existing AI governance frameworks, audit mechanisms, and checklists.
This research significantly contributes to the industry and sector by providing a practical structure that can be utilized to safely and sustainably implement AI systems in this critical sector. The AI compliance audit framework is a mechanism that allows the energy sector to place guardrails around the AI system that they are procuring or developing throughout its lifecycle. The framework considers a multi-dimensional audit regime, which can seamlessly integrate into existing quality, information technology, or environmental assurance processes. Notably, the framework ensures that the energy sector considers the integrated software systems collectively when auditing and ensuring compliance, not as individual components.
Lastly, the research provides a foundational structure for future researchers to expand on, focusing on gaps within the current governance structures, training regimes, and approaches to building a sustainable AI system environment.

A Proposed Model to Generate New Revenue Streams for Telecommunications Customer Service Providers (CSP) by Leveraging the Existing Infrastructure and Market Reach

Abhijit Shamkant Atale — Thu, 17 Apr 2025 00:00:00 +0000

Telecommunications Customer Services Providers, also known as customer service providers or CSPs have experienced a significant drop in their profitability in recent years. This phenomenon is global, in developed and developing markets alike. With new developments in the technology around 5G, IoT, Cloud, Blockchain and AI, many new avenues for revenue growth are opening up for the Telecom Service Providers (CSPs). While many Telecom Service Providers (CSPs) have tried various initiatives with new technologies, it has given only moderate success so far. There is no clear business model which would unlock sustainable and profitable growth for the Telecom Service Providers (CSPs). Through this research, I have tried to co-relate inside-out and outside-in perspectives through targeted interviews with senior professionals associated with the Telecom industry as well as consumers of telecom services in retail and enterprise segments, in to derive a framework model for the Telecom Service Providers (CSPs) to return to profitable growth, backed up with a comprehensive set of recommendations for the Telecom Service Providers (CSPs) to adopt in their business strategy for the future.

Generative Artificial Intelligence: Positive Impact on American Financial Institutions

Ravindra Nagvekar — Thu, 17 Apr 2025 00:00:00 +0000

Generative Artificial intelligence (GenAI) has played a significant role in influencing the operations of the financial institutions through monitoring market risks and credit risks. The purpose of this study is to determine the positive impacts of Generative AI on the American financial institutions. “Generative adversarial network” of the GenAI streamline the process of content development that supports managers of financial institutions for personalised advice. Additionally, analysis of historical data giddies up the process of decision making by analysing the sentiment of the current market. Furthermore, GenAI develop simulation based on the current data that assists in the evaluating different scenario that ease the process of decision making for financial institution.
Literature review chapter has reviewed the positive impacts of the GenAI within the financial institutions. It has been found that the theories like technology acceptance model and theory of reasoned action are beneficial for determining the behaviour of the financial institutions at the time of using GenAI. Implication of theories has effectively paved the way of conducting research within the context of implication of GenAI in financial institutions. Developing in-depth comparing between Predictive AI and Generative AI has also determined accessibility of GenAI capabilities in financial institutions.
Methodology chapter has supported this study to identify the most suitable methods for this research such as philosophy, approach, design of this research, data collection, and review of the research problem, questions, sampling, and data analysis. Primary quantitative research design helped this study to gather relevant information related to the positive impacts of GenAI on the financial institutions of North America through reliable primary sources. Positivism research philosophy was integrated for designing the research methodology as it views the phenomenon of Gen AI’s impact on financial institutions of North America. Additionally, integration of deductive research approach ensure evaluation of GAI’s impacts like risk assessment, investment decision through evaluating empirical evidence. Based upon the factors of philosophy and approach, quantitative strategy was undertaken to gain better visualisation on Gen AI’s impacts in finance. Apart from this, questionnaire was used as research instrument for collection of relevant information through closed ended questions. Therefore, survey of 35 participants allows opportunity to capture’s it’s their experience on the impact of Gen AI within financial institute of North America.
Use of Generative AI has played a major role for developing customer services of financial institutions for offering virtual assistants to customers with the use of AI chat bots. The study focuses on the outcome of the survey question that young adults are most aware about the application of modern technologies along with its impacts due to the exposures of technology in American Financial Institutions. Financial institutions of North America can focus on proactive risk management with the integration of Generative AI due to the ability for improving risk management strategy in customer satisfaction.
From the data analysis, generative artificial intelligence in managing financial institution activity along with opening new avenues in managing decision making, and predictive capability of American Financial Institution has obtained. It is seen that most of the respondents agreed that generative AI is effective in managing financial facilities in reducing issues regarding intellectual property.
Discussion on primary data analysis and previous theoretical framework helped to address an inclusion of GenAI over financial decision-making for North American institutions. Meeting research questions was an important part of this chapter to incorporate financial planning for organisations. Meaningful insight creation from vast amount of data set helps to banking employee to overcome banking operational challenges like employee abuse, intellectual property pressure.

How Stress Contributes to Workplace Errors and Incidents

Ashutosh Sharma — Thu, 17 Apr 2025 00:00:00 +0000

Stress can be defined as a state of mental pressure or concern caused by a difficult, unplanned, or unpleasant situation. These situations can arise from personal, professional, or external factors. These pressures (direct/indirect) are mostly generated from human’s own decisions or external factors that normally humans can’t control.
Workplace incidents refer to any unexpected and undesirable events that occur within a work environment. These incidents can range from common workplace accidents like slips, trips, and falls to machinery malfunctions to conflicts between employees. Errors in reports, presentations, and operating machines/equipment can lead to serious accidents, injuries, property damage, or even instances of violence.
These incidents can be caused mainly because of four factors: human error, system error, process error, or external factors. Human error is the most variable and causative factor for incidents or errors. Errors caused by humans are mainly due to a lack of knowledge, experience, concentration, or awareness, and stress is one of the most influential factors causing them.
Stress can arise from various sources, including work, relationships, financial challenges, health issues, and major life transitions. This study utilized data from both primary and secondary sources to illustrate how stress contributes to workplace errors and incidents. Employees can significantly decrease errors and incidents in both their professional and personal lives by identifying their specific stressors and implementing effective management strategies—such as meditation, healthy eating, exercise, or other stress-reducing activities.
Managing stress involves healthy coping strategies such as exercise, relaxation techniques, maintaining a balanced diet, getting enough sleep, and, if required, seeking social or professional support without hesitation. Practicing mindfulness and engaging in activities that bring joy and relaxation can help alleviate stress, reducing errors and incidents.

In conclusion, adopting a healthy lifestyle, good time management, adaptive corporate work culture, introducing hybrid working styles, and enhancing employee performance and productivity through training sessions can help reduce stress levels. Reducing constant social media interactions and promoting work-life balance can also contribute to calmer employees and fewer errors and workplace incidents. It is important to remember that stress is not always a negative experience; a certain level of stress can be beneficial as it can motivate individuals to perform at their best.

Analysing the Role of Management Skills, Leadership Styles, and Critical Factors in Achieving Successful Project Management Outcomes in Structural Organizations

Anshu Sharma — Thu, 17 Apr 2025 00:00:00 +0000

In structure organisations, this research seeks to understand how leadership styles, critical success factors, and management abilities all play a part in producing desirable project management results. Finding out what managers need to know, how leadership and team management styles affect projects, and what variables contribute most to a project's success were the main goals. A qualitative and quantitative approach is used whereby data from the key stakeholders in the form of closed-ended questionnaires is used alongside literature, reportage, and case studies. Convenience sampling helps to make the study convenient and feasible, while quantitative research employs the use of SPSS (Statistical Packages for Social Sciences) to analyses patterns, relations and trends. The findings underscore management competency areas, including communication, analysis and decision-making, and risk management as variables that play a significant role in defining the outcomes of projects. Transformational and collaborative leadership styles were identified as the most effective in motivating teams and improving performance, whereas transactional leadership produced mixed results. Moreover, the identified key success factors, including the involvement of key stakeholders, availability and distribution of resources, and organisational commitment, were found to be crucial in improving project performance. Several studies identified clear communication structures and well-established rules to enhance project efficiency and cooperation. The research concludes that effective project management necessitates attending to several facets of the management process and using best practices in leadership and management. They provide recommendations for enhancing managerial behaviours and communication with and within structured projects as well as advancing the theory of project management by capturing the interaction process of a project environment as depicted by the managerial competencies, leadership styles, and organisational structures.

Bridging Traditional ITSM and Modern Engineering: An Ethnographic Study of ITIL & SRE on GCP

Kranti Kiran Kumar Gedela — Thu, 17 Apr 2025 00:00:00 +0000

This research explores how large-scale organizations using ITIL as their primary ITSM framework can effectively work with vendors and partners using Google’s SRE. Through case studies, it examines the synergy of formal process management and automation-driven reliability practices, highlighting key challenges related to resource allocation, cultural misalignment, and tooling complexities. The findings demonstrate the importance of bridging ITIL’s robust governance and SRE’s adaptive engineering mindset to enhance service resilience, reduce downtime, and achieve faster innovation. The study introduces practical frameworks for incident management, communication protocols, and continual improvement, emphasizing specialized metrics such as SLAs, SLOs, and error budgets. By synthesizing empirical data and theoretical reflections, it provides a roadmap for hybrid operational models that align business-critical IT processes with next-generation reliability engineering. In essence, this dissertation underscores the strategic imperative of fusing ITIL and SRE to foster operational excellence and secure competitive advantage in rapidly evolving digital environments.

Multi-Facet Critical Review of Autonomous Vehicles in India

Ashutosh Deshpande — Thu, 17 Apr 2025 00:00:00 +0000

This research study will benefit the reader to gain deeper understanding about autonomous vehicles in Indian context in multi facet review. Secondary research is conducted via PESTLE model and Primary research is conducted via mixed methodology approach. Quantitative method using survey as a tool to understand awareness and perceptions of individuals on multiple facets of autonomous vehicles in India. Qualitative method using guided interview as a tool to understand views and opinions of specific stakeholders of the value chain of the mutual impact of autonomous vehicles in India.

The Impact of Higher Education on Leadership Styles in California Local Educational Agencies and How They Affect Turnover Rates and Job Satisfaction in Classified Employment

Biljana Babic Tatomirovic — Thu, 17 Apr 2025 00:00:00 +0000

The purpose of this mixed quantitative and qualitative phenomenological study was to explore the employee perception of the impact of the level of education on management styles in California Local Educational Agencies and how those management styles affect their everyday life and job satisfaction.
While there is substantial research on the correlation between education and leadership styles, the intersection of higher education, leadership styles and their direct impact on turnover rates and job satisfaction among Classified employees within California Local Educational Agencies remains underexplored.
A mixed-method phenomenological approach was employed, combining quantitative surveys, observations, and qualitative interviews. The quantitative component included a survey administered to forty-four Classified employees and managers at the Monterey County Office of Education, focusing on management styles, job satisfaction, managerial performance, and turnover-related factors. Qualitative data were collected through indepth interviews with eight Classified managers and employees selected based on covert observations conducted in public settings, meetings, and daily interactions. Data analysis involved triangulation to identify themes and patterns related to educational attainment and its effect on leadership behaviors.
Even though quantitative analysis showed that 51.5% of employees believe that their manager’s level of education impacted their management style, the qualitative analysis and the overall findings indicate that while higher education plays a role in shaping
managerial practices, practical experience and interpersonal skills are often seen as equally or even more crucial in effective leadership.

Higher education is among the most significant factors in producing management practices within California Local Educational Agencies. Managers with advanced academic qualifications are perceived as better leaders and exhibit management styles
that positively impact employee engagement and retention. The practical application of advanced theoretical knowledge remains a key area for improvement. The data suggests customized professional development programs should be implemented to blend academic credentials and real-world management challenges.
Advanced education combined with ongoing leadership training should show the best results in improving organizational effectiveness and employee satisfaction.