Global journal of Business and Integral Security

the EMOTIONALLY INTELLIGENT STORYTELLING THROUGH AI AND ML USING EMOTIONAL ARCS OF MOTION PICTURE THAT RESONATE WITH AUDIENCES

Prashanth Ramappa — 2024-07-02

Film and moviemaking production are an intricate process, mainly decision-making among its producers, Motion picture directors, and writers, especially for script selection. Movie or Filmmaking is a huge investment, it takes more of a resource of Capital, Manpower & Creativity. Traditional script evaluation methods: almost entirely subjective measurements; reliant on the vast and varied experiences of industry professionals (style) — thus inevitably creates bias disparities in decision making, often discounting new or unique narratives. Film producer should be clear whether the narrative is appropriate for the audience's typical emotional journey. Understanding emotions in scripts is a difficult and complicated task. Our Approach involved, combined the concept of Shapes of stories, Emotional Analysis using Natural Language Processing (wheel of emotion) and ML Clustering technique to solve challenge. Our Methodology involves the use of subtitle data to demystify the emotions in the story. We also apply NRCLex, a lexicon-based method, to associate with eight basic emotions and cluster similar movies within the six main story shapes. Our findings indicate that stories generally follow the six fundamental forms. We also found that movies in the "Man in the Hole" category where the hero faces an unexpected challenge, overcomes his fear, and succeeds in becoming a leader have the highest box office and popularity success.

Planned and Organized Deficit Spending (PODS)

Vidur Sahgal — 2024-06-25

This is the first time that “Planned and Organized” has been added to the words “Deficit Spending”. Modern Monetary Theory (Mitchell, 2014, 2022; Mosler, Mitchell and Watts, 2019), a comparable alternative, originally sourced to Australian economist Bill Mitchell and developed further by him, Warren Mosler, and L. Randall Wray (Wray, 2019) way back in 1992, and Professor Stephanie Kelton’s book published in June 2020 called “The Deficit Myth” (Kelton, 2021), came close to realizing PODS (Sahgal, 2022), but the major difference between PODS and MMT was that MMT still believed in taxes, whereas PODS does not. Planned and Organized Deficit Spending (PODS) is an extension of the Distributed Equilibrium Allowable Deficit Spending Theory (DEADS). It says that deficit spending can be planned and organized in a way that could make taxes unnecessary and reduce capital shortages and market fluctuations (inflation or deflation). About DEADS (PODS original avatar, followed by OPDS, and now finally PODS), ‘allowable’ meant subject to the resources available other than money. Instead of ‘equilibrium’, resources available and produced for an economy’s population in each period were the critical requirement. This would gradually be built up to a sustainable saturation level of supply for any given product, service, or agro in an economy. Assuming the supply lags away, this implies that eventually, any product introduced into the economy can immediately, or gradually, achieve full and sustainable supply; therefore, ‘saturation’ is the more important target. PODS will not cause any displacement of relevant current personnel. The economic and commerce sectors will require millions of additional personnel, thereby creating more employment opportunities. New roles would require minimal training in the theory. The subject of Economics has its head underground amidst sophisticated math and statistical methods and analysis that give the impression, like to an ostrich, that everything is going well mathematically with one’s head underground but not at ground level. Every time someone blames the subject, math becomes even more complicated and sophisticated while serving no real purpose. To prove PODS theory, there is no need for rigorous mathematics; rather, economists should understand the logic of PODS: the Liabilities of issued E-Digital Cash are balanced with Assets made from this E-Digital Cash. Maybe after reading PODS, the math and statistical analysis, along with other econometric and regression analysis tools, will be able to manage economics as a subject where all of us, as economists, settle the entire world. It is no longer “Economics” or home accounts and finances; it is “Arthshastra—the meaning of an economic or commercial decision, at any given moment, based on mutually acceptable exchange.

Exploring Reasons for Digitalization Not Percolating into the Power Sector to the Extent Expected in India and Suggesting a Framework to Expedite the Same

Koteswara Rao Pothala — 2024-06-20

Digitization, digitalization, or digital transformation represents an essential convergence of IT and OT (Operational Technology) crucial for various industries, including the power sector. This paradigm shift not only enhances business competitiveness but also fosters improved safety, reliability, and sustainability while reducing costs and errors. Digitalization reduces costs to one-third in fuel and one- fifth in operations and maintenance. Digitalization‘s role in integrating physical and digital realms, optimizing processes, and enhancing overall performance within the power sector is very evident.
Despite these obvious benefits, digitalization in the power sector, particularly in India, has not percolated to the anticipated extent. This research aims to delve into the reasons behind this shortfall, focusing on six key areas: strategy, operational excellence, regulatory landscape, technology, innovation, and economic considerations, collectively termed as 'SORTIE'. Additionally, it proposes a framework to expedite digitalization adoption by addressing these reasons. Through showcasing the effectiveness of the SORTIE framework in transitioning from trials to successful implementation, this study underscores the urgency and potential of digitalization in revolutionizing power generation.
By identifying and overcoming barriers to digitalization deployment, this research aims to drive significant change, inform strategic decision-making, and shape the future trajectory of the power sector towards sustainability and resilience in an increasingly digitized world.

Exploring the Impact of Leadership Styles on Followers' Engagement in Corporations: A Cross-Generational and Cross-Cultural Perspective

NGAI Man Lin Malina — 2024-06-20

Background
As corporations strive to embrace diversity and effectively manage their multigenerational workforce, understanding the impact of leadership styles on employee engagement and job performance becomes crucial. This thesis examines the impact of leadership styles that positively influence employee engagement and job performance from the followers’ perspectives, with a focus on the preferences and experiences of different generations within corporations. The study also explores the potential mediation factors of generations and national culture in the relationship.
Methods
This study employs a large-scale questionnaire survey as the primary research method. Participating companies were selected based on the criteria that they have over 700 employees and an annual revenue exceeding Euro 80 million. This ensures a diverse sample that represents organizations of significant size, generations, and financial standing. The 531 sample consists of employees from 25 companies across 18 markets in Asia and Europe.
Results
The research findings provide compelling evidence regarding the significant influence of leadership styles on employee engagement. Specifically, supervisors who exhibit transformational and democratic leadership styles have a positive impact on employee engagement. On the other hand, employees working under laissez-faire leaders tend to report good performance but lower job satisfaction.

The study identifies transformational and democratic leadership styles as the most desired leadership styles for enabling optimal employee performance. It is worth noting that a majority of respondents perceived their leaders as demonstrating a combination of two leadership styles rather than a single style. Furthermore, the study identifies "clear direction," "people-oriented behavior," and "recognition of achievements" as the top desired leadership behaviors among respondents.
Interestingly, the study did not find significant differences in the effects of leadership styles on employee engagement and job performance across different generations. However, "being approachable" emerged as a desired behavior specifically for Generation Z respondents.
Moreover, the research highlights the value placed by a high percentage of respondents on working in teams with diverse age groups. However, it is important to note that a smaller proportion of Generation Z respondents reported enjoying such diversity.
Regarding the cultural context, no significant differences were detected in the effects of leadership styles on employee engagement and job performance between Asia and Europe. However, it is noteworthy that the democratic leadership style has a more positive influence on engagement in Europe, whereas in Asia, it has a more positive influence on job performance.

Conclusion
These findings highlight the importance of considering cultural differences and perceptions of performance when examining the impact of leadership styles. Further research is needed to explore the complex interplay between leadership styles, multigenerational diversity, and national culture in different organizational contexts. Understanding these dynamics can help organizations tailor their leadership approaches to maximize employee engagement and job performance across diverse cultural backgrounds.

Personal, Relationship, and Professional Indicators: A Holistic Approach to Assess Satisfaction and Success in Life

Abdul Rashid Kolliyil — 2024-06-20

This research delves into the intricate nature of life satisfaction and success, tracing the historical evolution of concepts from the 17th century to the present. The study highlights the paradigm shift from materialism to a post-materialistic perspective, culminating in the contemporary emphasis on subjective social indicators. Through an extensive literature review, the research identifies a crucial gap in existing scholarship – the lack of integration of personal, relationship, and professional elements into a comprehensive framework for assessing life satisfaction.
The first objective investigates the interconnected factors influencing the satisfaction and success of individuals. A comprehensive exploration unfolds, revealing the dynamic interplay of personal, relationship, and professional dimensions. The study delves into multifaceted influences, including psychological foundations, health, personal development, social factors, environment, education, career, and economics. Through scholarly studies and real-world examples, the profound impact of various factors on satisfaction and success is illuminated, emphasizing the importance of a balanced approach.

The second objective introduces a groundbreaking life satisfaction metric, the Personal, Relationship, and Professional (PRP) Index. The rationale, methodology, and components of this tool are presented for a comprehensive assessment of an individual's well-being. The PRP serves as a proxy for life satisfaction, ranging from zero to one. Subsequent chapters will explore the implementation and validation of the index through empirical data and thorough analyses.
The third objective examines the transformative impact of PRP training on life satisfaction. The Experimental Group's positive shifts post-training underscore the program's influence on personal well-being, interpersonal dynamics, and professional satisfaction. Noteworthy positive impacts on specific age groups and genders emphasize the program's efficacy, and nuanced analysis adds depth to our understanding, highlighting the need for tailored interventions.
Contrasting with the Control Group, the Experimental Group's significant increase in PRP Index scores attests to the program's efficacy, reinforcing its impact on personal, relationship, and professional dimensions of life satisfaction. The research underscores the importance of demographic nuances in crafting targeted interventions for a tailored approach to well-being.
The final objective analyzes the personal, relationship, and professional characteristics of successful individuals through case studies. Using a holistic approach and case study methodology, the lives of renowned personalities, including Gandhi, Nelson Mandela, APJ Abdul Kalam, and Barack Obama, are explored. Findings reveal a notably high PRP index for each individual, indicating that their success was influenced by a harmonious interplay of personal, relationship, and professional elements. The research contributes to academic understanding and provides practical insights for individuals seeking fulfillment and achievement, aiming to inspire and guide individuals on their own journeys toward fulfillment and success.

Behavioral-Based Safety Leadership's Impact on Organizational Safety Culture and Incident Causation in the High-Risk Maritime Environment

Calvin Jordan Manjarres-Wahlberg — 2024-06-20

The impact of behavioural-based safety leadership on organisational safety culture and incident causation within the high-risk maritime environment has been researched in detail in this dissertation. The research discusses the hazards, risks and challenges associated with living and working at sea within the dynamic naval and merchant navy environments. The study explored the critical factors of leadership in shaping positive safety behaviours and the impact behavioural-based safety leadership has on reducing incident causation.
The research is grounded in a comprehensive review of existing academic and grey literature, which establishes a theoretical foundation encompassing safety leadership theories, organisational safety culture, and incident causation models. This background provides a context for understanding the complex link between leadership behaviours and safety outcomes within the high-risk maritime environment.
The research uses a mixed-methods approach, combining quantitative data from surveys with maritime professionals and qualitative insights from case studies and interviews.
This triangulation methodology provides a detailed investigation into the relationship between safety leadership behaviours, organisational safety culture and incident causation. Key findings include the identification of specific antecedents and leadership behaviours that positively influence safety culture including, gender diversity and mindset, safety training and evolving practices. Identified behaviours include effective communication, commitment to safety, and the ability to inspire and motivate workers/crew towards safety-oriented goals, with participants stating that their understanding of safety leadership included such things as leading by example, being the sample of good safety onboard, and walking the walk.
The study findings demonstrate that these results correlate with lower incident causation rates and an improved safety culture. The dissertation also highlights the vital role of leaders in setting safety standards, modelling positive safety behaviours and fostering a positive safety culture where safety is openly discussed, supported and addressed in a collaborative approach between workers and management.
Additionally, participants identified barriers to effective safety leadership within the maritime environment, including operational pressures, time, money, cultural factors, and resistance to change. The study recommends overcoming challenges with training and implementing a proactive safety culture from the top down.
In conclusion, this dissertation highlights the critically important role of behavioural- based safety leadership in ensuring a positive organisational safety culture while reducing incident causation rates in the high-risk maritime environment. It provides a pathway for maritime professionals to improve safety performance while suggesting a framework for future research into this vital area of social science.

Crowdsourcing in Software Testing: Opportunities for Software Companies

Paramjit Singh Aujla — 2024-06-20

This research is being conducted to explore and understand how effectively crowdsourcing techniques are utilised in the Information Technology industry today to build software products. The core question posed is: What are the business strategies and practices of IT Product development companies to build high-quality software products at a low cost?? The goal is to analyse data from various industry papers, organisations and products in the Information Technology industry and formally define the crowdsourcing techniques and practices beneficial for software product development.
The research utilized a qualitative approach, using an online interview questionnaire and semi-structured interviews. The interview questionnaire was shared with a wider audience working in the IT Industry with specialization skills in software testing, or development over social media platforms like LinkedIn.com. The Semi-structured interviews were conducted through using channels such as Zoom, and face-to-face interactions. The study focused on the software project experiences of various individuals having experience in the IT Industry, ranging from Testers to mid-senior and executive positions. All interviewees were carefully selected from the global locations to learn the variety of experiences and build an understanding of the usage of Crowdsourcing in Software Testing. Data were collected through interview questionnaires, interviews and web data scrapping. Abductive reasoning methods were employed in exploring Crowdsourcing awareness, such as the adoption and use of Crowdsourcing, the impact of Crowdsourcing on individuals and organizations, and the emergence of testing strategies based on Crowdsourcing.
The study revealed that Crowdsourcing for software testing is still a new field for many people. Software companies still prefer direct vendor contracts or full-time people to get the job done. It is observed that key concerns are falling in the areas of security, team management and infrastructure. Based on their experiences, crowdsourcing will evolve as a field: With the increasing demand for software products and services, the adoption of crowdsourced testing is expected to grow significantly. More companies are likely to embrace crowdsourced testing as a viable alternative to traditional testing methods, especially for large-scale or complex projects., Advanced testing tools: Crowdsourced testing platforms are likely to incorporate advanced testing tools and technologies such as AI, machine learning, and automation to improve testing accuracy and efficiency., Improved quality control: Crowdsourced testing platforms are likely to implement better quality control mechanisms to ensure that testing is conducted accurately and thoroughly. This could include improved tester selection processes, better testing guidelines, and more comprehensive reporting and feedback mechanisms.

Voice Technology and AI: Innovative Tools for Developing Inclusive Education, Disability Learning, and Mental Health Support

Vijay Anand Kunduri — 2024-06-20

This dissertation tackles a major obstacle in Natural Language Processing (NLP)
related to the analysis of unstructured and noisy utterances, specifically in Indian regional
languages. The training of NLP algorithms on corpora primarily available in languages like
English, French, and Chinese has limited applicability to regional languages due to the lack
of relevant corpora. This issue becomes more pronounced in real-world scenarios where
the speech is often distorted by background noise and non-sophisticated Automatic Speech
Recognition (ASR) engines.
To address this problem, the dissertation proposes an innovative solution that uses
ensemble methods and focuses on the accuracy of uttered sentences. The approach
combines rule-based Machine Learning and fuzzy logic-based algorithms to overcome
language variances and accurately identify full or partial matches of actual answers within
noisy utterances.

The methodology is adapted based on the language of the uttered answers. For
regional languages, the dissertation employs sequence matching and fuzzy matching
algorithms, with special consideration for answers containing numbers through the
utilization of number-to-word methods. In the case of English answers, the methodology
involves word form, fuzzy logic, and distance-based similarity matching.
The detailed description of the proposed solution emphasizes the inventive aspects
contributing to its efficacy. While specific diagrams or figures illustrating the components
are not provided, the absence of patented algorithms in the literature or prior art section
underscores the novelty of the proposed solution, presenting a distinct and valuable
contribution to NLP for regional languages.
In summary, this dissertation presents a groundbreaking approach to address the
challenges posed by unstructured and noisy utterances in NLP, particularly in Indian
regional languages. The ensemble of algorithms and language-specific methodologies
positions it as a novel and promising solution capable of significantly enhancing the
accuracy of understanding and matching uttered sentences.

Enhancing E-commerce Hybrid Recommendation Systems Using Metaheuristic Optimization Techniques

Hanumanth Raju — 2024-06-20

This study investigates the complicated nexus of recommender systems and sentiment analysis within e-commerce, with the goal of improving the customer experience and providing personalized product recommendations. Beginning with a thorough study introduction, the paper covers the background of the field, explaining the fundamental concepts of recommender systems, design principles, and the vital role of customer interest predictions. The exploration continues with the central theme of sentiment analysis in identifying user preferences with a complete explanation of sentiment analysis techniques such as rule-based, machine learning and deep learning methods. The integration of sentiment analysis into recommender systems is addressed, covering preprocessing, feature engineering, and collaborative filtering approaches. As the research goes beyond theoretical foundations, it evaluates sentiment analysis by processing customer reviews, detecting sentiments and using review metadata for sophisticated analysis.

Robust evaluation methodologies, metrics, and cross-validation techniques are explained, considering the multidimensionality of sentiment analysis. The chapter also links to domain-specific evaluation issues, user-centered evaluations, and ethical dimensions, thus, providing the challenges and ethical aspects of user feedback and interaction analysis. The toolbox of sentiment analysis that combines various NLP libraries, machine learning frameworks, sentiment analysis APIs, and custom models is opened, providing a complete picture of the available tools for practitioners. The study brought to light the real-world applications of sentiment-sensitive recommendation systems in personalized product recommendations, dynamic pricing, customer feedback analysis, social media marketing campaigns, user experience optimization, and brand reputation management. The implementation of the research offers a pathway for future trends such as integration with conversational AI, advancements in multimodal sentiment analysis, and ethical considerations. The literature review provides a strong basis for the research by exploring theories such as the Theory of Reasoned Action and Human Society Theory. The methodology section details how the study was conducted, including the participants, data collection, and analysis methods. The results and discussions present the findings and their significance. Finally, the research concludes with a summary, highlighting the implications of the findings for the development of sentiment-aware recommendation systems. It emphasizes the need for ongoing research, ethical considerations, and user education in this rapidly evolving field.
Keywords: Machine Learning, E-commerce, Sentiment Analysis Techniques, Personalized Product Recommendations

Impact of IT Investment on Indian and European Banks – An Analytical View

VIRENDRA DAFANE — 2024-06-20

Currently, technology is the primary facilitator of the financial market. It can be easily said that financial services are driven by technology. The primary trend of financial unbundling has generated a paradigm shift, allowing the minor player to compete with big giant banks. Moreover, much research has been done, and it has been in the area of how digital transformation or emerging technologies or total IT investment impact the financial services market. The research has been done with a single entity like Blockchain, data, or cloud and their impact on a specific market. There is a potential gap in the research as the research is limited to one market and precise technology. This research aims to examine the impact of IT investment on Indian and European markets and compare them in terms of financial attributes. For example, the Cost to income ratio has varied for Indian and European banks from 2017 to 2022.
This research has a hypothesis developed by theoretical aspects, which data-driven algorithms will test for validity. In the end, the study aims to understand the impact of IT investment on Indian and European banks and compare them.