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Volatility in Indian stock markets during COVID-19: An analysis of equity investment strategies
The aim of the paper is to evaluate the impact of novel COVID-19 on the returns and volatility of Indian stock markets with special reference to equity investment strategies of the Bombay Stock Exchange. For the purpose of evaluating the impact, the study has applied GARCH. The research has considered a time frame from March 2015 to January 2021. Prior to implementing GARCH model, pre-estimation tests (i.e., augmented Dickey-Fuller and ARCH-Lagrange multiplier) were conducted. Outcomes clearly indicate that the returns during the crisis for all the strategy indices have been negative, which means that the COVID-19 outbreak resulted in massive losses. Additionally, 'during crisis' period showed an increase in volatility for all the strategy indices depicting that the pandemic has a long-lasting effect and will take time to fade off. This research will help the investors in the investment decision process by giving them insights about the different strategies. 2021. -
Taste of your Hometown: Evoking Nostalgia through the Diner Space in Midnight Diner
Restaurant spaces are seen as a space that intersects between the personal and the cultural. This paper looks at a Japanese TV series, Midnight Diner, an adaptation of a Manga by Yaro Abe, where a tiny, not-so-popular restaurant in one of the back lanes in Tokyo serves food from midnight to 7 a.m. This show makes several meaningful connections between food, memory, and space as the customers come with specific food cravings, and the Master (the owner-chef of the Diner) is happy to customize. The diner space transcends the traditional meaning of a diner that not only serves food to satiate hunger but is an experience that evokes nostalgia for their home and their loved ones. The wistfulness in the lives of the customers for their home, people, and home-cooked food finds a release in the diner. The space of the diner acquires different meanings, as do the dishes the customer relishes. Thus, the paper explores the diner space as a symbolic space where each episode introduces a new character, a new story, and the past they deal with while the food is prepared and consumed on screen. The taste, smell, texture, and ingredients of the food in this diner stimulate the senses, and this space acquires emotional meaning for everyone stepping in. 2023, University of Malaya. All rights reserved. -
Metaheuristic Machine Learning Algorithms for Liver Disease Prediction
In machine learning, optimizing solutions is critical for improving performance. This study explores the use of metaheuristic algorithms to enhance key processes such as hyperparameter tuning, feature selection, and model optimization. Specifically, we integrate the Artificial Bee Colony (ABC) algorithm with Random Forest and Decision Tree models to improve the accuracy and efficiency of disease prediction. Machine learning has the potential to uncover complex patterns in medical data, offering transformative capabilities in disease diagnosis. However, selecting the optimal algorithm for model optimization presents a significant challenge. In this work, we employ Random Forest, Decision Tree models, and the ABC algorithmbased on the foraging behaviours of honeybeesto predict liver disease using a dataset from Indian medical records. Our experiments demonstrate that the Random Forest model achieves an accuracy of 85.12%, the Decision Tree model 76.89%, and the ABC algorithm 80.45%. These findings underscore the promise of metaheuristic approaches in machine learning, with the ABC algorithm proving to be a valuable tool in improving predictive accuracy. In conclusion, the integration of machine learning models with metaheuristic techniques, such as the ABC algorithm, represents a significant advancement in disease prediction, driving progress in data-driven healthcare. 2024, Iquz Galaxy Publisher. All rights reserved. -
Malicious Traffic Classification in WSN using Deep Learning Approaches
Classifying malicious traffic in Wireless Sensor Networks (WSNs) is crucial for maintaining the network's security and dependability. Traditional security techniques are challenging to deploy in WSNs because they comprise tiny, resourceconstrained components with limited processing and energy capabilities. On the other hand, machine learning-based techniques, such as Deep Learning (DL) models like LSTMs, may be used to detect and categorize fraudulent traffic accurately. The classification of malicious traffic in WSNs is crucial because of security. To protect the network's integrity, data, and performance and ensure the system functions properly and securely for its intended use, hostile traffic categorization in WSNs is essential. Classifying malicious communication in a WSN using a Long Short-Term Memory (LSTM) is efficient. WSNs are susceptible to several security risks, such as malicious nodes or traffic that can impair network performance or endanger data integrity. In sequential data processing, LSTM is a Recurrent Neural Network (RNN) appropriate for identifying patterns in network traffic data. 2023 IEEE. -
Designing Artificial Intelligence-Enabled Training Approaches and Models for Physical Disabilities Individuals
The focus of this research is on investigating AI-based strategies and models that can be used to develop workforce training systems specifically for individuals with physical disabilities. The goal is to leverage the advancements in artificial intelligence (AI) and its potential impact on workplace learning and development. There is an increasing demand for utilizing AI capabilities to design comprehensive training programs that are both inclusive and effective for people who face physical challenges. The research will examine effective strategies, real-life examples, and current AI-based training platforms for people with physical disabilities. Additionally, it aims to tackle the obstacles and ethical matters linked to incorporating AI in workforce training. These concerns include mitigating biases, ensuring accessibility, and safeguarding privacy. The outcomes of this study will assist in creating progressive approaches and frameworks driven by AI that can empower individuals with physical disabilities by improving their employability prospects while simultaneously fostering inclusivity within workforce training. The chapter will also explore the integration of AI-powered solutions in training programs for physically challenged individuals. By utilizing AI technologies like personalized learning algorithms, predictive analytics, and adaptive content delivery systems, training can be customized to cater to the unique requirements and learning needs of everyone. The implementation of AI has the potential to automate processes, analyze data effectively, and generate personalized learning pathways for improved accessibility. 2024 selection and editorial matter, Alex Khang; individual chapters, the contributors. -
Cultivating efficiency-harnessing artificial intelligence (AI) for sustainable agriculture supply chains
This chapter intends to investigate and present the possibility of utilizing artificial intelligence to transform the agricultural supply chain. The primary objective is to enhance efficiency, sustainability, and adaptability in response to a shifting climate and expanding global population. The results of this investigation provide significant and valuable knowledge for both new businesses and well-established corporations who have a vested interest in embarking on an intelligent and sustainable digital revolution within the agricultural sector and food supply chains. These findings present insights that can guide these enterprises in their pursuit of transforming their operations using technology to enhance efficiency, productivity, and sustainability. By harnessing the benefits offered by digitization, organizations operating within the agriculture industry will be able to streamline processes, optimize resource allocation, reduce waste, and improve traceability throughout the supply chain network while ultimately securing long-term success. 2024, IGI Global. All rights reserved. -
The inherent risk of climate change becoming a hindrance in a business supply chain
Purpose: A sophisticated network of interconnected supply chains serves as the central organising principle for most of the manufacturing serving the global economy. Right from computers and vehicles to life-saving pharmaceuticals and food is made possible by the supply web. The final goods part of a supply chain may include thousands of components from various global regions. These supply chains have been refined to achieve the highest speed and efficiency. Methodology: This study includes a sample of 127 firms that have been in business for at least 15 years and are familiar with business dynamics. The authors anticipate how climate risks, common in global supply networks, will evolve over the next several decades. This study examines the vulnerability of nine commercial value chains to climatic disasters. Also, it explores company and value chain vulnerabilities, financial losses, and adaptation or strategic methods to increase resilience. Findings: Companies must plan forward in terms of locations by retaining operational facilities while running new operations in less risky places. Without change, supply networks will become unstable and dangerous shortly. Using their climate objectives, businesses must decarbonise their supply chains. Businesses should connect with suppliers longer-term. The quality and dependability of a company's suppliers affect its success and safety. Future-focussed corporations are already engaging their suppliers on health, safety, and environmental issues. Significance: The typology may be helpful to executives as they make decisions about the strategic option(s) they wish to pick to address climate change. These decisions can also be influenced by the insights provided by the research about the present status of operations of other firms from different sectors all over the globe. 2023 by Chabi Gupta and Swati Bhatia. -
Data-driven behaviour finance for mutual fund investment decision making
When it comes to money and investing funds, the individual portfolio investor isn't always as logical as he feels he is, which is why there's a whole school of thought dedicated to explaining why people behave in irrational and weird ways. The primary objective of this research is to investigate the effects of five major behavioural biases on individual investor decisions in a metro city India, with a focus on mutual funds, as well as to examine how individuals make decisions to ensure that their investments generate greater returns for a better future. The statistical evidence shows that a variety of behavioural elements have a significant part in people' investment decision-making patterns, which has an impact on the population's economic situation. The purpose of this study is to illustrate how an individual's perspective, attitude, and conduct affect mutual fund investments. 2023, IGI Global. -
Blockchain technology toward green internet of thingsan exploratory survey
Over the past couple of decades, there has been a spike in industrial activity across the entire world, which has led to an increase in the utilization of fossil fuels. During the same era, technological innovations have triggered an increase in both climate change and carbon legacies. The use of energy by the Internet of Things (IoT) has resulted in a fresh dilemma, which has oriented our priority toward the design of an IoT ecosystem that is more ecological and sustainable. Institutions of higher learning and business corporations have shown interest in the green IoT because it facilitates improved energy-efficient delivery of services and simplifies the process to generate and make consumable use of renewable energy. Blockchain technology is gaining interest from energy producers, entrepreneurial ventures, investment firms, legislatures, and scientists since it is incredibly flexible, safe, and secure. This chapter focuses on the significance of blockchain technology in the green IoT community, highlights the critical considerations that need to be taken into account, and explores how blockchain technology renders the IoT ecosphere healthier and greener. In addition to this, it places an emphasis on the inherent necessity of establishing a long-term IoT infrastructure that takes utilization of the appropriate blockchain technology to another level altogether. 2023 Elsevier Inc. All rights reserved. -
How close are you to your end consumer? Data-driven insights to awesome customer experience
The delivery of a tailored customer experience is being widely recognised by executives in the technology industry as the key to unlocking revenue, minimising attrition, and providing growth. It is not simple to satisfy a consumer in today's market. Delivering reliable and efficient experiences across channels is more challenging than it has ever been because of the context of disparate privacy regulations, quick updates to browser technology, and an ever-evolving technological landscape. This research suggests that to do it right, the business needs to have the right people, processes, and technologies working in sync. This study highlights that many companies continue to invest in instruments and technology solutions before they have effectively accomplished the organisational transformation required to perform the role in a data-driven mode. Investments do not always yield the promised results since the basic pieces of mindset, vision, and people are not always in congruence. Consumers are no longer going to be 'just satisfied,' or 'even happy.' 2023, IGI Global. All rights reserved. -
Taming the HiPPO (Highest Paid Person's Opinion) with agile metrics and value management
If the organisation's ecosystem has an excess of HiPPOs, data, measured analytics, and other realtime information that minimises uncertainty can help them mitigate the consequences. They disregard the wisdom of the crowd, overlook the front-line staff's abilities, and risk disengaging the workforce. This research advocates agile metrics and value management to tame the HiPPO. The authors posit to reign in opinions with metrics. The corporate enlightenment brought about a revolutionary idea over three centuries ago: to elevate science and knowledge above magical thought and mysticism. When the authors convert this into modern terms, they are referring to data-driven management, analytics, and hypothesis validation. In fact, the idea of applying science in the form of true evidence, confirmed data, etc. to production processes underlies much of the industrial revolution. 2023, IGI Global. All rights reserved. -
Are you the one to stick around despite the high rate of attrition? Typical personality traits using Myers-Briggs framewor
Most employees say they have unfavourable sentiments about their organization, yet they often seem hesitant to follow through with their decision to leave. This presents a painful dichotomy for organizations that look for long term manpower solutions. This study examined the relationships between the Myers-Briggs' four personality dimensions (extraversion/introversion, sensing/intuition, thinking/feeling, and judging/perceiving) and the behaviour of employees to stick around with the organization for years even amidst a high attrition rate. After compiling all these observations, the authors propose the following five strategies for employers to take into consideration: Leveraging the power of belongingness, form addictive positive work environment, capitalise on the spillover effect, communicate with either the heart or the head, andprioritise having experiences above an employee status. This research will offer an introspection to both employees and the employers. 2023, IGI Global. All rights reserved. -
Mind of a portfolio investor: Which strategies should I use as a basis for my investment decisions
It is smart for investors to plan for a drop that may be accompanied by a recession in the late stages of a bull market. The authors examine a variety of passive and active strategies, as well as their success in different crises. However, while choosing the best of strategies in the worst of circumstances, investors must be cautious in defining 'best.' It's critical to comprehend not only the long-term performance but also the whole cost of putting various preventive measures in place. The authors analyse popular strategies like technical analysis, fundamental analysis, relying on financial news, seeking professional advice, tips from trade experts, and self-intuition while making portfolios. Our findings indicate that every investment is unique. Some defensive methods will be more effective than others in each case. As a result, diversification across several viable strategies may be the wisest course of action. 2023, IGI Global. All rights reserved. -
Why haven't you bought a solar panel? Consumerism at its "Green" best with the Myers-Briggs type indicator
This research study examined the relationships between Myers-Briggs' four personality dimensions and environmentally conscious consumption patterns. The study found that different personality types have different green purchase habits. The authors also propose five strategies for businesses who plan to venture into sustainable consumption. These strategies include leveraging the power of belongingness, forming addictive healthy habits, capitalizing on the domino effect, communicating with either the heart or the head, and prioritizing having experiences above owning things. The study's findings suggest that businesses need to take a more holistic approach to promoting sustainable consumption. Authors use discriminant analysis to evaluate whether each Myers-Briggs personality type had a distinct green purchase habit. For each of the four dichotomies associated with five kinds of green buying behaviors, SPSS was used to construct discriminant analysis indicators and outputs. 2023, IGI Global. All rights reserved. -
Securing end user computing environments using blockchain
COVID-19's phenomenal effect has expedited the adoption of digital technologies over several years, indicating that several of these breakthroughs are here to stay. Several enabling technologies are currently being implemented as major solutions for improving and responding to the pandemic's numerous issues, with blockchain being one of the preferred solution options. Blockchain can be used to re-structure processes, resulting in most effective operational and business models (e.g., democratising quality cancer detection with advanced artificial intelligence based radiomics technologies). The authors posit here that while there is a lot of anticipation about using blockchain to improve business capabilities, the lessons learned from the many pilots and proofs of concept so far should be considered. The necessity for a structured, formal decision-making process, based on good business logic and an awareness of the problem's process lifecycle, is however critical. Blockchain is a means to an end, not an end in and of itself. 2024, IGI Global. All rights reserved. -
Constructing an e-commerce model using the framework of blockchain
Blockchain technology is gaining immense popularity in the realm of online e-commerce, advertising, and consumerism. This study aims to develop a model that comprehends how blockchain can act as a significant disruptor for various functions and applications related to e-commerce. The research explores the possibility that this technological advancement has the potential to revolutionize the core operations of e-commerce industry by providing trade connections devoid of trust or need for specialized intermediaries or central authority in case of permission less blockchains. Furthermore, it could facilitate equitable access to immutable data across supply chains which may result in a major reorganization pertaining to information and value exchanged between businesses involved in electronic commerce and their customers. 2024, IGI Global. All rights reserved. -
Crop management using predictive analytics
The term "predictive analytics" covers a number of different statistical methods, such as "data mining," "machine learning," and "predictive modelling," which examine past and present data in order to formulate hypotheses and predictions about future events. The use of predictive analytics may provide farmers with the ability to predict future environmental changes more correctly, as well as the demand for their commodities, and improve their ability to make decisions. While predictive analytics may seem like an effective way to forecast future events, it cannot account for unforeseeable changes or external factors that could impact the accuracy of its predictions. Furthermore, relying solely on past and present data can lead to biased outcomes and fail to consider alternative scenarios that may occur. In essence, predictive analytics should not be used as the sole basis for decision-making in any given situation for crop management. 2024, IGI Global. All rights reserved. -
Knowledge or Personality: An Empirical Analysis of Behavioural Finance and Investor Cognitive Biases
This research attempts to analyze to what extent knowledge and tactics or enduring personality traits predict investor behaviour and cognitive biases in portfolio investment. This study is based on exploring a wide-ranging dataset: responses to a questionnaire survey together with transactional data of the same individual customers of an Indian stock company. From the questionnaire survey, the authors estimate measures of domain-general personality traits, such as the big five, as compared to the knowledge, financial literacy, competency, and attitude specific to investor equity trading. The results show the dominance of knowledge and tactics measures over personality-related measures when predicting nine different dependent variables of investment performance, investor cognitive biases, and portfolio investment activity. This research concludes with the discussion of the findings and with insights into theory and managerial implications. Copyright 2022, IGI Global. -
Machine Learningcloud-Based Approach to Identify and Classify Disease
The term "Internet of Things"(IoT) describes the process of creating and modeling web-related physical objects across computing systems. IoT-based healthcare applications have offered multiple real-time products and benefits in recent years. For millions of people, these programmers provide hospitalization can get regular medical records and healthy lives. The introduction of IoT devices in the health sector has several technological developments. This study uses the IoT to construct a disease diagnostic system. Wearable sensors in this system initially monitor the patient's sympathy impulses. The impulses are then sent by a network environment to a server. In addition, a new hybrid approach to evaluation decision-making was presented as part of this research. This technique starts with the development of a set of features of the patient's pulses. Based on a learning approach qualifications are neglected. A fuzzy neural model was used as a diagnostic tool. A specific diagnosis of a particular ailment, such as the diagnosis of a patient's normal and abnormal pulse or the assessment of insulin issues, would be modeled to assess this technology. 2022 IEEE. -
Voices of the Future: Generation Zs Views on AIs Ethical and Social Impact
As artificial intelligence (AI) becomes increasingly integral to modern society, its profound implications are coming to the forefront of discussions. This research paper investigates the perspective of Generation Z on the multifaceted societal and ethical impacts of AI. Gen Z is the first generation to fully embrace AI across all facets of life. Therefore, understanding their attitudes, concerns, and expectations towards AI is imperative for cultivating a responsible, adaptable, and ethically conscious society in the AI-driven era. This study addresses a significant research gap by exploring Gen Zs perceptions of the challenges associated with AI, such as issues related to privacy, data security, transparency, bias, public fear and more. It also examines the impact of AI on employment dynamics, specifically on job displacement and the necessity for reskilling in the face of AI-driven automation. The paper adopts a global perspective, acknowledging the variations in perception influenced by cultural, economic, and historical factors. Leveraging a sample size of approximately 200250 respondents aged 1825years, the research aims to provide a comprehensive view of Gen Zs viewpoints on AIs ethical and societal ramifications. Findings emphasize the need for transparent and accountable AI systems, as Gen Z is uncomfortable with the ambiguity in AI algorithms. Concerns about privacy and data security highlight the necessity for robust safeguards. They also advocate for strategies to address job displacement and ensure harmonious coexistence between humans and AI. In education, Gen Z sees AI as transformative, endorsing personalized learning. They stress the importance of regulatory frameworks to combat AI bias. They recognize AIs potential to enhance human connections and combat social isolation. The studys findings contribute to policy discussions, educational strategies, and business practices, offering insights into how to harness AIs benefits while mitigating its potential pitfalls. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.