Synergizing Humanity and Technology: A Human-Machine Collaboration for Business Sustainability in Industry 5.0
Human-machine collaboration; Industry 5.0; People-centric approach; Sustainability
In the context of Industry 5.0, this paper emphasizes the crucial role of human-machine collaboration for sustainable business practices. It explores the need for a people-centric approach, recognizing the significance of the human workforce alongside advanced technologies. The study investigates three influential theoriesActor-Network Theory (ANT), Activity Theory, and Socio-Technical Systems Theory (STS)proposing a novel Socio-Technical Interaction Network (STIN) model that synthesizes their strengths. The STIN model views systems as intricate networks of diverse actors, both human and non-human, acknowledging their agency and interactions within socio-technical environments. By incorporating elements from each theory, it prioritizes contextual analysis, considering socio-cultural and environmental influences on human-technology interactions. The STIN model aims to provide a holistic lens for interdisciplinary research and guide the design of technology-infused systems aligned with human needs and societal contexts. In conclusion, human-machine collaboration is deemed not just a technological necessity but a strategic imperative for organizations striving for long-term sustainability in Industry 5.0, fostering adaptability, innovation, and sustainable practices. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Nair S.; Kumar A.A.; Chacko E.; Simon S.
Studies in Systems, Decision and Control, Vol-535, pp. 105-115.
Springer Science and Business Media Deutschland GmbH
Nair S., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India; Kumar A.A., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India; Chacko E., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India; Simon S., Department of Psychology, Kristu Jayanti College, Karnataka, Bengaluru, India
Analyzing Risk-Return Trade-Offs Using ARCH and GARCH Models of the BRICS Countries
This study investigates financial markets in BRICS nations (Brazil, Russia, India, China, and South Africa) from 2003 to 2023. It examines mean returns, volatility, skewness, and kurtosis, assessing normality and data stationarity. ARCH-GARCH models uncover conditional heteroskedasticity and volatility clustering. It also explores mean reversion and momentum effects in the Nifty and MOEX indices. Findings show negative, near-zero mean returns, except for SSEC, which is modestly positive. Serial correlation suggests past values impact current returns. Volatility varies, with MOEX and SSEC having higher levels. ARCH-GARCH models indicate volatility clustering and non-normal return distributions. Mean reversion and momentum effects are identified in Nifty and MOEX, benefiting investors, financial institutions, and policymakers. This research informs investment strategies, risk management, and financial forecasts in BRICS economies, contributing to the understanding of the global financial landscape and potential contagion effects. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Shashidhar Yadav J.; Dhaku C.R.; Bhat S.R.; Jagadeesha G.T.; Manjunatha G.; Druvakumar M.
Studies in Systems, Decision and Control, Vol-540, pp. 109-119.
Shashidhar Yadav J., Department of Commerce, MLA Academy of Higher Learning, Karnataka, Bengaluru, India, School of Business and Management, Christ University, Bangalore, India; Dhaku C.R., Department of Commerce, CHRIST (Deemed to be University), Bengaluru, India, School of Commerce, Finance and Accountancy, Christ University, Bangalore, India; Bhat S.R., Department of Commerce, MLA Academy of Higher Learning, Karnataka, Bengaluru, India, School of Commerce and Management, Alliance Ascent College, Bangalore, India; Jagadeesha G.T., Department of Commerce, Seshadripuram College, Karnataka, Tumakuru, India; Manjunatha G., Department of Commerce, St. Claret College, Karnataka, Bengaluru, India; Druvakumar M., Department of Commerce, Kristu Jayanti College, Karnataka, Bengaluru, India
Advancing Nutrient Removal and Resource Recovery Through Artificial Intelligence: A Comprehensive Analysis and Future Perspectives
Artificial intelligence (AI); Environmental engineering; Nutrient removal; Resource recovery; Sustainable innovations; Wastewater treatment
The increasing difficulties associated with effectively controlling wastewater treatment operations while simultaneously satisfying the imperatives of nutrient removal and resource recovery have necessitated the use of advanced technology. This book chapter provides a comprehensive analysis of the use of artificial intelligence (AI) methods within this complex context. Utilizing a vast array of scholarly investigations and real-world implementations, this study explores the intricate domain of wastewater treatment, providing a comprehensive understanding of how artificial intelligence algorithms are used to enhance the efficiency of nutrient removal procedures and expedite the recovery of valuable resources. This chapter presents a thorough examination of the impact of artificial intelligence (AI) on sustainable innovations in wastewater treatment facilities. It accomplishes this through a comprehensive analysis of relevant data and the inclusion of real-world case studies. The findings of this research highlight the transformative effect of AI on conventional approaches to wastewater treatment, enabling the adoption of environmentally friendly and resource-efficient practices. The integration of artificial intelligence (AI) with wastewater management offers a fascinating story that highlights the shifting paradigm in the field of environmental engineering and the efficient exploitation of resources. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Springer Water, Vol-Part F3340, pp. 83-116.
Hemanth K.S., School of Computer Science and Applications, REVA University, Bengaluru, India, Department of Computer Science, Christ University, Bangalore, India; Deepika T., School of Computer Science and Applications, REVA University, Bengaluru, India; Lakshmi V., School of Computer Science and Applications, REVA University, Bengaluru, India
The use of artificial intelligence (AI) techniques for data collection and analysis is examined in this chapter. It also looks at the benefits, challenges, and future directions. It provides a broad overview of AI techniques and illustrates the use of generative adversarial networks (GANs), recurrent neural networks (RNNs), convolutional neural networks (CNNs), etc. in this area. Data recovery is an essential process when trying to recover lost or damaged data. For AI methods like CNN, the retrieval of image and video data has shown great promise. Using the power of deep learning, CNNs can search for patterns in data, assisting in the reconstruction and restoration of lost information. On the other hand, RNNs excel at retrieving serial data, such as text or time series data. These networks can efficiently learn dependencies and contexts, which makes it possible to precisely reconstruct missing or imperfect sequences. AI-based data analytics provides businesses with insightful information and opportunities. GANs, for example, are increasingly being used to generate and improve data, enabling organizations to expand the size of their datasets and improve the efficacy of their analytical models. Large amounts of data can also be divided up using A-based clustering algorithms, which are also well classified and provide insightful analysis and interpretation. In the gathering and analysis of data, AI has many benefits. Businesses can process and analyze enormous amounts of data in a fraction of the time thanks to this productivity-boosting automation of challenging and time-consuming tasks. By reducing bias and human error, AI techniques also increase accuracy, resulting in results that are more dependable and consistent. Additionally, AI-driven insights assist businesses in spotting trends, uncovering buried patterns, and coming to wise decisions that may not be apparent using traditional analytics methods. Due to privacy concerns, ethical considerations, interpretability, transparency, and accountability, AI deployment in data recovery and analysis is difficult. Future directions include collaboration between humans and AI, edge computing integration, and privacy-preserving methods. In conclusion, organizations looking to maximize their data assets stand to benefit greatly from the application of AI techniques to data analytics and data retrieval. 2024 selection and editorial matter, Kavita Saini, Swaroop S. Sonone, Mahipal Singh Sankhla, and Naveen Kumar.
Singh A.; Joshi A.; Sankhla M.S.; Saini K.; Choudhary S.K.
Artificial Intelligence in Forensic Science: an Emerging Technology in Criminal Investigation Systems, pp. 142-164.
Singh A., School of Forensic Science and Risk Management, Rashtriya Raksha University, Gujarat, India; Joshi A., Department of Forensic Science, School of Life Science, Christ Deemed-to-be University, Karnataka, Bangalore, India; Sankhla M.S., Department of Forensic Science, University Center for Research and Development (UCRD), Chandigarh University, Punjab, Mohali, India; Saini K., School of Computing Science & Engineering (SCSE), Galgotias University, Delhi, India; Choudhary S.K., Rashtriya Raksha University, Gujarat, India
Overview of Cyber Security in Intelligent and Sustainable Manufacturing
With the advent of the Internet of Things (IoT), a new transformation is predominant in the manufacturing industry, termed Industry 4.0. The revolution of IoT with artificial intelligence, Web3, robotics, and automation has transformed the traditional manufacturing system into a smart manufacturing system (SMS) by adding an intelligent component capable of automatic data collection through using sensors, processing data autonomously, and controlling machines remotely. However, adding automated intelligence, autonomous systems, and real-time data processing presents an insecure surface to cyber attackers to penetrate these cyber-physical systems (CPSs) and cause physical damage. This chapter presents a detailed discussion of cyber threats and incidents in the intelligent manufacturing industry, along with the available acceptable mitigation strategies. A taxonomy of cyber attacks on intelligent manufacturing systems clearly shows the difference between information technology threats and smart manufacturing cyber-threats. A detailed discussion on the limitations of SMSs in implementing cyber security is presented. Finally, some innovative machine learningbased security mechanisms (ML-based intrusion detection systems) are discussed that promise to detect anomalies/intrusions in such systems. 2025 selection and editorial matter, Ajay Kumar, Parveen Kumar, Yang Liu, and Rakesh Kumar.
Paul A.; Sinha S.; Kumar P.; Choudhary S.; Samdani K.; Mishra S.
Handbook of Intelligent and Sustainable Manufacturing: Tools, Principles, and Strategies, pp. 95-118.
Paul A., Banasthali Vidyapith (Deemed to be University), Rajasthan, India; Sinha S., CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Kumar P., Department of Mechanical Engineering, Rawal Institute of Engineering and Technology, Haryana, Faridabad, India; Choudhary S., Banasthali Vidyapith (Deemed to be University), Rajasthan, India; Samdani K., Banasthali Vidyapith (Deemed to be University), Rajasthan, India; Mishra S., Banasthali Vidyapith (Deemed to be University), Rajasthan, India
Sustainable Waste Management and Womens Empowerment
Waste management is a problem faced by major cities. Rural migration to urban areas created unplanned residential areas and high population density, and temporary living structures have a direct impact on poor waste management systems in urban areas. From September 2020 until February 2021, a case study was conducted (the first lockdown period of the COVID-19 Pandemic) among women members from an urban slum in Bangalore with objectives to understand the prevalent process of waste management and comprehend the association between womens empowerment and sustainable waste management in a slum community. The purposive sampling technique was applied to select 10 women members of the slum community for this community-based participatory research as co-researchers from the slum community, along with all stakeholders. The results show that the women members could implement the immediate plans on waste management, including educating their neighbours on waste management, to ensure that a large part of the society they are living in is aware of it. The women members demonstrated their motivation and willingness in their actions in the slum neighbourhood concerning sustainable waste management. They applied their participatory activities to empower other women in the area by focussing on every stretch of the slum and educating on the management of waste. All the actions by the women members in the urban slum community and the stakeholders of waste management in that community intend to support the quality of life and strengthen the resilience to climate change through sustainable waste-management and are reflected in SDG 3, SDG 5, SDG 11, and SDG 13. 2024 CRC Press.
Waste Management and Treatment: Advances and Innovations, pp. 278-293.
Karalam S., Department of Sociology and Social Work, Christ University, Bangalore, India; Vincent T.N., Department of Commerce, Christ University, Bangalore, India; Francis A., Social Work and Human Services, College of Arts, Society, and Education (CASE), Division of Tropical Environments and Societies (DTES), James Cook University, Douglas, Townsville, Australia
Role of Digital Lending in Serving Financially Excluded Individuals and Small Medium Businesses in India
Financial inclusion has become a national strategy for the achievement of an inclusive economy and inclusive society in emerging countries. Access and continuous usage of formal financial services by the financially excluded people are known as financial inclusion. Financially excluded people are still there across the globe and in India. In India, although there are many supply-side and demand-side constraints for promoting financial inclusion, the vital constraint of financial inclusion is the inability of formal financial institutions to serve the unbanked and underbanked by adopting disruptive technologies for their business models and by developing and delivering innovative and customised financial products and services. Formal financial institutions embrace technologies such as Artificial Intelligence, Machine Learning, and Big Data Analytics for their operations in a gradual pace when compared to FinTech start-ups. But Digital Lending Start-ups make all the efforts to serve the unbanked and underbanked population through AI-powered alternative scoring methodology and customised digital loans. This article focuses on the process in which Digital Lending Start-ups serve the financially excluded individuals and Small and Medium Businesses in India. Further, this article analyses the growth, acceptance, future potential, and limitations of digital lending in India. 2024 selection and editorial matter, Satyajit Chakrabarti, Saikat Chakrabarti, Amit Kumar Bhandari, Dipak Saha and Rabin Mazumder.
Perspectives in Finance and Digital Transformations in Business, pp. 211-217.
Ravikumar T., CHRIST, Deemed University, Bangalore, India; Murugan N., PSNA College of Engineering and Technology, Tamil Nadu, Dindigul, India; Suhashini J., PSNA College of Engineering and Technology, Tamil Nadu, Dindigul, India
IPR in Stem Cell Research, Therapy, and Regenerative Medicine
According to the World Trade Organization, intellectual property rights are rights given to persons over the creations of their minds. They usually give the creator an exclusive right over the use of his or her creation for a certain period. There is a critical need for fresh developments in the existing medical diagnostic techniques, therapy, pharmaceutical medications, and research, in a world where such a sizable number of people are afflicted with various ailments, some of which are fatal and still incurable. Pharmaceutical companies are developing novel and cutting-edge ways to treat diseases at an increasing rate. The major pharmaceutical corporations in the world, including Pfizer, Miltenyi, Biotec, AstraZeneca, and Mesoblast Limited are pursuing research in the area of stem cell and regenerative medicine. Regenerative medicine, stem cell research, and therapy are currently regarded as groundbreaking developments in the medical sciences. Understanding their intellectual property rights and the legal means through which these businesses can safeguard their discoveries becomes crucial. This paper will analyze the meaning of stem cell and regenerative medicines, the eligibility of IPR in Stem cell research under the Indian Patents Act, of 1970 and the morality and public issues related to the same. 2024 Taylor & Francis.
Intellectual Property Rights and Competition Law in India, pp. 30-41.
Doyil D., CHRIST (Deemed to be University), Delhi-NCR, India; Sharma M., School of Law, Justice, and Governance, Gautam Buddha University, India
Blockchain and Green Finance: The Way Forward
A disruptive digital force is altering business paradigms and increasing relevance around the world. Blockchain technology is attracting significant interest in India from a variety of businesses. As the range of uses for blockchain technology expands, industry leaders are adopting and modifying it to suit a variety of use cases. In 2016, adoption of blockchain technology gathered significant momentum in India. In a variety of use cases, many banks and commercial conglomerates have experimented with blockchain technology. Although blockchain technology is still in its infancy, Bitcointhe most well-known use casehas taken off very successfully in India, with several Bitcoin exchanges and wallets spreading throughout the nation. The regulatory organizations are establishing working groups to understand and monitor the development of blockchain technology in India after realizing the potential of the technology. Blockchain is used in green bonds, asset tokenization, carbon credit trading, and transparent reporting. One of the real-life examples is IBM and Veridium Labs, which have worked on a blockchain-based initiative to tokenize carbon credits. The purpose is to improve the efficiency and transparency of carbon trading. Veridium coins represent verified carbon credits, and blockchain secures the credits integrity and traceability. Recently the State Bank of India (SBI) has shown a growing interest in green finance and green bonds. The chapter investigates blockchain applications in the field of green finance. It addresses how blockchain-enabled green asset tokenization might boost liquidity and accessibility for investors, allowing a broader pool of participants to participate in sustainable investments. The article investigates the impact of DeFi platforms in supporting green lending and borrowing, hence lowering reliance on traditional financial intermediaries. 2024 selection and editorial matter, Sukanta Kumar Baral, Richa Goel, Tilottama Singh, and Rakesh Kumar; individual chapters, the contributors.
Green Metaverse for Greener Economies, pp. 22-36.
Divyashree K.S., School of Law, Christ University, Bangalore, India; Mishra A., School of Law, Christ University, Bangalore, India
Exploring the Impact of Behavioral Biases on Young Investors Portfolio Performance: An Examination through the Lens of Nudging Green: Behavioral Economics for Environmental Sustainability
Behavioral finance; Biases; Financial market; Investors behavior
PurposeThis research paper delves into identification of interaction and relationship among numerous factors like investors behavior, psychological factors of investors, specific biases, financial knowledge and literacy, and portfolio value of young investors. Through this research paper we can conclude that investors are increasingly affected by the biases that exist. These biases act as a hindrance in their process of decision making. Design/methodology/approachIn this research paper a survey was conducted and the poll consisted of various questions. In this research paper, a convenience sampling technique was used and responses from 295 investors were collected for analysis of the data. In this paper we have used descriptive analysis and regression correlation for the purpose of analysis which ultimately unfolds the relationship between biases and investors portfolios. FindingsThis paper unfolds the various behavioral factors and other factors that shape the investment portfolio of youth. The paper dwells into the intricate study of behavioral factors that affect youth and determines their investment pattern. Research limitation/implicationsLimited samples have been collected for this paper and that is the limitation of this paper. As the sample size is limited there is a high probability that with a larger group of investors, the behaviour pattern and biases may differ. As most of the investors are young their knowledge about trading market and investment market is quite limited which ultimately generates hindrances in analysis. Maximum number of investors are quite young which increases the probability of biases in the decision making process. Practical implicationsThis paper will help scholars, analysts, academicians, practitioners, policymakers, brokers, and investors to frame better strategies in order to deal with behavioural biases and other behavioural factors. In order to not get influenced with behavioral biases and other behavioral factors, young people can plan out their investments in a better way. The youth of our country can have greater understanding regarding investments if they are given enough wisdom regarding the same through workshops, webinars, seminars, lectures, curriculum. Originality/valueIn this paper investors behavior, psychological factors, specific biases, financial knowledge and literacy are factors that influence the investment portfolio of young investors. Young investors can keep these factors in mind in order to increase their portfolios value which will ultimately lead to better investment decisions among them. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
World Sustainability Series, Vol-Part F3319, pp. 85-104.
Rai A., Department of Commerce, CHRIST (Deemed to be University) Delhi NCR, Ghaziabad, India; Kar A., Department of Commerce, CHRIST (Deemed to be University) Delhi NCR, Ghaziabad, India; Singh S., Department of Commerce, CHRIST (Deemed to be University) Delhi NCR, Ghaziabad, India; Yadav S., Department of Commerce, CHRIST (Deemed to be University) Delhi NCR, Ghaziabad, India
Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Human Resource Professionals Perceptions on the Future of Work
Factors influencing STARA; HR Strategies; Opinion; Organizational performance; Perception; STARA awareness
Technology is revolutionizing the manner in which human resources are governed in establishments worldwide. As an increasing number of businesses adopt digital instruments to monitor employee performance, optimize procedures, and enhance communication, HRM must persistently innovate to keep pace with these alterations. The utilization of contemporary technology enables HR departments to become more proficient, streamline procedures, and make more astute decisions. Intelligent Technology, Synthetic Intelligence, Robotics, and Algorithms (STARA) technologies can be groundbreaking in this aspect, empowering establishments and their corresponding HR departments to exponentially flourish with their human resource relative initiatives. The objective of this investigation is to scrutinize the perspectives of HR Professionals on STARA awareness and their vision regarding the prospective influence of its integration on the future of work. Through the utilization of a mixed-data-based exploratory analysis, the researcher examines the facets of STARA awareness, STARA advantages, implementation challenges, and future scopes of STARA relative technologies to expedite HRM and organizational superiority. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Suvarna S.; Aranha R.; Balsundaram S.; Basavaraj S.
Studies in Systems, Decision and Control, Vol-537, pp. 307-321.
Suvarna S., Christ University, Bengaluru, India; Aranha R., Christ University, Bengaluru, India; Balsundaram S., Christ University, Bengaluru, India; Basavaraj S., Christ University, Bengaluru, India
Decent Work Deficit: A Challenge on the Women Empowerment in Indian Agricultural Sector
Agricultural sector; Decent work; Women empowerment
Women play a crucial role in Indian agriculture, but they also confront several obstacles that reduce their productivity and prevent them from fully engaging in the sectors development. The majority of women in India are employed in agriculture, which is one of the sectors that contributes most to the GDP and is essential to the economic development of the nation. Although women continue to have a significant and recognized role in agriculture, their function is frequently overlooked. Women make up about 75% of the full-time labor force on Indian farms. The nation wont develop unless its women farmers are empowered. Only through decent work labour the agriculture sector will be developed which will help in the empowermentof women agricultural Labourers in India. So the government should take all steps to implement the decent work concept of ILO in the Indian agricultural sector. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Rajan P.R.; Sindhu J.S.; Rishikesh K.B.; Shri M.R.
Studies in Systems, Decision and Control, Vol-535, pp. 301-308.
Rajan P.R., D. Y. Patil Institute of Management Studies, Pune, India, Economics, Zamorins Guruvayurappan College, Kozhikode, India; Sindhu J.S., PG and Research Department of Economics, A.M. Jain College, Meenambakkam, Tamil Nadu, Chennai, 600061, India; Rishikesh K.B., Department of Commerce, CHRIST (Deemed to be University), Bangalore, India, Bharathiyar University, Coimbatore, India; Shri M.R., PG and Research Department of Economics, A.M. Jain College, Meenambakkam, Tamil Nadu, Chennai, 600061, India
Computational techniques for sustainable green procurement and production
Computational techniques; computing; green procurement; procurement
Computational techniques are used to generate, solve, analyze, explain, or manage any simple or complex task. The use of environmentally responsible techniques to meet demand for resources, commodities, utilities, and services is known as green procurement. Computational technique in green procurement and production is one of the components of sustainable procurement, along with a commitment to social responsibility and good corporate behavior. Some solutions for this kind of issue are low-maintenance, energy-efficient, and long-lasting. Several experts and researchers provided their findings on the environmental impact of ICT with the use of computational techniques. Also, the importance of energy-efficient information technology for environmentally conscious and feasible information technology is a hot topic because a computer faces environmental challenges at every stage of its life, from development to use to disposal. Due to changing environmental conditions, corporations have prioritized carbon emissions in procurement and transportation, which have the highest carbon impact. To encourage potential suppliers to adopt environmentally friendly practices, green criteria should be introduced into public procurement. Environmentally friendly corporate practices and environmental conservation are considered significant tools through public procurement. Techniques for green procurement and production procedures have recently been correlated with the concept of computational techniques of green procurement and production, owing to the increased emphasis on the concept of computational approaches. For eco-friendly procurement and production operations, computational approaches are inculcated and presented in the same way that they are for green procurement and manufacturing. From this perspective, this chapter presents a methodology for merging computational techniques into green procurement and production in public procurement in the form of green computing. 2024 by Elsevier Inc. All rights reserved, including those for text and data mining, AI training, and similar technologies.
Computational Intelligence Techniques for Sustainable Supply Chain Management, pp. 275-300.
Parashar B., VIT-Bhopal University, Madhya Pradesh, Bhopal, India; Kautish S., LBEF Campus (APU Malaysia) Kathmandu, Nepal, Model Institute of Engineering and Technology, Jammu and Kashmir, Jammu, India; Chaurasia A., School of Commerce, Finance and Accountancy Christ (Deemed to be University), Uttar Pradesh, Ghaziabad, India
Strategizing Talent Acquisition for Fostering Future Workforce Success: Addressing Millennial Turnover and Hiring Challenges in a Rapidly Evolving Business Landscape
And hiring challenges; Employee retention; Employee turnover; Human resource management; Talent acquisition strategy
Rapid technical breakthroughs and a competitive labor market characterize today's business prospects, emphasizing the need for successful recruitment and talent acquisition. Preparing for your company's future workforce entails evaluating who, when, why, and how you hireall of which are mirrored in your talent acquisition strategy. If given the option, 49% of Millennial workers would quit their present employment within the next two years (2019 Deloitte Global Millennial Survey). Many businesses consider finding the right people with the proper abilities their most pressing hiring challenge. Companies that employ effective talent acquisition methods lead to a successful workforce. However, lousy hiring can significantly reduce company profitability and efficiency. This research paper aims to analyze the current talent acquisition practices and processes adopted by the company and to understand the various factors affecting talent acquisition practices. A proactive talent acquisition strategy, encompassing strategic workforce planning, employer branding, continuous talent pipelining, technological integration, skill development, collaboration with educational institutions, data-driven decision-making, and a commitment to diversity and inclusion, forms a comprehensive model for long-term sustainable success. By adopting and adapting these practices, organizations can build a resilient and adaptable workforce capable of navigating the challenges of an ever-evolving business landscape. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Philip B.; Mathew G.A.; Sebastian R.T.; Eshwari B.; Roopa M.B.; Mathews S.B.
Studies in Systems, Decision and Control, Vol-535, pp. 357-368.
Philip B., Department of Management, Kristu Jayanti College Autonomous, Bengaluru, India; Mathew G.A., Department of Management, Kristu Jayanti College Autonomous, Bengaluru, India; Sebastian R.T., Department of Management, Kristu Jayanti College Autonomous, Bengaluru, India; Eshwari B., Department of Management, Cambridge Institute of Technology, Bengaluru, India; Roopa M.B., Department of Business and Management, Christ University, Bengaluru, India; Mathews S.B., School of Management, Kristu Jayanti College, Bengaluru, India
Portfolio optimization using simulated annealing and quantum-inspired simulated annealing: A comparative study
Evolutionary algorithm; Portfolio optimization; Quantum-inspired metaheuristic; Quantum-inspired simulated annealing; Simulated annealing
Portfolio optimization has been a highly studied problem in financial investment expert systems. The nonlinear constraint portfolio optimization problem cannot be efficiently solved using traditional approaches. This chapter presents a metaheuristic approach to portfolio optimization using simulated annealing (SA). Experiments have been conducted on over 10 years of NASDAQ stock price data. This first-of-its-kind effort is also made to implement the quantum-inspired version of SA (QiSA) for portfolio optimization, and the results are compared with the classical approach. The optimization parameters are chosen using sensitivity analysis, and the results are compared using different statistical measures. Preliminary results show that the QiSA approach is very promising and faster than SA when applied to the portfolio optimization domain. 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications, pp. 213-243.
Gunjan A., Christ (Deemed to be University), Bengaluru, India; Bhattacharyya S., VSB Technical University of Ostrava, Ostrava, Czech Republic, Algebra University, Zagreb, Croatia
Food Security and Global Institutions: A Global Justice Perspective
Food security; Global institutions; Global justice; Human rights; Poverty
Food security refers to a condition where all people have physical and economic access, at all times, to sufficient, safe and nutritious food that meets their needs and food preferences to lead an active and healthy life. Universal Declaration of Human Rights, 1948 (UDHR) declares the right to food as a basic human rights. International Covenant on Economic, Social and Cultural Rights, 1976 (ICESR) explicitly recognises the right of everyone to food and mandates all state parties for its realization; also it recognizes everyones right to be free from hunger as a fundamental right. Further, it instructs the state parties to ensure equitable distribution of world food supplies to achieve the right of everyone to be free from hunger. Rome Declaration on World Food Security, 1996 reaffirmed the right of everyone to access to safe and nutritious food compatible with right to adequate food and also right to be free from hunger. United Nations Millennium Declaration set the goal for fighting hunger and resolved to reduce the proportion of people suffering from hunger to half by 2015, then Sustainable Development Goals were floated, inter alia, to end extreme poverty and achieve the target of zero hunger and food security by 2030. Regardless of its being a universal human rights, food security scenario across the globe is far from satisfactory and fair. Post COVID 19 scenario has seen a surge in undernourishment and food insecurity. According to The State of Food Security and Nutrition in the World, 2022, 3.1 billion people across the globe are unable to afford a healthy diet. At this juncture we are living in a deeply connected and globalized world run not by national institutions but by global institutions. The role of global institutions assume significance in a globalized world. Justice demands that policy planning and legal framework on food security should be fair and equitable; they should be based on the idea of entitlement and obligation. To achieve the goal of zero hunger and food security, what is required is an equitable and unified global governance approach premised upon the idea of global justice which shall fix obligations on global institutions. This chapter aims at examining the issue of food security from a global justice perspective and how it can be sustainably achieved. It will explain the concept of global justice and obligations of global institutions by relying upon few legal and political theories. Further, the chapter will explain the human rights perspective of the food security and the challenges involved with it. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Food Security in a Developing World: Status, Challenges, and Opportunities, pp. 53-71.
Mishra A., School of Law, Christ University, Bengaluru, India
Determinants; Food security; Global trade; Impact
Global trade can increase food availability and improve food security by facilitating food movement between countries and regions. However, it also poses challenges to food security, including the displacement of small-scale farmers and food producers, food safety risks, dependence on imports, and the distortion of global trade through agricultural subsidies. To ensure food security in global trade, a coordinated and multi-sectoral approach is needed that promotes sustain-able and equitable food systems, local food production, and food safety. Addressing these challenges is critical for ensuring the adequacy and accessibility of sufficient, safe, and nutritious food while fostering economic development and environmental sustainability. Economic development and government policies are crucial deter-minants of a countrys ability to engage in global trade and ensure food security. Climate and weather patterns, agricultural practices, infrastructure and transporta-tion, and market demand influence food security significantly. Furthermore, interna-tional conflicts disrupt trade and impact food security. Policymakers must consider all these factors while developing policies promoting trade and ensuring food secu-rity. To solve these complicated concerns and promote sustainable agriculture and trade practices, governments, international organizations, and the corporate sector must work in concert to improve food security. Food security has a significant impact on global trade, as the availability and accessibility of food directly affect a countrys ability to engage in international trade. When a country experiences food shortages may reduce or halt its exports, causing a ripple effect in the global economy and leading to higher food prices and insecurity in other countries that rely on imported food. Nevertheless, economies with high levels of food security and surplus food production are better positioned to engage in global trade. They export food to other countries, generating revenue and supporting economic growth by creating trade barriers, as importing countries may reject or restrict such food products, nega-tively impacting global trade. In addition to the economic impacts, food security also has broader societal and environmental implications. For example, food insecu-rity can lead to malnutrition, affecting individuals physical and cognitive develop-ment, particularly children. Moreover, unsustainable agricultural practices can lead to environmental degradation, affecting biodiversity, soil quality, and water resources, affecting food security. The determinants of food security in global trade and its impact are analyzed in this chapter. Since food security is an essential factor in inter-national trade, impacting trade flows, economic growth, and public health. Promoting sustainable agriculture and trade practices and building robust food security systems can support a more resilient and equitable global food system, benefiting producers and consumers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Food Security in a Developing World: Status, Challenges, and Opportunities, pp. 229-258.
Sukanya R., Department of Commerce, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
Delving into the Bubble Detection of Specific NSE Sector Indices
Global crisis; GSADF test; Market bubbles; Pandemic impact; Sector-specific
This study meticulously examines market bubbles within specific sectors of the National Stock Exchange (NSE) over the period from January 2017 to December 2023, employing robust methodologies like RADF, SADF, and GSADF tests. The analysis, centered on 11 sectoral indices, integrates GSADF values with RADF and SADF, offering nuanced perspectives that underscore the sector-specific nature of bubbles. Notably, the study highlights bubble occurrences during the 2020 global crisis due to pandemic, emphasizing their dynamic and diverse manifestations amid the pandemic. Exclusive identification of bubbles in NSE IT, NSE Metal, and NSE Pharma enriches the strategic insights available to investors, facilitating informed decision-making and risk management. The sector-wise approach contributes to a holistic understanding of market dynamics, providing investors with valuable tools to navigate the intricacies of the financial landscape. Future research avenues may delve into regulatory impacts on sector-specific bubbles and explore the interplay between macroeconomic indicators and sectoral bubbles, offering deeper insights into market dynamics. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Shashidhar Y.J.; Sujay C.; Saiprasad D.; Manjunatha G.; Druvakumar M.; Jagadeesha G.T.
Studies in Systems, Decision and Control, Vol-535, pp. 95-104.
Shashidhar Y.J., School of Business and Management, Christ University, Karnataka, Bengaluru, India; Sujay C., Faculty of Management and Commerce, PES University, Karnataka, Bengaluru, India; Saiprasad D., Department of Commerce, Government First Grade College, Karnataka, Thyamagondlu, India; Manjunatha G., Department of Commerce, St. Claret College, Karnataka, Bengaluru, India; Druvakumar M., Department of Commerce, Kristu Jayanti College, Karnataka, Bengaluru, India; Jagadeesha G.T., Department of Business Administration, Seshadripuram College, Karnataka, Tumakuru, India
Employees Job Satisfaction, Work-Life Balance, and Health During the Pandemic
COVID-19 pandemic; Health stress; Job satisfaction; Work-life balance
The impact of the COVID-19 pandemic on private enterprises has been particularly noticeable in the IT and non-ITES sectors. Work came to a complete halt due to the ensuing lockdown, severely affecting businesses and further harming industries like aviation and hospitality. Widespread job losses, shortened workweeks, minimum wage reductions, short-term leave policies, and even company closures have been the results. To understand the extent of these impacts, a descriptive study was conducted online in AprilMay 2021, involving 2439 white-collar workers from various private companies. Convenient sampling methods were used to gather data on the experiences of employees in these sectors during the pandemic. The survey's findings demonstrate a positive but weak association between Work-Life Balance and Health Stress (r?=?0.24, p?<?0.01) and a positive low correlation between Work-Life Balance and Job Satisfaction (r?=?0.23, p?<?0.01). Therefore, work-life balance and job satisfaction among employees were significantly correlated throughout the epidemic. Additionally, there was a negative moderate correlation between Health Stress and Job Satisfaction (r?= ?0.48, p?<?0.01), indicating that as Health Stress decreases, Job Satisfaction increases at moderate levels. The implications of the study were discussed further. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Babu K.; Gireesh K.; Sukumar V.; Sinha A.; Jethwani L.M.; Bhanu B.S.; Madhu Karnat S.
Studies in Systems, Decision and Control, Vol-535, pp. 481-491.
Babu K., Department of Psychology, Alliance University, Bangalore, India; Gireesh K., Department of Psychology, Alliance University, Bangalore, India; Sukumar V., Department of Psychology, Alliance University, Bangalore, India; Sinha A., Department of Psychology, Kristu Jayanti College (Autonomous), Bangalore, India; Jethwani L.M., Department of Psychology, Christ University, Bangalore, India; Bhanu B.S., Department of Psychology, Christ University, Bangalore, India; Madhu Karnat S., Department of Psychology, Gitam (Deemed to be University), Bangalore, India
Covid-19 prediction; Fuzzy soft MCDM; PRONE index; Self-organization; Swarm intelligence and Covid
The entire world experienced a rampant outbreak of Covid-19 beginning in December 2019. The spread of this disease was so rapid and aggressive that many developed countries struggled to control it. However, some countries such as China and Australia have done a commendable job of controlling this virus. Various studies have been done in parallel to analyze strategies to curb the spread of the virus. In many locations, people displayed swarm intelligence. The collective behavior of people was mixed. Some people followed the instructions of the health authorities. In addition to the instructions, people in some localities developed self-organization to resist the spreading of the virus. This research work mainly focuses on the prediction of coronavirus spread in different districts of Kerala by use of a fuzzy approach as the fuzzy approach is considered the best tool that would not show imprecise data in any situation. The PRONE (Predicted Risk of New Event) indexing algorithm was used for finding the intensity of the spread in five districts of Kerala (Trivandrum, Ernakulam, Kozhikode, Kannur, and Kasargod) and was evaluated under the input parameters of immunity of person, food habits, financial factors, and age with the total number of infected people as the output variable. An eight-step algorithm is provided to determine the PRONE index. Kasargod is more vulnerable to the virus. The final results show that this proposed model better predicts virus spread. 2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.
Kalayathankal S.J.; Sukumaran A.; Kureethara J.V.
Recent Trends in Swarm Intelligence Enabled Research for Engineering Applications, pp. 331-341.
Kalayathankal S.J., Jyothi Engineering College, Cheruthuruthy, Thrissur, India; Sukumaran A., Jyothi Engineering College, Cheruthuruthy, Thrissur, India; Kureethara J.V., Christ University, Bengaluru, India