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Big Data and Artificial Intelligence for Strategic Human Resource Management
In this modern world all the organizations are adopting the new technology and making the use of modern technologies to match the HR procedures with the strategic Big Data and AI enhance HR decision-making by providing insights into workforce demographics, performance patterns, and employee behavior. Together, they automate tasks like hiring, training, and performance reviews, while addressing skill gaps, talent acquisition, and retention with unmatched precision. The study examines several important applications, including predictive analysis for workforce planning, AI driven recruitment system and real-time employee sentiment analysis. Additionally, it looks at data protection issues, ethical issues and the necessity of HR personnel being skilled in order to use these technologies effectively. The study demonstrates how Big Data and AI have the ability to change SHRM from a reactive role into a proactive, value-creating discipline by examining case-studies and new trends. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Big Data Analytics: A Trading Strategy of NSE Stocks Using Bollinger Bands Analysis
The availability of huge distributed computing power using frameworks like Hadoop and Spark has facilitated algorithmic trading employing technical analysis of Big Data. We used the conventional Bollinger Bands set at two standard deviations based on a band of moving average over 20 minute-by-minute price values. The Nifty 50, a portfolio of blue chip companies, is a stock index of National Stock Exchange (NSE) of India reflecting the overall market sentiment. In this work, we analyze the intraday trading strategy employing the concept of Bollinger Bands to identify stocks that generates maximum profit. We have also examined the profits generated over one trading year. The tick-by-tick stock market data has been sourced from the NSE and was purchased by Amrita School of Business. The tick-by-tick data being typically Big Data was converted to a minute data on a distributed Spark platform prior to the analysis. 2019, Springer Nature Singapore Pte Ltd. -
Big Data Analytics Tools and Applications for Modern Business World
In the modern world, data is the unavoidable word. The digital environment in almost all our day to day life is linked with digital data. Effective data management is one of the important tasks. The gradual growth of technology in recent years, the generation of data has increased exponentially. Everything, ranging from sending a mail to simply browsing the internet generates data and this is collected and stored. This data has countless uses in various fields such as medicine, business, agriculture and marketing, but most of the time it goes unused. Business intelligence is a key factor in the current business world. Business growth is purely depending on technology. Technology is not only used in manufacturing it is applied to getting the customer. The data analytics is still in its earlier stages and has a long way to go before it yields favourable results. It is a good time as any to start working in this domain to utilize its prowess. This article has discussed the opportunities and growth of data analytics in the research domain. It can face soon when it reaches its advance stages. The big data is handling a larger amount of data in a conventional and non-conventional manner. Technology is playing a vital role to handle larger data from the database. This article is to discuss data analytics application in modern industry. In the technical perspective, big data Map-reduce is an advanced tool and for simulation part, R tool is used. 2020 IEEE. -
Big data analytics lifecycle
Big data analysis is the process of looking through and gleaning important insights from enormous, intricate datasets that are too diverse and massive to be processed via conventional data processing techniques. To find patterns, trends, correlations, and other important information entails gathering, storing, managing, and analyzing massive amounts of data. Datasets that exhibit the three Vs-volume, velocity, and variety-are referred to as "big data. " The vast amount of data produced from numerous sources, including social media, sensors, devices, transactions, and more, is referred to as volume. The rate at which data is generated and must be processed in real-time or very close to real-time is referred to as velocity. Data that is different in its sorts and formats, such as structured, semi-structured, and unstructured data, is referred to as being varied. 2024, IGI Global. All rights reserved. -
Big data analytics in tourism development and marketing: Theoretical perspectives on big data analytics in tourism marketing
The title of the suggested book chapter is " Theoretical Perspectives on Big Data Analytics in Tourism Marketing" and it is about the influence of big data analytics in the growth and promotion of tourism. It just shows how the AI and Metaverse can strategically use big data for better Market Segmentation and Customer behaviour analysis. This chapter looks at how metaverse technology allows tourists to participate in virtual experiences. Tourism companies can refine their marketing strategies, streamline operations, and provide value added experiences to their consumers by utilizing big data analytics. This Chapter underlines the power that big data has to change the tourism industry by enhancing decision making and spurring innovation in service provision. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Big Data Analytics and Intelligent Applications for Smart and Secure Healthcare Services
The book provides a comprehensive discussion for utilizing computational models such as artificial neural networks, agent-based models, and decision field theory, for reliability engineering. It further presents optimization solutions for smart and secure healthcare services. The text showcases how to predict the failure and repair rates of healthcare subsystems using computational intelligence. This book: Explores how data-driven methodologies and advanced computational intelligence are revolutionizing the healthcare industry, promoting efficiency, accessibility, and sustainability Highlights the pivotal role that big data analytics plays in harnessing vast amounts of patient records, clinical information, and real-time medical data to provide timely insights for healthcare professionals and policymakers Discusses the integration of artificial intelligence and machine learning techniques in healthcare, with a focus on revolutionizing disease detection, treatment planning, and resource allocation Lays the foundation for developing sustainable healthcare systems that are adaptable to long-term challenges, such as population growth, emerging diseases, and resource constraints Covers computational intelligence techniques, like fuzzy logic, neural networks, and evolutionary computations, emphasizing their role in solving complex, data-driven healthcare problems Includes topics like data management, visualization, protection, and complex adaptive systems, as well as hybrid computational intelligence techniques for synergistic problem-solving strategies This volume will serve as an ideal text for senior undergraduates, graduate students, and academic researchers in fields including electrical engineering, electronics and communications engineering, computer engineering, and mathematics. 2025 selection and editorial matter, Kamal Upreti, Nishant Kumar, Mohammad Shabbir Alam, Mohammad Shahnawaz Nasir and Debabrata Samanta; individual chapters, the contributors. -
Bifunctional CoPBO/Co-MOF composite electrocatalyst for energy-efficient hydrogen evolution by urea-assisted water splitting
Urea oxidation reaction (UOR) offers a lower energy alternative to generate hydrogen from urea-based wastewater while simultaneously contributing to environmental remediation. However, the commercial viability of this process is hindered by the inability of the electrocatalyst to achieve higher current densities for UOR due to the competition with the OER. In this study, a cobalt-MOF-derived CoPBO/Co-MOF composite electrocatalyst was synthesized over Ni foam using a solvothermal method followed by a simple chemical reduction method for UOR. The CoPBO/Co-MOF@NF demonstrated excellent electrocatalytic bifunctional activity with low potentials of +1.32 V and ?0.095 V for UOR and HER, respectively, at 100 mA/cm2 in 1 M KOH +0.33 M urea solution. Under industrial-level alkaline conditions (6 M KOH), the potential requirement for UOR is further decreased to 1.14 V, also achieving a high current density of 1 A/cm2 at only 1.35 V, which is below the thermoneutral voltage for water splitting. Comprehensive electrochemical kinetic analysis revealed that the CoPBO/Co-MOF composite effectively combines the attributes of CoPBO, for strong OH? adsorption and CoOOH formation, with the affinity of Co-MOF for urea adsorption and CO2 desorption, leading to enhanced UOR performance. Furthermore, in a zero-gap electrolyzer configuration, the CoPBO/Co-MOF@NF catalyst demonstrated remarkable efficiency in actual cow urine (with 1 M KOH), requiring only 1.39 V to achieve a current density of 100 mA/cm2 which is 0.5 V lower than in urea-free water splitting. 2025 -
Bifunctional Amorphous Transition-Metal Phospho-Boride Electrocatalysts for Selective Alkaline Seawater Splitting at a Current Density of 2Acm?2
Hydrogen production by direct seawater electrolysis is an alternative technology to conventional freshwater electrolysis, mainly owing to the vast abundance of seawater reserves on earth. However, the lack of robust, active, and selective electrocatalysts that can withstand the harsh and corrosive saline conditions of seawater greatly hinders its industrial viability. Herein, a series of amorphous transition-metal phospho-borides, namely Co-P-B, Ni-P-B, and Fe-P-B are prepared by simple chemical reduction method and screened for overall alkaline seawater electrolysis. Co-P-B is found to be the best of the lot, requiring low overpotentials of ?270mV for hydrogen evolution reaction (HER), ?410mV for oxygen evolution reaction (OER), and an overall voltage of 2.50V to reach a current density of 2Acm?2 in highly alkaline natural seawater. Furthermore, the optimized electrocatalyst shows formidable stability after 10,000 cycles and 30h of chronoamperometric measurements in alkaline natural seawater without any chlorine evolution, even at higher current densities. A detailed understanding of not only HER and OER but also chlorine evolution reaction (ClER) on the Co-P-B surface is obtained by computational analysis, which also sheds light on the selectivity and stability of the catalyst at high current densities. 2024 The Authors. Small Methods published by Wiley-VCH GmbH. -
Bibliometric Insights into the Nexus of Digital HR, Innovation, and Sustainability: Toward a Smart Workforce
HR professionals use AI, blockchain, cloud computing, big data analytics, and Metaverse to optimize the workforce as technology advances. These technologies boost corporate value, employee performance, and smart workforce development. Metaverse improves virtual reality training, 3D simulations, and wearable self-tracking technologies. Cloud computing simplifies simulations and collaborative mixed reality for employees. AI tools usage increases an organization's staff efficiency. Smart workforce tactics and workplace technologies improve success and human experience management, especially in virtual, remote, and collaborative work contexts. Many companies have failed to integrate Metaverse in the workplace despite advances in digital technologies. A Biblioshiny analysis- based systematic assessment of human capital management automation systems addresses this gap. This study examines smart workforce requirements and future automation trends at the organizational, managerial, and individual levels. Additionally, this study allows for the creation of a self-sustaining virtual HR system. 2025 Scrivener Publishing LLC. All rights reserved. -
Bibliometric Analysis: A Trends and Advancement in Clustering Techniques on VANET
In recent years, Traffic management and road safety has become a major concern for all countries around the globe. Many techniques and applications based on Intelligent Transportation Systems came into existence for road safety, traffic management and infotainment. To support the Intelligent Transport System, VANET has been implemented. With the highly dynamic nature of VANET and frequently changing topology network with high mobility of vehicles or nodes, dissemination of messages becomes a challenge. Clustering Technique is one of the methods which enhances network performance by maintaining communication link stability, sharing network resources, timely dissemination of information and making the network more reliable by using network bandwidth efficiently. This study uses bibliometric analysis to understand the impact of Clustering techniques on VANET from 2017 to 2022. The objective of the study was to understand the trends & advancement in clustering in VANET through bibliometric analysis. The publications were extracted from the Dimension database and the VOS viewer was used to visualize the research patterns. The findings provided valuable information on the publication author, authors country, year, authors organization affiliation, publication journal, citation etc. Based on the findings of this analysis, the other researchers may be able to design their studies better and add more perception or understanding to their empirical studies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Bibliometric Analysis on Multiobjective Optimization and Metaheuristic Algorithm
For difficult optimization issues, metaheuristic algorithms are effective methods for obtaining workable solutions quickly. In the past few years, continuous efforts have been put forward by researchers to develop new effective and robust metaheuristic algorithms for solving engineering optimization problems. The research aims to find the advancements made in multi-objective optimization and metaheuristic algorithms. Metadata of 4149 articles were extracted from Scopus from the year 2000 onward and bibliometric analysis was done with the help of the VOSviewer software. It was found that Mirjalili. S. has the highest number of citations (4011). IEEE Access has published the maximum number of documents (128), the University of Tehrans School of Industrial Engineering has contributed the most in this field of research (43 documents), and China has the most contribution among all the countries with 977 documents. In recent years, the terms optimization algorithms, exploration and exploitation, learning systems, decision-making, uncertainty analysis, sustainable development, supply chains, neural networks, forecasting, machine learning, and cloud computing are being mostly used by researchers. 2026 by Apple Academic Press, Inc. -
Bibliometric analysis of the impact of blockchain technology on the tourism industry
The tourism sector is one of the world's fastest-expanding industries. Because of the benefits, it provides to individuals and organizations, the tourism sector has attracted a lot of attention throughout the years. But because of its poor and obsolete data management techniques, this industry is in desperate need of reform. Blockchain technology is one method for managing and exploring data relevant to the tourism industry. This study used bibliometric methods to analyze the impact of blockchain technology on the tourism sector from 2017 to 2022. The publications were extracted from the dimensions database, and the VOS viewer software was used to visualize research patterns. The findings provided valuable information on the publication year, authors, author's country, author's organizational affiliations, publishing journals, etc. Based on the findings of this analysis, researchers may be able to design their studies better and add more insights into their empirical studies. 2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad. -
Bibliometric Analysis of Gifts in the Era of E-Commerce: A Data Mining Approach
Gifting is a universal phenomenon. It is deeply connected with history, human culture, social interactions, and economic activities. This study aims to look at the work of various researchers on online gifting. The keywords (gift OR gifts) AND (online OR electronic OR e-commerce OR virtual) were used on the Scopus Database. Bibliometric analysis was conducted on 397 relevant publications, which were filtered and selected from the list of 1398 documents. Analysis through Term co-occurrence map, Network visualization map of terms in title/abstract fields, and Topic trends, among others, was done. Four primary clusters were found in the Term co-occurrence map as well as Network Visualization Map Most of the research was from the USA and China. The multi-disciplinary element of gifting is visible in the analysis. Some of the emerging topics were virtual reality, live streaming, social networking, advertising, and online shopping. The impact of gifts in promotions and marketing showed the potential of gifts as a major tool for marketers. The study was limited to only the Scopus database and gives insights into the evolution of online gifting behaviour. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Bibliometric Analysis of AI Research in Sustainable Smart Cities
Smart cities have the potential to improve city-wide governance, environmental sustainability, sustainable transportation, and economic growth. Urban areas may find these advantages useful in their pursuit of SDG-11 objectives. A key component of smart city architecture is the addition of artificial intelligence (AI) and other smart technology into urban areas. The Artificial Neural Network (ANN) is a major machine learning approach. A number of review studies have already been published, reflecting the substantial interest in artificial neural networks (ANN) for smart city applications. In the past, researchers have shown an interest in studying structural monitoring applications, transportation systems, cybersecurity, and the Internet of Things (IoT). But knowledge about how ANN can help Smart Cities achieve SDG-11 is limited. This paper provides a systematic bibliometric analysis of present research trends on artificial neural networks for smart cities, with an emphasis on SDG-11. The research employed a keyword-based search to obtain 131 papers for content analysis and 743 papers for descriptive analysis. Both the amount of interest in the topic and the tendency for related topics to cluster have increased exponentially, according to the findings. Urbanization, Transportation, and Eco-friendly were identified as the main topics of this study. Specifically, this evaluation focuses on particular SDG-11 issues and provides insights on research trends and thematic importance. 2025 Saravanan Krishnan, A. Jose Anand and Raghvendra Kumar. -
Bibliographic Analysis of Soft Computing Components from 1999 2018 in India
The core component of the Soft Computing (SC) domain gives outstanding performances for solving problems compared to other problems solving techniques. In order to solve difficult problems, the majority of researchers are concentrating on the soft computing field. The sub-domains of the soft computing field include Genetic Algorithms, Fuzzy Logic, Machine Learning, Neural Networks, and others. In this paper, we aimed to investigate the contributions made by Indian organizations and authors on the topic of soft computing and its applications for the years 1999 to 2018 for the Scopus database. The study confirmed that the most number of papers published in the neural network with a count of 2127 and the most productive author was M.ChintamaniDeo, with 22 papers with the highest h-index and the Indian Institute of Technology, The most productive institution in the subject of Soft Computing is Roorkee, which has contributed 109 publications overall, garnered 355 citations, and has an h-index of 9. This led us to the conclusion that, in comparison to other sub-domains in the field of Soft Computing and its Applications, Indian Institutions and Indian Authors have produced the majority of publications in Neural Networks and Artificial Intelligence. 2024, Ismail Saritas. All rights reserved. -
Bi Functional Manganese-Pyridine 2,6 Dicarboxylic Acid Metal Organic Frameworks with Reduced Graphene Oxide as an Electroactive Material for Energy Storage and Water Splitting Applications
In recent years, metal organic frameworks (MOFs) with porous carbon materials have significantly improved the design and engineering of high performance electrode materials and have found applications in energy storage devices. This study explores the supercapacitor and electrocatalytic water splitting applications of Mn-MOF/reduced graphene oxide (rGO) composite synthesized via a hydrothermal technique using pyridine 2,6 dicarboxylic acid as a linker. Mn-MOF/rGO exhibits a specific capacitance of 428.28 F g?1 with a rate capability of 83.7% and high cyclic stability. The oxygen evolution reaction of the composite is evaluated using linear sweep voltammetry, and the overpotential is calculated to be 400 mV. Our primary goal is to investigate the effect of rGO on the electrochemical response of MOF. The dielectrode (Mn-MOF/rGO) electrolysis system exhibits long-run stability with a low cell potential of 1.8 V, indicating its prospective application as an excellent water electrolyzer. The combination of Mn-MOF with rGO helps in increasing the number of active sites, thereby improving its electronic conductivity by enhancing the electron transfer rate. The outstanding electrochemical behaviour of Mn-MOF/rGO paves the way for the use of rGO-incorporated Mn-MOF in bifunctional applications as energy-generating and storage devices. 2023 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Bharatanatyam and Art activism in the Networked Digital Space
All over the world, traditional models of art activism through dance involved performances that reached a limited audience, while the advent of networked digital spaces has vastly expanded the scope of art activism to a global level. Offering a qualitative netnographic exploration of how Bharatanatyam has been employed for such art activism in the digital space, this article examines the implications for this prominent traditional South Indian dance form in terms of stylistic changes as well as viewer reactions. Through content analysis of the viewer responses to ten popular renditions uploaded on YouTube over five years (20162020), we trace how the art form is evolving and how activist goals are reciprocated by the audience. Our findings confirm that Bharatanatyam has great potential to evolve by adapting novel social themes. However, while such contemporary renditions may elicit viewer responses that critically appraise specific social issues and pave the way for social change, the resulting innovations continue to co-exist with old conflicts and tensions about traditional art and its uses. 2023 The Author(s). -
Bhagawadgeeta
Bhagawadgeeta (the Divine Song of the Lord), stamp shows the traditional picture of Krishna and Arjuna on the battle field and a stanza 47 of chapter 2 of Bhagawadgeeta "Thy right id to work only, but never to its fruits". It was issued on August 25, 1978. -
Beyond trauma: a culturally grounded call for mindfulness and expressive arts in the mental health response to intimate partner violence among tribal women in India
Purpose This commentary aims to explore the urgent need for culturally grounded mental health interventions for tribal women survivors of intimate partner violence (IPV) in India. It advocates for the integration of mindfulness-based expressive art therapy (MBAT) as a culturally relevant, trauma-informed approach to healing that aligns with indigenous epistemologies and traditional modes of expression. Design/methodology/approach Using insights from a scoping review of existing literature on mindfulness and expressive art therapies for IPV survivors, this paper critically evaluates the limitations of Western therapeutic models in tribal contexts. It synthesizes theoretical frameworks, empirical evidence and cultural considerations to propose a decolonial model of healing centered on community, nonverbal expression and ancestral wisdom. Findings Mindfulness and expressive art therapies demonstrate efficacy in enhancing emotional regulation, reducing trauma symptoms and fostering resilience among IPV survivors. However, existing interventions often lack cultural adaptation and ignore the sociohistorical realities of tribal communities. This paper finds that when these therapeutic modalities are tailored to tribal worldviews through symbolic imagery, indigenous art forms and collective healing practices they become powerful tools for trauma recovery and identity restoration. Practical implications This commentary offers clear implications for practice, including culturally responsive therapist training, community-based MBAT delivery and participatory program design. It urges policymakers to incorporate MBAT into district-level public health initiatives and calls for further research on culturally adapted interventions in tribal settings. Originality/value This work contributes original insights by reframing MBAT not as an alternative therapy but as a culturally and spiritually congruent first-line approach for tribal IPV survivors. It bridges gaps in both theory and practice by integrating decolonial perspectives, arts-based methodologies and indigenous knowledge systems into mental health discourse. 2025 Emerald Publishing Limited -
Beyond Transcripts: A Learner-Centred Review for Closing the Graduate Skills Gap
The majority of the university graduates leave their courses with high grades, but they usually do not have the necessary skills needed in the working environments including teamwork, problem-solving and digital skills. This disconnect between higher education training and the needs of the industry is what is referred to as the graduate skills gap. The article consists of a literature review from 2020-2025 to explore how learner-centred pedagogy can be used to reduce this gap. The results have shown that project-based learning, real-life assessment, internship and micro-credential equip students better than conventional exams. Employers prefer technical and soft skills to academic performance, but most universities are facing problems with stiff curricula and lack of faculty training. This review proposes the incorporation of practice projects, industry partnership, and online skill records to fill the gap. These are some of the strategies that can be used to equip the students with the competencies needed in the current dynamically changing labour market. 2025 IEEE.