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Cognitive technology in human capital management: a decision analysis model in the banking sector during COVID-19 scenario
Cognitive technologies are products of the artificial intelligence (AI) domain which execute tasks that only humans used to perform. The impact of cognitive technologies on the management of human capital (HC) has a massive effect in the banking sector. This paper studies the transformation of cognitive technology to human capital management (HCM) in the banking sector during the COVID-19 pandemic. The study draws data from 201 bank employees working in private, public, and foreign banks using a multi-stage sampling method in India. A number of hypotheses were framed and tested using multivariate and regression analyses. The results from the study indicate a significant change in the performances of bank employees statistically during the transformation of cognitive technologies. Cognitive technologies such as payment, product customisation, self-services, workload alleviation, automated back-office function, and a personalised experience significantly contribute to the HCM. 2024 Inderscience Enterprises Ltd. -
Sibling Bereavement Among Young Indian Adults
This qualitative study explores the bereavement experiences of 12 surviving siblings in India, focusing on familial, societal, and cultural influences. Six themes emerged: The Demanding Familial Role, Isolation That Accompanies the Grief, Damaging Impact of Society, Positive Role of Friends and Family, Support Systems, and Continuing Bonds. Participants often felt the burden of supporting their parents, leading to personal grief suppression and isolation, exacerbated by societal stigmas. Conversely, empathetic friends, supportive extended family, and professional resources like therapy provided crucial coping mechanisms. Continuing bonds with the deceased offered comfort and connection. The study highlights the need for comprehensive support systems tailored to cultural and societal contexts. It emphasizes the importance of public awareness and education to foster a supportive response to bereavement. Further research with larger, more diverse samples is recommended. The Author(s) 2024. -
Impact of Digital Storytelling on Middle School Students' Attitudes Toward English Language Learning
The integration of digital storytelling (DST) into teaching has significantly influenced educational development, especially English language acquisition. This study examines the impact of DST-integrated pedagogy on students' attitudes and perceptions toward learning English. In a quantitative study using an experimental design, 200 middle school students were purposively selected and divided into control and experimental groups. The control group received the traditional method of language teaching, while the experimental group received the DST method. Data were collected through a survey and analysed using descriptive and Wilcoxon test. The results suggest that exposure to DST positively influenced students' attitudes and led to better understanding, engagement, and motivation in learning English in the treatment group. This suggests that incorporating DST into English lessons can improve teaching quality and students' overall progress. Further analysis is needed to fully explore the potential of DST-based instruction in developing language acquisition skills. 2024 IGI Global. All rights reserved. -
The impact of excess CSR expenditure on firm value anddividend payout in India: ananalysis using firm age andsize dynamics
Purpose: The paper looks at the impact of excess amount of CSR expenditure (CSRE) in relation to mandatory CSRE in an Indian context on dividend payout (DP) and firm value (FV) where CSRE is mandatory, as well as how this relationship varies between firms based on their age and size. Design/methodology/approach: A sample of the 657 companies listed on the National Stock Exchange (NSE) from 201415 to 202021 is used in the study, for which spending on CSR was mandatory. A two-step generalised method of the moment is employed to examine the relationship between the variables of interest. Findings: The results show that excess CSREs neither increase the firms valuation nor benefit shareholders' economic benefits, i.e. dividend distribution. However, a deeper analysis reveals that excess CSRE is positively associated with FV in the case of smaller firms and also positively corresponds with DP in the case of younger firms. Originality/value: The present study explicitly considers the excess CSR spending beyond the mandated requirements. It investigates whether such spending contributes to firms improving their valuation and explores its connection to DPs. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-02-2024-0136. 2024, Emerald Publishing Limited. -
Sociocultural aspects of the medicalisation of infertility: a comparative reading of two illness narratives
This paper is a comparative reading of variations in the medicalisation of infertility caused by sociocultural aspects, in two illness narratives by patients: Elizabeth Katkins Conceivability (2018), a story of navigating a fertility industry with polycystic ovarian syndrome and antiphospholipid syndrome in America and Rohini Rajagopals Whats a Lemon Squeezer Doing in My Vagina (2021), a discussion from India of a growing awareness of medicalisation in treatment of unexplained infertility. For this purpose, it first charts scholarship on illness narratives and medicalisation, noting a historical association. Following this, it shows how infertility, a physiological symptom of reproductive incapacity or failure to show clinical pregnancy, is generally medicalised. This paper reads the texts as showing hitherto unaddressed sociocultural aspects of infertilitys medicalisation. At the same time, drawing from existing sociological and anthropological scholarship, it shows how a reading of sociocultural aspects in medicalised infertility nuances understanding of its medicalisation. This comparative reading attends to sociocultural values and norms within the texts, including pronatalism, fetal personhood, kinship organisation, purity/pollution, individual reliance, sacred duty and so forth. It draws from scholarship on embodiment, rhetorical strategies and the language of medicine. It also shows how a patients non-medicalised, affective history ofdeep sickness caused by the biographical disruption of infertility is not that of apoor historian. In laying out the particularisation of such sociocultural values and norms across America and India, medicalisations migration from its origins to the margins reveals subjectivised, stratified reproduction in infertility illness narratives. This paper is part of a turn in scholarship away from understanding the medicalisation of infertility as naturalised and decontextualised. Author(s) (or their employer(s)) 2024. -
Modelling for working capital efficiency: integrating SBM-DEA and artificial neural networks in Indian manufacturing
Purpose: This study aims to present an innovative predictive methodology that transitions from traditional efficiency assessment techniques to a forward-looking strategy for evaluating working capital management(WCM) and its determinants by integrating data envelopment analysis (DEA) with artificial neural networks (ANN). Design/methodology/approach: A slack-based measure (SBM) within DEA was used to evaluate the WCME of 1,388 firms in the Indian manufacturing sector across nine industries over the period from April 2009 to March 2024. Subsequently, a fixed-effects model was used to determine the relationships between selected determinants and WCME. Moreover, the multi-layer perceptron method was applied to calculate the artificial neural network (ANN). Finally, sensitivity analysis was conducted to determine the relative significance of key predictors on WCME. Findings: Manufacturing firms consistently operate at around 50% WCME throughout the study period. Furthermore, among the selected variables, ability to create internal resources, leverage, growth, total fixed assets and productivity are relatively significant vital predictors influencing WCME. Originality/value: The integration of SBM-DEA and ANN represents the primary contribution of this research, introducing a novel approach to efficiency assessment. Unlike traditional models, the SBM-DEA model offers unit invariance and monotonicity for slacks, allowing it to handle zero and negative data, which overcomes the limitations of previous DEA models. This innovation leads to more accurate efficiency scores, enabling robust analysis. Furthermore, applying neural networks provides predictive insights by identifying critical predictors for WCME, equipping firms to address WCM challenges proactively. 2024, Emerald Publishing Limited. -
Trends in virtual influencers (VIs): A bibliometric analysis and SPAR-4-SLR protocol
This study aims to comprehensively understand qualitative and quantitative information about the current trends in VIs. It examines 106 articles published in Scopus-indexed journals between 2020 and 2024. The analysis was done with the help of Biblioshiny, an R-developed online application from the Bibliometrix package, and VOSviewer software for analytical and visualization purposes. This study was conducted using the SPAR-4-SLR protocol. The findings showed that recent years have been more productive, and many authors have demonstrated their interest in studying the VIs. Recent trends are social media, virtual reality, marketing, social networking, etc. The study employs a systematic review and bibliometric analysis to extract valuable insights from the extensive body of literature. These insights suggested several areas for future research, providing a roadmap for future researchers to proceed with their research in this area. The comprehensive scientific cartography of the area has yet to be presented; therefore, this study aims to synthesize the current knowledge frameworks within the field and determine the dominant research patterns in the specific area of investigation. 2024, Malque Publishing. All rights reserved. -
Exploring Drivers of Healthcare Utilization amongthe Working and Non-Working Elderly Population: Insights from LASI
Background: The elderly population of India has been growing exponentially over the past few decades, caused by a decline in fertility and an increase in life expectancy. The growth eventually has transcended the disease burden on the public healthcare system. This calls for a need to evaluate the healthcare utilization pattern of the elderly based on their socioeconomic and working condition. Methods: Study used access to public and private healthcare services to measure healthcare utilization. Descriptive analysis and multivariable logistic regression were used to understand utilization patterns by working status and some selected sociodemographic parameters. All the results were reported at a 95% confidence interval. Results: Using the data from the first wave of Longitudinal Ageing Study in India (LASI) with a sample of 22,680 older persons 60 years and above. The study identified that 50% of the working elderly access private services; however, 26% access public healthcare services. It was found that the working status of the elderly alone did not influence access to healthcare services, but education is also an essential indicator for utilizing healthcare services. Further, factors such as gender, marital status, religion, wealth, tobacco usage, self-rated health, ADL and IADL were significant predictors of healthcare services utilization for the elderly. Conclusion: This study suggests that there are not many differences found among working and non-working status with healthcare utilization, although some sociodemographic indicators are associated with the utilization of healthcare services, highlighting that increasing health needs among the elderly requires strengthening the quality and appropriate public investment in health. 2024 Taylor & Francis Group, LLC. -
Factor investing: evidence of long-only factor portfolios from the Indian market
The study examines the performance of long-only factor portfolios in the Indian market. An extended 8-factors model and well-known factor models are used to analyse the exposure and risk-adjusted performance of factor portfolios. The results reveal a mixed portfolio performance: market-driven factors like illiquid, winner, stable, and small offered better performance than those based on fundamental data like value, strong, and conservative. While the market factor is the primary return driver, the SMB and HML factors are the other standard return drivers. The portfolios showed exposure to the specific factor they are constructed upon, except for the strong portfolio. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Forced Labour, Global Supply Chain and TNCs: Recent Trends and Practices
The abolition of forced labour is a fundamental element of contemporary international human rights law, but the idea has undergone a protracted and complex history, and the scope of the various international mechanisms that handle different aspects of it is not always precisely defined. Slavery, forced labour, and related practices are strictly prohibited under international law. Forced labour is a longstanding and complex obstacle in global supply chains, frequently associated with the desire for inexpensive products and the outsourcing of manufacturing processes to nations with lax labour regulations. The growing power of transnational corporations (TNCs) poses significant challenges to workers at the bottom of supply chains. However, disagreements have made it unclear how to deal with new forms of forced labour, or modern forms of slavery. This confusion highlights the need for a comprehensive approach to combating these issues. Efforts to stop or restrict forced labour will be made easier with a clear legal definition at both the national and international levels, particularly with an emphasis on the human rights perspective. 2024 Kluwer Law International BV, The Netherlands -
Elastic circuit de-constructor: a pattern to enhance resiliency in microservices
Cloud-based workloads have proliferated with the deep penetration of the internet. Microservices based handling of high volume transactions and data have become extremely popular owing to their scalability and elasticity. The major challenge that cloud-based microservice patterns face is predicting dynamic load and failure patterns, which affect resiliency and uptime. Existing Circuit breaker patterns are biased toward denying incoming requests to maintain acceptable latency values, at the cost of availability. This paper proposes the Elastic Circuit De-Constructor (ECD) pattern to address these gaps. The proposed ECD pattern addresses this challenge by dynamically adapting to changing workloads and adjusting circuit-breaking thresholds based on real-time performance metrics. The proposed ECD pattern introduces a novel De-constructed state, that allows the ECD to identify alternate paths pre-defined by the application, ensuring user requests continue to be routed to the microservice. By leveraging Availability, Latency and Error rate as performance metrics, the ECD pattern is able to balance the fault tolerance and resiliency imperatives in the cloud-based microservices environment. The performance of the proposed ECD pattern has been verified against both no Circuit Breaker and a default Circuit Breaker setting. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Corporate social initiatives and wealth creation for firms-an empirical examination
Purpose: This study aims to examine whether social initiatives adopted by firms lead to improved financial performance. The authors analyse the impact of different elements of social initiatives on wealth creation for firms in terms of operating and market performance. Design/methodology/approach: The study is based on the social initiative scores of over 4,500 firms collected from Thomson Reuters' ESG database. The study uses two-stage least squares (2SLS) to analyse the relationship between social initiatives and firm performance. Findings: Profitable, mature, capital intensive and firms with high sales growth rate tend to invest more in social initiatives. Firms with high agency costs invest in social initiatives for workforce efficiency, maintaining human rights and product responsibility. The study documents evidence that social investments are value creating mechanism for firms which leads to improved financial performance in terms of operating and stock market performance. Firms with high dividend intensity invest in social initiatives for workforce welfare and human rights initiatives. Investment in employee well-being and community initiatives results in intangible benefits such as improved stock market valuation. Practical implications: The research model has not considered the impact of intervening variables to understand the relationship between corporate social performance and corporate financial performance. Social implications: Firms ought to recognize that social investment is beneficial in terms of value creation of firms as stock market perceive such investments favourably. Firms must focus more on community development initiatives and workforce initiatives for the value creation of firms compared to investments directed towards human rights initiatives and product responsibility initiatives. Originality/value: This study focusses exclusively on the social dimension of the CSR activities. The authors examine the impact of social welfare scores on firm performance by analysing the valuation effects on scores representing workforce, human rights, community and product responsibility. Moreover, the paper also examines the impact of a new dimension of product responsibility on firm performance. They also focus on both aspects of financial performance in terms of operating performance (proxied by ROE) and the joint impact of both operating and market performance (proxied by Tobins Q). This paper contributes to the research on the linkage of social performance to financial performance by observing that firms with high agency cost characteristics tend to invest in social initiatives for work force efficiency, maintaining human rights and product responsibility. 2024, Emerald Publishing Limited. -
UNDERGRADUATE STUDENTS (UG) MOTIVATION TO FIT LOOKS AND ITS EFFECT ON ACADEMIC PERFORMANCE MEDIATED BY PHYSICAL EXERCISE, SLEEP PATTERN, AND MALADAPTIVE EATING; [MOTIVAO DOS ALUNOS DE GRADUAO (UG) PARA ADEQUAR A APARCIA E SEU EFEITO NO DESEMPENHO ACADICO MEDIADO POR EXERCIO FICO, PADR DE SONO E ALIMENTAO MAL ADAPTATIVA]
India is one of the largest youth-populated countries in the world. Technological advancements during and post-COVID have gifted most youth with personal computers/smartphones and internet connectivity at an affordable price. Thus, binge-watching social media has become the order of the day. Youths are excessively interested in building fit-looks for their psychosocial well-being. However, it has adversely changed their life routine and academic performance. Thus, the present study attempted to measure the relationship between their motivation to fit looks and academic performance in the presence of mediating variables like physical exercise, sleeping, and eating patterns. The study surveyed 300 UG students attending physical exercise or gym classes. The study employed mediation analysis to find the relationship. Results revealed a total and indirect effect between motivation to fit looks and academic performance in the presence of mediating variables, explaining the full mediation effect. The study warrants future researchers to explore the reasons for these relationships with a qualitative approach and identify plausible suggestions to improve youths psychosocial well-being. 2024 Universidade Estadual de Maringa. All rights reserved. -
International Journal of Operational Research: a retrospective overview between 2005 and 2020
The study presents a retrospective analysis of the International Journal of Operational Research (IJOR) across its 16 years of publication, 2005 to 2020. IJOR is a journal of international repute that publishes original and peer-reviewed research in the management sciences, decision sciences, and operation research domain. The journal reached its 17th year of publishing in 2021. This study provides a comprehensive overview of 1,023 publications using the bibliometric data analysis technique. The study focuses on the contribution of IJOR to the knowledge domain through publishing trends, authorship patterns, dominant authors, prominent articles, nature of studies, and thematic analysis. Co-occurrence analysis of all keywords, co-authorship, citation and co-citation analysis of authors, countries, and institutions is performed through VOSviewer software. The findings of the study emphasise the relationship of IJOR to different fields. 2024 Inderscience Enterprises Ltd. -
A Deep Ensemble Framework for DDoS Attack Recognition and Mitigation in Cloud SDN Environment
Much research has been done in the recent past on the absolute shift of Internet infrastructure in order to make it more significantly programmable, configurable and make it more conveniently feasible. Software Defined Networking (SDN) forms the basis for this absolute shift in Internet infrastructure. When you look at the benefits of an SDN-based cloud environment they are monumental. Namely, network traffic control and elastic resource management. The SDN-based cloud environment becomes susceptible to cyber threats, especially like that of Distributed Denial of Service (DDoS) attacks and other cyber-attacks that perturb the SDN-based cloud environment. Hence, automated Machine Learning (ML) models are an efficient way to protect against these cyber-attacks. This research will develop a deep learning-based ensemble model for DDoS attack detection and classification (DLEM-DDoS) in a cloud environment. Long Short-Term Memory (LSTM), 1-D Convolutional Neural Networks (1D-CNN) and Gated Recurrent Unit (GRU) are the three DL models integrated into an ensemble model that classifies the incoming packet by majority voting classifiers. Network traffic data including source and destination IP addresses, packet and byte counts, packet and byte rates, flow duration, protocol types and port numbers are fed into the DLEM-DDoS model. This model preprocesses this data by converting categorical values (like protocol types) into numerical values and removing any missing values. Once collected and preprocessed, the data is fed into deep learning models (LSTM, 1D-CNN, GRU) within the framework for analysis. Finally, in this research using the DLEM-DDoS technique an efficient DDoS attack mitigation scheme in an SDN-based cloud environment is demonstrated. The report shows comprehensive stimulations as well as a superiority into the current approaches in terms of several measures. 2024 S. Annie Christila and R. Sivakumar. This open-access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license. -
The Role of Imposter Phenomenon on Self-Handicapping and Psychological Distress among Young Adults
The Imposter Phenomenon (IP), characterized by persistent self-doubt and a fear of being exposed as a fraud despite objective success, is a growing concern, particularly among young adults. This study explores the intricate relationships between the Imposter Phenomenon, Self-handicapping, and Psychological Distress in a sample of 242 young adults aged 1825. The data is analysed using descriptive statistics, correlation, and regression. Findings from a comprehensive survey, utilizing the Clance Impostor Phenomenon Scale, the Self-Handicapping Scale, and the Mental Health Inventory reveal a significant positive correlation and prediction between the Imposter Phenomenon and self-handicapping and a positive relationship between the Imposter phenomenon and psychological distress. These findings contribute to a deeper understanding of how the Imposter Phenomenon influences self-handicapping behaviours in young adults, shedding light on the psychological distress associated with these experiences. The study underscores the need for targeted interventions to address imposter feelings and their potential consequences on mental well-being in this vulnerable population, ultimately aiming to foster a healthier and more resilient generation. The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024. -
Exploring the potential application of Cr2AlC MAX phase as an emerging electrocatalyst for overall water splitting
A three-dimensional (3D) chromium carbide ceramic type, H-phase (211) categorized as Cr2AlC, MAX phase has garnered enormous attention in recent times due to its unique structure and bonding, surface area, thermal stability, and thermo-electrical conductivity, and hydrophilicity. A simple synthesis approach is proposed for obtaining layered Cr2AlC, MAX phase, with X-ray diffraction data and SEM morphology confirming the formation of the H-phase. The electrocatalyst Cr2AlC is being utilized for electrocatalytic water splitting application. The Cr2AlC is observed to exhibit an overpotential and Tafel slopes of 215 mV/88.3 mV dec? 1 for the hydrogen evolution reaction (HER) and 376 mV/96.5 mV dec? 1 for the oxygen evolution reaction (OER), respectively, demonstrating good stability for up to 7200s. This study establishes a straightforward method for producing emergent material, Cr2AlC MAX phase, and highlights its promising applications in water electrolysis, hydrogen evolution, and oxygen evolution reactions. Qatar University and Springer Nature Switzerland AG 2024. -
Detection and analysis of android malwares using hybrid dual Path bi-LSTM Kepler dynamic graph convolutional network
In past decade, the android malware threats have been rapidly increasing with the widespread usage of internet applications. In respect of security purpose, there are several machine learning techniques attempted to detect the malwares effectively, but failed to achieve the accurate detection due to increasing number of features, more time consumption decreases in detection efficiency. To overcome these limitations, in this research work an innovative Hybrid dual path Bidirectional long short-term memory Kepler dynamic graph Convolutional Network (HBKCN) is proposed to analyze and detect android malwares effectively. First, the augmented abstract syntax tree is applied for pre-processing and extracts the string function from each malware. Second, the adaptive aphid ant optimization is utilized to choose the most appropriate features and remove irrelevant features. Finally, the proposed HBKCN classifies benign and malware apps based on their specifications. Four benchmark datasets, namely Drebin, VirusShare, Malgenome -215, and MaMaDroid datasets, are employed to estimate the effectiveness of the technique. The result demonstrates that the HBKCN technique achieved excellent performance with respect to a few important metrics compared to existing methods. Moreover, detection accuracies of 99.2%, 99.1%,99.8% and 99.8% are achieved for the considered datasets, respectively. Also, the computation time is greatly reduced, illustrating the efficiency of the proposed model in identifying android malwares. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Positive ageing: self-compassion as a mediator between forgiveness and psychological well-being in older adults
Purpose: Positive aging aims to promote the physical health and psychological well-being of older adults for them to age successfully. Under the domain of positive aging, this study aims to explore the mediating role of self-compassion between forgiveness and psychological well-being in older adults. Design/methodology/approach: It was based on a quantitative research design, with a sample of 250 individuals within the age group of 6075 years. Data was collected using Self-compassion Scale (2003), Heartland Forgiveness Scale (2005) and Psychological Well-being Scale. Analysis was performed using Pearsons correlation, linear regression, followed by the generalised linear model of mediation. Findings: The results revealed a significant (p ? 0.001), high and positive correlation between self-compassion and forgiveness (r = 0.821), forgiveness and psychological well-being (r = 0.852) and self-compassion and psychological well-being (r = 0.802). Linear regression suggested that self-compassion and forgiveness are significant (p ? 0.001) predictors of psychological well-being, causing a variance of 75.6%. Mediation revealed significant (p ? 0.001) direct, indirect and total effect between the variables, showing that self-compassion partially mediates the relationship between forgiveness and psychological well-being. Research limitations/implications: The findings provide valuable insights on how fostering self-compassion along with forgiveness can improve psychological well-being among the elderly, however, research on additional variables, drawing comparisons between gender, economic status and clinical populations can be further explored. Nevertheless, this study can be used to develop interventions and therapeutic techniques to enhance self-compassion and forgiveness to improve psychological well-being among older adults. Originality/value: As per the best knowledge of the researcher, this work is original as it is a primary research and no data has been collected of a similar nature from the participants. 2024, Emerald Publishing Limited. -
E-shopping orientation, trust and impulse buying in the online context a study based on female members of Generation Z in India
A large number of studies have attempted to understand consumer behaviour in the online context. One construct that has been of particular interest to marketers, retailers and researchers, is impulse buying behaviour. The number of studies attempting to understand the drivers of impulsive purchases has been on a rise. The current pandemic also saw a rise in impulsive purchases and the interest in the construct was renewed. The current study is based on the S-O-R model and evaluates the relationship between e-shopping orientation, trust and impulse buying behaviour. The findings are based on data collected from female members of Generation Z and suggest that frequent visits to e-retail stores and increased patronage can increase the level of trust in the retail partner and influence the number of impulsive purchases. The findings are particularly significant for retailers looking to drive sales through impulsive purchases. In addition, the findings provide empirical support for the application of the S-O-R model to online retail context. Copyright 2024 Inderscience Enterprises Ltd.