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Study of the personal factors influencing voluntary turnover amongst women
In a country where the economic and social independence of a woman is dependent on the way households are structured and organised, the rise in their education and decline in their workforce participation rate is an indication of their paradoxical situation. In this study we evaluate the direct effect of the factors in the personal domain of women on her career break decision. The data from 402 Indian women was analysed using Exploratory Factor Analysis and Confirmatory Factor Analysis, which was then followed by Structural Equation Modelling to check the conceptual model developed through literature review. In present study support personal predictors to turnover intention outcome model, confirming the influence of role conflict, role expectation, role perception, stress, financial soundness, role overload and guilt. Role perception and expectation of women were most significant factors influencing turnover intention of women, implying that the most important change needed is for a change in their own mindset and those around them to arrest their exit from the workforce. 2021 Ecological Society of India. All rights reserved. -
Determinants of consumer retention strategies for telecom service industry in Central India
The telecommunication industry has witnessed a tremendous growth in recent times in India. It has not only been limited to voice calls, but also integrated into every aspect of human life. This has resulted in the rapid rise of market players, offering innovative products and services. In this changing scenario, we have tried to design and check a model of various factors such as loyalty, satisfaction and switching barriers (customer relationship management, alternative attractiveness and switching cost) influencing consumer retention strategies in Indian telecom service industry. A structured and undisguised questionnaire and a convenient sampling method have been used to collect the data from respondents from three most populous cities (Indore, Bhopal, and Ujjain) of Central India. Around 450 questionnaires were distributed, out of which 318 usable responses were received for final analysis. The instrument was checked for validity and reliability before the data was analyzed. The hypotheses were tested through Structure Equation Modelling (SEM) for direct effect, and Multiple Moderating Regression Analysis (MMRA) for moderating effect. The results suggested that loyalty, satisfaction, switching barriers and customer relationship management are positively related and have a direct influence on consumer retention, but the relationship with alternative attractiveness has been found weak. Switching cost, as moderating variable, was found to be very effective and showed significant deviation in the relationship between independent and dependent variables. Vinod Sharma, Sunny Joseph, Jeanne Poulose, 2018 -
Data-Driven Decision Making
This book delves into contemporary business analytics techniques across sectors for critical decision-making. It combines data, mathematical and statistical models, and information technology to present alternatives for decision evaluation. Offering systematic mechanisms, it explores business contexts, factors, and relationships to foster competitiveness. Beyond managerial perspectives, it includes contributions from professionals, academics, and scholars worldwide, delivering comprehensive knowledge and skills through diverse viewpoints, cases, and applications of analytical tools. As an international business science reference, it targets professionals, academics, researchers, doctoral scholars, postgraduate students, and research organizations seeking a nuanced understanding of modern business analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
An Analytical Study on the influence of using Trimmed Gait Energy Images for Human Gait Biometrics using Deep Learning
Gait based human recognition is founded on the principle that every human being has a distinctive style of walking. With the rise in the use of video surveillance devices, gait is one of the most convenient biometrics to use, in forensics. This paper is an analytical study of the effect of using trimmed Gait Energy Images (GEI) for Human Recognition using different deep learning techniques. Gait energy images are a spatiotemporal, silhouette-based representation of the human gait. GEIs from the CASIA B Multiview dataset was used to build two other sets of data by subtracting the upper body Deep learning and transfer learning techniques including Convolution Neural Networks (CNN) and VGG16 algorithms had been implemented to carry out the recognition. Results showed that the performance of the model using upper body images gives a greater accuracy than the lower body images. It has also been observed that the accuracy of recognition provided by the upper part of the body is almost the same as that achieved by the whole body, which brings forth the idea that the upper part of the body is the most pertinent in Human Identification using Gait as a biometric. 2022 IEEE. -
Collaborative service robots and employee career sustainability: a mixed-methods study of trust and innovativeness as moderators
Purpose This study aims to explore how the integration of collaborative service robots (cobots) in the workplace influences employees long-term career sustainability. Specifically, it investigates the moderating roles of perceived innovativeness, trust and employee type in this relationship. The research integrates insights from decent work theory, career sustainability theory, perceived innovativeness theory and initial trust theory to develop and validate a comprehensive conceptual framework. Design/methodology/approach A sequential mixed-method design was adopted. In Phase I, qualitative data were gathered through in-depth interviews with ten senior women managers from software development firms in India. Using grounded theory analysis via NVivo, key themes and constructs were identified. In Phase II, a structured questionnaire was developed based on these findings and distributed among employees working in manufacturing, logistics and hospitality sectors industries actively using service robots. A total of 755 usable responses were analysed using structural equation modelling with SmartPLS 4. Findings The analysis confirmed that humanrobot collaboration effectiveness, perceived working conditions and perceived autonomy significantly impact employees career sustainability, as reflected through their health, happiness and productivity. Furthermore, both trust in service robots and perceived organisational innovativeness emerged as significant mediators in these relationships. In addition, the strength of these relationships varied across managerial and non-managerial employees, highlighting the contingent role of employee type in shaping career sustainability outcomes in robot-enabled workplaces. Practical implications The findings provide actionable insights for HR professionals, technology managers and policymakers by underscoring the need for role-sensitive implementation strategies when introducing collaborative robots. Tailoring trust-building and innovation initiatives according to employee roles can help ensure that automation supports, rather than undermines, sustainable career development. Originality/value This study advances the human-centred automation literature by introducing employee type as a critical boundary condition in the relationship between collaborative robotics and career sustainability. Through a multidisciplinary and mixed-methods approach, it offers nuanced theoretical and practical contributions to understanding differential employee experiences in technologically augmented work environments. 2026 Emerald Publishing Limited -
Exploring the mediating role of job and life satisfaction between workfamily conflict, familywork conflict and turnover intention
Purpose: This study investigates the influence of work-to-family and family-to-work conflict on turnover intention (career break), mediated through job and life satisfaction among Indian women in the service sector, using role conflict theory as the base. Design/methodology/approach: A total of 421 usable responses from women who had taken a career break were collected using a 36-item scale from six major metro cities in India through social and digital media platforms. A purposive-cum-snowballing sampling method was adopted. The hypotheses were tested using structural equation modeling (SEM) through AMOS. Findings: Findings suggest that job satisfaction (JS) is a significant predictor of turnover intention, both when work spills into the family domain, and family responsibilities spill into the work domain, thereby confirming the mediating influence of JS. Interestingly, life satisfaction (LS) only seems to mediate between inter-domain conflict and turnover intention partially. Research limitations/implications: This is a descriptive study, and is thereby limited in terms of its generalizability, specifically as it included respondents only from six major metro cities in India. Practical implications: The extended work-family conflict model could help managers structure organizational interventions that support women to deal with the challenges of managing the demands of both work and family domains, thereby reducing the negative influence on JS. Such initiatives could help reduce career breaks among women. Originality/value: We explored the cause of career breaks among Indian urban women employed in the service sector, using the extended model of inter-role conflict and their attitudes towards both life and job. 2024, Emerald Publishing Limited. -
Beyond the Pink Slip: Mental Health Challenges Among Displaced IT Workers in India
The case explores and undertakes the journey of pink slips, technological disruption, and the silence around mental health through the experiences of Karan. The events are drawn from reallife situations and have been adapted to protect the identity of the individual. The case follows Karan Jadhav, a mid-level IT professional working in Bengaluru. He tries to navigate his life after being laid off during a strategic downsizing at a Multinational Company (MNC) where he has been working for more than 10 years. Karan finds himself battling with anxiety over unpaid bills and a constant dread of not finding a job. In a country such as India, the job is associated with a sense of identity, purpose, self-esteem, self-efficacy, and social acceptance and respect. Karan's story reflects the human cost of technological disruption, lack of social and emotional support around mental health, and policy gaps that leave the displaced professionals vulnerable and with poor to no support. Designed for courses i.organizational Behaviour, HRM, or Public Policy, it invites learners to explore mental health inclusion, workplace transitions, and the complex socio-economic and emotional realities of job loss. 2025 NeilsonJournals Publishing. -
Structured text programming to visualize the distribution of packages on a conveyor
Automation is a process of increasing production and reducing the downtime of any industry. With the integration of sensor data to the cloud using an OPC-VA communication protocol, the automation becomes more prominent and interesting. However, many existing industrial controllers do not support open platform communication unified architecture (OPC-VA) and it needs an IIoT device to connect the cloud. The existing programmable logic controller in any industry have to be connected to an IIoT device through Ethernet. Sensors connected to the controller will transmit the data to the IIoT device. The transmission can also be bidirectional. In this paper, a conveyor which distributes packages is simulated in Codesys and it is visualized in a human-machine interface (HMI) screen which is in-built in the software. The hardware set-up is made with the industrial controller to execute the same. A methodology to send the data from the controller to the cloud using open platform communication unified architecture (OPC-UA) is proposed 2023 IEEE. -
Integration of Industrial Robots to Enhance Warehouse Efficiency in an Industry 4.0 Environment Using Digital Twin Technology
An automated warehouse serves as a facility designed for the storage of materials with a comprehensive inventory management system. This system meticulously monitors the loading and unloading of materials with minimal human intervention. The core operations within an automated warehouse are executed through the utilization of sophisticated software tools. This specific system falls within the purview of Manufacturing Execution Systems (MES). The integration of industrial robots is a pivotal aspect of warehouse automation, serving to meet the demands of efficiency while simultaneously reducing space requirements and overall operational costs within the warehouse management system. Industrial robots excel in executing processes swiftly and with precision, enhancing overall operational efficiency. This paper outlines the authors approach, which involves the programming of an industrial controller and the utilization of an Industry 4.0 Application Programming Interface (API) to facilitate communication with a 3D warehouse in Factory IO for loading materials. The programming of the industrial controller is carried out using the Sequential Function Chart (SFC) language, adhering to the IEC61131-3 standard. 2026 Scrivener Publishing LLC. -
Meaning in life buffers mental health risks in South Indian transgender (Hijra) women
Purpose This study aims to investigate the mediating role of meaning in life (MIL) in the relationships among depression, anxiety, stress (DAS) and quality of life (QOL) among transgender (Hijra) women in South India. The concept of QOL extends beyond the absence of negative mental states such as DAS; it includes overall mental health, well-being and personal evaluations of life circumstances. Design/methodology/approach This study is based on a sample survey of 302 transgender women selected via convenience sampling from five states in South India. The MIL scale, Depression, Anxiety and Stress Scale (DASS-21) and QOL tools were culturally validated and tested, with reliability confirmed through a pilot study (n = 15). Correlation, regression and mediation analyses were conducted to explore the relationships. Findings A strong positive correlation between MIL and QOL was found. The DAS score has a significant negative correlation with QOL. The Presence of Meaning (PoM) subscale emerged as a crucial predictor for overall QOL, whereas the Search for Meaning (SoM) subscale showed predictive value for psychological health. MIL negatively mediates the relationship between DAS, and QOL, suggesting that it buffers mental health risks. Originality/value These findings reinforce the notion that meaning-making is an active life-affirming process, particularly for transgender women navigating adversity. The POM enriches the QOL and acts as a buffer against existential despair. This highlights the need for interventions that foster meaning-making as a pathway to resilience, emphasizing agency, authenticity and purpose pursuit in the face of existential anxiety. 2025 Emerald Publishing Limited -
Catalysts of Change: The Transformative Journey from HR 1.0 to HR 5.0 Innovations, Challenges, and Strategies in Human Resource Management with Technology and Data-Driven Integration
Human Resource Management (HRM) has evolved significantly, transitioning from HR 1.0 to HR 5.0 due to technological advancements, shifting demographics, and the demands of the global business environment. This chapter highlights the evolution of HRM discussions, focusing on the key changes, concerns, and approaches that have characterized this transformation. In the HR 1.0 phase, the emphasis was on paperwork and routine clerical tasks. This laid the basis for the kind of advancement that was HR 2.0, which brought into account computerization and rudimentary data interconnection. In HR 3.0, SHRM became dominant, meaning that organizational HR practices were oriented only to achieving strategic objectives. There was a shift in the application of digital technology in performing human resource activities under the emergence of HR 4.0. The present phase is called Human Resources 5.0 (HR 5.0), which marked the strain referred to as ''People First." This approach is a mixture of Technologies Focus and Humanity Focus with an ample concern on the experience and emotional state of the employees fused with the capacity of the organizations to deal with competitive issues common to most firms. It also explores the influences that have led to these changes such as; technological developments, geographic expansion, and prospective staff demands. It also looks at possible risks linked to each shift among them, resistance to change in organization cultures, threats to data privacy amongst others plus the need to acquire higher skills. Moreover, the triple-layered paper maps actionable approaches toward the transformation of HR that are supported by cases that focus on learning culture, diversification, inclusion, and the utilization of big data. Reading through this paper to understand how HR has evolved from 1.0 to 5.0, will help HR managers, and organizations get ideas on how to meanwhile shape their human resource management strategies and advancement in the ever-growing global economy. 2025, The Research Publication. All rights reserved. -
Enhancing Disease Prediction in Healthcare: A Comparative Analysis of PSO and Extreme Learning Approach
The healthcare business generates a tremendous quantity of data, and the goal is to collect it and use it effectively for analysis, prediction, and treatment. The best approach to disease management is disease prevention through early intervention. There are a number of methods that can advise you on how to treat a specific sickness, but much fewer that can tell you with any degree of certainty if you will actually get sick in the first place. Preprocessing, feature selection, feature extraction, and model training are all parts of the proposed method. The suggested layout includes a preprocessing stage that takes care of things like moving average, missing values, and normalization. Feature selection describes the process of selecting the most relevant features from a dataset. After gathering features, the models are trained using PSO-ELM. The proposed strategy is superior to the widely used PSO and ELM. 2023 IEEE. -
The Optimization of Output of Wind Turbine with the Ongoing Grid System through BP Method Using ANN
Wind turbines are intricate devices that need careful planning, evaluation, and installation to guarantee peak performance under a range of environmental circumstances. Comprehensive load calculations, performance evaluations, and iterative optimisation processes are all part of the design process. However, complex simulation techniques are required to adequately depict the non-linear behaviour of wind turbine systems because of their complicated structure. Automation of optimisation processes and simulation executions is crucial to optimise the design process and manage the large number of simulations that are needed. This work provides a thorough framework using back propagation (BP) and artificial neural networks (ANN) for simulation and optimization that will make it easier to manage and automate the execution of iterative simulations during the design and development of wind turbines. The framework's main goals are to make design load case simulations easier and optimise activities more automatically. The framework makes it possible to optimise wind turbine systems and explore design options more effectively by automating these procedures. Three example optimisation jobs illustrate the framework's versatility and functionality. 2024 IEEE. -
Value co-creation through search efforts and customer involvement impacting purchase intention of smart phones /
International Journal of Recent Technology And Engineering, Vol.8, Issue 3, pp.3894-3902, ISSN No: 2277-3878. -
Exploring the far-reaching consequences of malnutrition during pregnancy and beyond: A comprehensive review
In India, maternal and infant malnutrition continues to be a significant contributor to health problems. Fetal malnutrition can result from an inadequate nutrient supply, necessary nutrition services, and ideal practices before, during, and following pregnancy. This comprehensive review delves into the complex relationships among hormone changes, microbial ecosystems, and nutrition, and how these relationships affect the health of mothers and their offspring. The review highlights how important it is to maintain good nutrition during pregnancy and to comprehend the dietary modifications that pregnant people make on their own to create interventions that work. Important minerals like calcium, iron, folic acid, iodine, and vitamin D are covered. Acknowledging the mutualistic association between the eating habits of mothers and the diverse microbiomes found in their gut, vagina, and oral channels, the review explores the influence on hormone levels and their consequences during gestation. Diverse fetal developmental needs are depicted by the table that outlines food requirements for each of the three trimesters. The detrimental effects of poor prenatal nutrition on a mothers health and its repercussions for neonates are examined. The effects of malnutrition after delivery, including difficulties throughout pregnancy, healing periods, and general effects on mental and physical health, are well studied. The study, which adopts a worldwide viewpoint, finds that societal norms, information gaps, and poverty are the main causes of malnutrition. Prevention techniques are discussed, emphasizing the significance of taking a comprehensive approach to addressing this vital issue in both the Indian and global contexts. 2024 Visagaa Publishing House. -
Simulation and multiscale modeling of carbon nanomaterials
Carbon nanomaterials have become more and more significant for simulation and multiscale modeling due to their distinctive features and prospective uses in a variety of disciplines. We give a thorough computational analysis of the electrical, mechanical, and thermal characteristics of carbon nanotubes, graphene, and fullerenes in this chapter. Our simulations combine classical and quantum mechanical techniques, such as density functional theory and molecular dynamics. We are able to bridge the gap between atomistic simulations and macroscopic behavior thanks to our multiscale modeling technique, which offers important insights into the behavior of carbon nanomaterials at various length and time scales. For the creation and advancement of novel nanomaterials for diverse applications, our findings offer a basic knowledge of the characteristics of carbon nanomaterials. 2025 Elsevier Inc. All rights reserved. -
Perception vs. reality: Analysing the nexus between financial literacy and fintech adoption
Fintech has revolutionized the financial services sector, fundamentally transforming how individuals and businesses manage their finances. However, effective and responsible utilization of these innovative services may require a certain degree of financial competence. To explore this possibility, this study investigates the nexus between financial literacy and fintech usage in the Indian context, considering two distinct measures of financial literacy. Primary data were collected conveniently from 391 respondents through a cross-sectional survey. Probit regression was applied to analyze the relationship between the two dimensions of financial literacy and the adoption of fintech services across three segments: mobile banking, mobile payments, and digital lending. The findings reveal a positive relationship between individuals subjectively perceived financial literacy and their propensity to use all three fintech services. Conversely, objectively measured financial literacy demonstrates a positive association only with the likelihood of using mobile banking. The study also identifies demographic characteristics as contributing factors to variations in fintech adoption. The studys findings hold value for policymakers and fintech service providers, as they underscore the importance of enhancing individuals subjective perceptions of their financial abilities to promote wider adoption of fintech services. Shamli Prabhakaran, Mynavathi L., 2023. -
Does Fintech Usage Alter the Relationships Between Financial Literacy, Behaviour and Well-Being? Evidence from India
The emergence of fintech has rapidly transformed the way people manage their finances, yet its impact on personal financial outcomes remains relatively understudied. This study aims to examine how fintech usage (FTU) influences the relationship between financial literacy (FL) and financial well-being (FWB) through financial behaviour (FB) using a moderated mediation model. Using a proprietary dataset, the hypothesised relationships are analysed applying the PROCESS macro in IBM SPSS Statistics. The analysis reveals that FB is a partial mediator in the FL-FWB equation, while FTU negatively moderates the relationship between FL and FB. However, FTU does not significantly moderate the relationship between FL and FWB. The findings carry significant implications for policymakers and fintech service providers. Policymakers should strive to include a digital literacy component in financial education programs to better equip individuals to navigate todays digitalised society, while fintech companies should focus on designing products that complement users FL and facilitate the adoption of financially healthy behaviours. Copyright 2025 Shamli Prabhakaran, Mynavathi L. -
Does Fintech Usage Improve or Impair Financial Behavior? Evidence from Indian millennials
The fintech revolution has transformed the landscape of personal finance, but its impact on individual financial behavior remains underexplored. Addressing this gap, the present study examines how fintech usage interacts with financial literacy to shape financial behavior among Indian millennials. Using a proprietary dataset, the study employs PLS-SEM to assess the moderating role of fintech usage in the relationship between financial literacy and financial behavior, considering both objective and subjective dimensions of financial literacy. The findings indicate that while financial literacy positively influences financial behavior, using fintech weakens this association. This negative influence is especially evident among users who overestimate their financial competence. The direct impact of fintech usage on financial behavior is also negative, showcasing the need for fintech services that complement users' financial literacy and promote financially healthy behaviors. These findings shed light on the darker side of fintech adoption and have significant implications for policymakers, fintech service providers, and consumers, emphasizing the need for tailored financial literacy programs that promote responsible fintech usage and encourage financial discipline. 2025 Academy of Taiwan Information Systems Research. All rights reserved. -
Synthesis, in vitro and theoretical studies on newly synthesized deep blue emitting 4-(p-methylphenylsulfonyl-5-aryl/alkyl)oxazole analogues for biological and optoelectronic applications
In the present study, a series of 4,5-di-substituted oxazole derivatives (compounds 2a-p) were synthesized, using a novel methodology for the simultaneous determination of their biological and optoelectronic applications. Among the screened molecules, compounds 2j, 2 l and 2o showed very good antimicrobial potencies with MICs up to 1 g/mL. Furthermore, the photophysical parameters were estimated using theoretical and experimental techniques for optoelectronic applications. The excited-state dipole moment being higher than that of the ground state, investigated using solvato-chromatic method showed a redistribution of the electron densities in the excited state for the fluorophores. The HOMO-LUMO energies of the fluorophores estimated by using density functional theory (DFT) are found to be in good agreement with the experimental values. The electrophilic and nucleophilic sites were also recognized with the help of molecular electrostatic potential 3D plots using time-dependent-DFT computational analysis. The specific and non-specific interactions between the solutesolvent were analyzed by multiple linear regression analysis using Kamlet-Abound-Taft and Catalan parameters. Further, the global chemical reactivity descriptor parameter was also calculated. The photophysical properties of the fluorophores suggest that these may be considered as potential probes for OLED, solar cell, and chemosensor applications. 2022 Elsevier B.V.