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Moderating influence of critical psychological states on work engagement and personal outcomes in the telecom sector
Organizations want their employees to be engaged with their work, exhibiting proactive behavior, initiative, and responsibility for personal development. Existing literature has a dearth of studies that evaluate all the three key variables that lead to optimal employee performancecritical psychological states (CPSs), work engagement, and personal outcomes. The present study attempts to fill that gap by linking the variable CPSs (which measures experienced meaningfulness, responsibility, and knowledge of results) with the other two. The study surveyed 359 sales personnel in the Indian telecom industry and adopted standardized, valid, and reliable instruments to measure their work engagement, CPSs, and personal outcomes. Analysis was done using structural equation modeling (SEM). Findings indicated that CPSs significantly moderate the relationship between personal outcomes and work engagement. The Author(s) 2014. -
Development and Validation of Work Environment Services Scale (WESS)
Purpose: This study presents a nine-factor, 32-item measure of work environment scale in the service sector. A healthy work environment is one in which employees trust the people they work for, have pride in what they do, and enjoy working with the people (Levering and Moskowitz, 2004). Methodology: This instrument builds on the conceptual model espoused by Insel and Moos (1974), Gordon (1973), Fletcher and Nusbaum (2010), Amabile et al. (1996), and Spector (2003). The scale included items elicited through a literature review, the use of the Delphi technique with a panel of experts, and tested on 824 full-time employees from nine service sector industries and five major cities in India. Findings: The Work Environment Services Scale (WESS) is a reliable and valid scale useful for measuring the nine work environment factors in the Indian services organization, with its own norms and a detailed manual. Originality/Value: The prevailing scales for measuring work environment do not capture the influence of ethics, recreation facilities, and the impact of social giving on the work environment. Most scales were suitable for sectors in the Western context, and there were no Indian scales measuring service employees' perception of their work environment. 2021 Harold Andrew Patrick et al., published by Sciendo 2021. -
Managing workplace diversity: Issues and challenges
Diversity management is a process intended to create and maintain a positive work environment where the similarities and differences of individuals are valued. The literature on diversity management has mostly emphasized on organization culture; its impact on diversity openness; human resource management practices; institutional environments and organizational contexts to diversity-related pressures, expectations, requirements, and incentives; perceived practices and organizational outcomes related to managing employee diversity; and several other issues. The current study examines the potential barriers to workplace diversity and suggests strategies to enhance workplace diversity and inclusiveness. It is based on a survey of 300 IT employees. The study concludes that successfully managing diversity can lead to more committed, better satisfied, better performing employees and potentially better financial performance for an organization. The Author(s) 2012. -
Intention to Stay as a Moderator on Employee Job Satisfaction and Organizational Citizenship Behavior
International Journal of Management Studies, Statistics & Applied Economics, Vol-2 (2), pp. 65-74. ISSN-2250-0367 -
Commitment of Information Technology Employees in Relation to Perceived Organizational Justice
The IUP Journal of Organizational Behaviour Vol. XI, No. 3. pp 23-40, ISSN No. 0972-687X -
Socialization tactics and new entrants adjustments in the information technology context /
PES Business Review, Vol. 8, Issue 1, pp.19-28 ISSN No. 0973-919X -
Expression of dissatisfaction in relation to managerial leadership strategies and its impact in Iinformation technology organizations /
Skyline Business Journal, Vol.8, Issue 1, pp.29-35, ISSN: 1998-3425. -
Organizational culture, leadership styles, personal commitment and learning organization:An exploratory study
There is an accelerating change in the scope of all areas of human existence in this century. There are tidal waves of changes being felt by academicians also. To accept change that provides internal steadiness while moving ahead is one of the challenges academic institutions have to face. To improve an organization's quality there are many routes for organizational development through change. -
Brain Tumor Classification Using an Ensemble of Deep Learning Techniques
The article reflects on the classification of brain tumors where several deep learning (DL) approaches are used. Both primary and secondary brain tumors reduce the patient's quality of life, and therefore, any sign of the tumor should be treated immediately for adequate response and survival rates. DL, especially in the diagnosis of brain tumors using MRI and CT scans, has applied its abilities to identify excellent patterns. The proposed ensemble framework begins with the image preprocessing of the brain MRI to enhance the quality of images. These images are then utilized to train seven DL models and all of these models recognize the features related to the tumor. There are four models which are General, Glioma, Meningioma, and Pituitary tumors or No Tumor model, which helps in reaching a joint profitable prediction and concentrating solely on the strength of the estimation and outcome. This is a significant improvement over all the individual models, attaining a 99. 43% accuracy. The data used in this research was gotten from Kaggle website and comprised of 7023 images belonging to four classes. Future work will focus on increasing the dataset size, investigating additional DL architectures, and enhancing real-Time detection to improve the accuracy of diagnostic scans and their overall relevance to clinical practice. 2013 IEEE. -
Modeling a Logistic Regression based Sustained Approach for Cancer Detection
This assessment and treatment of cancer may be done using logistic regression. To properly forecast whether a tumour is malignant or benign, the likelihood of binary outcomes may be simulated based on input variables and taken into account for factors like volume, topology and texture. It aids in risk assessment by estimating an individual's likelihood of developing cancer using factors like age-group, relatives past data, life choices and gene based markers. Logistic regression plays an important role in early cancer detection and creating screening tools that identify high-risk individuals through patent characteristics, biomarkers, and medical imaging data. Prediction of the probability of survival based on age, tumor characteristics, treatment options and comorbidities is useful for survival analysis. In a comparative study, logistic regression achieved a high accuracy of 97.4%, along with random forest, in cancer detection and diagnosis. 2023 IEEE. -
Sustainable Climatic Metrics Determination with Ensemble Predictive Analytics
Sustainable features are dependent on vital climatic elements that has a prominent impact on the retention of sustainability provided its metrics are in desired domain. Regression analysis and ensemble learning models are some of the predictive analytics methods which were used to detect the association of every feature on sustainable criteria. Weather samples from Delhi during 1970-2020 is used in the research which considers features like humidity, pollutant level, temperature etc which are gathered from several authenticated sites like pollution management unit of India. After analyzing several elements affecting weather endurability, it is noticed that pollutant level and temperature exhibit the highest significance recording 30% and 44% respectively. Also the R-square metric of 86% and 82% was observed with implementation of analytics models. The major conclusion recorded that random forest outperformed regression model and it established the importance of predictive analytics in predicting sustainability results. The research validated the relevance of climatic tracking for regulating sustainability. 2023 IEEE. -
Identifying Wage Inequality in Indian Urban Informal Labour Market: A Gender Perspective
This chapter elucidates the wage differential between male and female informal workers in urban labour market by using employment and unemployment survey 61st (2004-2005) round, 68th (2011-2012), and Periodic Labour Force Survey 2019-2020 data of National Sample Survey Office (NSSO) unit level data. This study found that gender inequality not only increased during getting job but also persists after getting job during wage distribution. Based on the Oaxaca-Blinder (OB) decomposition, it is revealed that gender wage inequality is more in the labour market due to the labour market discrimination, that is, unexplained components. Hence, this study helps researcher, policy makers and government to fix the gender wage discrimination issues exist in the Indian labour market. This will enhance economic growth through the rise of the women labour force participation. 2024 A. Vinodan, S. Mahalakshmi, and S. Rameshkumar. -
Drivers of Rural Non-farm Sector Employment in India, 19832019
Using the national-level employment and unemployment surveys (NSS and PLFS) and the macro-level data for the period 20052019, this article explores the trends and recent growth patterns of rural non-farm sector employment in India. It also examines the micro-level factors determining individuals preference towards non-farm sector jobs and the macro-level factors responsible for the growth of non-farm sector employment in rural India. The main findings of the study suggest that although rural non-farm sector employment is rising in absolute terms, its growth rate has slackened in recent years. While the level of education and skill training, market wage rates and socio-cultural setups are among the key micro-level factors determining farmnon-farm employment choices of rural folks, at the macro-level, the growth of investment in capital goods, the number of factories, investment in infrastructure development and the growth of the manufacturing sector are crucial for the growth of non-farm sector jobs in India. Based on these findings, it is argued that the improvement of human capabilities through increased investment in education and skill, and the growth of non-farm sector employment through the development of rural infrastructure and industrialization measures, are necessary to sustain the structural transformation and to harness the demographic dividend in India. JEL Codes: J01, J21, J43, J64 2024 Research and Information System for Developing Countries & Institute of Policy Studies of Sri Lanka. -
Feminization of hunger in climate change: linking rural womens health and wellbeing in India
The links between climate change, food security and womens wellbeing remain an under-investigated area. This paper contributes to this area through a thorough examination of how women experience food insecurity in farming households in rural India. The households are located in four agro-climatic regions in India. These regions experience varied climatic pressures, and this diversity allows us to explore a wider variety of womens experiences in their attempts to maintain household food security as the climate changes. The study finds that women, even in comparatively more food-secure households, suffer from food insecurity. One of the reasons for this is that womens food habits and mealtimes have altered in recent years due to the increase in their work pressures. The worst effects are to be found in drought-prone areas, and there are greater vulnerabilities among women-headed households, indicating that the impacts of climate change are exacerbated by cultural norms that further hinder the role of women in farm activities. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Heat transport of nano-micropolar fluid with an exponential heat source on a convectively heated elongated plate using numerical computation
Purpose: The study of novel exponential heat source phenomena across a flowing fluid with a suspension of microparticles and nanoparticles towards a convectively heated plate has been an open question. Therefore, the impact of the exponential heat source in the transport of nano micropolar fluid in the existence of magnetic dipole, Joule heating, viscous heating and convective condition effects has been analytically investigated. Influence of chemical reaction has also been exhibited in this discussion. Design/methodology/approach: The leading equations are constructed via conservation equations of transport, micro-rotation, energy and solute under the non-transient state situation. Suitable stretching transformations are used to transform the system of partial differential equations to ordinary. The transformed ODEs admit numerical solution via RungeKutta fourth order method along with shooting technique. Findings: The effects of pertinent physical parameters characterizing the flow phenomena are presented through graphs and discussed. The inclusion of microparticles and nanoparticles greatly affects the flow phenomena. The impact of the exponential heat source (EHS) advances the heat transfer characteristics significantly compared to usual thermal-based heat source (THS). The thermal performance can be improved through the effects of a magnetic dipole, viscous heating, Joule heating and convective condition. Originality/value: The effectiveness of EHS phenomena in the dynamics of nano micropolar fluid past an elongated plate which is convectively heated with regression analysis is for the first time investigated. 2019, Emerald Publishing Limited. -
Mental Health Data Analysis Using Cloud
In health care related research studies, there exists a need for retrieving patient's health record from multiple sites. So here comes the digitization of health records, which leads to a wide range of access to various users such as doctors, patients, psychiatrists and pharmacists. The sensitive nature of individual health care data pose a threat to security. Moreover, the increased access of health information by the users threatens the privacy and confidentiality of the stored data. Notwithstanding the existing privacy protection approaches used for mental health records, we suggest a privacy preserving data analysis methodology enabling protection of health records, once user access to records are granted. This paper mainly focuses on utilizing the data analysis approach in preserving privacy of personal health records to overcome the drawbacks of existing approaches. 2020 IEEE. -
A predictive model on post-earthquake infrastructure damage
Disaster management initiatives are employed to mitigate the effects of catastrophic events such as earthquakes. However, post-disaster expenses raise concern for both the government and the insurance companies. The paper provides insights about the key factors that add to the building damage such as the structural and building usage properties. It also sheds light on the best model that can be adopted in terms of both accuracy and ethical principles such as transparency and accountability. From the performance perspective, random forest model has been suggested. From the perspective of models with ethical principles, the decision tree model has been highlighted. Thus, the paper fulfills to propose the best predictive model to accurately predict the building damage caused by earthquake for incorporation by the insurance companies or government agency to minimize the post-disaster expenses involved in such catastrophic event. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
Denial of Service Attacks in the Internet of Things
A DoS attack is the most severe attack on IoT and creates a crucial challenge for the detection and mitigation of such attacks. A DoS attack occurs at multiple layers of the IoT protocol stack and exploiting the protocol vulnerabilities disrupts communication. Traditional mechanisms employ single-layer detection of DoS attacks, which individually detect and mitigate attacks. However, it is essential to establish a general framework for detecting DoS attacks in a real-time environment and coping with diversified applications. This can be achieved by fetching attack features of multiple layers to create a pool of numerous attacks and then designing a system that detects the attack when fed with specific attack features. This chapter comprehensively analyzes the research gap in the DoS attack detection techniques proposed. Secondly, we offer a two-stage framework for DoS attack detection, comprising Fuzzy Rule Manager and Neural Network (NN), to detect cross-layer DoS attacks in real time. The Input Data Type (IDT) is derived using a fuzzy rule manager that can identify the type of input dataset as usual or attack in real time. This IDT is passed to the NN along with the real-time dataset to increase detection accuracy and decrease false alarms. 2024 selection and editorial matter, Vinay Chowdary, Abhinav Sharma, Naveen Kumar and Vivek Kaundal; individual chapters, the contributors. -
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.