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Empirical Analysis of Antecedents and Mediators of Student Loyalty Among Undergraduate Business Students in Bangalore,India
The higher education sector has undergone major changes throughout India which has led to increase in competition for institutions in this sector. Thus, there is a need to find ways to attract and retain the potential and current students. Student loyalty is crucial to createsustainable competitive advantage. Student loyalty is widely accepted as a critical factor in the long term economic success of an educational institution that aims at positive recommendation (word of mouth) by students and attracting the students back to newlinethe institution for further studies. Review of literature reveals that service quality, price fairness, customer value, customer satisfaction and affective commitment are key newlineantecedents to customer loyalty. newlineObjectives - The objectives of this research study are based on theoretical underpinnings in the literature. The main objectives of the study are: 1. To empirically test the proposed structural model of relationships among six constructs: educational service quality, perceived fee fairness, perceived value, student satisfaction, affective commitment, and student loyalty in the undergraduate business programs. 2. To analyze the influence of educational service quality and perceived fairness on student loyalty (ultimate dependent variable). 3. To examine the mediating effect of perceived value, student satisfaction, and affective newlinecommitment on the relationship between educational service quality and student loyalty. 4. To find out the mediating effect of perceived value and student satisfaction on the relationship between perceived fee fairness and student loyalty. 5. To find out the perceptual dimensions of student assessments of educational service quality, fee fairness, value, satisfaction, commitment and student loyalty. Variables of the Study newline1. Educational Service Quality Independent Variable (Exogenous variable) 2. Perceived Fee Fairness Independent Variable (Exogenous variable) 3. Perceived Value Mediating variable (Endogenous Variable) -
Empirical analysis of borrowers' motivation to use online peer-to-peer lending platforms in India
Established on the technology acceptance model, this paper puts forward a model to understand the borrowers' motivation to use (MU) peer-to-peer (P2P) lending platforms. Data from 362 Indian users were employed to test the research model by applying structural equation modelling. The results show that perceived intention, ease of use, and usefulness have significant relation in motivating borrowers to use P2P lending platforms. However, borrowers' perceptions of trust had an insignificant impact on MU the P2P lending platform. When compared to the individual technology acceptance model, the integrated model provides further explanation regarding the motivation of borrowers to use P2P lending platforms. The study contributes to the theoretical area by identifying the factors that motivate borrowers to use P2P lending platforms for their short-term financial requirements, from a unified perspective. In addition, this research provides insights about borrowers' MU P2P lending platforms in India. Copyright 2023 Inderscience Enterprises Ltd. -
Empirical analysis of ensemble methods for the classification of robocalls in telecommunications
With the advent of technology, there has been an excessive use of cellular phones. Cellular phones have made life convenient in our society. However, individuals and groups have subverted the telecommunication devices to deceive unwary victims. Robocalls are quite prevalent these days and they can either be legal or used by scammers to trick one out of their money. The proposed methodology in the paper is to experiment two ensemble models on the dataset acquired from the Federal Trade Commission (DNC Dataset). It is imperative to analyze the call records and based on the patterns the calls can classify as a robocall or not a robocall. Two algorithms Random Forest and XgBoost are combined in two ways and compared in the paper in terms of accuracy, sensitivity and the time taken. 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Empirical Assessment of Artificial Intelligence Enablers Strengthening Business Intelligence in the Indian Banking Industry: ISM and MICMAC Modelling Approach
Considering the context of the issue based on literature survey and expert opinion, this study investigates the drivers of Artificial Intelligence (AI) implementation, which further strengthens the Business Intelligence (BI) in taking better decision-making industries in India. For the purpose of serving the objective of examining the enablers towards having a smarter AI ecosystem in banking, the relevance of identified enablers from exhaustive literature survey were discussed with the experts from banking sector and AI professionals. Based on their opinion, 15 final enablers were defined based on the data collected have been put through Interpretive Structural Modelling (ISM) that reveals the binary relationship between the enablers to draw a hierarchical conclusion, and then assess the enablers about their independence, linkage, autonomous character, and dependence based on their calculated driving and dependence power through MICMAC analysis. The ISM and MICMAC integrated approaches have been used to establish interdependence among the enablers of AI in banking in India context. The study reveals that strong algorithms result in building quality AI information, and also the efforts from management related to commitment, financial readiness towards technological advancement, training, and skill development are quite essential in making the baking system smarter and would enable the industry to take better management decision. 2023 selection and editorial matter, Deepmala Singh, Anurag Singh, Amizan Omar & S.B Goyal. -
Empirical estimation of multilayer perceptron for stock market indexes
The return on investment of stock market index is used to estimate the effectiveness of an investment in different savings schemes. To calculate Return on Investment, profit of an investment is divided by the cost of investment. The purpose of the paper is to perform empirical evaluation of various multilayer perceptron neural networks that are used for obtaining high quality prediction for Return on Investment based on stock market indexes. Many researchers have already implemented different methods to forecast stock prices, but accuracy of the stock prices are a major concern. The multilayer perceptron feed forward neural network model is implemented and compared against multilayer perceptron back propagation neural network models on various stock market indexes. The estimated values are checked against the original values of next business day to measure the actual accuracy. The uniqueness of the research is to achieve maximum accuracy in the Indian stock market indexes. The comparative analysis is done with the help of data set NSEindia historical data for Indian share market. Based on the comparative analysis, the multilayer perceptron feed forward neural network performs better prediction with higher accuracy than multilayer perceptron back propagation. A number of variations have been found by this comparative experiment to analyze the future values of the stock prices. With the experimental comparison, the multilayer perceptron feed forward neural network is able to forecast quality decision on return on investment on stock indexes with average accuracy rate as 95 % which is higher than back propagation neural network. So the results obtained by the multilayer perceptron feed forward neural networks are more satisfactory when compared to multilayer perceptron back propagation neural network. Springer International Publishing Switzerland 2016. -
Empirical evidence on usability of mobiles in health care
Healthcare industry today has seen a lot of innovation and transformation like any other industry. With technological advancements it is growing leaps and bounds. One of the major challenges before the world today is effective management of diseases. The healthcare industry has been benefitted with the usage of information and communication technology (ICT). When integrated properly this technology has the potential to provide solutions to increased demands in quality, efficiency and improved workflow to help streamline healthcare operations. newlineDeveloping countries today are facing an increasing incidence of non communicable and communicable disease. M-health has the potential to extend help in both the fronts. Peep into various scenarios reveal that majority of diseases that kill people in the rural areas are curable with little information and this information dissemination can happen through mobiles which have a deeper penetration than any other technology. Most of the innovations in mobile technologies have not been evaluated beyond the pilot stage. Thus there is a need newlineto evaluate these interventions for them to become acceptable and usable by the patients and healthcare professionals. Various researchers time and again have argued the need for usability studies in healthcare innovations. This study is unique as it caters to both the aspects: technology acceptance and health technology acceptance and the context of usability. There is a large pool of studies which are available for technology acceptance but for healthcare context there has to be a mix of technology acceptance behavior and health behavior newlineacceptance. Researchers like Nutbeam (1998) have highlighted the importance of health behavior which is defined as activities which individuals take up irrespective of their health status for the objective of health maintenance even if such behavior may not be effective in the end. -
Empirical evidence on usability of mobiles in healthcare /
Healthcare industry today has seen a lot of innovation and transformation like any other industry. With technological advancements it is growing leaps and bounds. One of the major challenges before the world today is effective management of diseases. The healthcare industry has been benefitted with the usage of information and communication technology (ICT). When integrated properly this technology has the potential to provide solutions to increased demands in quality, efficiency and improved workflow to help streamline healthcare operations. -
Empirical Study on Categorized Deep Learning Frameworks for Segmentation of Brain Tumor
In the medical image segmentation field, automation is a vital step toward illness detection and thus prevention. Once the segmentation is completed, brain tumors are easily detectable. Automated segmentation of brain tumor is an important research field for assisting radiologists in effectively diagnosing brain tumors. Many deep learning techniques like convolutional neural networks, deep belief networks, and others have been proposed for the automated brain tumor segmentation. The latest deep learning models are discussed in this study based on their performance, dice score, accuracy, sensitivity, and specificity. It also emphasizes the uniqueness of each model, as well as its benefits and drawbacks. This review also looks at some of the most prevalent concerns about utilizing this sort of classifier, as well as some of the most notable changes in regularly used MRI modalities for brain tumor diagnosis. Furthermore, this research establishes limitations, remedies, and future trends or offers up advanced challenges for researchers to produce an efficient system with clinically acceptable accuracy that aids radiologists in determining the prognosis of brain tumors. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Empirical study on The Role of Machine Learning in Stress Assessment among Adolescents
Stress is a psychological condition that people who are experiencing difficulties in their social and environmental well-being face, and it can cause several health problems. Young individuals experience major changes during this crucial time, and they are expected to succeed in society. It's critical for people to master appropriate stress management techniques to ensure a smooth transition into adulthood. The transition to new settings, lifestyles, and interactions with a variety of people, things, and events occurs during adolescence. In this study, a dataset was utilized to classify 520 Indian individuals' stress levels into three categories: normal, moderate, and severe. Support Vector Machines, KNN, Decision Trees, Naive Bayes and CNN were among the different classification techniques that were taken into consideration. The CNN Algorithm was found to be the most reliable method for categorizing diseases linked to mental stress. The study's main goal is to create a classification model that can correctly classify a variety of samples into distinct levels of psychological discomfort. 2023 IEEE. -
EMPIRICALLY VALIDATING THE JOB CHARACTERISTICS MODEL IN THE HEALTHCARE SECTOR
The original model developed by Hackman & Oldham (1976, 1980) was tested for the healthcare sector in India following three staged model as proposed by the original authors. Out of several studies conducted so far using this model, majority of the studies had adopted two staged model. Stratified sampling technique was adopted to select the hospitals (equal number of hospitals selected from private, public and trust hospitals). Convenience sampling was adopted to administer the questionnaire (questionnaires were administered to the target sample from hospitals that gave permission under the three categories). Judgmental sampling method was adopted for deciding whom to administer the questionnaire. Inclusion and exclusion criteria included as employees should have worked for minimum 12 months in the present hospital to complete the questionnaire. 1550 questionnaires were distributed and 1244 fully completed questionnaires were compiled for analysis (80% response rate). Initially the model was tested using structural equation modeling. The study found that the job characteristics model as suggested by Oldham and Hackman (1976 and 1980) did not find good fit in the healthcare sector in India. Further the model was tested separately for nursing, paramedical and nonmedical category as they were the major stake holders in the healthcare sector. The result of the second model fit was also poor and found further fall in strength, which was tested based on the categorization ?? paramedical, nursing and nonmedical staff. Hence, the researcher found no scope of testing the structural equation model any further. Therefore, as the measurement model fails, the researcher intended to explore the dimensions using exploratory factor analysis. The result of the exploratory analysis indicated extracted 17 dimensions from 83 items. These 17-factors extracted from the exploratory factor were applicable to the Indian healthcare sector. This new tool needs to be tested in India for measuring the job characteristics, psychological states and personal outcome linkages. In this study we have analyzed the implications based on the results found. Some of the implications of the study were in the area of autonomy and feedback from the core job dimensions, experienced meaningfulness and knowledge of result from the critical psychological states and general satisfaction and specific satisfaction on pay from the personal outcome. We found very low pay satisfaction among the healthcare workers in India. It is suggested to the future scholars to experiment with the proposed new tool in the future research and explore the new model. A focused study interview could be conducted to find out the responses to job design using the qualitative approach and interviewing the most experienced professionals in hospitals. Two stage model could be tested in the Indian healthcare sector that is job characteristics and personal outcome, excluding critical psychological states. Key words: Job characteristics model, Healthcare, Paramedical, Nonmedical, Nurses. -
EmploChain: A Blueprint for Blockchain-Driven Transformation in Employee Life Cycle Management
Integrating blockchain technology into human resource management presents both transformative opportunities and implementation challenges that need to be addressed. This paper proposes a blockchain-based EmploChain Framework, a decentralized ledger approach specifically designed to enable Employee Life Cycle Management by harnessing the potential of blockchain technology. The study looks at the potential benefits of the proposed framework, including increased security, transparency, and automation. The paper also looks at potential limitations like scalability concerns and implementation costs and explores the possible solutions to overcome them. The aim of this research is to provide a thorough understanding of the framework's implications, thereby facilitating informed decisions to implement EmploChain Framework for managing the Employee Life Cycle of an organization.. 2024 IEEE. -
Employee attrition and absenteeism analysis using machine learning methods: Application in the manufacturing industry
HR analytics has been envisaged as recent research trend for providing a comprehensive decision support system to the top level management in terms of employee's performance, recruitment and behaviour analysis. Globally, organizations are using technology to support and ease HR processes. Every organization should give maximum value to every available human resource, and they should minimize the attrition and absenteeism rate and ensure what are the factors that contribute towards employee attrition as well as the causes for workmen absenteeism. The ultimate objective is to correctly identify attrition and absenteeism in order to assist the company to improve retention tactics for key personnel and increase employee satisfaction. Through this chapter, a machine learning-based model is proposed to get quick results for such employee attrition and workmen absenteeism. The model is trained and tested for its accuracy. The result shows that the proposed model has high sensitivity. The managerial implications are also discussed for taking informed decisions. 2023, IGI Global. All rights reserved. -
Employee Attrition, Job Involvement, and Work Life Balance Prediction Using Machine Learning Classifier Models
Employee performance is an integral part organizational success, for which Talent management is highly required, and the motivating factors of employee depend on employee performance. Certain variables have been observed as outliers, but none of those variables were operated or predicted. This paper aims at creating predictive models for the employee attrition by using classifier models for attrition rate, Job Involvement, and Work Life Balance. Job Involvement is specifically linked to the employee intentions to turn around that is minimal turnover rate. So, getting justifiable solution, this paper states the novel and accurate classification models. The Ridge Classifier model is the first one it has been used to classify IBM employee attrition, and it gave an accuracy of 92.7%. Random Forest had the highest accuracy for predicting Job Involvement, with accuracy rate of 62.3%. Similarly, Logistic Regression has been the model selected to predict Work Life Balance, and it has a 64.8% accuracy rate, making it an acceptable classification model. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023. -
Employee Challenges and its Solutions in Virtual Information Technology Industry
This study aimed at identifying the challenges faced by the employee working in virtual environment, to further propose a conceptual model and to explore the enabling factors required to provide sustainable solutions to these challenges. An organizations precursors are a must to mitigate the identified challenges by adopting the suggested solutions. In this era of IT and ICT, it is inevitable to understand what are those challenges, issues or problems employee of a virtual team faces and how do they resolve them or behave in that particular scenario. Radically changing work environment impacts the workforce productivity. In this ICT environment, it is unavoidable to expect challenges emerged out of such working conditions. Further, to study challenges becomes crucial for a better work environment. The qualitative grounded theory method approach has been used to identify challenges of 20 cases through in-depth interview techniques. The interviews have been then transcribed, coded and categorized. The conceptual model is the final outcome of this research work that depicts the challenges, the precursors ?? a company must have and last but not the least the recommended solutions to mitigate challenges. Keywords ?? IT (Information Technology), ICT (Information and Communication Technology), Challenges (A challenge is a general term referring to things that are imbued with a sense of difficulty and victory). -
Employee development and training as a tool for improving employee performance in an organization /
Patent Number: 202241025596, Applicant: Dr. Rekha N Patil.
Employee development and training as a tool for improving employee performance in an organization Abstract: A company's long-term success depends on how well its employees are trained and how well they are taught new things. Workers can use these programmes to improve their skills, but businesses can use them to improve employee productivity and the company's culture at the same time. The 2020 Work Institute found that cutting down on employee turnover has a big impact on a company's bottom line. -
Employee development and training as a tool for improving employee performance in an organization /
Patent Number: 202241025596, Applicant: Dr. Rekha N Patil.
Employee development and training as a tool for improving employee performance in an organization Abstract: A company's long-term success depends on how well its employees are trained and how well they are taught new things. Workers can use these programmes to improve their skills, but businesses can use them to improve employee productivity and the company's culture at the same time. The 2020 Work Institute found that cutting down on employee turnover has a big impact on a company's bottom line. -
Employee development and training as a tool for improving employee performance in an organization /
Patent Number: 202241025596, Applicant: Dr. Rekha N Patil.
Employee development and training as a tool for improving employee performance in an organization Abstract: A company's long-term success depends on how well its employees are trained and how well they are taught new things. Workers can use these programmes to improve their skills, but businesses can use them to improve employee productivity and the company's culture at the same time. The 2020 Work Institute found that cutting down on employee turnover has a big impact on a company's bottom line. -
Employee development and training as a tool for improving employee performance in an organization /
Patent Number: 202241025596, Applicant: Dr. Rekha N Patil.
Employee development and training as a tool for improving employee performance in an organization Abstract: A company's long-term success depends on how well its employees are trained and how well they are taught new things. Workers can use these programmes to improve their skills, but businesses can use them to improve employee productivity and the company's culture at the same time. The 2020 Work Institute found that cutting down on employee turnover has a big impact on a company's bottom line. -
EMPLOYEE ENGAGEMENT IN RELATION TO ORGANIZATIONAL CITIZENSHIP BEHAVIOR IN INFORMATION TECHNOLOGY ORGANIZATIONS
Employee contribution becomes a critical business issue because in trying to produce superior output, companies have no choice but to try and engage not only the body but the mind and soul of every employee. Most organizations today realize that a satisfied employee is not necessarily the best employee in terms of loyalty and productivity. The best employee is really an engaged employee ?? one who is intellectually and emotionally bound with the organization, who feels passionate about its goals and is committed towards its values. This employee goes the extra mile beyond the basic job requirements. Currently, organizations expect their employees to be proactive and show initiative, collaborate smoothly with others, take responsibility for their own professional development, and to be committed to high quality performance standards. Thus employees who feel energetic and dedicated and who are absorbed by their work, employees who can create a culture in the organization that would be for the well-being of the organization and people involved in the organization are most critical for the organization. These voluntary behaviors which contribute to the business unit performance are Organizational Citizenship Behaviors. Engaging employees of an organization is critical to the organizations success. Employee Engagement is often the most significant differentiator between competing IT organizations. This is true particularly for service based IT companies as revenues are directly proportional to number of engaged workforce in the organization. Majority of researches on employee engagement from survey houses and consultancies have established the relationship between employee engagement, financial business performance and profitability. Interestingly, there are very few academic literatures on engagement. Several literatures on OCB have highlighted the relationship between OCB and productivity, in-role performance, and business unit performance. However there has been no research established to find out if there is any relationship between employee engagement and OCB. In this research, the researcher is interested to focus on employee engagement and OCB in Indian and multinational companies operating in the IT sector in India. The research is focused to analyze if the dimensions of OCB like helping behavior, taking initiative, self development indicate the engagement levels of an employee. Based on the review of literatures and identified the gap, the investigator felt an imperative need to pursue with the current research. The sample consisted of 235 IT professionals from both Indian and MNC companies. The judgmental and convenient sampling technique was adopted for selecting the respondents. Two standard tools were used to measure the variables of the study:- 1.Employee Engagement questionnaire by Dilys Robinson (2004), the reliability for the scale was.880. 2.Organizational Citizenship Behavior questionnaire by Podsakoff (2000), the reliability for the scale was .703 The major findings of the study were - i. There was a positive significant relationship between Employee Engagement and Organizational Citizenship Behavior. ii.The drivers of engagement viz. pay and benefits, feeling valued and involved, training and development, job satisfaction, management, colleagues, equal opportunities, communication, current career intention are found to have significant positive correlation with Employee Engagement. iii.There was a significant negative relation between Employee Engagement and stress and work pressure. iv.The variable with highest influence on engagement was current career intension, followed by job satisfaction, pay & benefits, management, equal opportunities, and organization citizenship behavior. v.The variables colleagues, communication, training and development, feeling valued and involved were not found to have any significant impact on Employee Engagement. vi. There were significant differences in job satisfaction behavior between men and women professionals. Job satisfaction was significantly higher for women than for men. vii.There were significant differences in organizational citizenship behavior between men and women professional. The Organizational citizenship Behavior was higher for men than women. viii.There were significant differences in current career intension between different age groups. Current career intension was generally increasing with age, with the exception of the 41-45 yr. age group. There was no significant difference in other dimensions between age groups. ix.There was no significant difference in any of the dimensions based on work experience. x.There were significant differences in satisfaction with pay and benefits based on qualification. Satisfaction with pay and benefits was highest for professionals with PhDs, and lowest for post-graduates. xi.Stress and work pressure was highest for graduates, and lowest for PhDs there was no significant difference in other dimensions based on qualification. xii.There were significant differences in Employee Engagement and the type of companies. Employee Engagement was higher for professionals working in Multi National Companies than for those in Indian companies. xiii.Satisfaction with management was higher for professionals working in Multi National Companies than those working in Indian companies. xiv.Satisfaction with management was significantly higher for professionals working in Multi National Companies than those working in Indian companies. xv.Stress and work pressure was significantly higher for professionals working in Indian companies than those working in Indian companies. xvi.At a micro level analysis, it was found that type of IT company the employees belonged did not significantly differ among pay and benefits, feeling valued and involved, job satisfaction, colleagues, equal opportunities, training and development and current career intention. xvii.It was found that the driver qualification did not have any significant difference among feeling valued and involved, colleagues, equal opportunities, job satisfaction training and development and management. xviii.Gender did not significantly differ among the variables feeling valued and involved, colleagues, equal opportunities,training and development and current career intention, and management. xix.It was found that age did not significantly differ among any of the dimensions like feeling valued and involved, colleagues, equal opportunities, job satisfaction training and development and management. Length of service in the organization did not significantly differ among employees in any of the dimension. xx.It was found that there was no significant difference between Organizational citizenship Behavior, age of the employees, work experience of the employees, and qualification of the employees. xxi.It was found that there was no significant difference between Organizational citizenship Behavior, age of the employees, work experience of the employees, and qualification of the employees. xxii.It was found that male employees were satisfied with pay and benefits. xxiii.Female employees were feeling more valued and involved than male employees. xxiv.The female employees were more satisfied with the training and development activities. xxv.It was found that female employees had more levels of Employee Engagement than male employees. xxvi.It was found that female employees were more satisfied with management and colleagues. xxvii.Male employees seem to undergo more of stress and work related pressure than male employees. xxviii.It was found that male employees were more satisfied with communication and equal opportunities. xxix.Female employees had more intentions to stay with their companies than male employees. xxx.The level of Organizational citizenship Behavior was higher for men than women. xxxi.Employees working in MNCs were satisfied with pay and benefits, feeling valued and involved training and development. xxxii.Employee engagement level of MNC employees was higher than Indian employees. xxxiii.The stress and work pressure was higher for Indian employees than MNC employees. -
EMPLOYEE ENGAGEMENT: ANTECEDENTS AND CONSEQUENCES
Employee engagement is the emotional connection and dedication that employees feel towards their organisation. It is a term used to describe how dedicated, enthusiastic and involved employees are towards/with their job and the organisation they work for. Antecedents are the variables that influence and contribute towards employee engagement, while consequences are the outcomes linked with employee engagement. Attrition of intellectual capital, disengagement with work, issues of conflict with students, lack of job satisfaction, etc. in the centres of higher education are becoming a burgeoning problem and constructive employee engagement is seen as the solution to these issues. The present study aims to examine the factors responsible for employee engagement as well as the outcomes that are derived due to effective implementation of employee-engagement practices. Data has been collected from 117 faculty members of higher-education institutions from South India using simple random sampling. Data has been analysed with the help of Excel, SPSS and AMOS, using statistical tools like T-test, ANOVA and SEM. The proposed model reflects strong positive association between antecedent variables like autonomy, rewards and recognitions, and fair and equitable treatment and employee engagement, and job satisfaction, organisational commitment and intention to stay as the outcomes of employee engagement. 2024 Published by Faculty of Engineering.