Developing HRIS for Predictive Attrition and Retention management of Indian IT Engineers- using ANN, ANOVA and Smart PLS

Growth of IT sector in India (Heeks, 2015) is phenomenal, however, employee turnover has been a persistent issue in IT sector (Yiu & Saner, 2008). Voluntarily turnover among employees has been attributed to dissatisfaction with organizational factors and individual characteristics (Elkjaer &...

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Published in:International journal of innovative technology and exploring engineering Vol. 8; no. 9S; pp. 710 - 715
Format: Journal Article
Language:English
Published: 23.08.2019
ISSN:2278-3075, 2278-3075
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Abstract Growth of IT sector in India (Heeks, 2015) is phenomenal, however, employee turnover has been a persistent issue in IT sector (Yiu & Saner, 2008). Voluntarily turnover among employees has been attributed to dissatisfaction with organizational factors and individual characteristics (Elkjaer & Filmer, 2015). Therefore, this research examines how to retain employees in IT firms, by focusing on the Job attitudes, theory of individual differences and theory of planned behaviour. It also explores which individual characteristics contribute to employee turnover intent, as a consequence of their negative job attitudes. The techniques of Artificial Neural Networks, Two-way ANOVA and PLS testing have been utilised. The analysis confirms the proposition that individual differences have an effect on job attitudes, which ultimately affect the turnover intention.
AbstractList Growth of IT sector in India (Heeks, 2015) is phenomenal, however, employee turnover has been a persistent issue in IT sector (Yiu & Saner, 2008). Voluntarily turnover among employees has been attributed to dissatisfaction with organizational factors and individual characteristics (Elkjaer & Filmer, 2015). Therefore, this research examines how to retain employees in IT firms, by focusing on the Job attitudes, theory of individual differences and theory of planned behaviour. It also explores which individual characteristics contribute to employee turnover intent, as a consequence of their negative job attitudes. The techniques of Artificial Neural Networks, Two-way ANOVA and PLS testing have been utilised. The analysis confirms the proposition that individual differences have an effect on job attitudes, which ultimately affect the turnover intention.
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Snippet Growth of IT sector in India (Heeks, 2015) is phenomenal, however, employee turnover has been a persistent issue in IT sector (Yiu & Saner, 2008). Voluntarily...
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