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Impact of Emotional Intelligence on Job Performance among Working Women in it Sector(Chennai) : An Empirical Study

Journal: IMPACT : International Journal of Research in Humanities, Arts and Literature (IMPACT : IJRHAL) (Vol.6, No. 01)

Publication Date:

Authors : ; ;

Page : 395-402

Keywords : Emotional Intelligence; Factor Analysis; Job Performance; Women Employees; IT Sector Etc;

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The technological advancements and growth in the IT sector have created a growing demand for skilled manpower in IT sector. Considering the high growth of the Information Technology industry in India and its vast global coverage and the huge employment potential that it offers create a separate platform that addresses women's challenges in the IT industry. Emotional intelligence plays major role in managing stress for women employees, and also improving the performance of the individual. Emotional intelligence is the ability to identify our own emotions and those of others to self motivate ourselves. It helps to increase emotional self awareness, expression, creativity, tolerance, trust and integrity to improve relations within and across the organization and thereby increase the performance which in turn gives a better standard of living. It is recognized that emotional intelligence is more important to job performance than any other leadership skill. It is said that our emotional intelligence is more than twice as important as our technical knowledge. The research study aims to find out the factors that help to motivate once intelligence by having proper assessment and control over emotions. The structured questionnaires on Emotional Intelligence were used to collect the primary data from 90 working women employees from IT sector with special reference to Chennai region. The result was validated using Factor Analysis and Garrett ranking techniques and is also used to rank the factor responsible for job performance. The result found that KMO Measure of sampling adequacy is 0.856. This shows that the sample size is adequate for 22 variables to identify the predominant factors.

Last modified: 2018-02-16 21:22:54