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The IUP Journal of Management Research :
The IUP Journal of Emotional Intelligence as a Predictor of Job Satisfaction: A Study Amongst Faculty in India
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Emotional intelligence at work has a great influence on the level of job satisfaction and in turn on work performance. This study aims at determining and establishing a relationship between strategic emotional intelligence and job satisfaction among faculty members in Arts and Science institutions. The study employs the Mayer-Salovey-Caruso’s Emotional Intelligence Test and Wong’s job satisfaction inventories to quantify emotional intelligence and job satisfaction levels respectively. Sample consists of 98 faculty members in Tamil Nadu, India, and various statistical tools have been used to interpret the data.

 
 

Faculty members with nominal control of emotions are in a better position to deliver their responsibilities. Moreover, control over emotions influences the level of satisfaction in their jobs, which, in turn, affects the teaching process, including transfer of knowledge, molding of student behavior in the institution, and various other roles played by the faculty members.

Job satisfaction is “the emotional reaction a worker has towards his/her job after a comparison of the outputs he/she expects or desires with real outputs” (Cranny et al., 1992). Job satisfaction refers to how pleased employees are with their job. Emotional intelligence is a type of intelligence which involves the ability to measure one’s own and others’ emotions, to differentiate between the emotions and use it to guide one’s thinking and actions (Mayer and Salovey, 1997).

Hence, the aim of the present study is to investigate the relationship between strategic emotional intelligence and job satisfaction among the faculty members of arts and science colleges in Tamil Nadu, India.

 
 

Management Research Journal, Multinational Companies, Indian Pharmaceutical Sector, Financial Management, Working Capital Management, Public Sector Enterprises, Inventory Management, Credit Management, Multinational Private Sector Companies, Multiple Regression Techniques, Pharmaceutical Companies.