Analysis of EAC Using Multiple Regression and Conditional Process: A Statistical Approach

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Abstract

In the modern world of increased competition, evolving technologies and volatile environment every institution must poise themselves to innovate and change, not only to prosper but merely to survive. The situation is more acute in institutions of higher education in India where things are changing with unprecedented speed. The survival of the institutions will depend upon the adaptability of their employees to embrace the change. However, employees' acceptance to change cannot be developed overnight and also in isolation. It requires intensity and persistency of efforts in the right direction from the management. In the present paper, the researchers have identified the role of emotional intelligence and locus of control in enhancing employees' acceptance to change in HEIs, Uttarakhand using multiple regression and conditional process analysis. The data for the present study were collected using stratified sampling and structured questionnaires from 432 employees from various HEIs in Uttarakhand. The finding revealed that EI enhances the EAC in HEI. Further, it also revealed that Job Satisfaction acts as a partial mediator in the relation between EI and EAC.

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Singh, M., Ghai, S., Mishra, A. K., & Goyal, N. (2024). Analysis of EAC Using Multiple Regression and Conditional Process: A Statistical Approach. Journal of Reliability and Statistical Studies, 17(1), 109–136. https://doi.org/10.13052/jrss0974-8024.1715

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