How to ameliorate employee engagement among government school teachers? Empirical evidence

Abstract

Purpose

The purpose of this paper is to investigate the impact of three predictors (emotional intelligence, perceived supervisor support and work–life balance) on employee engagement.

Design/methodology/approach

The employee engagement and its predictor variables considered have been assessed by a survey using a structured questionnaire. Data were collected for 628 government school teachers of Punjab state of India. SEM using SmartPLS software was used to estimate the relationship between employee engagement and its predictors (emotional intelligence, perceived supervisor support and work–life balance).

Findings

The results reveal that the three predictors (emotional intelligence, perceived supervisor support and work–life balance) have a significant positive impact on employee engagement of the government school teachers.

Practical implications

School authorities need to draft teacher-friendly policies so that teachers can stay deeply engrossed in their work and can handle work and family demands. Engaged teachers brim with positive energy, thereby energetically and vigorously preoccupying themselves in their work, leaving no time and space for negative thoughts.

Originality/value

The influence of emotional intelligence, perceived supervisor support and work–life balance on employee engagement of government school teachers is unprecedented. The study also tested the model in a holistic manner. Since the study is based on an Indian sample, it also adds to growing literature on employee engagement in nonwestern countries. The results are of great value to government authorities, school managements, HR managers and policymakers who are seeking to develop practices that enhance employee engagement at workplaces.

Citation

Kaur, R. and Randhawa, G. (2024), "How to ameliorate employee engagement among government school teachers? Empirical evidence", International Journal of Educational Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJEM-09-2023-0484