Factors Predicting Employee Happiness at Work: A Linear Discriminant Analysis Approach
Shiwani Singh et al.
What the paper says
The goal of our study was to identify the constructs that most accurately distinguish between employees who are happy and unhappy at work. The study explores employee happiness in a non-Western context, addressing a gap in existing research predominantly focused on Western settings. To determine the major predictors of employee happiness at the workplace, a linear discriminant analysis was performed. A total of 250 questionnaires were distributed, and 153 responses were successfully received through the convenience sampling method from the banking sector employees of Gorakhpur district (Uttar Pradesh, India). The results denote that the linear discriminant function was well-suited for categorising employees at the workplace as either happy or unhappy. The findings reveal that the most distinguishing factor was work–life balance (WLB), followed by co-worker support, thriving at work and overall perceived fairness, respectively. Moreover, our results unveil important implications for policymakers to prioritise the WLB issues of the banking sector employees, as it emerged as a prominent and critical concern among them. Furthermore, organisations should foster a collaborative work culture that not only facilitates learning and personal growth but also nurtures healthy relationships among employees.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.