A Longitudinal Survey of Job Satisfaction among Pharmaceutical Executives: An Unconditional Latent Growth Curve Study

Abstract

Cross-sectional studies have been done to explore job satisfaction (JS) among pharmaceutical executives. However, limited evidence of increment or decrement in JS is provided in cross-sectional studies. Latent growth curve models provide a computational framework for evaluating changes in perception and behavior using longitudinal data. Drawing from Locke’s theory of satisfaction, the study explored change in the perception of JS among pharmaceutical executives. To the best of the authors’ knowledge, this is the first study to use a longitudinal design to explore the trajectory of change in JS among pharmaceutical marketing executives using unconditional latent growth curve analysis. Data were collected using an online survey questionnaire from a cohort sample of 1,023 pharmaceutical executives over 3 unequal time waves- T1 (406, June 2021) during COVID-19; and post-COVID periods-T2 (401, July 2022); and T3 (216, March 2023) using random sampling. Covariance-based structural equation modeling in EQS 6.4 was used for analysis. The model showed an acceptable fit. The mean score of JS was significant and positive (Intercept factor; M=2.265, p<0.01). The positive linear growth trend in JS was obtained (growth factor increment=4.594, p<0.01) at each time point. Initial satisfaction states of individual executives were not necessarily linked to changes in mean values over time. The study observed that JS has been on a positive growth trajectory since the COVID-19 pandemic. The study indicates improvement in working conditions by employers since the pandemic and/or coping strategies by employees. This study gives a simple guide to performing latent growth analysis in behavioral research. Keywords: Covid-19, Job satisfaction, Latent growth curve, Locke’s theory of satisfaction, Longitudinal study, Pharmaceutical marketing, Structural equation modeling.