Job satisfaction and job performance in the media industry: A synergistic application of partial least squares path modelling

Purpose – The purpose of this paper is to examine the relationship between job satisfaction and employee performance in the media industry as well as the role of demographic variables, namely, age, gender, income, marital status, and the level of education as categorical moderators on this relationship. Design/methodology/approach – A total of 220 valid questionnaires were collected from employees in the Malaysian media industry to examine the goodness of model fit, sign indeterminacy, measurement model, and structural relationships between constructs. Using partial least squares (PLS) path modelling, this study introduces a full-fledged structural equation modelling approach by applying ADANCO 1.1 advanced composite modelling and SmartPLS 3.2.3. PLS-multi-group analysis is applied to examine the heterogeneity of data and test the hypotheses on moderating variables. Findings – Payment, promotion, supervision, operating conditions, co-workers, and nature of the work were found to be conducive to employees’ job performance, among which co-workers generated the highest path coefficient followed by operating conditions, payment, and promotion. Hypotheses on the relationships between fringe benefits, contingent rewards, communication, and job performance were rejected. Age, gender, and level of education were found as moderators to the relationship between facets of job satisfaction and employees’ job performance. Practical implications – The results of importance performance map analysis can help managers and decision makers to prioritize their actions. The findings show that co-workers and operating conditions have the highest importance and payment and contingent rewards have the highest performance on job performance in the media industry. Originality/value – This study is among the few that investigates the relationship between job satisfaction and job performance in the media industry by considering demographic factors as the moderating variables. This study also contributes methodologically through the introduction of a synergistic PLS approach