Psychological needs, engagement, and work intentions : A Bayesian multi-measurement mediation approach and implications for HRD

Purpose – The purpose of this study was to empirically examine the utility of self-determination theory (SDT) within the engagement–performance linkage. Design/methodology/approach – Bayesian multi-measurement mediation modeling was used to estimate the relation between SDT, engagement and a proxy measure of performance (e.g. work intentions) (N = 1,586). To best capture the phenomenon of engagement, two measures of engagement (i.e. the Utrecht Work Engagement Scale-9 [UWES-9] and the Job Engagement Scale [JES]) and one measure of harmonious and obsessive passion (HOPS) were utilized. The HOPS was split into separate scales (harmonious and obsessive passion). SDT was operationalized through the Basic Psychological Needs at Work Scale (BPNS). Performance was operationalized through a latent proxy of work intentions. Findings – Results demonstrated that the association between SDT and engagement were positive. Indirect effects between SDT and work intentions were significant for only two of the four measures of engagement (i.e. the UWES and Harmonious Passion). Hypotheses were partially supported. Practical implications – SDT operated as an appropriate framework for capturing the underlying psychological structures of engagement for each of the four measures. In some cases, engagement did not mediate the relation between SDT and performance as expected, highlighting the contextual nature of engagement in both application and measurement. Originality/value – This is one of the first studies to explicitly link a broad well-established psychological theory to engagement. This connection allows researchers to explain the latent processes of engagement that underpin the observed relationships of engagement in practice. Moreover, this is one of only a handful of studies that has used a multi-measurement approach in exploring the engagement–performance linkage and one of the only studies to use Bayesian methodology.