Self-Determination Theory and Workplace Outcomes: A Meta-Analysis.

Applications of self-determination theory (SDT) in workplace contexts have demonstrable utility in identifying motivational determinants of adaptive workplace outcomes (e.g., job satisfaction, work engagement) implicated in employee well-being and work productivity and effective stress management. Studies have found consistent SDT-stipulated associations between theory constructs (e.g., psychological need satisfaction, autonomous motivation) and adaptive workplace outcomes, although with substantive between-study variability. The current meta-analysis synthesised research reporting relations among SDT constructs and workplace outcomes and tested a novel model specifying SDT-stipulated predictions. In the proposed model, associations between employees' perceived need support from workplace leaders and adaptive and maladaptive workplace outcomes were mediated by autonomy, competence, and relatedness need satisfaction and autonomous and controlled motivation forms. Multilevel meta-analysis of data from studies identified in a systematic database search (k = 192) confirmed SDT-consistent patterns of averaged correlations among theory constructs and outcomes. Meta-analytic structural equation modelling analysis of the proposed model indicated positive direct perceived need support-need satisfaction, need satisfaction-autonomous motivation forms, and autonomous motivation forms-adaptive outcome effects consistent with theory. Most salient, indirect effects of need support on adaptive workplace outcomes, and negative indirect effects on maladaptive outcomes, mediated by need satisfaction and autonomous motivation forms were observed. Moderation analyses indicated that model varied effects by work type, employee type, and country cultural orientation and GDP ranking. The analysis updates and advances prior research syntheses of SDT in workplace contexts providing robust support for the model including mechanism-related effects and identification of key moderators on which model effects are conditional.