CULTIVATING POSTGRADUATE STUDENTS RESEARCH PRODUCTIVITY: EXPLORING INTERPLAY BETWEEN RESEARCH SELF-EFFICACY AND SUPERVISORY SUPPORT

Abstract

Research productivity by postgraduate students not only furthers their academic and professional growth but substantially influences the broader scholarly community and the societal context as well. This research focused on the influence of research self-efficacy toward research productivity and perceived moderating effect of supervisory support. The interaction between these two critical factors is essential to enhance research productivity among postgraduate students in Indonesian higher education. Quantitative methodology is employed in this research study. The purposive sampling technique was used which included postgraduate students who engaged in research activities as its criteria. The sample size calculations used Slovin formulation and as many as 514 respondents were obtained comprising of 330 Master's students and 184 PhD students in Indonesia,.  SmartPLS-4 was utilised to conduct structural equation model partial least square for data analysis. The results indicated that self-efficacy positively impacts research productivity. Furthermore, perceived supervisory support enhanced the interaction between research self-efficacy and research productivity. This investigation enriches theoretical landscape by applying Bandura's social cognitive theory to postgraduate research. Practically, based on these findings, it suggests that academic institutions can design research training programs to increase students’ research self-efficacy levels, and develop strategies to facilitate supportive supervisory relationships which increases research productivity. Future research should employ longitudinal designs to clarify the causal relationships between research self-efficacy and research productivity, as well as replicate the research in various cultural and academic environments to improve its generalizability. Additionally, it should aim to incorporate objective productivity metrics and investigate other potential moderators and mediators to intensify the understanding of the factors and mechanisms driving research productivity.