Predictors of research productivity of academic staff in Kyambogo University, Uganda

Abstract

This study examined whether ascriptive, individual, leadership and institutional factors predict research productivity of academic staff at KyU as suggested by Mantikayan and Abdulgani (2018) model. Specifically, the study looked at whether ascriptive, individual, leadership and institutional factors were predictors of research productivity. In the study, four research hypotheses were tested. The first hypothesis (H1) postulated that ascriptive factors (gender, age, & personality) were predictors of research productivity. The second hypothesis (H2) suggested that individual factors (self-efficacy, motivation, commitment, research orientation, & research skills) were predictors of research productivity. The third hypothesis (H3) postulated that leadership factors (regard of a leader as a scholar & research-oriented) were predictors of research productivity. The fourth hypothesis (H4) suggested that institutional factors (mentoring, resource support rewards, the sufficiency of work time, culture, & emphasis on research) were predictors of research productivity. Using the positivist research paradigm and the predictive cross-sectional survey design, data were collected from 165 academic staff using the questionnaire survey method. In terms of analysis the four hypotheses (H1 - H4) were tested using multiple linear regression models. The study findings showed that the three hypotheses (H1, H3 & H4) were not supported. The second hypothesis (H2) had only two constructs namely: motivation (β = 0.215, p = 0.025) and research skills (β = 0.246, p = 0.008) being significantly positive predictors of research productivity. It was thus concluded that Mantikayan and Abdulgani’s model does not adequately explain the factors that predict the research productivity of academic staff in Kyambogo University. Therefore, I recommend that the University management should put more emphasis in strengthening the motivation and the research skills of the academic staff in order to improve their research productivity.