Predicting academic staff intention to stay in Tanzanian universities using Job Embeddedness Model: Smart PLS approach

Abstract

Turnover is one of the reasons for the inadequacy of academic staff in Tanzanian universities as in many other African countries. This study examined the relationship between job embeddedness and academic staff Intention to Stay in Tanzanian Universities, as a key step towards combating the problem of turnover. A survey of 314 academic staff from selected public and private universities in Tanzania was conducted and Smart PLS Structural Equation Modeling was used in examining the relationship. Further, PLS-MGA was conducted to examine whether a significant difference exists in the influence of job embeddedness on the intention to stay among academic staff in Public and Private Universities. The findings indicated that Job Embeddedness sufficiently predicted academic staff Intention to Stay in Tanzania's universities, with organization fit and organization sacrifice exerting main influences. The relationships varied between public and private universities with stronger relationships in private than in public universities. It was concluded that job embeddedness is an important predictor of intention to stay, and its inclusion in retention models may improve retention of academic staff in Tanzania's universities. Private Universities in Tanzania may especially find more affirmative results in terms of retention, by improving the fit between their academic members of staff and their universities.