Determinants of E-Resources Usage Intensity of Postgraduate Students in a Kenyan Private University

Abstract

The aim of this study was to ascertain the determinants of usage intensity of e-resource platforms accessible to postgraduate students of a Kenyan private university. The research applied Technology Acceptance Model (TAM) to make sense of e-resource interaction and usage by postgraduate university students within a developing country context. Cross-sectional descriptive survey design was used. The target population was 225 postgraduate students who were on session during September 2017 semester and who had completed at least one year of study. From this, 79 eligible respondents were randomply sampled. Perception data was matched against users„ uniform resource locator (URL) log count. Inferences were drawn using correlation and regression technique. The study established that TAM factors explained 10.9 percent of the variability in the student‟s eresource usage intensity. The results showed that perceived ease of use had no statistically significant predictive power on e-resource usage intensity. The results also indicated that perceived usefulness did not significantly predict the student‟s e-resource usage intensity. Similarly, perceived behavioural factors did not significantly predict the student‟s e-resource usage intensity. The results challenge the applicability of TAM for explaining technology acceptance and usage as far as e-resource usage is concerned. Conclusion was drawn that TAM factors are not adequate for explaining postgraduate student„s e-resource usage intensity in a Kenyan private university. University librarians should be user-centric in the design of all its systems. This calls for collecting the views of users and bringing their input on board as opposed to library logic where the library staff create a system based on what they believe is good for the users. More studies that integrate objective data mined from e-resource servers with perception data using a larger dataset should be conducted to confirm or refute the findings of this research. Meta analysis of such studies can lead to the development and validation of new models for explaining e-resource usage especially in a resource-constrained country.