1. Folorunso, O., & Ogunseye, S. O. (2008). Applying an enhanced technology acceptance model to knowledge management in agricultural extension services. Data Science Journal, 7, 31-45.
This research investigates the applicability of Davis’s Technology Acceptance Model (TAM) to agriculturist’s acceptance of a knowledge management system (KMS), developed by the authors. It is called AGROWIT. Although the authors used previous Technology Acceptance Model user acceptance research as a basis for investigation of user acceptance of AGROWIT, the model had to be extended and constructs from the Triandis model that were added increased the predictive results of the TAM, but only slightly. Relationships among primary TAM constructs used are in substantive agreement with those characteristic of previous TAM research. Significant positive relationships between perceived usefulness, ease of use, and system usage were consistent with previous TAM research. The observed mediating role of perceived usefulness in the relationship between ease of use and usage was also in consonance with earlier findings. The findings are significant because they suggest that the considerable body of previous TAM-related information technology research may be usefully applied to the knowledge management domain to promote further investigation of factors affecting the acceptance and usage of knowledge management information systems such as AGROWIT by farmers, extension workers, and agriculture researchers.
2. Folorunso, O., Ogunseye, O. S., & Sharma, S. K. (2006). An exploratory study of the critical factors affecting the acceptability of e‐learning in Nigerian universities. Information management & computer security
Education delivery via electronic media is becoming relevant in Nigeria educational systems, especially the universities. In spite of this, there are hindrances affecting the total acceptability of this technology. Design/methodology/approach – In this paper, we investigated these critical factors by analyzing the questionnaires collected from three sampled universities in Nigeria: private, public and state owned universities. Findings – The results obtained indicated that mass unawareness, low computer literacy level and cost were identified as the critical factors affecting the acceptability of the technology. Originality/value – Analysis herein has shown the factors affecting the acceptability of e‐learning in Nigeria. The results obtained will assist policy makers by finding solutions to literacy problems in Nigeria.