global-journal-of-computer-science-and-technology-d-neural-ai Global Journal of Computer Science and Technology - D: Neural & AI 0975-4350 0975-4172 Global Journals Publishing Group Incorporated 10.34257/GJCSTDVOL23IS1PG27 50635 End-User Business Intelligence Tools Adoption in a Higher Education Institution Socio-Technical Analysis of BI Dashboard Adoption DakayIrish Tejero - FerolinRosana J. CanilloAngie Ceniza - PHILIPPINES, University of San Carlos 10 04 2023 23 D1 27 33

This study examines how business intelligence (BI) tools are adopted in a higher education setting. It made use of the theories of Diffusion of Innovation (DOI), Technology Readiness Index, and Technology Acceptance Model (TAM). The psychometric features of the intended end-users were defined using TAM. The technology readiness of the users was assessed using TRI. The DOI was used to describe the innovation itself. The important factors for the adoption of the technology in this particular environment were identified through the examination of both quantitative and qualitative data. To gain a better understanding of the socio-technical system as a whole, a systems dynamics tool is presented to model the interaction of these elements along with the recommended interventions.

 technology readiness user acceptance innovation system dynamics causal loop diagram. Full Text

This study examines how business intelligence (BI) tools are adopted in a higher education setting. It made use of the theories of Diffusion of Innovation (DOI), Technology Readiness Index, and Technology Acceptance Model (TAM). The psychometric features of the intended end-users were defined using TAM. The technology- readiness of the users was assessed using TRI. The DOI was used to describe the innovation itself. The important factors for the adoption of the technology in this particular environment were identified through the examination of both quantitative and qualitative data. To gain a better understanding of the socio-technical system as a whole, a systems dynamics tool is presented to model the interaction of these elements along with the recommended interventions.