Data Mining Technology Adoption in Institutions of Higher Learning: A Conceptual Framework Incorporating Technology Readiness Index Model and Technology Acceptance Model 3

Abstract

The adoption of Data Mining Technology (DMT) is on the rise due to its ability to discover hidden knowledge amongst large amounts of data. This technology is particularly important to organisations for making well-informed decisions and formulating strategic plans. However, previous studies on DMT have focused more on evaluating methods and techniques-rather than focusing on end-user perspectives. Moreover, studies on the adoption of DMT have been successfully conducted in various fields except for education, in particular, regarding the utilisation of DMT at an individual-level. Motivated by these problems, this study seeks to integrate the Technology Readiness Index (TRI) and the Technology Acceptance Model 3 (TAM3) into a model that will investigate end-user (individual-level) determinants of DMT adoption, specifically in the context of Institutions of Higher Learning (IHLs) in Malaysia. Several determinants from past literature were adopted and adapted in proposing the newly integrated TRI and TAM3 model. Ultimately, this model could aid management personal, particularly decision makers, to predict the acceptance or rejection of DMT in IHLs.