Complexities in making effective and timely business decisions in highly competitive markets
have driven many organisations to adopt data-driven, decision-making processes using
Business Intelligence (BI) applications. Despite these applications being suited for use in most
organisations regardless of size, only larger enterprises have reached a stage of maturity in BI
use, while small and medium-sized enterprises (SMEs) still lag behind. Although there is a rich
body of literature on information technology (IT) adoption and implementation, literature
relating to BI adoption, especially in the SME context, remains limited. This study addresses
the lack of a research framework for examining the current state of BI adoption and the
identification of factors influencing decisions for BI adoption in SMEs. To address this
research gap and support the adoption rate of BI in SMEs, the study develops a comprehensive
research framework for categorising SMEs into different levels of BI adoption and explores the
enabling factors that influence BI adoption in SMEs. In order to classify organisations into
different BI levels, this study applies the information evolution model (IEM) used widely by
practitioners to evaluate the levels of BI adoption in organisations. In investigating factors
involved in adoption decisions, the study employs a multiple-perspective framework based on
three adoption models, including the diffusion of innovation (DOI) theory, the technology organisation-environment (TOE) model, and the information systems adoption model for small
business. The developed research framework contains eleven enabling factors covering four
characteristics: technological innovation, environment, organisation, and owner-managers.