Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/205898 
Year of Publication: 
2016
Citation: 
[Journal:] Cogent Business & Management [ISSN:] 2331-1975 [Volume:] 3 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2016
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
Increased complexities in making effective and timely business decisions in highly competitive markets have driven organisations worldwide to adopt business intelligence (BI) technologies. Large enterprises have reached a mature stage of BI adoption while small- and medium-sized enterprises (SMEs) still lag behind—despite organisations of all sizes can benefit from the use of this technology to aggregate, manage and analyse data for assisting decision-making that enhances profitability. This study proposes a BI maturity model for SMEs that distinguishes different levels of BI maturity and identifies the factors that currently impact their levels of BI adoption. The proposed model is empirically tested using survey data from 427 SMEs and analysed using multinomial logistic regression. Results indicate that BI adoption in Thai SMEs is still at an initial stage, with the majority being classified in the lowest level of BI maturity. Significant factors that impact the levels of BI adoption are relative advantage, complexity, organisational resource availability, competitive pressure, vendor selection and owner-managers’ innovativeness. Results from the study can be used by government agencies to develop strategies to increase the rate of BI adoption among SMEs. IT vendors also can use the results to determine which SMEs they should target.
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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