Evaluation of data analytics-oriented business intelligence technology effectiveness: an enterprise-level analysis

Abstract

PurposeA crucial question still remains unanswered as to whether data analytics-oriented business intelligence (hereafter, BI) technologies can bring organizational value and benefits. Thereby, several researchers called for further empirical research to extend the limited knowledge in this critical area. In an attempt to deal with this issue, we presented and tested a theoretical model to assess BI effectiveness at the organizational benefits level in this research article.Design/methodology/approachThe suggested research model expands the application of the DeLone and McLean model in BI technology success or effectiveness research from individual level to organizational level. A cross-sectional survey is developed to obtain primary quantitative data from business and technology managers who are depending on BI technologies to make operational, technical and strategic decisions in Jordanian-listed firms.FindingsEmpirical findings show that system quality, information quality and training quality are significant predictors of user satisfaction, but not of perceived benefit. Data quality was found to be a strong predictor of both perceived benefit and user satisfaction. The influence of perceived benefit on user satisfaction was significant in turn both factors positively affect organizational benefits.Originality/valueThis research paper is a pioneering effort to assess BI technology effectiveness at an organizational level outside the context of developed countries. To the best of the authors’ knowledge, no prior research has combined all dimensions used in this research in one single model.