Computers (Oct 2022)

A Systemic Mapping Study of Business Intelligence Maturity Models for Higher Education Institutions

  • Christopher Lee Stewart,
  • M. Ali Akber Dewan

DOI
https://doi.org/10.3390/computers11110153
Journal volume & issue
Vol. 11, no. 11
p. 153

Abstract

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Higher education institutions (HEIs) are investing in business intelligence (BI) to meet the increasing demand for information stemming from their operations. Information technology (IT) managers in higher education may turn to BI maturity models to evaluate the current state of HEIs’ BI operation capabilities and evaluate the readiness for future improvements. However, generic BI maturity models do not have domain-specific attributes that ensure a high degree of compatibility with HEIs. This study’s objective is to survey maturity models that could be used in HEIs and identify those used for BI to perform an analysis of their qualities and identify future avenues for research into HEI-specific BI maturity models. A systemic mapping was undertaken via both a keyword and snowball search of five indexing services, 6037 articles were processed using inclusion and exclusion criteria resulting in the identification of forty-one academic works regarding maturity model uses which were mapped to ten categories. The mapping reveals an increasing number of publications featuring maturity models for HEI, particularly since 2018, focused on e-learning and ICT. A single instance of a BI maturity model for HEI emerged in 2022 within the European HEI context. The HE-BIA MM has more dimensions than most other models identified, yet only a single co-occurrence of dimensions was identified in name only. We conclude that BI maturity models for HEI are emerging as a field of research with future directions for research including exploring co-occurrence of dimensions with existing maturity models, performing case studies, and validation of HE-BIA MM outside the European HEI context.

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