Abstract
The aim of this article is to identify patterns of co-occurrence in assessments regarding implementation determinants, benefits, barriers, post-implementation changes, and organizational outcomes associated with the use of Cloud Business Intelligence (CBI), as well as to identify enterprise segments with similar perceptions of these phenomena. The study was based on data obtained from 400 enterprises using cloud-based business analytics solutions. The analysis employed an exploratory approach, combining Multivariate Correspondence Analysis (MCA) with Ward's hierarchical cluster analysis. The results indicate that perceptions of CBI implementation have a multidimensional, non-random structure, and respondents' responses form distinct patterns that differentiate organizations in terms of the observability of benefits, the level of perceived implementation effectiveness, and the exposure to barriers. Based on this, five enterprise segments were identified, differing not only in their assessment of implementation outcomes but also in their organizational, technological, and decision-making profiles.
Paper Type
Short Paper
DOI
10.62036/ISD.2026.122
Determinants of Cloud Business Intelligence Implementation: An MCA and Cluster Analysis Approach
The aim of this article is to identify patterns of co-occurrence in assessments regarding implementation determinants, benefits, barriers, post-implementation changes, and organizational outcomes associated with the use of Cloud Business Intelligence (CBI), as well as to identify enterprise segments with similar perceptions of these phenomena. The study was based on data obtained from 400 enterprises using cloud-based business analytics solutions. The analysis employed an exploratory approach, combining Multivariate Correspondence Analysis (MCA) with Ward's hierarchical cluster analysis. The results indicate that perceptions of CBI implementation have a multidimensional, non-random structure, and respondents' responses form distinct patterns that differentiate organizations in terms of the observability of benefits, the level of perceived implementation effectiveness, and the exposure to barriers. Based on this, five enterprise segments were identified, differing not only in their assessment of implementation outcomes but also in their organizational, technological, and decision-making profiles.
Recommended Citation
Dziembek, D., Bajdor, P., Becker, J. & Lemieszewski, Ł.(2026). Determinants of Cloud Business Intelligence Implementation: An MCA and Cluster Analysis Approach. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.122