Dataset for "From Rationality to Intuition: The Effect of Business Intelligence Information Uncertainty on Decision-Making Processes"
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Title Business Intelligence Information Uncertainty and Decision-Making: Experimental Dataset and Outputs Description (Summary) This repository contains the raw and processed data from an experimental study investigating how different levels of Business Intelligence (BI) information uncertainty influence decision-making styles (intuitive vs. rational), and the moderating effect of user experience. The experiment involved 72 professionals and used scenario-based vignettes to simulate varying levels of uncertainty. Included in the archive are: SurveyResponses.sav: Raw data from participant responses, originally collected in French, with variable labels aligned to the manuscript. SPSS output files grouped by analysis type: Reliability analyses (Cronbach's alpha) Normality tests Wilcoxon and Friedman tests Moderation and correlation analysis README_BI_Decision_Uncertainty.md: Provides an overview of the dataset structure, English variable names, Likert coding, and the mapping of computed variables to hypotheses Ha, Hb, and Hc. All statistical output files are labeled in French; an accompanying README provides translations and interpretations. This dataset supports the findings reported in the article: From Rationality to Intuition: The Effect of Business Intelligence Information Uncertainty on Decision-Making Processes by Anas El Ouarzadi and Karim Charaf (2025). Keywords Business Intelligence Decision-Making Information Uncertainty Intuition Rationality Experimental Study SPSS Dual-Process Theory User Experience Behavioral Decision-Making Authors Anas El OuarzadiResearcher, ISCAE Business School – Laboratory of Finance and Management ControlEmail: aelouarzadi_doct21@groupeiscae.ma Karim CharafProfessor and Director, Doctoral Center, ISCAE Business School Recommended Citation [dataset] El Ouarzadi, A., & Charaf, K. (2025). Business Intelligence Information Uncertainty and Decision-Making: Experimental Dataset and Outputs. Zenodo. https://doi.org/10.5281/zenodo.15161414
