A Predictive Model for Organizational Decision-Making Quality in Healthcare Organizations Using Big Data Analytics Capabilities

This article presents a machine learning-based predictive framework for assessing organizational Decision-Making Quality (DMQ) using Big Data Analytics Capabilities (BDAC) in healthcare organizations. The proposed framework integrates five BDAC dimensions—organizational, technical, analytical, cognitive, and social—and evaluates four supervised machine learning classifiers: Artificial Neural Network (ANN), Naive Bayes (NB), Decision Tree (DT), and Support Vector Machine (SVM). The study is based on data collected from 205 healthcare professionals in Jordan. The experimental results demonstrate that the Naive Bayes classifier achieved the highest predictive accuracy (87%), highlighting the effectiveness of integrated BDAC dimensions in improving organizational decision-making.