This study aims to analyze managerial decision-making in dealing with market demand uncertainty in the digital era through a data-driven and analytical approach. Demand uncertainty has become a major challenge for managers due to rapid changes in consumer behavior and dynamic market conditions. The research employs a quantitative approach involving twenty respondents consisting of managers and supervisors in organizations that have adopted digital technologies. Data analysis is conducted descriptively and further examined using a simulation of Structural Equation Modeling with Partial Least Squares to test the relationships among variables. The findings indicate that the implementation of data-based decision-making improves the quality of managerial decisions and reduces perceived demand uncertainty. However, digital technology functions as a supporting tool, while managerial judgment remains the key determinant of final decisions. This study provides empirical insights for managerial practices in addressing market uncertainty in the digital economy.
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