Integration of Big Data Analytics in Management Information Systems for Consumer Behavior Prediction

Abstract

This research aims to understand the integration process of big data analytics in Management Information Systems (MIS) and its impact on predicting consumer behavior. Using a qualitative case study method, the research explores the determinants of successful integration, the challenges faced, and the contribution of big data analytics in supporting data-driven decision-making in organizations. Data was collected through in-depth interviews, observations, and document analysis at organizations that have implemented big data analytics in their SIM. The results showed that data quality, human resource competencies, and management support are key factors for successful integration. This integration improves the accuracy and speed of predicting consumer behavior, which has a positive impact on operational efficiency and customer satisfaction. This research provides theoretical contributions in the development of Management Information Systems and big data literature, as well as practical recommendations for organizations that want to optimize SIM functions through big data analytics.