Systematic Review of Big Data Applications in Decoding Consumer Behaviors

Big data is pivotal in understanding consumer behavior and predicting consumer decisions. However, research has predominantly focused on specific consumption aspects, with a noticeable gap in systematic reviews on big data’s role in consumer behavior studies. This paper systematically reviews 127 articles to identify key topics, significance, challenges, and emerging trends in the application of big data to consumer behavior research. Our findings indicate that big data analysis in this field primarily focuses on consumer attitudes, behavior patterns, decision-making processes, and the impact of major events. Big data is categorized into structured and unstructured types, with deep learning, machine learning, and text data as essential research methods, particularly for predicting consumer trends. Future research should focus on enhancing data quality, improving model interpretability, and fostering stronger collaboration between academia and industry. This study advances the understanding of how big data can be effectively leveraged in consumer behavior research, highlighting its potential benefits and challenges.