Abstract: As an important medium for product experiences and subjective attitudes to be expressed, consumer needs and preferences can be comprehensively reflected by online reviews. In recent years, widespread attention has been paid to intelligent user requirement management based on online review data by scholars in fields such as marketing, information systems, and product development, and significant results have been achieved. However, a systematic conceptual framework and a holistic understanding of online review-driven intelligent user requirement management are found to be lacking in existing research. To this end, based on bibliometric analysis and a systematic literature review, a summary of related research is provided in this paper from three aspects: intelligent user requirement acquisition, intelligent user requirement analysis, and intelligent user requirement configuration. Finally, in conjunction with cutting-edge research such as multimodal data analysis and large language models, future research trends are further explored.

Key words: online reviews, intelligent requirement management, intelligent requirement analysis, intelligent requirement configuration, large language models