Brand Image of Beijing’s Time-Honored Restaurants: An Analysis Through Large Language Model-Driven Review Mining

Understanding consumer perceptions of brand image is vital for the sustainable development of China Time-honored Brands, which combine cultural heritage with commercial value. This study aims to systematically analyze the brand image of Beijing’s time-honored restaurants by developing a large language model (LLM)-driven framework that advances beyond the limits of traditional text mining in semantic depth and adaptability. Using Dianping reviews from 2016 to 2022, we apply the Qwen3-32B model to map consumer feedback onto a Functional–Experiential–Symbolic (F–E–S) framework. Sentiment quantification and clustering analysis are employed to generate brand image profiles and identify common brand types, while topic modeling is used to uncover the specific consumer concerns shaping these perceptions. The results reveal a dual structure: the symbolic dimension, rooted in cultural heritage, is consistently high and stable, whereas the functional and experiential dimensions, associated with daily operations, are relatively low and highly volatile. Clustering further distinguishes two significantly different categories: comprehensive performers and heritage struggler brands. The key difference lies in whether brands can transform symbolic capital derived from historical legacy into positive consumer experiences through excellent operational performance. By integrating dynamic and structural perspectives, this study advances brand image research and provides data-driven insights to guide the targeted management and modernization of heritage brands.