Industrial tourism serves as a medium for disseminating industrial culture and strengthening public awareness. Quantifying the discrepancies between official projections and public perceptions is essential for shaping the destination image and enhancing appeal and competitiveness. This study examines five industrial heritage creative industry parks using large language models (LLMs) and multimodal data to address this issue. The results indicate the following: (1) Multimodal data fusion improves feature representation. (2) A clear discrepancy exists between official projections and public perceptions. The official perspective emphasizes the Cultural value of heritage, in contrast to the public’s greater concern with the Service experience perception. Despite this divergence, there is alignment in the recognition of the Creative industry form dimension. (3) Public sentiment regarding the parks is predominantly positive. However, an analysis of negative sentiments reveals that insufficient supporting facilities and poor consumption experience are the primary sources of dissatisfaction. Through large language models and multimodal data, this study proposes a framework for quantifying the gaps between official projections and public perceptions. It also provides practical insights and empirical support for the management and planning of industrial heritage creative industry parks.
Yang et al. (Thu,) studied this question.
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