Optimization Strategies for Museum Wayfinding System Design Based on NLP and SEM

WANG Chaowei; ZHENG Gangqiang; SUN Jiawei; WANG Zheng

doi:10.19554/j.cnki.1001-3563.2025.16.042

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (16) : 472-483. DOI: 10.19554/j.cnki.1001-3563.2025.16.042

Design Discussion

Optimization Strategies for Museum Wayfinding System Design Based on NLP and SEM

WANG Chaowei, ZHENG Gangqiang^*, SUN Jiawei, WANG Zheng

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Abstract

The work aims to construct a design optimization pathway for museum wayfinding systems based on Natural Language Processing (NLP) and Structural Equation Modeling (SEM), systematically elucidating the mechanisms through which key design factors influence visitor satisfaction and proposing universally applicable optimization strategies to enhance the overall quality and user experience of wayfinding systems. Text mining techniques were employed to extract user comments from multiple tourism platforms, with NLP-based word frequency analysis and co-occurrence matrices utilized to identify focal points of visitor attention. Guided by user experience theory and information design principles, qualitative interviews were conducted to delineate core design domains which were subsequently transformed into measurable indicators. Exploratory factor analysis and principal component analysis were applied to extract latent variables, enabling the development and validation of a Structural Equation Model (SEM) to analyze the path relationships between critical factors and visitor satisfaction. The model exhibited a robust fit, confirming the significant positive effects of five exogenous variables on satisfaction, including cultural functionality, information transmission, visual design, interactivity, and usability, with information transmission identified as the most pivotal factor. Drawing on path coefficient results, a systematic optimization framework encompassing five key design dimensions was proposed, delineating a prioritized sequence and strategic directions for intervention in wayfinding system design. Grounded in empirical evidence, a satisfaction-oriented optimization pathway for museum wayfinding systems is put forward, offering theoretical foundations and methodological support for the systematic design and evidence-based decision-making of such systems and extending the application of Structural Equation Modeling in design studies, demonstrating strong transferability and practical value.

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museum wayfinding system / Natural Language Processing (NLP) / Structural Equation Modeling (SEM) / design influencing factors / design optimization strategies

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WANG Chaowei, ZHENG Gangqiang, SUN Jiawei, WANG Zheng. Optimization Strategies for Museum Wayfinding System Design Based on NLP and SEM[J]. Packaging Engineering. 2025, 46(16): 472-483 https://doi.org/10.19554/j.cnki.1001-3563.2025.16.042

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