Perception and Optimization Strategies for Museum Study Tour Experiences from the Mass Consumer Perspective

Yu Qin () and Ping Huang ()
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Yu Qin: Chengdu University of Information Technology, School of Management
Ping Huang: Chengdu University of Information Technology, School of Management

A chapter in Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025), 2025, pp 468-474 from Springer

Abstract: Abstract By investigating the perceived quality of museum study tour experiences, this study aims to propose optimization strategies to refine these perceptions. Online reviews (n = 2,983) from Ctrip were analyzed via Python and ROST, including high-frequency word statistics and sentiment analysis. This allowed the identification of hotspots, core themes, and emotional tendencies in the mass consumer group’s feedback on museum study tours, thereby assessing the perceived quality of their experiences. The perceived quality of museum study tour experiences is generally positive. However, challenges such as inconsistent service levels, irregular ticket booking practices, and inadequate crowd control persist. This study proposes five optimization strategies to address these shortcomings, aiming to improve the study tour experience and promote the healthy development of museum-based educational tourism.

Keywords: educational tourism; museums; study tour experience; mass consumer group; semantic network analysis (search for similar items in EconPapers)
Date: 2025
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DOI: 10.2991/978-94-6463-770-0_52

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