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Pedaling beyond ratings: A data-driven quest to Unravel the determinants of guided bicycle-tour satisfaction
被引：0
|作者：
Chen, Li-Hsin
[1
]
机构：
[1] Natl Kaohsiung Univ Hospitality & Tourism, Int Masters Program Tourism & Hospitality, 1 Songhe Rd, Kaohsiung, Taiwan
关键词：
Bicycle tourism;
Guided tours;
Participant satisfaction;
Text mining;
Automated content analysis;
Cross-cultural study;
SEASONAL-VARIATION;
TRAVEL BEHAVIOR;
CYCLING TOURISM;
ATTRIBUTES;
PERSPECTIVE;
DIMENSIONS;
D O I：
10.1016/j.tourman.2024.104906
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ;
0830 ;
摘要：
Guided bicycle tours are often overlooked in the bicycle-tourism literature. This study addresses that gap by developing an Integrated Framework for Guided Bicycle Tours (IFGBT), which takes account of the complex interplay of various temporal and contextual factors to provide a holistic understanding of guided bicycle-tour participants' satisfaction. To establish the IFGBT, this study employed a text-mining approach on a dataset comprising 151,654 online reviews from 100 guided bicycle tours conducted in 36 countries between 2006 and 2022. The results suggest three key determinants of satisfaction: the characteristics of the tour participants, the tour quality, and the resources of the destination. The study also highlights temporal factors, such as seasonality, and COVID-19, as complex determinants of satisfaction. The pandemic unexpectedly boosted satisfaction due to reduced tourism, especially in peak seasons. Social interactions, guide competencies, and local regulations also emerged as significant influencers on satisfaction levels.
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页数：19
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