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.

中文翻译：

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超越评级的骑行：以数据驱动的探索，揭示自行车导游满意度的决定因素

在自行车旅游文献中，带导游的自行车旅游经常被忽视。本研究通过开发导游自行车旅游综合框架（IFGBT）来解决这一差距，该框架考虑了各种时间和背景因素的复杂相互作用，以提供对导游自行车旅游参与者满意度的整体了解。为了建立 IFGBT，本研究对一个数据集采用了文本挖掘方法，该数据集包含 2006 年至 2022 年间在 36 个国家进行的 100 次导游自行车之旅的 151,654 条在线评论。结果表明了满意度的三个关键决定因素：旅行参与者的特征、旅游质量、目的地资源。该研究还强调季节性和 COVID-19 等时间因素是满意度的复杂决定因素。由于旅游业减少，尤其是在旺季，此次大流行意外地提高了满意度。社交互动、导游能力和当地法规也成为满意度水平的重要影响因素。