This study examines how consumers make decisions when selecting restaurants online. It introduces a framework that categorizes decision-makers into four distinct styles - quick experts, hasty amateurs, casual novices, and relaxed professionals – based on their prior dining experience and time spent on the selection task. Through clickstream analysis of 282 participants using Yelp, we employed an algorithmic approach to identify these patterns and analyzed their information search and processing behaviors. Results revealed distinct patterns: experienced users conducted focused, sophisticated searches and prioritized credible sources, while less experienced users employed broader searches and were more influenced by promotional content. All groups exhibited satisficing behavior, but experienced users were more discriminating. We conclude that experience and time constraints significantly influence online restaurant selection strategies. These findings contribute to understanding consumer behavior in hospitality contexts, provide insights for hospitality managers to optimize digital presence, extends the theoretical framework of hospitality consumer decision-making.

中文翻译：

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分析在线餐厅选择中的消费者决策模式：Yelp 上的信息处理方式研究

本研究考察了消费者在网上选择餐厅时如何做出决定。它引入了一个框架，根据决策者之前的用餐经验和在选择任务上花费的时间，将决策者分为四种不同的风格——快速的专家、匆忙的业余爱好者、休闲的新手和放松的专业人士。通过使用 Yelp 对 282 名参与者进行点击流分析，我们采用了算法方法来识别这些模式，并分析了他们的信息搜索和处理行为。结果揭示了不同的模式：有经验的用户进行集中、复杂的搜索并优先考虑可靠的来源，而经验不足的用户使用更广泛的搜索，并且受促销内容的影响更大。所有组都表现出令人满意的行为，但有经验的用户更具辨别力。我们得出的结论是，经验和时间限制会显着影响在线餐厅选择策略。这些发现有助于了解酒店环境中的消费者行为，为酒店管理者提供优化数字存在的见解，扩展酒店消费者决策的理论框架。