Raise the Expectation Bar and Lower the Tolerance? Effects of Being Listed in a Restaurant Guide on Customers' Online Rating Behavior

• 成果类型: Article
• 署名作者: Yang, Hui; Lu, Xianghua; Qiu, Liangfei; Zhang, Yicheng
• 署名单位: Fuzhou University; Fudan University; State University System of Florida; University of Florida; Huazhong University of Science & Technology
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1177/10591478261429211
• 发表日期: 2026
• 关键词: word-of-mouth; service quality; satisfaction; reputation; IMPACT; antecedents; reviews; MODEL; brand

摘要

Creating curated guides or lists (e.g., Top 100 Places to Eat) is a common operational strategy employed by platforms as part of their reputation systems to assist customers in decision-making. Prior research has largely highlighted the effects of such guides on customer word-of-mouth (WOM) volume and valence. Moving beyond these aggregate WOM metrics, we extend this stream to examine how being listed in a guide (BLG) influences customers' likelihood of providing ratings and rating composition across valence types (compliments, complaints, and neutral ratings), drawing on the zone of tolerance framework. Using large-scale empirical data, we find that BLG increases customers' likelihood of rating but reduces overall valence, with a higher proportion of complaints and neutral ratings and a lower proportion of compliments. The effect is particularly pronounced among merchants with additional high-quality signals (e.g., higher prices, greater popularity, and superior prior ratings). Evidence from both observational data and a randomized experiment further reveals the underlying mechanisms, showing that BLG increases customer involvement and raises desired expectations more dramatically than adequate ones. These triangulated findings contribute to the literature by providing in-depth insights into how and why BLG affects customer rating behaviors and thus, merchants' WOM. Our findings underscore the importance of strategic operations management for platforms when designing and managing their reputation systems, with significant implications for technology management.