The Bright Side of Lower Quality: Evidence from Restaurant Exploration

• 成果类型: Article; Early Access
• 署名作者: Carrera, Clara; Martinez-de-Albeniz, Victor; Sosa, Manuel E.
• 署名单位: University of Navarra; IESE Business School; INSEAD Business School
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2022.04141
• 发表日期: 2025
• 关键词: online user reviews; prospect theory; Recommendation systems; Heckman selection correction; quality reference

摘要

The value derived from hedonic goods is affected by reference effects at the time of consumption, usually in the form of quality standards. Consumption typically involves two steps: First, the consumer chooses a given good, among a pool of available choices; then, the consumer experiences the good and derives a satisfaction from it. Between both steps, consumers might build expectations about the good that might affect the ultimate realized utility. We investigate the role of quality references in this two-stage (choice-outcome) process. We develop a flexible framework for estimating quality references and their effect in choice and outcome that can include consumers' own past experiences, as well as that of others, and can give salience to more recent or more distant past experiences. Using novel longitudinal data from online restaurant reviews, we find evidence of quality loss aversion in the choice decision stage in accordance with prospect theory. However, in the outcome stage, we do find evidence of the opposite to loss aversion, that is, satisfaction is affected much less than one would expect when going to a lower quality restaurant. This is consistent with consumers adjusting their expectations downward and suggests that expectation adjustment protects consumers when they experience a good of lower-thanreference quality. Our results challenge the implicit assumption made by most recommendation systems that the expectation building process after making a choice does not change the outcome and imply that it may be better to patronize activities by alternating between high-and low-quality choices.