More Satisfied or More Aroused? Understanding the Effects of Arousal in Online Reviews on Product Demand From New Versus Returning Customers in the Service Sector

• 成果类型: Article; Early Access
• 署名作者: Zhang, Jing; Xu, Jian; Wang, Xuequn; Fan, Weiguo; Yao, Xiaoxu; Yang, Zhonghua
• 署名单位: Dongbei University of Finance & Economics; University of New Mexico; University of Iowa; Jilin University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1177/10591478251345136
• 发表日期: 2025
• 关键词: Online Review; Product Demand; emotion; arousal; Repatronage Behaviors

摘要

Online reviews play an important role in explaining product demand. Our study extends the literature by assessing how arousal (the intensity of the emotion), an important dimension of emotion, and valence (the positiveness of the emotion) can affect product demand across different customer groups. Specifically, regarding product demand from new customers, consumers infer service quality from expressed valence and arousal from other consumers' reviews. Regarding product demand from returning customers, consumers develop perceptions of service quality based on experienced valence and arousal (reflected in their reviews). We then examine product demand from new customers (studies 1 and 2a) as well as that from returning customers (studies 1 and 2b), and establish the external and internal validity regarding the moderating effects of arousal on different types of product demand. The results reveal that, although arousal has positive moderating effects for both new and returning customers, the strengths of the moderating effects differ. Furthermore, valence and arousal from other customers do not have significant effects for returning customers. Our study contributes to the literature by clarifying the moderating effect of arousal on product demand and by providing a more nuanced understanding of product demand at the customer profile level. Our results thus offer important practical suggestions regarding how to explain product demand across different customer groups by considering the textual information (i.e., arousal) of customer reviews.