报告题目:Falling Behind vs. Falling Short: How Horizontal and Vertical Performance Comparisons Drive Online Review Manipulation
报 告 人:王 乐 西安交通大学
报告时间:2025年11月7日(周五)下午4:00
报告地点:3044am永利集团C403会议室
报告人简介:
王乐,西安交通大学经济与金融学院教授,博士生导师,电子商务系系主任,陕西省电子商务与电子政务重点实验室副主任。入选国家级青年人才、陕西省杰青、陕西省三秦学者青年拔尖人才、西安交通大学青年拔尖人才A类。以第一作者或通讯作者在Information Systems Research (UTD24), Production and Operations Management (UTD24)和《管理科学学报》,《南开管理评论》等知名期刊发表论文40余篇。在《光明日报》、《经济日报》、《中国社会科学报》发表理论多篇理论文章。其中多篇论文获ESI 高被引论文、Wiley 年度高被引论文、期刊封面论文以及多个国内外学术会议的最佳论文。
报告内容简介:
Although prior research has largely attributed online review manipulation to inferior firm performance, the underlying mechanisms driving such unethical behaviors remain insufficiently theorized. Drawing on Performance Feedback Theory, this study posits that relative performance comparisons—both horizontal (against competitors) and vertical (against a firm’s own past self)—rather than absolute performance, better explain firms’ review manipulation intensity. Using a mixed-methods approach, we first analyze a comprehensive dataset of 42,188 hotels and their reviews across two major Chinese online platforms, employing fixed effects panel regressions with instrumental variables. We then conduct a pre-registered experimental study to establish causal inference. Our findings yield three key insights: First, both vertical and horizontal rating differences significantly predict review manipulation intensity, while absolute ratings show no significant effect after controlling for these relative comparisons. Second, horizontal and vertical rating differences exhibit a substitutive relationship, with firms strategically prioritizing one comparison over the other based on contextual pressures. Third, contrary to theoretical expectations regarding horizontal comparisons, firms consistently favor self-injection of positive reviews over injecting unfavorable reviews to competitors across both comparison types. Additionally, heterogeneity analyses further reveal that platform-endorsed and chain hotels are more responsive to vertical comparisons, while non-endorsed and independent hotels prioritize horizontal comparisons. By uncovering the relational and adaptive nature of online review manipulation, this research advances theoretical understanding of social comparison mechanisms underlying unethical behavior in digital platforms and offers actionable strategies for detection and prevention tailored to firm characteristics and comparison types.
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