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Unlocking the power of multidimensional ratings: empirical analyses and designs from mediation models

调解 心理学 功率(物理) 实证研究 计量经济学 计算机科学 认知心理学 社会心理学 经济 统计 数学 社会学 社会科学 量子力学 物理
作者
Yuanyang Wang,Maoxin Han,Kai Li
出处
期刊:Internet Research [Emerald Publishing Limited]
标识
DOI:10.1108/intr-03-2023-0219
摘要

Purpose Prior papers have not fully examined the relationship between multidimensional (MD) ratings and review helpfulness, which may limit the potential of MD ratings in mitigating information asymmetry. Thus, leveraging signaling theory and cued recall, we analyzed the direct and indirect impacts of MD ratings on review helpfulness and subsequently derived corresponding design guidelines. Design/methodology/approach We adopted a multiple mediation model to examine the direct and indirect effects of MD ratings on review helpfulness. We conducted a series of econometric analyses to ensure the robustness of our conclusions. Additionally, Fisher’s permutation test was adopted to assess the potential heterogeneity in these impacts across various hotel types. Findings Leveraging the review data from TripAdvisor.com, we found that, beyond the positive direct impacts of MD ratings, there are significant indirect impacts positively mediated by review writing effort but negatively mediated by content polarity, accounting for 55% of the total impact. Moreover, we revealed that these impacts exhibit significant heterogeneity across different hotel types, online rank and rating valence. Finally, we incorporated both these identified impacts and their heterogeneity into the design of an MD ratings system, yielding guidelines regarding the quantity and category of dimensional ratings. Originality/value We extended the determinants of review helpfulness to the areas of MD ratings and highlighted the impact of the interaction of review functions on review helpfulness. Besides, we emphasized the importance of the signaling environment and illustrated how the effects of signals were shaped by cognitive processes, i.e. cued recall. Finally, we offered practical design rules regarding the quantity and category of dimensional ratings, aiming to maximize the power of MD ratings.
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