While many online platforms use incentive hierarchies to stimulate consumers to generate more online reviews, the extent to which these hierarchies influence reviewer behavior is not fully understood. This study, drawing on image motivation theory and consumer attention theory, takes a novel approach to investigate whether reviewers strategically adjust their review behavior after reaching higher ranks in a hierarchy. We use data from rank change timestamps on platforms to accurately identify reviewers' ranks when posting reviews and then employ a quasi-natural experimental design for causal inference. Additionally, we use Fisher's permutation test to explore the different effects at various ranks. The empirical results reveal that reviewers tend to increase their review length and insert more pictures into their reviews after they reach higher ranks. Reviewers at lower ranks tend to submit more extreme ratings upon rank advancement, whereas their higher-ranking counterparts do not demonstrate significant change. Unlike ratings, reviewers tend to consistently increase the sentiment intensity of their expressions in text after reaching higher ranks. Furthermore, our findings indicate that the magnitude of changes in reviewing behavior only shows an increasing trend in the early stages of rank progression. These insights contribute to a better understanding of the efficacy of incentive hierarchies and offer practical implications for decision-making by platform managers.

中文翻译：

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激励等级加剧了注意力的竞争：在线评论的研究


虽然许多在线平台使用激励等级制度来刺激消费者产生更多在线评论，但这些等级制度对评论者行为的影响程度尚不完全清楚。本研究借鉴图像动机理论和消费者注意力理论，采用一种新颖的方法来调查评论者在达到更高等级后是否会战略性地调整他们的评论行为。我们使用平台上排名变化时间戳的数据来准确识别评论者在发布评论时的排名，然后采用准自然的实验设计进行因果推理。此外，我们使用费舍尔排列检验来探索不同等级的不同效果。实证结果表明，审稿人在达到较高排名后倾向于增加审稿长度并在审稿中插入更多图片。排名较低的审稿人往往会在排名提升时提交更极端的评分，而排名较高的审稿人则不会表现出显着的变化。与评级不同的是，评论者在达到更高的排名后往往会不断增加他们在文本中表达的情感强度。此外，我们的研究结果表明，评论行为的变化幅度仅在排名进展的早期阶段显示出增加的趋势。这些见解有助于更好地理解激励层次结构的有效性，并为平台管理者的决策提供实际意义。