We study how firms respond to online customer reviews in a competitive market where they jostle with one another for sales based on online ratings. The focus of this paper is on how firms can optimally manage their ratings through management response and how review ratings affect the sales and profits of competing firms. We develop a controlled diffusion process to model the coevolution of sales and ratings as a function of the response strategy chosen to maximize profit over time. Our model considers a variety of factors, such as profit margin and customer rating sensitivity, that influence a firm’s effort to manage ratings and subsequently its sales and profits. More response effort needs to be exerted to manage ratings when either the profit margin of a tour is very high or customers are very sensitive to ratings. We estimate our model using data on Ctrip’s tours that include each tour’s sales, reviews, prices, and tour features. We find that consumers anchor their beliefs in the mean market rating and that their purchase decisions depend on the tour’s rating relative to this anchor. Thus, relative, rather than absolute, ratings matter. Our study informs firms on how competition and other primitives impact their efforts to manage ratings and hence profit. Our methodology allowed us to conduct “what-if” analyses, for example, to study what would happen to the review ratings, sales, and profits of a tour if a firm adopted a different response strategy. We were also able to provide turnaround strategies for struggling tours, i.e., factors that a loss-making tour should change if it wishes to make a positive profit. Ultimately, we conducted a competitive analysis that allowed us to modify certain parameters that affect the intensity of competition and hence the sales and the profits of competing tours. Finally, we demonstrate the flexibility of the model by extending it to incorporate multiple state variables that might affect the response strategy.

中文翻译：

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回应竞争市场中的在线评论：一种受控的扩散方法

我们研究公司如何在竞争激烈的市场中回应在线客户评论，在竞争市场中，他们根据在线评级相互竞争销售。本文的重点是公司如何通过管理层回应最佳地管理其评级，以及审查评级如何影响竞争公司的销售和利润。我们开发了一个受控的扩散过程来模拟销售和评级的共同进化，作为选择的响应策略的函数，以随着时间的推移最大化利润。我们的模型考虑了多种因素，例如利润率和客户评级敏感度，这些因素会影响公司管理评级的努力以及随后的销售额和利润。当旅游的利润率非常高或客户对评级非常敏感时，需要做出更多的响应努力来管理评级。我们使用携程旅游的数据来估计我们的模型，这些数据包括每个旅游的销售、评论、价格和旅游特征。我们发现消费者将他们的信念锚定在平均市场评级中，并且他们的购买决定取决于旅游相对于该锚点的评级。因此，相对而非绝对的评级很重要。我们的研究让公司了解竞争和其他原语如何影响他们管理评级和利润的努力。我们的方法允许我们进行“假设”分析，例如，研究如果公司采用不同的响应策略，旅游的评论评级、销售和利润会发生什么变化。我们还能够为陷入困境的旅游提供周转策略，即亏损的旅游如果希望获得正利润就应该改变的因素。最终，我们进行了竞争分析，使我们能够修改影响竞争强度的某些参数，从而影响竞争旅游的销售和利润。最后，我们通过扩展模型以包含可能影响响应策略的多个状态变量来展示模型的灵活性。