聚焦前沿 | 市场学顶刊 MS 最新专题研究选辑
点击上方蓝字关注我们
聚焦前沿
Marketing Research
MS选辑
-转发自UIBE全球营销-
感谢对外经贸大学熊伟教授团队
M
S
0
1
Marketing Research
我会存活下来：用顾客评分来预测业务失败
I Will Survive: Predicting Business Failures from Customer Ratings
作者：Christof Naumzik, Stefan Feuerriegel, Markus Weinmann
Marketing Science, Published Online:10 Nov 2021,https://doi.org/10.1287/mksc.2021.1317
Abstract:
The success, if not survival, of service businesses depends on their ability to satisfy their customers. Yet, businesses often recognize slumping customer satisfaction too late and ultimately fail. To prevent this, marketers require early warning tools. In this paper, we build upon online ratings as a direct measure of customer satisfaction and, based on this, predict business failures. Specifically, we develop a variable-duration hidden Markov model; it models the rating sequence of a service business in order to predict the likelihood of failure. Using 64,887 ratings from 921 restaurants, we find that our model detects business failures with a balanced accuracy of 78.02%, and this prediction is even possible several months in advance. In comparison, simple metrics from practice have limited ability in predicting business failures; for instance, the mean rating yields a balanced accuracy of only around 50%. Furthermore, our model recovers a latent state (“at risk”) with an elevated failure rate. Avoiding the at-risk state is associated with a reduction in the failure rate of more than 41.41%. Our research thus entails direct managerial implications: we assist marketers in monitoring customer satisfaction and, for this purpose, offer a data-driven tool that provides early warnings of impending business failures.
摘要：
服务企业的成功，如果不是生存的话，取决于它们满足顾客的能力。然而，企业往往很晚才意识到顾客满意度的下降，并最后以失败告终。营销人员需要早期预警工具来防止这种情况的发生。在本文中，我们将在线评级作为顾客满意度的直接测量指标，并以此为基础对业务的失败进行预测。具体来说，我们开发了一个期间可变的隐马尔可夫模型，这个模型对服务业务的评分序列进行建模，以预测失败的可能性。我们根据921家餐厅的64887个评级的数据发现，我们的模型检测业务失败的平衡准确率为78.02%，甚至提前几个月就可以做出这些预测。相比之下，来自实践的简单指标在预测业务失败方面的能力有限；例如，基于平均评分得到的平衡准确率仅为50%左右。此外，我们的模型可以使企业从具有较高失败率的潜在（“风险”）状态中复原。避免处于风险状态与降低超过41.41%以上的失败率有关。因此，我们的研究具有直接的管理意义：协助营销人员监控顾客满意度，并为此为目标，提供了一种能为即将发生的业务失败提供早期预警的、数据驱动的工具。
关键词：隐马尔可夫模型（hidden Markov model），顾客评分（customer ratings），业务失败（business failure），服务管理（service management）
M
S
0
2
Marketing Research
被星级诅咒的爱人：
受欢迎程度的信息在在线约会中的作用
Star-Cursed Lovers: Role of Popularity Information in Online Dating
作者：Behnaz Bojd, Hema Yoganarasimhan
Marketing Science, Published Online: 12 Nov 2021, https://doi.org/10.1287/mksc.2021.1301
Abstract:
We examine the effect of user’s popularity information on their demand in a mobile dating platform. Knowing that a potential partner is popular can increase their appeal. However, popular people may be less likely to reciprocate. Hence, users may strategically shade down or lower their revealed preferences for popular people to avoid rejection. In our setting, users play a game where they rank-order members of the opposite sex and are then matched based on a stable matching algorithm. Users can message and chat with their matches after the game. We quantify the causal effect of a user’s popularity (star rating) on the rankings received during the game and the likelihood of receiving messages after the game. To overcome the endogeneity between a user’s star rating and her unobserved attractiveness, we employ nonlinear fixed-effects models. We find that popular users receive worse rankings during the game, but receive more messages after the game. We link the heterogeneity across outcomes to the perceived severity of rejection concerns and provide support for the strategic shading hypothesis. We find that popularity information can lead to strategic behavior even in centralized matching markets if users have postmatch rejection concerns.
摘要：
我们在一个移动约会平台上考察了用户受欢迎程度的信息对其需求的影响。知道一个潜在对象很受欢迎可以增加他们的吸引力。然而，受欢迎的人做出回应的可能性不大。因此，用户可能会有策略地隐藏起来或降低他们对受欢迎人群所展现出来的偏好，以避免自己被拒绝。在我们的设置中，让用户玩一个游戏，他们对异性成员进行排名，然后根据一种稳定的匹配算法进行匹配。游戏结束后，用户可以留言和聊天。我们对用户受欢迎程度（星级）对游戏期间收到的排名以及游戏后收到消息的可能性的因果影响进行了量化分析。为了克服用户的星级与其未被观测到的吸引力之间可能存在的内生性问题，采用了非线性固定效应模型。结果发现，受欢迎的用户在游戏期间的排名较差，但是在游戏结束后会收到更多的消息。我们将结果的异质性与对被排斥担忧的感知严重性联系起来，并支持了战略隐藏假设。我们发现，如果用户对匹配后可能遭受拒绝感到担忧，即使是在集中匹配的市场中，受欢迎程度的信息也会带来策略性的行为。
关键词：受欢迎程度的信息（popularity information），在线评分（online ratings），战略性隐藏（strategic shading），在线约会（online dating），集中匹配的市场（centralized matching markets），双边平台（two-sided platforms）
END
更多内容扫码观看，让营销更有力量！
让营销更有力量！
营销科学家
高雅有品位的营销科学思想、理论前沿动态和精彩案例的分享平台，我们坚持营销的科学性与高品位，拒绝营销的大忽悠与低俗化，推动营销科学理论研究与实践应用，促进经济发展与社会进步。
【免责声明】
1、我们尊重原创，也注重分享。本公众平台原创文章版权归作者和平台共同所有，转载文章其版权归原作者和来源媒体平台所有；
2、本公众平台转载内容包括视频、文章和广告等，仅以信息传播和分享为目的，供感兴趣的读者学习参考之用，未经授权禁止用于商业用途，如无意中侵犯了哪个媒体、公司 、企业或个人等的知识产权，请联系处理；
3、本平台对转载和分享的内容、陈述、观点保持中立，不对所包含内容的真实性、准确性和合法性提供任何明示或暗示的保证，本公众平台将不承担任何责任。
图文编辑：李一鑫 审校：张希贤
欢迎转发到工作群和朋友圈，让更多人了解、学习和思考！