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Do submission devices influence online review ratings differently across different types of platforms? A big data analysis

机译:在不同类型的平台上,提交设备对在线评论评级的影响是否不同?大数据分析

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摘要

Deploying big data analytical techniques to retrieve and analyze a large volume of more than 2.7 million online consumer reviews (OCRs), this work sheds light on how mobile devices used by consumers to post online reviews influence their satisfaction with services. More specifically, we conduct a multi-platform study of TripAdvisor. com and Booking.com OCRs pertaining to hotel services across eight leading tourism destination cities in the American and European continents over the period 2017-2018. By adopting multivariate regression analyses, we show that OCR ratings are positively influenced by the use of mobile devices on Booking.com. The opposite effect is observed on TripAdvisor. These asymmetric effects can be explained in light of different online review policies across the platforms analyzed. Theoretical and managerial contributions and implications for digital platforms, big data analytics, electronic word of mouth, and marketing research are examined.
机译:这项工作采用大数据分析技术来检索和分析超过 270 万条在线消费者评论 (OCR) 的大量内容,揭示了消费者用于发布在线评论的移动设备如何影响他们对服务的满意度。更具体地说,我们对TripAdvisor进行了多平台研究。2017-2018 年期间,与美洲和欧洲大陆八个主要旅游目的地城市的酒店服务相关的 com 和 Booking.com OCR。通过采用多元回归分析,我们发现在 Booking.com 上使用移动设备对OCR评级有正向影响。在TripAdvisor上观察到相反的效果。这些不对称效应可以根据所分析平台的不同在线评论政策来解释。研究了对数字平台、大数据分析、电子口碑和营销研究的理论和管理贡献和影响。

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