移动互联网情境下消费者点评的行为模式与激励机制—基于大数据与计量模型的实证研究

Mobile Internet is not just reproduction of traditional Internet on the terminals like mobile phone, but disruptive technology and business model. So consumer behavior inevitably would exhibit some new patterns. Based on the research stream of consumer’s behavior in social media (including online review), this project explores not only rating valence, content features and emotional expression, but also underlying mechanism why they behave this way. Some new theoretical perspectives, such as temporal contiguity effect and circumplex model of emotions, are introduced to help with the research. And more importantly, they are all on the basis of unique characteristics of Mobile Internet comparing to traditional desktop environment. This project refers to econometric modeling and big data approach used in IS research. The social media contain rich observational data about consumer review-writing behavior, due to which this project could make rigor empirical results by econometric modeling and analysis. This research helps both electronic commerce and social media website understand the systematic difference of consumer behavior between mobile and traditional Internet. Based on the research project, they could find proper ways to manage online review, improve the function of review system and mobile application, which could enhance consumer satisfaction and stickiness.

移动互联网并非传统互联网在手机等移动终端上简单复制，而是颠覆性的新技术与应用情境，那么消费者在线行为必然存在新的模式及规律。本项目依据最新的消费者点评及社会媒体用户行为研究流派，结合时间临近效应、情绪环状模型等理论视角，基于移动互联网技术特征以及与传统桌面情境的比较视角，深入探索在移动情境下消费者点评时的星级评价、内容特征与情绪表达等行为模式及规律，以及影响点评行为持续性/活跃度的激励因素及底层机制。本项目参考大样本客观数据与计量模型构建的IS研究范式，基于社会媒体大数据蕴含的客观、丰富的点评行为信息，以文本挖掘工具辅助计算部分定性指标，构建适合上述具体问题的动态计量模型及稳健性分析，进而获得可靠的实证结论。研究成果有助于电子商务或社会媒体网站理解消费者点评行为在移动与桌面情境的系统化差异，从而科学地应用及管理在线评论、改善评价系统及移动端应用功能设计，进而增进网站黏性及消费者满意度。