Dynamic effects of user- and marketer-generated content on consumer purchase behavior: Modeling the hierarchical structure of social media websites

作者:

Highlights:

• We develop a score covering position effect of social media contents.

• The score helps analyzing the effects of contents on individuals and organizations.

• We apply our score to investigate economic effects of Facebook fanpage contents.

• We show that our score improves econometric models for predicting economic effects.

• We show that a retailer's conversion rate depends on its social media contents.

摘要

User- and marketer-generated content items on social media platforms are supposed to have an impact on economic target variables, such as variables measuring consumers' purchase behavior. The position of each content item – and thus the impact on economic variables – changes with newly appearing items. We propose a hierarchy score to capture the dynamics of the content items on social media platforms. In order to mimic the reduced visibility of earlier content items, our hierarchy score computes the position of content items based on the number of text line equivalents of content items above a particular item. Employing the proposed hierarchy score in a dynamic regression framework for data of a large online store yields improved estimates and predictions compared to a variety of other models.

论文关键词:Social media,User-generated content,Marketer-generated content,Content hierarchy,Dynamic regression

论文评审过程:Received 15 March 2018, Revised 8 July 2018, Accepted 10 July 2018, Available online 17 July 2018, Version of Record 11 August 2018.

论文官网地址:https://doi.org/10.1016/j.dss.2018.07.001