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

• Published in: Decision Support Systems Vol. 113; pp. 43 - 55
• Main Authors: Scholz, Michael, Schnurbus, Joachim, Haupt, Harry, Dorner, Verena, Landherr, Andrea, Probst, Florian
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.09.2018; Elsevier Sequoia S.A
• Subjects: Consumer behavior; Content hierarchy; Digital media; Dynamic regression; Hierarchies; Impact analysis; Marketer-generated content; Mathematical models; Position measurement; Social media; Social networks; Structural hierarchy; Studies; User behavior; User generated content; Visibility; Websites; Marketer-generated content; User-generated content; Dynamic regression; Content hierarchy; Social media
• ISSN: 0167-9236; 1873-5797
• DOI: 10.1016/j.dss.2018.07.001

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. •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.