Facebook likes and corporate revenue: testing the consistency between attitude and behavior

Abstract

Whether a person’s attitude is predictive or consistent with their behavior is a topic that has generated much research in the literature. The current study attempts to address this research question using a big data approach in a social media advertising context. Both attitude (i.e. clicking the “like” button for a company’s Facebook posts) and behavior (i.e. purchasing products from the company) are measured in a naturalistic setting. The goal is to examine whether Facebook “likes” on companies’ posts are significantly related to those companies’ revenue. The authors estimate panel models by using nearly eight years of data containing the S&P 500 companies’ Facebook activities in conjunction with their financial performance information. The results suggest that the number of Facebook “likes” is positively associated with revenue across the models. The study concludes with specific theoretical and practical implications and limitations.