A longitudinal exploration of the relations between electronic word-of-mouth indicators and firms' profitability: Findings from the banking industry. Issue 6 (December 2016) - Tang, Chuanyi; Mehl, Matthias R.; Eastlick, Mary Ann; He, Wu; Card, Noel A.
Highlights: We employ Automatic Text Analysis to extract valuable information contained in text online reviews. We examine the patterns of the bi-directional relations between eWOM indicators and banks' profitability over time. Both star ratings and expressed anger in eWOM significantly predict firms' future profitability. Star ratings are a consistent predictor of firms' future profitability over time and expressed anger explains additional variance of firms' future profitablility beyond the star ratings. Both star ratings and verbalized positive feelings reflect firms' past financial performance. Abstract: Prior research on electronic word-of-mouth (eWOM) has focused on the predictive utility of star ratings. Extending these studies conceptually and methodologically, this paper employed Automatic Text Analysis to investigate the predictive utility of evaluative textual information contained in online reviews. Based on a real-world dataset that matched eWOM with annual financial performance of 68 banks over an eight-year period, this study tested patterns of the bi-directional relations between eWOM indicators and banks' profitability over time. Results showed that both star ratings and consumers' verbalized emotions in eWOM significantly predicted increases in firms' future profitability, which is measured by Return on Assets. Star ratings emerged as a consistent predictor, and their effects lasted for at least two years. Expressed anger predicted lower profitability in the following year and explained additional variance beyond the star ratings. Finally, higher firm profitability was prospectively related to higher star ratings and more verbalized positive feelings in next year's eWOM.