Narrative, visual and numerical intellectual capital disclosure as predictors of earnings per share

Using content analysis and multiple regression this study investigates the predictability of earnings per share as a value relevance measure, of narrative, vi­ sual, and numerical intellectual capital disclosure of the top 30 listed firms in Sri Lanka during a six year period. The findings show that frequency of numerical disclosure is a predictor of earnings per share, and the interaction of numerical and visual types of disclosure associates negatively with earnings per share. The frequency of numerical disclosure predicts both value realization and value relevance. The prediction feature of numerical disclosure is consistent with a resource-based theoretical perspective, suggesting communicating resources and capabilities from intellectual capital translating into financial performance. The lack of predictive ability of the narrative and visual disclosure types tends to support an agenda setting theoretical perspective.