Drawing on multi-dimensionality of authenticity, this study focuses on the role of two distinct authenticities: nominal and expressive. We propose that the type of authenticity in a review will vary based on the reviews’ lexical density (word level) and breadth (sentence level). Using the decision tree induction approach, the main and interaction effects of the dimensions and forms of authenticity are examined for their effect on review helpfulness. The preliminary analysis of 470 reviews demonstrate that the lexical density form of expressive authenticity is a predominant predictor of online review helpfulness. Additionally, the effects of expressive authenticity depth, nominal authenticity breadth and depth on online review helpfulness, vary based on the expressive breadth. The decision tree induction approach provides new theoretical insights that extends the frontiers of authenticity and practical implications on online review helpfulness.
Guduru, Rakesh, Francis Andoh-Baidoo, Emmanuel Ayaburi, and Jerald Hughes. 2023. “How Does the Authenticity in an Online Review Affect Its Helpfulness? A Decision Tree Induction Theory Development Approach.” In Proceedings of the 56th Hawaii International Conference on System Sciences. https://hdl.handle.net/10125/103112.
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Proceedings of the 56th Hawaii International Conference on System Sciences