Managers’ Responses to Online Reviews for Improving Firm Performance: A Text Analytics Approach

Abstract

In the era of electronic word-of-mouth, firms are under the pressure to respond to online reviews strategically to maintain and enhance the reputation and financial viability. Guided by service recovery theory and affect theory, this study develops a framework that classifies management responses to seek actionable opportunities to improve firm performance. Using 37,896 managerial responses to online reviews for 390 hotels in three U.S cities, we employ text mining techniques such as sentiment analysis and topic modeling to develop an “AAAA” framework that classifies the responses into four categories: Acknowledgment, Account, Action, and Affect. We evaluate the effectiveness of this framework on subsequent reviews and hotel revenue. Among the management response characteristics, we find that Acknowledgment and Action are significantly associated with future review ratings. The relationships between these characteristics and hotel revenue can be further moderated by hotel class. This study provides implications on how to effectively utilize firm resources to manage responses to online consumer reviews toward increased financial performance.

Keywords: Managerial responses, Text mining, Financial performance, Response framework