In the era of electronic word-of-mouth, firms face pressure to respond to online reviews strategically to maintain and enhance their reputation and financial viability. With guidance from service recovery theory and affect theory, we developed 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 employed text-mining techniques such as sentiment analysis and topic modeling to develop a framework that classifies the responses into four categories: acknowledgment, account, action, and affect. We evaluated this framework’s effectiveness on subsequent reviews and hotel revenue. Among the management response characteristics, we found that acknowledgment and action were significantly associated with future review ratings. Furthermore, hotel class moderated the relationships between these characteristics and hotel revenue. This study provides recommendations to firms about how they can manage their resources to manage responses to online consumer reviews toward increased financial performance.
Deng, T., Lee, Y., & Xie, K. (2021). Managers’ Responses to Online Reviews for Improving Firm Performance: A Text Analytics Approach. Communications of the Association for Information Systems, 49, pp-pp. https://doi.org/10.17705/1CAIS.04937
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