Managerial Response to Online Positive Reviews: Helpful or Harmful?

Chaoqun Deng () and T. Ravichandran ()
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Chaoqun Deng: Paul H. Chook Department of Information Systems and Statistics, Zicklin School of Business, Baruch College, City University of New York, New York, New York 10010
T. Ravichandran: Lally School of Management, Rensselaer Polytechnic Institute, Troy, New York 12180

Information Systems Research, 2024, vol. 35, issue 4, 1802-1823

Abstract: Managerial responses to negative reviews could be easily understood as a brand-safeguarding strategy by firms because negative reviews can damage a company’s reputation. However, it is unclear if managers should respond to positive reviews and if so, if such action helps or hurts the firm. We develop a theoretical framework to explicate the mechanisms underlying the effects of managerial responses to positive reviews on user reviewing behaviors in online platforms. We classify positive reviews into four types: one-sided affective reviews, two-sided affective reviews, one-sided instrumental reviews, and two-sided instrumental reviews. We classify managerial responses as tailored and template responses. Using natural language processing and deep learning algorithms, we extract information presented in the texts in the reviews and responses. We theorize and test which kinds of managerial responses to positive reviews are helpful and which of them are harmful. Overall, we find that a tailored response is more appropriate when responding to two-sided instrumental positive reviews and one-sided affective positive reviews, whereas template responses work for one-sided instrumental positive reviews and two-sided affective positive reviews. Not responding would be an effective strategy for mixed positive reviews. We interpret and discuss the theoretical and practical implications of our findings and lay out guidelines for future research.

Keywords: online word of mouth; managerial responses; online positive reviews; natural language processing; deep learning; information value and ambiguity (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orisre:v:35:y:2024:i:4:p:1802-1823

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