Strategies and conditions for crafting managerial responses to online reviews

Abstract

The present study investigates how managerial responses to online reviews can help managers maintain relationships with past and future customers, exploring the question through the lens of the uncertainty reduction theory and the rapport management model. The present work crawled 446,663 customer reviews and 96,633 tour managerial responses on Ctrip.com using Python. Through randomly selecting 1000 responses, Study 1 manually identified nine managerial response strategies to customer online reviews. The Bidirectional Encoder Representations from Transformers (BERT) model was then adopted to automatically label the strategies used in all of the managerial responses. Employing negative binomial regression models, Study 2 then examined the interactions between attributes of customer reviews and managerial responses as a method for estimating helpfulness votes. The results indicate that excessively lengthy, highly templated, and unfocused managerial responses to customer reviews can dampen the relationship between customers’ information processing and their perception of the helpfulness of online reviews.