We study the affinity between managers' responses and customer reviews and explore its influence on review convergence, customer ratings, and prices. While previous research has explored the influence of product reviews on price and reputation, little attention has been given to the effectiveness of managers' responses and their impact on product price and rating. This study fills this gap by examining managers' responses and their correlation with product review convergence/divergence. Additionally, we investigate whether managers respond similarly to their peers and whether their responses are tailored to specific product review issues or exhibit a general similarity to their past responses. We develop a deep learning framework to understand semantic textual information in managers' responses and analyze the semantic affinity score. We investigate the dynamic relationships among the affinity of managers' responses and product reviews, review convergence, product reputation and price with the Panel Vector Autoregression model with a travel dataset from TripAdvisor.com.

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