The Role of Sentiment Tendency in Affecting Review Helpfulness for Durable Products: Nonlinearity and Complementarity

The online review has become an important pillar in the decision-making process for purchasing experience products, especially durable goods with relatively high prices. Using a rich data set for automobiles, we quantify the sentiment tendency expressed in textual reviews, and empirically examine the nonlinearly inverted U-shaped relationship between customer satisfaction and sentiment tendency. We then investigate the nonlinear influences of review sentiment and depth on helpfulness. Furthermore, we study the relationship between numerical rating and text contents, i.e., sentiment tendency and review depth, in promoting the review helpfulness, and quantitatively identify the complementary effect of sentiment tendency. Our results indicate that both numerical ratings and sentiments expressed in text contents contribute to an increase in review helpfulness. Compared with polarized reviews, the neutral ones better benefit helpfulness and customer satisfaction. We also find that reviews with moderate depth are more helpful. Based on the empirical findings, we discuss several managerial implications for review system designers and consumers in the durable product market.