HARNESSING THE PREDICTIVE VALUE OF ONLINE WORD-OF-MOUTH FOR IDENTIFYING MARKET SUCCESS OF NEW AUTOMOBILES: INPUT VERSUS OUTPUT WORD-OF-MOUTH PERSPECTIVES

The automotive industry evaluates various success factors to achieve competitive advantage in selling products. Existing studies have predicted the of newly launched automobiles based on an economic perspective. However, such as dynamic changes consumer preferences and emergence numerous automobile brands pose difficulty understanding product quality. This study proposes a method market using text mining techniques online user opinions for cars. By analyzing customer experiences expectations through their opinions, we can anticipate demand more easily. proposed is reviews from portal automobiles. Based literature review, this presents framework input versus output word-of-mouth (WOM). It also integrates existing derives functional categories relevant keywords. analysis identifies differences consumer-interest that lead short-term or normal results sales. In addition, it confirms elements WOM produces varying depending timing these are employed relation launch (i.e., before after product’s launch). revealed which dimensions characteristics important identifying sales volume share specific types models. provide theoretical predicting industry. practical insights into classification information forecasts paper provides empirical about how analyzed differently predictive power forecasting