Autores
John Jianjun Zhu, Yung-Chun Chang, Chih-Hao Ku, Stella Yiyan Li, Chi-Jen Chen
Fecha de publicación
2020/11/28
Origen
Journal of Business Research
Editor
Elsevier
Descripción
This research proposes and tests mechanisms for defining and identifying the critical online consumer reviews that firms could prioritize to optimize their online response strategies, while incorporating the latest artificial intelligence (AI) technology to deal with the overwhelming volume of information. Three sets of analytical tools are introduced: Heuristic Processing, Linguistic Feature Analysis, and Deep Learning-based Natural Language Processing (NLP), to extract review information. Twelve algorithms to classify critical reviews were developed accordingly and empirically tested for their effectiveness. Our econometric analysis of 110,146 online reviews from a chain operation in hospitality industry over seven years identifies six outstanding algorithms. Firm value rating, comment length, valence, and certain consumer emotions, in addition to past comment-response behavior, are found to be superior in predicting …
Citas totales
20212
Artículos de Google Académico
JJ Zhu, YC Chang, CH Ku, SY Li, CJ Chen - Journal of Business Research, 2020