Integrated Online Consumer Preference Mining for Product Improvement with Online Reviews

摘要

Exploring consumer preferences for a product is essential for the enterprise in product improvement. Many studies have been conducted in consumer preference. However, few studies have concentrated on evaluating the product and service characteristics of a speci?c product, to facilitate product and service improvements. This study proposes a systematic research framework for exploring major product and service features that re?ect consumer preferences based on the online reviews. By creatively integrating quantitative studies of multiple linear regression and meta-analysis,this study expects to generate a feature-based preference importance ranking. Furthermore, by adopting an importance-satisfaction analysis, we can draw a matrix that is valuable in product improvement.Coupled with the preference rankings, implications for competitive strategies that facilitate product improvement can be drawn. The effectiveness of this methodology is veri?ed by a case study of laptop on the basis of the online reviews from amazon.cn.