Integrated Online Consumer Preference Mining for Product Improvement with Online Reviews

Li Jie (), Lan Qiaoling (), Liu Lu () and Yang Fang ()
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Li Jie: School of Economics and Management, Hebei University of Technology, Tianjin300401, China
Lan Qiaoling: School of Economics and Management, Hebei University of Technology, Tianjin300401, China
Liu Lu: School of Economics and Management, Hebei University of Technology, Tianjin300401, China
Yang Fang: School of Economics and Management, Hebei University of Technology, Tianjin300401, China

Journal of Systems Science and Information, 2018, vol. 7, issue 1, 17-36

Abstract: 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 specific product, to facilitate product and service improvements. This study proposes a systematic research framework for exploring major product and service features that reflect 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 verified by a case study of laptop on the basis of the online reviews from amazon.cn.

Keywords: consumer preference; product improvement; online reviews; meta-analysis (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:jossai:v:7:y:2018:i:1:p:17-36:n:2

DOI: 10.21078/JSSI-2019-017-20

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