201. Modelling consumer satisfaction based on online reviews using the improved Kano model from the perspective of risk attitude and aspiration
- Author
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Zeshui Xu, Chenxi Zhang, Yiqi Hu, Meng Zhao, and Hao Liu
- Subjects
aspiration ,HF5001-6182 ,Computer science ,kano ,05 social sciences ,Perspective (graphical) ,Economic growth, development, planning ,02 engineering and technology ,Consumer satisfaction ,Kano model ,0502 economics and business ,0202 electrical engineering, electronic engineering, information engineering ,risk attitude ,HD72-88 ,050211 marketing ,020201 artificial intelligence & image processing ,Business ,Marketing ,online reviews ,satisfaction function ,Finance - Abstract
With the development of e-commerce, an increasing number of online reviews can serve as a promising data source for enterprises to improve online products. This paper proposes a method for modelling consumer satisfaction based on online reviews using the improved Kano model from the perspective of risk attitude and aspiration. Firstly, the attributes concerned by consumers are extracted from online reviews, and sentiment analysis of the extracted attributes is carried out using Standford CoreNLP. Secondly, to identify the types of product attributes, an improved Kano model is proposed based on the effects of product attributes on consumer total utility. On this basis, different attribute types are illustrated from the perspective of risk attitude. Then, the consumer aspirations are mined based on the risk attitudes of different attributes and the attribute impact on consumer satisfaction. According to the risk attitudes and aspirations of different attributes, the quantified satisfaction functions are constructed to provide more objective and accurate improvement suggestions. Finally, the proposed method is applied to the hotel service improvement to illustrate the effectiveness. First published online 13 April 2021
- Published
- 2021