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.

As customer demands continue to evolve, service quality has become increasingly important for service providers. In response, service providers have become more focused on service design and understanding customer requirements (CRs) to gain a competitive advantage. As a method to investigate the characteristics of CRs, the Kano model is often combined with quality function deployment (QFD) to analyze the CRs and translate them into design requirements (DRs). However, previous studies have overlooked the financial status of service providers, which is also essential for service design. To propose a service design method that can be applied to various service industries, this article proposes an online reviews-driven Kano-QFD method for service design. First, CRs are extracted from online reviews. Second, the Kano model is employed to classify CRs and determine their importance, while considering the financial statuses of the service providers. The QFD model is then used to convert CRs into DRs and an optimization model is constructed based on the importance of DRs, and their correlation with CRs. Moreover, a case study is presented to demonstrate the effectiveness of the proposed method in designing hotel services. Finally, the validity of the proposed method for service design is illustrated by comparing it with previous methods.