An increasing number of people use social media to share their consumption experiences. Publicly available online reviews have become a significant source of information, which manufacturers use to better understand customer needs and preferences. To facilitate product improvement, this study first considers the inconsistencies between the numerical product ratings and the textual product reviews to establish the inconsistent ordered choice model (IOCM) for measuring customer preferences with regard to product features. The IOCM model effectively reduces the negative impact of inconsistent reviews on the quality of the customer preference measurement model. On the basis of customer preferences obtained from the IOCM model, we then develop a sentiment-based importance–performance analysis (SIPA) model to analyze the categorization of product features for guiding product development. Compared with the original IPA model, the proposed SIPA model in this paper introduces sentiment-importance into the IPA model that makes the product improvement more adaptive to customer preferences. Finally, we empirically evaluate the effectiveness of our proposed IOCM model and illustrate the utility of our proposed SIPA model.

中文翻译：

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以评论为导向的客户偏好评估模型，用于产品改进：基于情感的重要性-绩效分析

越来越多的人使用社交媒体分享他们的消费经验。公开可用的在线评论已成为重要的信息来源，制造商可以使用这些信息来更好地了解客户的需求和偏好。为了促进产品改进，本研究首先考虑了产品的数字额定值与文本产品评论之间的不一致之处，以建立不一致的订购选择模型（IOCM），以测量客户对产品功能的偏好。IOCM模型有效地减少了不一致的评论对客户偏好评估模型质量的负面影响。根据从IOCM模型获得的客户偏好，然后，我们开发一种基于情感的重要性－性能分析（SIPA）模型，以分析产品功能的分类以指导产品开发。与原始IPA模型相比，本文提出的SIPA模型在IPA模型中引入了情感重要性，从而使产品改进更加适应客户的偏好。最后，我们根据经验评估了我们提出的IOCM模型的有效性，并说明了我们提出的SIPA模型的实用性。