Cross-Cultural Difference in Product Preference in Consumer Review-Based Text Mining Methods: a Case Study on Smart Band

Abstract

The aim of this study is to compare the cross-cultural differences in product preference among users from different countries, taking Mi band 3 as a case study. With the development of global market, more and more products and services are sold across the globe. Users from different cultures have different behaviors, cognitive styles, and value systems. Therefore, product should be designed to meet the needs and preferences of users from different cultural groups. Compared to traditional research method such as survey questionnaire or interview that requires variety of foreigners as participants, text mining methods from online reviews save much more cost and time. We collected review data from the following three websites: Naver of South Korea, Jingdong of China, and Amazon of the United States. Text mining methods including opinion mining, sentiment analysis, and semantic network analysis were performed. Firstly, product aspects were extracted from reviews according to word frequency. This indicates how much users are paying attention to different aspects of the product. Fine-grained sentiment analysis was conducted to find out customer satisfaction with different product aspects. Then, the words most associated with each product aspect were listed. Cluster analysis was conducted and the topic of each cluster was summarized. Lastly, cross-cultural difference among three countries from the results was observed and discussed. Though there exist similar issues in product preferences among South Korea, China, and the United States, cross-cultural differences about Mi band 3 are shown in many product aspects. The outcome can suggest implications for making strategies in product internationalization and product localization for the global marketing of smart band.