Paper Title
Sustainable Kpop Business Model Development Through The Integration of Qualitative Research and Data Analytics

Abstract
The development of information and communication technologies (ICTs) offers an environment which cultural content and trends can be easily and rapidly shared. Korean modern cultural content, which is called Korean Wave, has been spread and consumed in countries where share cultural similarities and other continents which are located far from Korea. In Korean Wave, K-pop has been contributing to promote the national identity of South Korea and able to generate enormous profits for K-pop companies. To develop a sustainable business model for K-pop, identifying a successful mechanism of K-pop is important. Especially, examining and knowing reasons of consuming K-pop by consumers in different locations and cultural backgrounds will be critical areas for maintaining the current popularity of K-pop and promoting in other countries where K-pop has not been able to penetrate. Therefore, this research would like to investigate using qualitative research approach how the different countries express their interests in K-pop in different ways. In particular, based on web traffic data which represents users’ information search behaviors, we would like to analyze the level of interest rate of K-pop in different countries and related keywords. By doing so, we would like to identify the characteristics of each country on K-pop, the differences between countries, and the reasons of the occurrence of the differences. This research will be able to offer a theoretical implication that the success mechanism of K-pop is different based on the conditions of each country and in practice, this research will be able to contribute to the development of sustainable K-pop business models. Finally, in a policy level, this research will be able to offer critical implications for developing policies to promoting and spreading of cultural content of South Korea. Keywords- KPOP, Korean Culture, Information Search Behavior, Web Search Traffic, Google Trend, Qualitative Research, Data Analysis, Bigdata