이요인 이론 기반 텍스트 마이닝을 통한 한·중 스마트홈 앱 서비스 사용자 평가 차이에 대한 연구

A Study on the Evaluation Differences of Korean and Chinese Users in Smart Home App Services through Text Mining based on the Two-Factor Theory: Focus on Trustness

With the advent of the fourth industrial revolution, technologies such as the Internet of Things, artificial intelligence and cloud computing are developing rapidly, and smart homes enabled by these technologies are rapidly gaining popularity. To gain a competitive advantage in the global market, companies must understand the differences in consumer needs in different countries and cultures and develop corresponding business strategies. Therefore, this study conducts a comparative analysis of consumer reviews of smart homes in South Korea and China. This study collected online reviews of SmartThings, ThinQ, Msmarthom, and MiHome, the four most commonly used smart home apps in Korea and China. The collected review data is divided into satisfied reviews and dissatisfied reviews according to the ratings, and topics are extracted for each review dataset using LDA topic modeling. Next, the extracted topics are classified according to five evaluation factors of Perceived Usefulness, Reachability, Interoperability,Trustness, and Product Brand proposed by previous studies. Then, by comparing the importance of each evaluation factor in the two datasets of satisfaction and dissatisfaction, we find out the factors that affect consumer satisfaction and dissatisfaction, and compare the differences between users in Korea and China. We found Trustness and Reachability are very important factors. Finally, through language network analysis, the relationship between dissatisfied factors is analyzed from a more microscopic level, and improvement plans are proposed to the companies according to the analysis results.