Exploring factors affecting mobile commerce adoption in the United States, Korea, and China: The tests of theories, models, and cultural differences

Mobile phones have become a ubiquitous Internet connection device, accessing the Web and doing mobile computing at ever-increasing speeds. Based on the tremendous growth in the number of mobile phone subscribers and the development of mobile Internet technologies, mobile commerce (m-commerce) has emerged as a new business phenomenon. However, while a significant number of studies have investigated the use of electronic commerce (e-commerce), the field of m-commerce has been left virtually unexplored.;This study proposed a research model for predicting and explaining the adoption of m-commerce services and its potential factors. With data from the U.S., Korea, and China, this study compared the effects of factors, verified whether the presented research model was applicable in each country, and finally, proposed an extended model of existing research model for explaining m-commerce services adoption. In addition, this study investigated whether the presented research model varies, whether each factor presented and hypothesized as an important predictor of m-commerce service adoption varies across the countries, and whether cultural factors presented in cross-national studies affect hypothesized predictors, the intention to adopt m-commerce services, and actual use of m-commerce services. With Hofstede's four cultural dimensions, this study adopted lifestyle segments and clusters presented in previous studies as alternative measurement tools to detect cultural differences in three countries.;The results offered valid and solid research models that can be applicable in both transactional and non-transactional m-commerce services adoptions, and particularly, this study extended existing model of technology adoption, and this extended technology acceptance-adoption model (ETAAM) was successfully supported by empirical investigation. In addition, there were differences among countries in suggested models, and this study concluded that by using both individual-level approach (lifestyle clusters) and Hofstede's cultural dimensions, cross-national differences in technology adoption can be explained in more detail and more accurately. Finally, the implications for businesses, limitations of this study, and suggestions for the future studies were discussed at the end of chapter.