This study conducted an empirical analysis of the factors that affect the adoption rate of ERP/SF technology, an information system operated by the company via UTAUTmodel. It also analyzed howthese factors affected intent of usage and information technology. The study found that in terms of behavioral intention to use ERP/SF technology, effort expectancy, social influence, hedonic motivation and price value were found to have positive influence(+) on the intention to use ERP/SF technology, However, performance expectancy and facilitating conditions had no significant impact on the use of ERP/SF technology. In addition, in terms of IT information technology, performance expectancy, social influence, facilitating conditions and price value were found to have positive(+) influence on IT, but effort expectancy and hedonicmotivationwere found to have no significant impact on IT. The limitations of this study and the future direction of research based on it are as follows. First, the start of the Korea Smart Factory began with a public-private smart factory promotion teamestablished in June 2015, and achieved quantitative growth over the past few years. However, because its qualitative growth is only basic, it is believed that it will be necessary to develop standardmanuals and develop compatiblemodules thatmeet the characteristics of companies for qualitative growth in the future. Second, with the need for additional potential factors considering the current speed of technology development and business environment, there should be more independent variables that affect the use of ERP/SF technology and IT in addition to the basic variables of UTAUT. Therefore, it is necessary to reorganize and develop researchmodels in consideration of more data research and the reality of businesses in the future. Third, in order to obtain objective and generalized research results, surveys and research should be conducted on a nationwide scale of probability samples and according to each level of smart factory. However, it is not easy to obtain statistical figures in a standardized way because the limits of the questionnaire and the environment facing the company are all different. Therefore, with the introduction of statistical techniques that enhance the objectivity of research by collecting more samples in the future, it is expected that not only large companies but also small andmedium-sized companies will be able tomaximizemarket standards and industrial linkage efficiency. Fourth, it seems necessary to develop an integrated model for the entire process from order to shipment to foster the mind of manufacturing innovation for companies in the future and to apply smart factory technology using the system. Fifth, the promotion of smart factories is expected to reduce the number of simple labor force and increase the number of people with technical skills. Therefore, it requires government's measures to cope with these changes in the labor market and a smart factory construction solution for the post-pandemic periods to prepare for the unexpected business environment.