醫療機構接受無線射頻辨識技術（RFID）相關因素之探討

Abstract

While “Ubiquitous Taiwan” project will become the most important Information policy, the adoption of the Radio Frequency Identification (RFID) technology is the way to realize ubiquitous. The statistics show that the Department of Industrial Technology of Ministry of Economic Affairs has increased its R&D subsidies for private enterprises to NTD 67 million in 2005, and is set to further boost these subsidies to over NTD 100 million in 2006. Many hospitals began to adopt RFID technology because the work done by medical staff is onerous. If infirmaries can utilize RFID technology effectively, it will result in improving the accuracy of patient identification and the safety of using medications. The acceptance and use of technology is always an important issue in the MIS academic field. Since Davis proposed the Technology Acceptance Model (TAM in 1989, many scholars continuously modified or enhanced the model with the purpose to better explain why technology is accepted and used. This research intends to use the “Unified Theory of Acceptance and Use of Technology”, UTAUT (Venkatesh et al., 2003）as a foundation and combine the “Value Model”（Cronin et al., 2000）into a theoretic framework to investigate the factors that influence the healthcare organizations adopting RFID. The study first surveyed and reviewed related literature, formulated the research framework, and developed the instrument to measure why medical workers adopting RFID. 150 copies of the instrument were sent to 5 hospitals, a total of 85 copies were returned. Four are eliminated because of invalid responses, 81 copies of the instrument were used in the analysis. The research shows that the main independent variables such as performance expectance, effort expectance, social influence and service value have positive relations to the dependent variable, behavior intention. It also shows that, in the value model, sacrifice doesn’t have a significant effect on service value. Finally, as indicated in moderating variables, different factor levels may have different effects. For example, effort expectance has significant effect on behavior intention, but it is subject to age difference. For those who are from 30 to 50 years-old were expected to have easy- to-use technology.