{"title":"What Drives Mobile Health Care? An Empirical Evaluation of Technology Acceptance","authors":"Jen-Her Wu, Shu-Chin Wang, Li-Min Lin","doi":"10.1109/HICSS.2005.689","DOIUrl":null,"url":null,"abstract":"The proliferation of mobile communication and computing technologies in supporting highly specialized tasks and services in health care has made it increasingly important to understand the factors essential to technology acceptance by health care professionals. This paper presents a conceptual model to examine what determines medical professionals’ acceptance of mobile healthcare systems. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to test the reliability and validity of the measurement model. The results indicate that compatibility and computer self-efficacy (CSE) have significant direct effect on behavioral intent, whereas technical support and training have strong indirect impact on behavioral intent through the mediator of CSE. Among these, the compatibility has the most significant contribution to behavioral intent. Yet, the hypothesis for management support effect on behavioral intention to use is not supported.","PeriodicalId":355838,"journal":{"name":"Proceedings of the 38th Annual Hawaii International Conference on System Sciences","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"43","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 38th Annual Hawaii International Conference on System Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HICSS.2005.689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 43
Abstract
The proliferation of mobile communication and computing technologies in supporting highly specialized tasks and services in health care has made it increasingly important to understand the factors essential to technology acceptance by health care professionals. This paper presents a conceptual model to examine what determines medical professionals’ acceptance of mobile healthcare systems. The structural equation modeling technique was used to evaluate the causal model and confirmatory factor analysis was performed to test the reliability and validity of the measurement model. The results indicate that compatibility and computer self-efficacy (CSE) have significant direct effect on behavioral intent, whereas technical support and training have strong indirect impact on behavioral intent through the mediator of CSE. Among these, the compatibility has the most significant contribution to behavioral intent. Yet, the hypothesis for management support effect on behavioral intention to use is not supported.