An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry

By Feng-Cheng Tung, Su-Chao Chang, Chi-Min Chou. Int. J. Medical Informatics, 2008

510 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems and Management, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/b0636b3fc162df2de13862bad3c2d9c7d233cbca

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Citations in the corpus

THE TECHNOLOGY ACCEPTANCE MODEL: ITS PAST AND ITS FUTURE IN HEALTH CARE (2009, unknown): “Several studies were set in Taiwan [103,109,110], Hong Kong [32,48,49], the UK [96,104], Australia [102,111], and the mainland US [98,99,106,107] and Hawaii [97].”
Trust in AI and Its Role in the Acceptance of AI Technologies (2022, methodology): “The role of trust was tested in the use of a new information system (Tung et al., 2008) and different online services, such as online games (Wu & Liu, 2007), banking (Suh & Han, 2002), social network sites (Sledgianowski & Kulviwat, 2009), and shopping (Gefen et al., 2003), among others.”
Comparison of the middle-aged and older users' adoption of mobile health services in China (2014, unknown): “[17] F.”
Factors influencing autonomous vehicle adoption: an application of the technology acceptance model and innovation diffusion theory (2020, methodology): “…the ease of use in PCI and PEOU in TAM are repeat constructs and most of the current paper on the integration of TAM and IDT only deal with either of the two constructs (Tung, Chang, and Chou 2008; Poong, Eze, and Talha 2009), this research excludes the ease of use construct from the eight PCIs.”
Understanding the impact of social media usage among organizations (2017, background): “Previous research has investigated trust in various dimensions and found that the greater the trust in a technology, the more likely it is to be adopted in an organization [23,24,45,25].”
Investigating the impacting factors for the healthcare professionals to adopt artificial intelligence-based medical diagnosis support system (AIMDSS) (2018, background): “Another study on the enabling factors for electronic logistics information system acceptance demonstrated that perceived ease of use positively inﬂuences trust in electronic logistics information system (Tung and Chou 2008).”
Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT (2015, unknown): “This construct was positively associated with effort expectancy three times out of four [28,34,35] and with behavioral intention to use the EPR four times out of five [28,33,34,36].”