The utilization of e‐government services: citizen trust, innovation and acceptance factors *

By Lemuria D. Carter, France Bélanger. Information Systems Journal, 2005

2,371 citations recorded by the source corpus.

Subfields: Information Systems and Management, Political Science and International Relations, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/0a954386b36717010e3b07391da43916afa72ad1

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Citations in the corpus

Impact of Trust and Privacy Concerns on Technology Acceptance in Healthcare: An Indian Perspective (2020, positive): “Studies have supported trust as a vital construct for predicting acceptance of technology [18]; [42]; [89]; [91].”
Trust and Electronic Government Success: An Empirical Study (2008, background): “Hence, there are two dimensions of citizen’s trusting beliefs toward an e-government Web site—trust in government and trust in technology [11, 65].”
Expanding the Technology Acceptance Model with the Inclusion of Trust, Social Influence, and Health Valuation to Determine the Predictors of German Users’ Willingness to Continue using a Fitness App: A Structural Equation Modeling Approach (2018, background): “…continuance intention, supporting findings of various studies into the impact of the two constructs on the adoption of various forms of technology (e.g. Carter & Belanger, 2005; Chau & Lai, 2003; Gefen et al., 2003; Kwon & Wen, 2010; Wu & Wang, 2005) and, specifically, on people ’ s inclination to…”
Determinants of end-user acceptance of biometrics: Integrating the "Big 3" of technology acceptance with privacy context (2013, background): “Compatibility has also been shown to contribute significantly to the accurate prediction of acceptance intent [9].”
Augmenting the Technology Acceptance Model with Trust: Commercial Drivers’ Attitudes towards Monitoring and Feedback (2012, background): “In the context of e-commerce and e-government, it has been shown that trust in the e-vendor can influence intentions to transact on a website (Carter & Bélanger, 2005; Pavlou, 2003).”
Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM) (2020, background): “These models have been verified multiple times to determine their effectiveness for many information technology-based applications [26].”
Managing Citizens' Uncertainty in E-Government Services: The Mediating and Moderating Roles of Transparency and Trust (2016, background): “2011)—have been used to examine factors affecting citizens’ adoption and use of a variety of e-government services, such as government websites (Barnes and Vidgen 2004), electronic tax filing (Carter and Belanger 2005), electronic voting systems (Yao and Murphy 2007), and general electronic public s”
Extending the two‐stage information systems continuance model: incorporating UTAUT predictors and the role of context (2011, background): “Furthermore, based on prior relevant research (Carter & Bélanger, 2005; Pavlou & Fygenson, 2006), post-usage trust will have a positive inﬂuence on continuance intention, in addition to its indirect effect via post-usage attitude.”
The imperative of influencing citizen attitude toward e-government adoption and use (2015, methodology): “This pressing problem needs urgent research attention since the success of e-government is highly dependent upon citizens’ adoption and use of e-government services (Carter & Bélanger, 2005; Ozkan & Kanat, 2011; Panagiotopoulos et al., 2012).”
Extending the Technology Acceptance Model to assess automation (2011, background): “Trust has also been considered as a direct determinant of BI, accounting for substantial variation in user adoption of e-government (Carter and Bélanger 2005).”
Investigating the Importance of Trust on Adopting an Autonomous Vehicle (2015, background): “Previous studies have conﬁrmed that trust is a major construct for predicting the adoption of automation (Carter & Bélanger, 2005; Gefen et al., 2003; Lee & Moray, 1992, 1994; Lee & See, 2004; Parasuraman et al., 2008; Pavlou, 2003).”