Are the Drivers and Role of Online Trust the Same for All Web Sites and Consumers? A Large-Scale Exploratory Empirical Study

By Y. Bart, Venkatesh Shankar, Fareena Sultan, Glen L. Urban. 2005

1,208 citations recorded by the source corpus.

Subfields: Information Systems and Management, Organizational Behavior and Human Resource Management, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/23987f45c20a05fc2aed8502ad4cad66a06b4070

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Citations in the corpus

How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust (2010, background): “As customers expect that any website should be free from errors (Bart et al., 2005), they are likely to trust websites that contain accurate, current, and complete information (Kim, Song, Braynoy, & Rao, 2005) and those that adhere to the rules of correct spelling, grammar, and syntax (Koehn, 2003).”
Examining Trust in Information Technology Artifacts: The Effects of System Quality and Culture (2008, background): “com brand in the experiment may have increased reported levels of trust due to its high brand familiarity [4].”
Achieving customer value from electronic channels through identity commitment, calculative commitment, and trust in technology (2007, background): “A study by Bart, Shankar, Sultan, and Urban (2005) supports this explanation.”
When good conflict gets better and bad conflict becomes worse: the role of social capital in the conflict–innovation relationship (2009, background): “…Moorman et al. 1992; Morgan and Hunt 1994), individual persons (Bstieler 2006; Dwyer et al. 1987; Moorman et al. 1992), or a hybrid of the two (Bart et al. 2005). how the intra-organizational social context—as represented by the dimensions of social interaction and trust between functional…”
Online Trust: State of the Art, New Frontiers, and Research Potential (2009, background): “Bart et al. (2005) furthered extant research and found that trust is a mediating construct between antecedents such as website and consumer characteristics and consequences such as behavioral intent.”
Discovering Unobserved Heterogeneity in Structural Equation Models to Avert Validity Threats (2013, background): “…applications, especially in the marketing, econometrics, and sociology literatures, have utilized finite mixture models to uncover unobserved heterogeneity, thereby improving theoretical and practical implications (e.g., Bart et al. 2005; DeSarbo et al. 2006; Reinecke 2006; Tueller and Lubke 2010).”
The Relationship among Product Risk, Perceived Satisfaction and Purchase Intentions for Online Shopping (2020, background): “Besides, for Bart et al. (2005) these products are well understood and usually entail less information-searching by consumers, resulting in a lower level of perceived financial risk.”
Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping (2007, background): “The main differences are (Bart et al., 2005; Gefen and Straub, 2003; Jarvenpaa et al., 2000; Roy et al., 2001; Wang and Emurian, 2005; Yoon, 2002): The parties involved may interact across different times and locations: rules and regulations may vary across these zones.”
Online Peer and Editorial Recommendations, Trust, and Choice in Virtual Markets (2005, background): “Most importantly, online trust may affect consumers’ willingness to make a purchase (Bart, Shankar, Urban, & Sultan, 2004).”