Inexperience and experience with online stores: the importance of TAM and trust
Abstract
An e-vendor's website inseparably embodies an interaction with the vendor and an interaction with the IT website interface. Accordingly, research has shown two sets of unrelated usage antecedents by customers: (1) customer trust in the e-vendor and (2) customer assessments of the IT itself, specifically the perceived usefulness and perceived ease-of-use of the website as depicted in the technology acceptance model (TAM). Research suggests, however, that the degree and impact of trust, perceived usefulness, and perceived ease of use change with experience. Using existing, validated scales, this study describes a free-simulation experiment that compares the degree and relative importance of customer trust in an e-vendor vis-a-vis TAM constructs of the website, between potential (i.e., new) customers and repeat (i.e., experienced) ones. The study found that repeat customers trusted the e-vendor more, perceived the website to be more useful and easier to use, and were more inclined to purchase from it. The data also show that while repeat customers' purchase intentions were influenced by both their trust in the e-vendor and their perception that the website was useful, potential customers were not influenced by perceived usefulness, but only by their trust in the e-vendor. Implications of this apparent trust-barrier and guidelines for practice are discussed.
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Disposition to trust is positively correlated with trustworthiness dimensions in the online environment.
“Previously, several studies subjected the disposition to trust to the analysis in the online environment and found a positive correlation between it and trustworthiness dimensions (Gefen et al., 2003; Teo and Liu, 2007; Kim et al., 2008; Lu et al., 2010; Hallikainen and Laukkanen, 2018).”
From How Culture and Trustworthiness Interact in Different E-Commerce Contexts: A Comparative Analysis of Consumers' Intention to Purchase on Platforms of Different Origins (2021) · cites this paper as Gefen et al., 2003
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- Authors
- Gefen, D., Karahanna, E., & Straub, D. W.
- Affiliations
- Drexel University (US)
- University of Georgia (US)
- Georgia State University (US)
- Venue
- IEEE Transactions on Engineering Management
- Published
- 2003-08
- Volume
- 50
- Issue
- 3
- Pages
- 307-321
- ISSN
- 0018-9391 (ISSN-L)
- 1558-0040
- OpenAlex
- W2151845630
- Cited by
- 965
- References
- 90
- Citations by year
- 2026: 29 · 2025: 40 · 2024: 39 · 2023: 47 · 2022: 41 · 2021: 68 · 2020: 35 · 2019: 42 · 2018: 46 · 2017: 39 · 2016: 40 · 2015: 49 · 2014: 63 · 2013: 50 · 2012: 62
- FWCI
- 36.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Engineering Management (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Customer Service Quality and Loyalty
- Social Sciences › Business, Management and Accounting › Marketing › Consumer Behavior and Marketing Influence
- Keywords
- online store, e-commerce, consumer trust, technology acceptance model, perceived usefulness, perceived ease of use, customer experience, repeat customers, new customers, purchase intention
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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