Do I Trust You Online, and If So, Will I Buy? An Empirical Study of Two Trust-Building Strategies
Abstract
This research investigates the effectiveness of various trust-building strategies to influence actual buying behavior in online shopping environments, particularly for first-time visitors to an Internet store that does not have an established reputation. Drawing from the literature on trust, we developed a model of how trust-building strategies could affect trust and the consequences of trust. We investigated two trust-building strategies: portal association (based on reputation categorization and trust transference) and satisfied customer endorsements (based on unit grouping, reputation categorization, and trust transference). A series of two studies was conducted at a large public university in Hong Kong. The first study employed a laboratory experiment to test the model in an online bookstore environment, using a real task that involves actual book purchases. Of the two strategies investigated, satisfied customer endorsement by similar peers, but not portal association, was found to increase consumers' trusting beliefs about the store. This, in turn, positively influenced consumers' attitudes toward the store and their willingness to buy from the store, which ultimately led to actual buying behaviors. To gather further insights on the two Web strategies investigated, a second study was conducted using a questionnaire survey approach. Overall, the findings corroborated those in the first study. Specifically, it shows that endorsements by similar (local, nonforeign) peers, but not by dissimilar (foreign) peers, were effective means of developing trust among first-time visitors to online stores.
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A first visitor to an online store largely forms their first impression from the website user interface, and cognitive-based trust can be affected by the website interface.
“A first visitor to an online store largely form their first impression from the website user interface, and hence cognitive-based trust can be affected by the website interface (Lim et al., 2006).”
From Individual level culture influence on online consumer iTrust aspects towards purchase intention across cultures: A S-O-R model (2015) · cites this paper as Lim et al., 2006
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“With the growth of e-commerce as a market and economic force over the past two decades (Lim et al. 2006), the concept of trust has inevitably attracted many researchers’ attention, causing to have been studying it using some models from various disciplines.”
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- Authors
- Lim, K. H., Sia, C. L., Lee, M. K. O., & Benbasat, I.
- Affiliations
- City University of Hong Kong (HK)
- University of British Columbia (CA)
- Venue
- Journal of Management Information Systems
- Publisher
- Informa UK Limited
- Published
- 2006-10
- Volume
- 23
- Issue
- 2
- Pages
- 233-266
- ISSN
- 0742-1222 (ISSN-L)
- 1557-928X
- OpenAlex
- W2083365829
- Cited by
- 505
- References
- 63
- Citations by year
- 2026: 13 · 2025: 20 · 2024: 26 · 2023: 27 · 2022: 28 · 2021: 20 · 2020: 21 · 2019: 26 · 2018: 37 · 2017: 30 · 2016: 20 · 2015: 33 · 2014: 32 · 2013: 34 · 2012: 30
- FWCI
- 40.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Management Information Systems (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Social Sciences › Sociology and Political Science › Digital Marketing and Social Media
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- online trust, trust-building strategies, online shopping, first-time visitors, online store, peer similarity, reputation, purchase intention, online bookstores
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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