Journal article
Trust and tam in online shopping: AN integrated model
MIS quarterly, v 27(1), pp 51-90
01 Mar 2003
Abstract
A separate and distinct interaction with both the actual e-vendor and with its IT Web site interface is at the heart of online shopping. Previous research has established, accordingly, that online purchase intentions are the product of both consumer assessments of the IT itself—specifically its perceived usefulness and ease-of-use (TAM)—and trust in the e-vendor. But these perspectives have been examined independently by IS researchers. Integrating these two perspectives and examining the factors that build online trust in an environment that lacks the typical human interaction that often leads to trust in other circumstances advances our understanding of these constructs and their linkages to behavior.
Our research on experienced repeat online shoppers shows that consumer trust is as important to online commerce as the widely accepted TAM use-antecedents, perceived usefulness and perceived ease of use. Together these variable sets explain a considerable proportion of variance in intended behavior. The study also provides evidence that online trust is built through (1) a belief that the vendor has nothing to gain by cheating, (2) a belief that there are safety mechanisms built into the Web site, and (3) by having a typical interface, (4) one that is, moreover, easy to use.
Metrics
Details
- Title
- Trust and tam in online shopping: AN integrated model
- Creators
- David Gefen - Drexel University, Decision Sciences (and Management Information Systems)Elena Karahanna - Management Information Systems, Department Terry College of Business, University of Georgia, United StatesDetmar W. Straub - Robinson College of Business, Georgia State University, United States
- Publication Details
- MIS quarterly, v 27(1), pp 51-90
- Publisher
- MIS Quarterly
- Number of pages
- 40
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:000181423100004
- Scopus ID
- 2-s2.0-0344096683
- Other Identifier
- 991019168361704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Information Systems
- Information Science & Library Science
- Management