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Cited by 165

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Critical design factors for successful e-commerce systems

Kim, Jinwoo, Lee, Jungwon·2002·Behaviour & Information Technology

Abstract

The primary goal of this paper is to identify critical design factors that have substantial effects on the performance of e-commerce systems. This paper presents a theoretical model that examines the relationships among detailed design factors, perceived quality level and final performance of e-commerce systems. Two consecutive empirical studies were conducted to verify the theoretical model. Results from these studies reveal that the information phase among four transaction phases was the most influential in the final performance of e-commerce systems. Among the myriad design factors related to the information phase, product-related information, depth and variety of the system structure, variety of list view for products, consistency of product and background presentation, and variety of presentation for product information were all found to be closely related to the perceived quality level. This paper ends with the theoretical and practical implications of the study results.

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Metadata

Authors
Kim, J., & Lee, J.
Venue
Behaviour & Information Technology
Published
2002-01
Volume
21
Issue
3
Pages
185-199
ISSN
  • 0144-929X (ISSN-L)
  • 1362-3001
OpenAlex
W2056425598
Cited by
165
References
1
FWCI
6.55
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Critical design factors for successful e-commerce systems. https://app.cochat.ai/papers/10.1080/0144929021000009054
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Kim, J., & Lee, J. (2002). Critical design factors for successful e-commerce systems. Behaviour & Information Technology. https://doi.org/10.1080/0144929021000009054

Data sources

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.