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Cited by 274

The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.

Internet retail store design: How the user interface influences traffic and sales

Lohse, Gerald L., Spiller, Peter·2006·Journal of Computer-Mediated Communication

Abstract

Given the resources needed to launch a retail store on the Internet or change an existing online storefront design, it is important to allocate product development resources to interface features that actually improve store traffic and sales. We identified features that impact store traffic and sales using regression models of 1996 store traffic and dollar sales as dependent variables and interface design features such as number of links into the store, hours of promotional ads, number of products, and store navigation features as the independent variables. Product list navigation features that reduce the time to purchase products online account for 61% of the variance in monthly sales. Other factors explaining the variance in monthly sales include: number of hyperlinks into the store (10%), hours of promotion (4%) and customer service feedback (1%). These findings demonstrate that the user interface is an essential link between the customer and the retail store in Web-based shopping environments.

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Crossref · 10.1111/j.1083-6101.1999.tb00339.x

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Metadata

Authors
Lohse, G. L., & Spiller, P.
Venue
Journal of Computer-Mediated Communication
Published
2006-06-23
Volume
5
Issue
2
Pages
0-0
ISSN
1083-6101 (ISSN-L)
OpenAlex
W1965937355
Cited by
274
References
19
FWCI
30.52
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Internet retail store design: How the user interface influences traffic and sales. https://app.cochat.ai/papers/10.1111/j.1083-6101.1999.tb00339.x
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Lohse, G. L., & Spiller, P. (2006). Internet retail store design: How the user interface influences traffic and sales. Journal of Computer-Mediated Communication. https://doi.org/10.1111/j.1083-6101.1999.tb00339.x

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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.