Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 259

The DOI matches its Crossref record; 75 of the 75 references it cites were found in a registry or an index.

Using an Attribute-Based Decision Support System for User-Customized Products Online: An Experimental Investigation1

Kamis, Arnold, Koufaris, Marios, Stern, Tziporah·2008·MIS Quarterly

Abstract

In the decision support systems literature, most studies have concentrated on the direct effects of DSS use and design on decision outcomes and user performance in the workplace. Fewer DSS studies have integrated decision process variables, such as user beliefs and attitudes, in their models. In this paper, we examine the mediating role of decision process variables in the use of an online customer DSS. We do so through an experimental study of an alternative-based and an attribute-based DSS for product customization by online customers. Using cognitive fit and flow theories, we develop a theoretical model with four mediating decision process variables (perceived usefulness, perceived ease of use, perceived enjoyment, and perceived control) and two of their antecedents: interface design (attribute-based versus alternative-based) and task complexity (choice set size). Our results show that the impact of DSS interface design on behavioral intentions is fully mediated by perceived usefulness and perceived enjoyment, although not by perceived control. Specifically, we verify that users of an attribute-based DSS express higher perceived usefulness and perceived enjoyment than users of an alternative-based one. In addition, we find that task complexity has an interesting relationship with usefulness and enjoyment, both ofwhich follow an inverted U-shaped curve as choice set size increases. Finally, we find that for users of the alternative-based DSS, perceived ease of use and perceived control decrease as task complexity increases. However, the attribute-based DSS alleviates that decline for both variables. Among other contributions, our results indicate the importance of including decision process variables when studying DSS as well as the complex effect of task complexity on those variables. Our study also provides some important guidelines for online companies that provide customer DSS on their websites, especially the danger of providing too many product choice options that can overwhelm customers and harm their shopping experience.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.2307/25148832

Cites

75 of 75 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 75 references

Cited by

See all 259

Metadata

Authors
Kamis, A., Koufaris, M., & Stern, T.
Venue
MIS Quarterly
Publisher
MIS Quarterly
Published
2008-03-01
Volume
32
Issue
1
Pages
159-177
ISSN
  • 0276-7783 (ISSN-L)
  • 2162-9730
OpenAlex
W3123652873
Cited by
259
References
75
FWCI
32.26
Type
journal article
Language
en
Open access
closed

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 ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Using an Attribute-Based Decision Support System for User-Customized Products Online: An Experimental Investigation1. https://app.cochat.ai/papers/10.2307/25148832
The paper
Kamis, A., Koufaris, M., & Stern, T. (2008). Using an Attribute-Based Decision Support System for User-Customized Products Online: An Experimental Investigation1. MIS Quarterly. https://doi.org/10.2307/25148832

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.