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Refining and Extending the Business Model With Information Technology: Dell Computer Corporation

Kenneth L. Kraemer, Jason Dedrick,·2000·The Information Society

Abstract

The exceptional performance of Dell Computer in recent years illustrates an innovative response to a fundamental competitive factor in the personal computer industry - the value of time. This article shows how Dell's strategies of direct sales and build-to-order production have proven successful in minimizing inventory and bringing new products to market quickly, enabling it to increase market share and achieve high returns on investment. The Dell case illustrates how one business model may have inherent advantages under particular market conditions, but it also shows the importance of execution in exploiting those advantages. In particular, Dell's use of information technology (IT) has been vital to executing both elements of its business model - direct sales and build-to-order - and provides valuable insights into how IT can be applied to achieve speed and flexibility in an industry in which time is critical. Many of the insights gained from this case can be applied more generally to other time-dependent industries, suggesting that the findings from the Dell case will have implications for a growing number of companies and industries in the future.

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Metadata

Authors
Kenneth L. Kraemer, J. D.
Venue
The Information Society
Published
2000-03
Volume
16
Issue
1
Pages
5-21
ISSN
  • 0197-2243 (ISSN-L)
  • 1087-6537
OpenAlex
W2114151405
Cited by
194
References
0
FWCI
14.94
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Refining and Extending the Business Model With Information Technology: Dell Computer Corporation. https://app.cochat.ai/papers/10.1080/019722400128293
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Kenneth L. Kraemer, J. D. (2000). Refining and Extending the Business Model With Information Technology: Dell Computer Corporation. The Information Society. https://doi.org/10.1080/019722400128293

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