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Cited by 385

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

The Impact of Data Integration on the Costs and Benefits of Information Systems

Goodhue, Dale L., Wybo, Michael D., Kirsch, Laurie J.·1992·MIS Quarterly

Abstract

For many organizations, the ability to make coordinated, organization-wide responses to today’s business problems is thwarted by the lack of data integration or commonly defined data elements and codes across different information systems. Though many researchers and practitioners have implicitly assumed that data integration always results in net benefits to an organization, this article questions that view. Based on theories of organizational information processing, a model of the impact of data integration is developed that includes gains in organization-wide coordination and organization-wide decision making, as well as losses in local autonomy and flexibility, and changes in system design and implementation costs. The importance of each of these impacts is defended by theoretical arguments and illustrated by case examples. This model suggests that the benefits of data integration will outweigh costs only under certain situations, and probably not for all the data the organization uses. Therefore, MIS researchers and practitioners should consider the need for better conceptualization and methods for implementing “partial integration” in organizations.

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Registry

Crossref · 10.2307/249530

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Metadata

Authors
Goodhue, D. L., Wybo, M. D., & Kirsch, L. J.
Venue
MIS Quarterly
Publisher
MIS Quarterly
Published
1992-09-01
Volume
16
Issue
3
Pages
293-311
ISSN
  • 0276-7783 (ISSN-L)
  • 2162-9730
OpenAlex
W1530624724
Cited by
385
References
3
FWCI
16.82
Type
journal article
Language
en
Open access
closed

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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.