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Stimulating Ideas Through Creative Software

MacCrimmon, Kenneth R., Wagner, Christian·1994·Management Science

Abstract

A central task of management is decision making and a crucial aspect of decision making is having good alternatives from which to choose. This paper investigates whether computer-based procedures for idea generation can help individuals to develop solution alternatives more creatively. Our conceptual framework considers creative processes, environments, outputs, and individuals. In particular, generating alternatives is viewed as a process of “making connections” —internal connections among problem elements and external connections between a problem and its environment. We have developed a computer program (GENI) which incorporates a variety of techniques to assist in making these different types of connections. The program is described and an experimental test with several managerial problems is presented. The results show that use of the program leads to the development of significantly more creative alternatives than does a control treatment. There is an amplification effect in that the performance of the more creative individuals is improved the most. Thus the findings suggest that computerized idea generation leads to more creative alternatives resulting in potentially better managerial decisions.

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Metadata

Authors
MacCrimmon, K. R., & Wagner, C.
Venue
Management Science
Published
1994-11
Volume
40
Issue
11
Pages
1514-1532
ISSN
  • 0025-1909 (ISSN-L)
  • 1526-5501
OpenAlex
W2062705063
Cited by
221
References
0
FWCI
3.68
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Stimulating Ideas Through Creative Software. https://app.cochat.ai/papers/10.1287/mnsc.40.11.1514
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MacCrimmon, K. R., & Wagner, C. (1994). Stimulating Ideas Through Creative Software. Management Science. https://doi.org/10.1287/mnsc.40.11.1514

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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.