The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
On the Benefits and Pitfalls of Analogies for Innovative Design: Ideation Performance Based on Analogical Distance, Commonness, and Modality of Examples
Abstract
Drawing inspiration from examples by analogy can be a powerful tool for innovative design during conceptual ideation but also carries the risk of negative design outcomes (e.g., design fixation), depending on key properties of examples. Understanding these properties is critical for effectively harnessing the power of analogy. The current research explores how variations in analogical distance, commonness, and representation modality influence the effects of examples on conceptual ideation. Senior-level engineering students generated solution concepts for an engineering design problem with or without provided examples drawn from the U.S. Patent database. Examples were crossed by analogical distance (near-field vs. far-field), commonness (more vs. less-common), and modality (picture vs. text). A control group that received no examples was included for comparison. Effects were examined on a mixture of ideation process and product variables. Our results show positive effects of far-field and less-common examples on novelty and variability in quality of solution concepts. These effects are not modulated by modality. However, detailed analyses of process variables suggest divergent inspiration pathways for far-field vs. less-common examples. Additionally, the combination of far-field, less-common examples resulted in more novel concepts than in the control group. These findings suggest guidelines for the effective design and implementation of design-by-analogy methods, particularly a focus on far-field, less-common examples during the ideation process.
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Cites
Categorization and Representation of Physics Problems by Experts and Novices*
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981) · Cognitive Science · doi:10.1207/s15516709cog0502_2 · Cited by 5,248
(1991) · Choice Reviews Online · doi:10.5860/choice.28-5376 · Cited by 4,207
Duncker, K. (1945) · Psychological Monographs · doi:10.1037/h0093599 · Cited by 2,938
Boden, M. A. (2004) · doi:10.4324/9780203508527 · Cited by 2,775
Gick, M. L., & Holyoak, K. J. (1980) · Cognitive Psychology · doi:10.1016/0010-0285(80)90013-4 · Cited by 2,552 · cited 2×
“from memory [20] or notice as relevant to one’s target problem [5].”
BackgroundAdvances in Instructional Psychology
(2019) · Routledge eBooks · doi:10.4324/9781315864341 · Cited by 2,532
Structure mapping in analogy and similarity.
Gentner, D., & Markman, A. B. (1997) · American Psychologist · doi:10.1037//0003-066x.52.1.45 · Cited by 1,816
Chase, W. G., & Simon, H. A. (1973) · Visual Information Processing · doi:10.1016/b978-0-12-170150-5.50011-1 · Cited by 1,419
Metrics for measuring ideation effectiveness
Shah, J. J., Smith, S. M., & Vargas-Hernandez, N. (2003) · Design Studies · doi:10.1016/s0142-694x(02)00034-0 · Cited by 1,095
Synectics: The Development of Creative Capacity
Gordon, W. J. J. (1961) · Bibliothèque et Archives nationales du Québec (Québec government) · Cited by 885
Cited by
Fixation and creativity in concept development: The attitudes and practices of expert designers
Crilly, N. (2015) · Design Studies · doi:10.1016/j.destud.2015.01.002 · Cited by 330
McKenney, S., Kali, Y., Markauskaite, L., & Voogt, J. (2015) · Instructional Science · doi:10.1007/s11251-014-9337-2 · Cited by 161
Providing Timely Examples Improves the Quantity and Quality of Generated Ideas
Siangliulue, P., Chan, J., Gajos, K. Z., & Dow, S. P. (2015) · Proceedings of the 2015 ACM SIGCHI Conference on Creativity and Cognition · doi:10.1145/2757226.2757230 · Cited by 99
Self-citationA new strategy to reduce design fixation: Presenting partial photographs to designers
Cheng, P., Mugge, R., & Schoormans, J. P. L. (2014) · Design Studies · doi:10.1016/j.destud.2014.02.004 · Cited by 89
Data-Driven Design-By-Analogy: State-of-the-Art and Future Directions
Jiang, S., Hu, J., Wood, K. L., & Luo, J. (2022) · Journal of Mechanical Design · doi:10.1115/1.4051681 · Cited by 86
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Metadata
- Authors
- Chan, J., Fu, K., Schunn, C., Cagan, J., Wood, K., & Kotovsky, K.
- Venue
- Journal of Mechanical Design
- Publisher
- ASME International
- Published
- 2011-08-01
- Volume
- 133
- Issue
- 8
- ISSN
- 0161-8458 (ISSN-L)
- 1050-0472
- 1528-9001
- OpenAlex
- W2028994502
- Cited by
- 288
- References
- 45
- FWCI
- 26.75
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chan, J., Fu, K., Schunn, C., Cagan, J., Wood, K., & Kotovsky, K. (2011). On the Benefits and Pitfalls of Analogies for Innovative Design: Ideation Performance Based on Analogical Distance, Commonness, and Modality of Examples. Journal of Mechanical Design. https://doi.org/10.1115/1.4004396
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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