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Research Papers

On the Benefits and Pitfalls of Analogies for Innovative Design: Ideation Performance Based on Analogical Distance, Commonness, and Modality of Examples

[+] Author and Article Information
Joel Chan

 University of Pittsburgh, LRDC Room 823, 3939 O’Hara Street, Pittsburgh, PA 15260joc59@pitt.edu

Katherine Fu

 Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213kfu@andrew.cmu.edu

Christian Schunn

 University of Pittsburgh, LRDC Room 821, 3939 O’Hara Street, Pittsburgh, PA 15260schunn@pitt.edu

Jonathan Cagan

 Carnegie Mellon University, Scaife Hall 419, 5000 Forbes Avenue, Pittsburgh, PA 15213jcag@andrew.cmu.edu

Kristin Wood

 University of Texas-Austin, 1 University Station, ETC 4.146B, M/C C2200, Austin, TX 78712-1063ood@mail.utexas.edu

Kenneth Kotovsky

 Carnegie Mellon University, Baker Hall 342F, Pittsburgh, PA 15213kotovsky@andrew.cmu.edu

d statistics estimate the size of the difference in group means in terms of the average standard deviation of the two groups in the contrast; in this case, d = 0.60 estimates that the mean probability of transfer is greater with far-field vs nearfield examples by 0.60 of a standard deviation (a moderate to large difference).

J. Mech. Des 133(8), 081004 (Aug 01, 2011) (11 pages) doi:10.1115/1.4004396 History: Received December 20, 2010; Revised June 07, 2011; Published August 01, 2011; Online August 01, 2011

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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Copyright © 2011 by American Society of Mechanical Engineers
Topics: Design , Project tasks
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Figures

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Figure 1

Comparison of experimental procedures for analogy vs. control groups

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Figure 2

Example participant solution concepts

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Figure 3

Summary of intermetric correlations. Numbers shown are Pearson’s r. All correlations are significant at p < 0.01.

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Figure 4

Summary of effects of example distance. *p < 0.05 and **p < 0.01. Control group data are shown in white bars. Error bars are ±1 standard error.

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Figure 5

Summary of effects of example commonness. *p < 0.05and **p < 0.01. Control group data are shown in white bars. Error bars are ±1 standard error.

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Figure 6

Mean novelty of solution concepts by example distance and commonness. *p < 0.05. Error bars are ±1 standard error.

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Figure 7

Summary of effects of example modality. *p < 0.05 and **p < 0.01. Control group data are shown in white bars. Error bars are ±1 standard error.

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