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Orienting through the Variants of the Shah’s A-Posteriori Novelty Metric

Published online by Cambridge University Press:  26 July 2019

Abstract

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Different variants of a-posteriori novelty metrics can be found in the literature. Indeed, such a kind of assessment procedures is often used to extract useful information about creativity and/or idea generation effectiveness. In particular, the metric proposed by Shah et al. in 2003, is one of the most used and discussed in the literature. However, scholars highlighted some flaws for this metric, and some variants have been proposed to overcome them. This paper argues about the variants proposed for the a-posteriori metric of Shah et al., and proposes a selection framework to support researchers in selecting the most suited for their experimental needs. The proposed selection framework also highlights important research hints, which could pave the way for future activities. More specifically, it is still necessary to support the identification of the best-suited abstraction framework to assign weights to attributes, and the assignment of weights should be better supported as well. Moreover, this paper highlights the presence of “uncommonness of key attributes”, which needs to be investigated for experimental cases where ideas missing some key attributes are present.

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Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Boden, M.A. (2004), The Creative Mind: Myths and Mechanism, 2nd ed., Routledge, London, available at: https://doi.org/10.4324/9780203508527Google Scholar
Brown, D.C. (2014), “Problems with the Calculation of Novelty Metrics”, Proceedings of the 6th Int. Conf. on Design Computing and Cognition, available at: http://web.cs.wpi.edu/∼dcb/Papers/DCC14/DCC14-Brown-Novelty-workshop.pdf.Google Scholar
Cascini, G., Fiorineschi, L. and Rotini, F. (2018), “Investigating on the Re-use of Conceptual Design Representations”, International Design Conference - Design 2018, pp. 10091020.Google Scholar
Fiorineschi, L., Frillici, F.S. and Rotini, F. (2018a), “Issues Related to Missing Attributes in A-Posteriori Novelty Assessments”, International Design Conference - Design 2018, pp. 10671078.Google Scholar
Fiorineschi, L., Frillici, F.S. and Rotini, F. (2018b), “A-Posteriori Novelty Assessments for Sequential Design Sessions”, International Design Conference - Design 2018, pp. 10791090.Google Scholar
Fiorineschi, L., Frillici, F.S., Rotini, F. and Tomassini, M. (2018), “Exploiting TRIZ Tools for enhancing systematic conceptual design activities”, Journal of Engineering Design, Vol. 29 No. 6, pp. 259290.Google Scholar
Gero, J.S. (1990), “Design Prototypes : A Knowledge Representation Schema for Design”, AI Magazine, Vol. 11 No. 4.Google Scholar
Jagtap, S. (2016), “Assessing Design Creativity: Refinements to the Novelty Assessment Method”, International Design Conference - DESIGN 2016, pp. 10451054.Google Scholar
Jansson, D.G. and Smith, S.M. (1991), “Design fixation”, Design Studies, Vol. 12 No. 1, pp. 311.Google Scholar
Johnson, T.A., Caldwell, B.W., Cheeley, A. and Green, M.G. (2016), “Comparison and Extension of Novelty Metrics for Problem-Solving Tasks”, Proceedings of the ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC/CIE 2016, available at: https://doi.org/10.1115/DETC2016-60319.Google Scholar
Linsey, J.S., Clauss, E.F., Kurtoglu, T., Murphy, J.T., Wood, K.L. and Markman, a. B. (2011), “An Experimental Study of Group Idea Generation Techniques: Understanding the Roles of Idea Representation and Viewing Methods”, Journal of Mechanical Design, Vol. 133 No. 3, p. 031008.Google Scholar
Nelson, B.A., Wilson, J.O., Rosen, D. and Yen, J. (2009), “Refined metrics for measuring ideation effectiveness”, Design Studies, Elsevier Ltd, Vol. 30 No. 6, pp. 737743.Google Scholar
Pahl, G., Beitz, W., Feldhusen, J. and Grote, K.H. (2007), “Engineering Design” 3rd Ed, Springer-Verlag London, available at: https://doi.org/10.1007/978-1-84628-319-2Google Scholar
Peeters, J., Verhaegen, P.A., Vandevenne, D. and Duflou, J.R. (2010), “Refined Metrics for Measuring Novelty in Ideation”, Proceedings of IDMME - Virtual Concept 2010, pp. 14.Google Scholar
Sarkar, P. and Chakrabarti, A. (2011), “Assessing design creativity”, Design Studies, Elsevier Ltd, Vol. 32 No. 4, pp. 348383.Google Scholar
Shah, J.J., Vargas-Hernandez, N. and Smith, S.M. (2003), “Metrics for measuring ideation effectiveness”, Design Studies, Vol. 24 No. 2, pp. 111134.Google Scholar
Sluis-Thiescheffer, W., Bekker, T., Eggen, B., Vermeeren, A. and De Ridder, H. (2016), “Measuring and comparing novelty for design solutions generated by young children through different design methods”, Design Studies, Elsevier Ltd, Vol. 43, pp. 4873.Google Scholar
Srinivasan, V. and Chakrabarti, A. (2009), “SAPPHIRE-An Approach to Analysos and Synthesis”, International Conference on Engineering Design - ICED'09, Stanford, CA, USA, pp. 417428.Google Scholar
Srivathsavai, R., Genco, N., Katj, N. and Seepersad, C.C. (2010), “Study of Existing Metrics Used in Measurement if Ideation Effectiveness”, Proceedings of the ASME 2010 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2010.Google Scholar
Vargas-Hernandez, N., Okudan, G.E. and Schmidt, L.C. (2012a), “Effectiveness Metrics for Ideation: Merging Genealogy Trees and Improving Novelty Metric”, Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2012, available at: https://doi.org/10.1115/DETC2012-70295.Google Scholar
Vargas-Hernandez, N., Schmidt, L.C. and Okudan, G.E. (2012b), “Systematic Ideation Effectiveness Study of TRIZ”, Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2012, pp. 110.Google Scholar
Vargas-Hernandez, N., Schmidt, L.C. and Okudan, G.E. (2013), “Systematic Ideation Effectiveness Study of TRIZ”, Journal of Mechanical Design, Vol. 135 No. 10, p. 101009.Google Scholar
Viswanathan, V.K. and Linsey, J.S. (2018), “Role of Sunk Cost in Engineering Idea Generation : An Experimental Investigation”, Journal of Mechanical Design, Vol. 135 No. December 2013, pp. 121002 112.Google Scholar