Subjectivity of novelty metrics based on idea decomposition

References

• Boden, M. A. (2004). The creative mind: Myths and mechanism (2nd ed.). Routledge. https://doi.org/10.4324/9780203508527
   Google Scholar
• Brown, D. C. (2014). Problems with the calculation of novelty metrics. Proceedings of the 6th int. conf. on design computing and cognition.
   Google Scholar
• Cascini, G., & Russo, D. (2007). Computer-aided analysis of patents and search for TRIZ contradictions. International Journal of Product Development, 4(1/2), 52–67. https://doi.org/10.1504/IJPD.2007.011533
   Google Scholar
• Choi, S., Kang, D., Lim, J., & Kim, K. (2012). Expert systems with applications A fact-oriented ontological approach to SAO-based function modeling of patents for implementing function-based technology database. Expert Systems With Applications, 39(10), 9129–9140. https://doi.org/10.1016/j.eswa.2012.02.041
   Google Scholar
• Cohen, J. (1968). Weighted kappa: Nominal scale agreement with pro-vision for scaled disagreement or partial credit. Psychological Bulletin, 70(4), 213–220. https://doi.org/10.1037/h0026256
   Google Scholar
• Corazza, G. E., & Agnoli, S. (Eds.). (2016). Creativity in the twenty first century multidisciplinary contributions to the science of creative Thinking. Springer Science+Business Media. https://doi.org/10.1007/978-981-287-618-8
   Google Scholar
• Eckert, C., Alink, T., & Ruckpaul, A. (2011). Different notions of function: Results from an experiment on the analysis of an existing product. Journal of Engineering Design, 22(11–12), 811–837. https://doi.org/10.1080/09544828.2011.603297
   Google Scholar
• Eckert, C., Ruckpaul, A., Alink, T., & Albers, A. (2012). Variations in functional decomposition for an existing product: Experimental results. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 26(2), 107–128. https://doi.org/10.1017/S0890060412000029
   Google Scholar
• Eisenbart, B., Gericke, K., & Blessing, L. T. M. (2013). An analysis of functional modeling approaches across disciplines. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 27(3), 281–289. https://doi.org/10.1017/S0890060413000280
   Google Scholar
• Fiorineschi, L., Frillici, F. S., & Rotini, F. 2018). Issues related to missing attributes in A-posteriori novelty assessments. International design conference - Design 2018 (pp. 1067–1078), Dubrovnik - Croatia.
   Google Scholar
• Fiorineschi, L., Frillici, F. S., & Rotini, F. (2019). Orienting through the variants of the Shah A-Posteriori novelty metric. Proceedings of the design society: International conference on engineering design (pp. 2317–2326), Delft - The Netherlands. https://doi.org/10.1017/dsi.2019.238
   Google Scholar
• Fiorineschi, L., Frillici, F. S., & Rotini, F. (2020). Impact of missing attributes on a posteriori novelty assessments. Research in Engineering Design, 31(2), 221–234. https://doi.org/10.1007/s00163-020-00332-x
   Google Scholar
• Fiorineschi, L., Frillici, F. S., Rotini, F., & Tomassini, M. (2018). Exploiting TRIZ Tools for enhancing systematic conceptual design activities. Journal of Engineering Design, 29(6), 259–290. https://doi.org/10.1080/09544828.2018.1473558
   Google Scholar
• Gadd, K. (2011). TRIZ for engineers: Enabling inventive problem solving. John Wiley and sons, Inc.
   Google Scholar
• Gero, J. S. (1990). Design prototypes : A knowledge representation schema for design. AI Magazine, 11(4), 26-36. https://doi.org/10.1609/aimag.v11i4.854
   Google Scholar
• Gero, J. S., & Kanessegiesser, U. (2004). The situated function–behaviour–structure framework.pdf. Design Studies, 25(4), 373–391. https://doi.org/10.1016/j.destud.2003.10.010
   Google Scholar
• Hannah, R., Joshi, S., & Summers, J. D. (2012). A user study of interpretability of engineering design representations. Journal of Engineering Design, 23(6), 443–468. https://doi.org/10.1080/09544828.2011.615302
   Google Scholar
• Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1(1), 77–89. https://doi.org/10.1080/19312450709336664
   Google Scholar
• Hennessey, B. A., Amabile, T. M., & Mueller, J. S. (2011). Consensual assessment. Encyclopedia of creativity (Vol. 1, 2nd ed.). Academic Press. https://doi.org/10.1016/b978-0-12-375038-9.00046-7
   Google Scholar
• Jagtap, S. (2016). Assessing design creativity: Refinements to the novelty assessment method. International design conference - DESIGN 2016 (pp. 1045–1054), Cavtat, Dubrovnik - Croatia.
   Google Scholar
• Jagtap, S. (2019). Design creativity: Refined method for novelty assessment. International Journal of Design Creativity and Innovation, 7(1–2), 99–115. https://doi.org/10.1080/21650349.2018.1463176
   Google Scholar
• Jagtap, S., Andreas, L., Viktor, H., Elin, O., & Anders, W. (2015). Interdependency between average novelty, individual average novelty, and variety. International Journal of Design Creativity and Innovation, 3(1), 43–60. https://doi.org/10.1080/21650349.2014.887987
   Google Scholar
• Jansson, D. G., & Smith, S. M. (1991). Design fixation. Design Studies, 12(1), 3–11. https://doi.org/10.1016/0142-694X(91)90003-F
   Google Scholar
• Johnson, T. A., Caldwell, B. W., Cheeley, A., & 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, Charlotte, North Carolina. https://doi.org/10.1115/DETC2016-60319
   Google Scholar
• Kershaw, T. C., Bhowmick, S., Seepersad, C. C., & Hölttä-Otto, K. (2019). A decision tree based methodology for evaluating creativity in engineering design. Frontiers in Psychology, 10(JAN), 1–19. https://doi.org/10.3389/fpsyg.2019.00032
   Google Scholar
• Linsey, J. S., Clauss, E. F., Kurtoglu, T., Murphy, J. T., Wood, K. L., & 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, 133(3), 031008. https://doi.org/10.1115/1.4003498
   Google Scholar
• Lopez-Mesa, B., & Vidal, R. (2006). Novelty metrics in engineering design experiments. 9th international design conference, DESIGN 2006 (pp. 557–564). Dubrovnik - Croatia.
   Google Scholar
• Nelson, B. A., Wilson, J. O., Rosen, D., & Yen, J. (2009). Refined metrics for measuring ideation effectiveness. Design Studies, 30(6), 737–743. https://doi.org/10.1016/j.destud.2009.07.002
   Google Scholar
• Pahl, G., Beitz, W., Feldhusen, J., & Grote, K. H. (2007). Engineering design (3rd ed.). Springer-Verlag. https://doi.org/10.1007/978-1-84628-319-2
   Google Scholar
• Peeters, J., Verhaegen, P. A., Vandevenne, D., & Duflou, J. R. (2010). Refined metrics for measuring novelty in ideation. Proceedings of IDMME - Virtual concept 2010 (pp. 1–4), Bordeaux - France.
   Google Scholar
• Ranjan, B. S. C., Siddharth, L., & Chakrabarti, A. (2018). A systematic approach to assessing novelty, requirement satisfaction, and creativity. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 32(4), 390–414. https://doi.org/10.1017/S0890060418000148
   Google Scholar
• Sarkar, P., & Chakrabarti, A. (2008). Studying engineering design creativity - Developing a common definition and associated measures. J. S. Gero (Ed.), NSF international workshop on studying design creativity’08, Aix-en-Provence  - France.
   Google Scholar
• Sarkar, P., & Chakrabarti, A. (2011). Assessing design creativity. Design Studies, 32(4), 348–383. https://doi.org/10.1016/j.destud.2011.01.002
   Google Scholar
• Shah, J. J., Vargas-Hernandez, N., & Smith, S. M. (2003). Metrics for measuring ideation effectiveness. Design Studies, 24(2), 111–134. https://doi.org/10.1016/S0142-694X(02)00034-0
   Google Scholar
• Silvia, P. J., Winterstein, B. P., Willse, J. T., Barona, C. M., Cram, J. T., Hess, K. I., … Richard, C. A. (2008). Assessing creativity with divergent thinking tasks: Exploring the reliability and validity of new subjective scoring methods. Psychology of Aesthetics, Creativity, and the Arts, 2(2), 68–85. https://doi.org/10.1037/1931-3896.2.2.68
   Google Scholar
• Sluis-Thiescheffer, W., Bekker, T., Eggen, B., Vermeeren, A., & De Ridder, H. (2016). Measuring and comparing novelty for design solutions generated by young children through different design methods. Design Studies, 43(March), 48–73. https://doi.org/10.1016/j.destud.2016.01.001
   Google Scholar
• Srinivasan, V., & Chakrabarti, A. (2009). SAPPHIRE-An approach to analysis and synthesis. International conference on engineering design - ICED’09 (pp. 417–428). Stanford, CA, USA.
   Google Scholar
• Srinivasan, V., & Chakrabarti, A. (2010). Investigating novelty-outcome relationships in engineering design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, 24(2), 161–178. https://doi.org/10.1017/S089006041000003X
   Google Scholar
• Srivathsavai, R., Genco, N., Katj, & Seepersad, 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, Montreal - Canada.
   Google Scholar
• Tsourikov, V. M., Batchilo, L. S., & Sovpel, I. V. (2000). US006167370A. US Patent 006167370A.
   Google Scholar
• Vargas-Hernandez, N., Okudan, G. E., & Schmidt, L. C. (2012). 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, Chicago, Illinois. https://doi.org/10.1115/DETC2012-70295
   Google Scholar
• Vargas-Hernandez, N., Schmidt, L. C., & Okudan, G. E. (2012). 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. 1–10), Chicago, Illinois.
   Google Scholar
• Vargas-Hernandez, N., Schmidt, L. C., & Okudan, G. E. (2013). Systematic ideation effectiveness study of TRIZ. Journal of Mechanical Design, 135(10), 101009. https://doi.org/10.1115/1.4024976
   Google Scholar
• Vermaas, P. E., & Eckert, C. (2013). My functional description is better! Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 27(3), 187–190. https://doi.org/10.1017/S089006041300019X
   Google Scholar
• Viswanathan, V. K., & Linsey, J. S. (2018). Role of sunk cost in engineering idea generation : An experimental investigation. Journal of Mechanical Design, 135(December2013), 121002 1–12. https://doi.org/10.1115/1.4025290
   Google Scholar
• Walpole, R. E., Myers, R. H., Myers, S. L., & Ye, K. (2012). Probability and statistics for engineers and scientists (Vol. 3rd, 9th ed.). Prentice Hall. https://doi.org/10.1017/CBO9781107415324.004
   Google Scholar
• Weaver, M. B., Caldwell, B. W., & Sheafer, V. (2019). Interpreting measures of rarity and novelty: Investigating correlations between relative infrequency and perceived ratings. Proceedings of the ASME design engineering technical conference (Vol. 7), Anaheim, CA. https://doi.org/10.1115/DETC2019-97828
   Google Scholar