Proposal of a Research Methodology to Increase the Robustness of the Conjoint Trends Analysis Method through Its Formalization

  • Angela Cadavid
  • Jorge Maya
Conference paper
Part of the Lecture Notes in Production Engineering book series (LNPE)


Nowadays, the product user experience (UX) is essential in the design of innovative products. Several methods assist in defining this UX. Some help to define the aesthetic appearance of a product (which conveys the desired UX). They are very precise but are also complex and expensive to use. Others are easy and inexpensive to use but imprecise. The Conjoint Trends Analysis Method (CTAM) lies between these two extremes. However, several CTAM’s instructions can be biased by the subjectivity of the CTAM user. Therefore, this research seeks to increase the CTAM robustness by formalizing instructions and making its concepts more explicit, aiming to increase its accuracy. Six experiments divided in four studies are proposed to respond to different research questions. Finally, there is a discussion on how the results can provide a basis from which to extract more robust guidelines for each step of the CTAM.


Conjoint Trends Analysis Method product aesthetics user experience product embodiment product appearance 


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  1. 1.
    Pahl, G., Beitz, W., Wallace, K.: Engineering design: a systematic approach. Springer (1996)Google Scholar
  2. 2.
    Ulrich, K.T., Eppinger, S.D.: Product design and development. McGraw-Hill (2011)Google Scholar
  3. 3.
    Otto, K.N., Wood, K.L.: Product design. Prentice Hall, Englewood Cliffs (2000)Google Scholar
  4. 4.
    Hekkert, P., Schifferstein, H.: Introducing product experience. In: Product Experience, pp. 1–8 (2008)Google Scholar
  5. 5.
    Cagan, J., Vogel, C.M.: Creating breakthrough products: Innovation from product planning to program approval. FT Press (2002)Google Scholar
  6. 6.
    Jordan, P.W.: Pleasure with products: Human factors for body, mind and soul. In: Human Factors in Product Design: Current Practice and Future Trends, pp. 206–217 (1999)Google Scholar
  7. 7.
    Matzler, K., Hinterhuber, H.H.: How to make product development projects more successful by integrating Kano’s model of customer satisfaction into quality function deployment. Technovation 18, 25–38 (1998)CrossRefGoogle Scholar
  8. 8.
    Castano, M., Hernan, J., Arenas, M., Velez, M.: Implementation and Assessment of the Trend Boards Method in a Product Design Engineering Program. In: Proceedings of the 13th International Conference on Engineering and Product Design Education E&PDE 2011, pp. 541–546 (2011)Google Scholar
  9. 9.
    Rodríguez, A.G.: The reality of Colombian SMEs: a challenge for develpment. Program Improvement Corporate Enviromental Conditions. FUNDES Colombia (2003) (in Spanish)Google Scholar
  10. 10.
    Bouchard, C., Christofol, H., Roussel, B., Aoussat, A.: Identification and integration of product design trends. In: International Conference on Engineering Design, Munich (1999)Google Scholar
  11. 11.
    Bereciartua, A., Bouchard, C., Ferecatu, M., Logerot, G., Rigouste, L., Vitale, C.: Meta Deliverable 1-state of the art (2007)Google Scholar
  12. 12.
    Mougenot, C.: Modélisation de la phase d’exploration du processus de conception de produits, pour une créativité augmentée. Design Studies 27, 587–613 (2008)Google Scholar
  13. 13.
    Eckert, C., Stacey, M., Clarkson, P.: Algorithms and inspirations: creative reuse of design experience. In: Proeedings of Greenwich 2000: The International Symposium on Digital Creativity, pp. 1–10 (2000)Google Scholar
  14. 14.
    Ericsson, K.A.: Protocol analysis and expert thought: Concurrent verbalizations of thinking during experts’ performance on representative tasks. In: The Cambridge Handbook of Expertise and Expert Performance, pp. 223–241 (2006)Google Scholar
  15. 15.
    Graziano, A.M., Raulin, M.L.: Research methods: A process of inquiry. HarperCollins College Publishers (1993)Google Scholar
  16. 16.
    Mougenot, C., Bouchard, C., Aoussat, A., Westerman, S.: Inspiration, images and design: an investigation of designers’ information gathering strategies. Journal of Design Research 7, 331–351 (2008)CrossRefGoogle Scholar
  17. 17.
    Hanington, B., Martin, B.: Universal Methods of Design: 100 Ways to Research Complex Problems, Develop Innovative Ideas, and Design Effective Solutions. Rockport Publishers (2012)Google Scholar
  18. 18.
    Mougenot, C., Watanabe, K., Bouchard, C., Aoussat, A.: Visual materials and designers’ cognitive activity: Towards in-depth investigations of design cognition. International Association of Societies of Design Research, Seoul (2009)Google Scholar
  19. 19.
    Bonnardel, N., Marmèche, E.: Towards supporting evocation processes in creative design: A cognitive approach. International Journal of Human-Computer Studies 63, 422–435 (2005)CrossRefGoogle Scholar
  20. 20.
    Sternberg, R.J., Mio, J.: Cognitive psychology. Wadsworth Pub. Co. (2008)Google Scholar
  21. 21.
    Pearsall, J., Hanks, P.: The new Oxford dictionary of English. Clarendon Press (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Product Design EngineeringUniversidad EAFITMedellinColombia

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