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A BOUNDARY OBJECT FOR MAPPING, COMPARING, AND INTEGRATING PRODUCT DESIGN METHODS

Published online by Cambridge University Press:  19 June 2023

Jesse Velleu*
Affiliation:
University of Michigan
Diann Brei
Affiliation:
University of Michigan
Richard Gonzalez
Affiliation:
University of Michigan
Jonathan Luntz
Affiliation:
University of Michigan
*
Velleu, Jesse Lucas, University of Michigan, United States of America, [email protected]

Abstract

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There are innumerable design methods that exist across a wide spectrum of disciplines, ranging from engineering, to marketing, to psychology. However, the organic, multidisciplinary nature of methodological development in design leads to challenges in comparing or combining methods. Disciplinary perspectives can create conceptual 'boundaries' that may not align with the fluidity of the problems that designers may need to address. It is challenging to work between the boundaries of these design methods due to the unclear delimitation of exactly where and how methods may be integrated. Nomenclature is unstandardized and different terminologies may describe similar phenomena. To address this, a boundary object—the Actor-Abstraction matrix—is developed to recontextualize each of these divergent methods onto a common scale so they may be better understood in reference to their peers. A meta-analysis of four established design methods is performed to demonstrate the flexibility of this conceptual device. With this tool, existing design methods may be more easily examined to identify points of compatibility and gaps in their coverage, and could also serve as a powerful platform for the creation of new design methods in the future.

Type
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), 2023. Published by Cambridge University Press

References

Al-Fedaghi, S. (2016), “Function-Behavior-Structure Model of Design: An Alternative Approach”, International Journal of Advanced Computer Science and Applications, Vol. 7, https://dx.doi.org/10.14569/IJACSA.2016.070719.CrossRefGoogle Scholar
Blessing, L.T. and Chakrabarti, A. (2009), DRM: A Design Reseach Methodology, Springer.CrossRefGoogle Scholar
Boatwright, P. and Cagan, J. (2010), Built to Love: Creating Products That Captivate Customers, Berrett-Koehler Publishers.Google Scholar
Chung, W. and Fortier, S. (2013), “Context as a System, Product as a Component, and the Relationship as Experience”, in Marcus, A. (Ed.), Design, User Experience, and Usability. Design Philosophy, Methods, and Tools, Springer, Berlin, Heidelberg, pp. 2937, https://dx.doi.org/10.1007/978-3-642-39229-0_4.CrossRefGoogle Scholar
Cross, N. (2021), Engineering Design Methods: Strategies for Product Design, John Wiley & Sons.Google Scholar
Desmet, P. and Hekkert, P. (2007), “Framework of Product Experience”, p. 11.Google Scholar
Desmet, P.M.A., Ortíz Nicolás, J.C. and Schoormans, J.P. (2008), “Product personality in physical interaction”, Design Studies, Vol. 29 No. 5, pp. 458477, https://dx.doi.org/10.1016/j.destud.2008.06.003.CrossRefGoogle Scholar
Eisentraut, R. and Günther, J. (1997), “Individual styles of problem solving and their relation to representations in the design process”, Design Studies, Vol. 18 No. 4, pp. 369383, https://dx.doi.org/10.1016/S0142-694X(97)00007-0.CrossRefGoogle Scholar
Forlizzi, J. and Ford, S. (2000), “The building blocks of experience: an early framework for interaction designers”, Proceedings of the 3rd Conference on Designing Interactive Systems: Processes, Practices, Methods, and Techniques, Association for Computing Machinery, New York, NY, USA, pp. 419423, https://dx.doi.org/10.1145/347642.347800.CrossRefGoogle Scholar
Gero, J.S. (1990), “Design Prototypes: A Knowledge Representation Schema for Design”, AI Magazine, Vol. 11 No. 4, pp. 2626, https://dx.doi.org/10.1609/aimag.v11i4.854.CrossRefGoogle Scholar
Gero, J.S. and Kannengiesser, U. (2014), “The function-behaviour-structure ontology of design”, An Anthology of Theories and Models of Design, Springer, pp. 263283.Google Scholar
Gerrike, K., Eckert, C. and Stacey, M. (2017), “What do we need to say about a design method?”, presented at the 21th International Conference on Engineering Design (ICED 2015), Vancouver, Canada.Google Scholar
Green, P.E. and Srinivasan, V. (1990), “Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice”, Journal of Marketing, SAGE Publications Inc, Vol. 54 No. 4, pp. 319, https://dx.doi.org/10.1177/002224299005400402.CrossRefGoogle Scholar
Gregory, S.A. (2014), The Design Method, Springer US.Google Scholar
Hassenzahl, M. (2007), “The hedonic/pragmatic model of user experience”, Towards a UX Manifesto, pp. 1014.Google Scholar
Hassenzahl, M. (2018), “The Thing and I (Summer of ’17 Remix)”, in Blythe, M. and Monk, A. (Eds.), Funology 2: From Usability to Enjoyment, Springer International Publishing, Cham, pp. 1731, https://dx.doi.org/10.1007/978-3-319-68213-6_2.CrossRefGoogle Scholar
Hassenzahl, M. and Tractinsky, N. (2006), “User experience - a research agenda”, Behaviour & Information Technology, Taylor & Francis, Vol. 25 No. 2, pp. 9197, https://dx.doi.org/10.1080/01449290500330331.CrossRefGoogle Scholar
Houssin, R., Sun, H. and Gardoni, M. (2010), “A behavioural design approach to improving mechanical system design with integration of use conditions”, International Journal of Design and Innovation Research, Vol. 5 No. 3, pp. 124.Google Scholar
ISO. (2018), Ergonomics of Human-System Interaction—Part 11: Usability: Definitions and Concepts, No. ISO 9241-11:2018, International Standardization Organization (ISO), Switzerland.Google Scholar
ISO. (2019), “ISO 9241-210:2019”, ISO.Google Scholar
Kang, X., Yang, M., Wu, Y. and Ni, B. (2018), “Integrating Evaluation Grid Method and Fuzzy Quality Function Deployment to New Product Development”, Mathematical Problems in Engineering, Hindawi, Vol. 2018, p. e2451470, https://dx.doi.org/10.1155/2018/2451470.CrossRefGoogle Scholar
Kiran, D.R. (2016), Total Quality Management: Key Concepts and Case Studies, Butterworth-Heinemann.Google Scholar
Law, E.L.-C. (2011), “The measurability and predictability of user experience”, Proceedings of the 3rd ACM SIGCHI Symposium on Engineering Interactive Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 110, https://dx.doi.org/10.1145/1996461.1996485.CrossRefGoogle Scholar
Michalek, J.J., Feinberg, F.M. and Papalambros, P.Y. (2005), “Linking Marketing and Engineering Product Design Decisions via Analytical Target Cascading*”, Journal of Product Innovation Management, Vol. 22 No. 1, pp. 4262, https://doi.org/10.1111/j.0737-6782.2005.00102.x.CrossRefGoogle Scholar
Murakami, T. and Koyanagi, T. (2017), “Proposal of Delta Design Map Based on Function, Behavior, Structure and User Experience for Design Ideation Support”, presented at the ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers Digital Collection, https://dx.doi.org/10.1115/DETC2017-68058.CrossRefGoogle Scholar
Nagamachi, M. (2016), Kansei/Affective Engineering, CRC Press.CrossRefGoogle Scholar
Neto, W.F. and Pires, A.R. (2020), “Kansei Engineering and Quality Function Deployment: Development of Methodology for the Identification of User-Centralized Project Improvements”, in Fukuda, S. (Ed.), Advances in Affective and Pleasurable Design, Springer International Publishing, Cham, pp. 300309, https://dx.doi.org/10.1007/978-3-030-20441-9_32.CrossRefGoogle Scholar
Papalambros, P.Y. (2015), “Design Science: Why, What and How”, Design Science, Cambridge University Press, Vol. 1, https://dx.doi.org/10.1017/dsj.2015.1.CrossRefGoogle Scholar
Park, J., Han, S.H., Kim, H.K., Oh, S. and Moon, H. (2013), “Modeling user experience: A case study on a mobile device”, International Journal of Industrial Ergonomics, Vol. 43 No. 2, pp. 187196, https://dx.doi.org/10.1016/j.ergon.2013.01.005.CrossRefGoogle Scholar
Qian, L. and Gero, J.S. (1996), “Function–behavior–structure paths and their role in analogy-based design”, AI EDAM, Cambridge University Press, Vol. 10 No. 4, pp. 289312.Google Scholar
Rajeshkumar, S., Omar, R. and Mahmud, M. (2013), “Taxonomies of User Experience (UX) evaluation methods”, 2013 International Conference on Research and Innovation in Information Systems (ICRIIS), presented at the 2013 International Conference on Research and Innovation in Information Systems (ICRIIS), pp. 533538, https://dx.doi.org/10.1109/ICRIIS.2013.6716765.Google Scholar
Ramaswamy, R. and Ulrich, K. (1993), “Augmenting the house of quality with engineering models”, Research in Engineering Design, Vol. 5 No. 2, pp. 7079, https://dx.doi.org/10.1007/BF02032576.Google Scholar
Sadeghi, L., Dantan, J.-Y., Mathieu, L., Siadat, A. and Aghelinejad, M.M. (2017), “A design approach for safety based on Product-Service Systems and Function–Behavior–Structure”, CIRP Journal of Manufacturing Science and Technology, Vol. 19, pp. 4456, https://dx.doi.org/10.1016/j.cirpj.2017.05.001.CrossRefGoogle Scholar
Schütte, S. (2002), “Designing Feelings into Products: Integrating Kansei Engineering Methodology in Product Development”, Institutionen för konstruktions- och produktionsteknik.Google Scholar
Sener, Z. and Karsak, E.E. (2011), “A combined fuzzy linear regression and fuzzy multiple objective programming approach for setting target levels in quality function deployment”, Expert Systems with Applications, Vol. 38 No. 4, pp. 30153022, https://dx.doi.org/10.1016/j.eswa.2010.08.091.CrossRefGoogle Scholar
Singh, R.K., Rajput, V. and Sahay, A. (2018), “A Literature Review On Quality Function Deployment (QFD)”, IAETSD Journal For Advanced Research In Applied Sciences, Vol. 5 No. 8, pp. 245250.Google Scholar
Siu, K.W.M. (2005), “Pleasurable products: public space furniture with userfitness”, Journal of Engineering Design, Taylor & Francis, Vol. 16 No. 6, pp. 545555, https://dx.doi.org/10.1080/09544820500273383.CrossRefGoogle Scholar
Star, S.L. (2010), “This is Not a Boundary Object: Reflections on the Origin of a Concept”, Science, Technology, & Human Values, SAGE Publications Inc, Vol. 35 No. 5, pp. 601617, https://dx.doi.org/10.1177/0162243910377624.CrossRefGoogle Scholar
Star, S.L. and Griesemer, J.R. (1989), “Institutional Ecology, ‘Translations’ and Boundary Objects: Amateurs and Professionals in Berkeley's Museum of Vertebrate Zoology, 1907-39”, Social Studies of Science, SAGE Publications Ltd, Vol. 19 No. 3, pp. 387420, https://dx.doi.org/10.1177/030631289019003001.CrossRefGoogle Scholar
Sun, X., Houssin, R., Renaud, J. and Gardoni, M. (2019), “A review of methodologies for integrating human factors and ergonomics in engineering design”, International Journal of Production Research, Vol. 57 No. 15–16, pp. 49614976, https://dx.doi.org/10.1080/00207543.2018.1492161.CrossRefGoogle Scholar
Tharchen, T., Garud, R. and Henn, R.L. (2020), “Design as an interactive boundary object”, Journal of Organization Design, Vol. 9 No. 1, p. 21, https://dx.doi.org/10.1186/s41469-020-00085-w.CrossRefGoogle Scholar
Tovares, N., Boatwright, P. and Cagan, J. (2014), “Experiential Conjoint Analysis: An Experience-Based Method for Eliciting, Capturing, and Modeling Consumer Preference”, Journal of Mechanical Design, Vol. 136 No. 101404, https://dx.doi.org/10.1115/1.4027985.CrossRefGoogle Scholar
Van den Hoven, E., Frens, J., Aliakseyeu, D., Martens, J.-B., Overbeeke, K. and Peters, P. (2007), “Design research & tangible interaction”, Proceedings of the 1st International Conference on Tangible and Embedded Interaction, Association for Computing Machinery, New York, NY, USA, pp. 109115, https://dx.doi.org/10.1145/1226969.1226993.Google Scholar
Wang, C.-H. (2015), “Integrating Kansei engineering with conjoint analysis to fulfil market segmentation and product customisation for digital cameras”, International Journal of Production Research, Taylor & Francis, Vol. 53 No. 8, pp. 24272438, https://dx.doi.org/10.1080/00207543.2014.974840.CrossRefGoogle Scholar
Wellings, T., Williams, M. and Tennant, C. (2010), “Understanding customers’ holistic perception of switches in automotive human–machine interfaces”, Applied Ergonomics, Vol. 41 No. 1, pp. 817, https://dx.doi.org/10.1016/j.apergo.2009.03.004.CrossRefGoogle Scholar
Yannou, B., Cluzel, F. and Lamé, G. (2018), “Adapting the FBS Model of Designing for Usage-Driven Innovation Processes”, presented at the ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, American Society of Mechanical Engineers Digital Collection, https://dx.doi.org/10.1115/DETC2018-86166.CrossRefGoogle Scholar
Zarour, M. and Alharbi, M. (2017), “User experience framework that combines aspects, dimensions, and measurement methods”, edited by Park, E. Cogent Engineering, Vol. 4 No. 1, p. 1421006, https://dx.doi.org/10.1080/23311916.2017.1421006.CrossRefGoogle Scholar