Product design: a vectors field-based approach for preference modelling

Taking the needs of a consumer into account is imperative in product design. In many cases, aesthetic properties are as important as technical functions. When one considers the subjective part of the requirements, the feelings, impressions, sensations or preferences customers have must be quantified and modelled in advance. This is a major challenge in industrial design. Methods and tools need to be developed so that the subjectivity of the human assessment can be captured and integrated into the design process. In this context, we propose a new method based on vectors fields for modelling customers' preferences. Our method models the preferences in a perceptual space, in which the perceptual attributes of a family of products can be described. In this paper, we have used multidimensional scaling for building the perceptual space and we have applied our method in an example based on a set of 15 cars. Using customer's preferences obtained by pairwise comparison, our method allows the modelling of complex preference structures; in particular, inconsistent and intransitive preferences. Our results are intended to provide the designer with a description of the perceptual attributes of the product and information to position the next generation of products in a high preference area.

[1]  J. Douglas Carroll,et al.  A quasi-nonmetric method for multidimensional scaling VIA an extended euclidean model , 1989 .

[2]  Jean-François Petiot,et al.  A multidimensional scaling approach for product design and preference modeling , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[3]  J. M. Kittross.  The measurement of meaning , 1959 .

[4]  R. Shepard,et al.  Multidimensional Scaling: Theory and Applications in the Behavioral Sciences, Volume 1. , 1973 .

[5]  George A. Hazelrigg.  On Irrationality in Engineering Design , 1997 .

[6]  F. Lootsma.  Multi-Criteria Decision Analysis via Ratio and Difference Judgement , 1999 .

[7]  J. Dixon,et al.  Engineering Design , 2019, Springer Handbook of Mechanical Engineering.

[8]  Panos Y. Papalambros,et al.  Principles of Optimal Design: Author Index , 2000 .

[9]  Mitsuo Nagamachi,et al.  Kansei Engineering: A new ergonomic consumer-oriented technology for product development , 1995 .

[10]  V. Rao,et al.  Research for product positioning and design decisions: An integrative review , 1995 .

[11]  J. Hauser,et al.  Profit Maximizing Perceptual Positions: An Integrated Theory for the Selection of Product Features and Price , 1981 .

[12]  E. Brunswik,et al.  The Conceptual Framework of Psychology , 1954 .

[13]  T. Saaty,et al.  Ranking by Eigenvector Versus Other Methods in the Analytic Hierarchy Process , 1998 .

[14]  L. A. Goodman,et al.  Social Choice and Individual Values , 1951 .

[15]  George A. Hazelrigg,et al.  The Implications of Arrow’s Impossibility Theorem on Approaches to Optimal Engineering Design , 1996 .

[16]  José Antonio Rosa,et al.  Assessing industrial buyers' perceptions of quality and their effects on satisfaction , 1995 .

[17]  Wayne S. DeSarbo,et al.  A Constrained Unfolding Methodology for Product Positioning , 1986 .

[18]  Bernard Yannou,et al.  Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics , 2004 .

[19]  El Mostafa Qannari,et al.  New models for the analysis of paired comparison data; segmentation of the panel , 2000 .

[20]  Hildegarde Heymann,et al.  Preference mapping: relating acceptance of “creaminess” to a descriptive sensory map of a semi-solid , 1999 .

[21]  Alastair Macdonald,et al.  Aesthetic intelligence: Optimizing user-centred design , 2001 .

[22]  Suzanne Winsberg,et al.  A quasi-nonmetric method for multidimensional scaling of multiway data via a restricted case of an extended indscal model , 1989 .

[23]  A. Tversky.  Intransitivity of preferences. , 1969 .

[24]  Klaus Krippendorff,et al.  Product Semantics: Exploring the Symbolic Qualities of Form , 1984 .

[25]  Rungtai Lin,et al.  An application of multidimensional scaling in product semantics , 1996 .

[26]  John B. Carroll,et al.  A Plea for Compactness. , 1964 .

[27]  A. Tversky,et al.  Context-dependent preferences , 1993 .

[28]  J.S. Finan,et al.  The analytic hierarchy process: Does adjusting a pairwise comparison matrix to improve the consistency ratio help? , 1997, Comput. Oper. Res..

[29]  Shang H. Hsu,et al.  A semantic differential study of designers’ and users’ product form perception , 2000 .

[30]  P. Moran.  On the method of paired comparisons. , 1947, Biometrika.

[31]  Ming-Chuen Chuang,et al.  Expressing the expected product images in product design of micro-electronic products , 2001 .

[32]  Roger N. Shepard,et al.  Multidimensional scaling : theory and applications in the behavioral sciences , 1974 .