Modelling perceptions of craftsmanship in vehicle interior design

• Published in: Journal of engineering design Vol. 22; no. 2; pp. 129 - 144
• Main Authors: Ersal, Ilkin, Papalambros, Panos, Gonzalez, Richard, Aitken, Thomas J.
• Format: Journal Article
• Language: English
• Published: Abingdon Taylor & Francis 01.02.2011; Taylor & Francis Ltd
• Subjects: Acceptability; agreement measures; Automobiles; Automotive engineering; Cluster analysis; Clusters; craftsmanship; customer perceptions; Data reduction; Design engineering; Interior design; Lists; multidimensional scaling; Perception; Perceptions; Product design; Studies; Tables (data); vehicle interior design
• ISSN: 0954-4828; 1466-1837
• DOI: 10.1080/09544820903095219

In the automobile industry, one approach for assessing craftsmanship is to have experienced designers evaluate the craftsmanship of a vehicle interior on a set of vehicle craftsmanship characteristics. This article extends one industry approach by evaluating vehicle interior craftsmanship in a quantitative manner. Study 1 presents data suggesting that an existing craftsmanship scale does not lead to acceptable levels of consensus across evaluators nor to interpretable clusters or dimensional spaces after data reduction. A new list of interior characteristics and perceived attributes of craftsmanship is developed and analysed using a functional dependence table (FDT). Study 2 uses the new list of perceived attributes and shows there is an improved degree of consensus across evaluators, meaningful clusters and spatial arrangements emerge using cluster analysis and multidimensional scaling, and the clusters from the evaluators' data are consistent with the subproblems that emerged from the FDT of product attributes and characteristics. The paper demonstrates that engineering designers can use this approach to guide their work about perceived craftsmanship. One benefit of the proposed method is that engineering designers can work at the level of perceived product attributes (the same attributes potentially observed by the consumer) and map those attributes to engineering characteristics.