Beyond usability: designing for consumers' product experience using the Rasch model

Abstract

Many manufacturers wish to relate the physical properties of their products to customers' affective responses so that they can improve the design of their products. Rasch measurement theory is a novel approach in this context that could offer business benefits over other approaches. The aim of the research was to determine whether Rasch measurement theory can support the construction of a scale to measure the affective impression of a moisturizer cream elicited by the compliance of the moisturizer's packaging. The compliances of packaging used to develop a scale for the impression of the contents of the packaging in previous research were measured. New packaging prototypes were manufactured with a range of compliances to determine whether affective responses to them could be predicted. A new sample of sixty seven participants rated the prototypes against Likert statements on a five-point scale. The statements were derived from descriptions of the users' product experience. The scale was recalibrated using a multi-facet Rasch model. It was found that the affective responses to the prototypes fell within the range predicted by the original scale. The results demonstrate that Rasch measurement theory can be used to achieve the objective correspondence between affective responses and the physical properties of a product, and the information can be used in new product development.

Transparency in product design: investigating design intentions and consumers’ interpretations

“…Previous studies have also investigated the different product personality traits that product designs can convey (Desmet, Nicolas, andSchoormans 2008, Mugge, Govers, and and the effects of certain product personality traits on consumers' perception of product performance quality (Mugge 2011). Furthermore, different toolkits have been developed to support designers in styling activities (Giannini, Monti, and Podehl 2006, Chen and Owen 1998, Hsiao and Wang 1998, Camargo and Henson 2015, Barnes and Lillford 2009 and in material selection activities (Kesteren, Bruijn, andStappers 2008, Karana et al 2015).…”

Kansei for the Digital Era

“…Researchers now use physiological measurements such as electroencephalography [17] and eye tracking [37], paired with self-report questionnaires using item response theory [38], and making use advanced modelling techniques such as neural network analysis and sparse Bayesian learning [39]. Qualitative research techniques such as empathy mapping and phenomenology can be used [14].…”

Systematic Literature Reviews in Kansei Engineering for Product Design—A Comparative Study from 1995 to 2020

“…There are emotional design methodologies based on Kansei engineering with different adaptations, such as applying the Rasch model [ 39 ] or big data [ 40 ], building QFD matrices [ 41 ] or making use of aesthetic intelligence [ 42 ] and some work reviewing design methodologies in general [ 43 ]. However, no review compiles relevant methodologies based on emotional design and compares them.…”