Investigating vehicle interior designs using models that evaluate user sensory experience and perceived value

Liang, Ching Chien; Lee, Ya Hsueh; Ho, Chun Heng; Chen, Kuo Hsiang

doi:10.1017/s0890060419000246

Cited by 13 publications

(9 citation statements)

References 22 publications

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“…In the field of Kansei engineering, many research methods pre-define a number of perceptual emotional words and product feature words based on the expert knowledge. Then, they use questionnaire surveys and on-site interviews to assess the emotional attitudes of users to different product element combinations to achieve the product design (Liang et al ., 2019). However, this method relies too much on the subjective cognition of domain experts and there is a certain lag in the investigation time, which cannot meet the requirements of enterprises for user demand analysis in the current competitive environment.…”

Section: Discussionmentioning

confidence: 99%

Evaluating aircraft cockpit emotion through a neural network approach

Chen

Chu

et al. 2020

AIEDAM

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Studies show that there are shortcomings in applying conventional methods for the emotional evaluation of the aircraft cockpit. In order to resolve this problem, a more efficient cockpit emotion evaluation system is established in the present study to simply and quickly obtain the cockpit emotion evaluation value. To this end, the neural network is applied to construct an emotional model to evaluate the emotional prediction of the interior design of the aircraft cockpit. Moreover, several technologies and the Kansei engineering method are applied to acquire the cockpit interior emotional evaluation data for typical aircraft models. In this regard, the radical basis function neural network (RBFNN), Elman neural network (ENN), and the general regression neural network (GRNN) are applied to construct the sentimental prediction evaluation model. Then, the three models are comprehensively compared through factors such as the model evaluation criteria, network structure, and network parameters. Obtained experimental results indicate that the GRNN not only has the highest classification accuracy but also has the highest stability in comparison to the other two neural networks, so that it is a more appropriate method for the emotional evaluation of the aircraft cockpit. Results of the present study provide decision supports for the emotional evaluation of the cockpit interior space.

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Section: Discussionmentioning

confidence: 99%

Evaluating aircraft cockpit emotion through a neural network approach

Chen

Chu

et al. 2020

AIEDAM

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“…It follows that designers in the automotive industry need to acknowledge these changes and increasingly shift consideration of UX alongside the more traditional considerations of form, materiality, and manufacturing of vehicles. This is not to deny that UX has been integral to automotive design in the past; however, we argue that now there is a heightened emphasis due to a shift in the industry toward recognizing the emotional needs of consumers (Liang et al , 2019).…”

Section: Introductionmentioning

confidence: 94%

“…Liang et al (2019) studied the perception of sensory experience using a method based on Kansei engineering principles. They found correlations between certain descriptors (e.g., relaxation, comfort) and particular automotive interior features.…”

Section: Introductionmentioning

confidence: 99%

A method to explore strategies to communicate user experience through storyboards: an automotive design case study

Rodda

Ranscombe

Kuys

2022

AIEDAM

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An engaging user experience is an increasingly important design characteristic in the automotive industry. Compared with physical design characteristics (form, material, mechanical design, appearance), automotive designers find UX (user experience) challenging to communicate during the early stages of the design process without investing in expensive prototypes and/or models. This paper presents the development of a method to explore strategies to communicate UX through the medium of storyboards early in the design process. The method enables links to be drawn between the design tool of storyboarding and the attributes of theoretical UX outlined in theoretical frameworks. By applying this method in a case study of a storyboard created by Ford Design Asia Pacific, we identify how the theoretical attributes of UX are manifested, and we also highlight certain attributes of UX that are difficult to convey during the early phases of automotive design. This research thus contributes a method relevant to practice that assists with effectively communicating UX in early-stage automotive design where higher fidelity prototyping is unviable. Additionally, it enables the study of storyboard outcomes in the design process to assess the degree to which the intended UX is communicated. In doing so, it contributes a first step toward formalizing the analysis of UX in concept design, which in turn opens up this highly subjective area to further research in the automated analysis of conceptual design and even generative design.

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“…The discussion on value in design in the literature can be split into four main streams: (1) product and (2) process value management; (3) economic value of design; and (4) human values in design. Product value management has a focus on the analysis and modelling of value in terms of objectives, functions, cost, benefits, user perception, quality, needs, wants, and worth (Bertoni and Bertoni 2019;Boderick 1992;Colombo et al 2020;Fowler 1990;Kim 2020;Liang et al 2020;Mudge 1989). Some approaches consider the relationships between different elements involved.…”

Section: Chase (2001)mentioning

confidence: 99%

ValueD: a model of cognitive value determination in design

Reber

Duffy

Hay

et al. 2021

Journal of Engineering Design

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In spite of the increasing importance placed on the creation and delivery of value, it is unclear what value is and how it is determined in design. In this paper, the first descriptive model of value determination (ValueD) is presented to clarify the key elements and mechanisms involved. ValueD describes value determination as a cognitive process that is situated and dependent on an agent's knowledge. The variables involved are: an entity interpreted by an agent; a situation of an agent; knowledge of an agent; a criteria prioritisation activity; a criteria selection activity; and a criteria judgement activity. The output of the value determination process is a value statement. Value is shown to refer to a judgement on the extent an interpreted entity satisfies an agent's criteria. The ValueD model is evaluated through comparison against seven axioms of value and a protocol analysis of an engineering design episode. The article concludes with a discussion of strengths, limitations, and future work on ValueD, and its relationship with key value concepts such as added value, exchange and perceived value, benefit, and need.

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Investigating vehicle interior designs using models that evaluate user sensory experience and perceived value

Cited by 13 publications

References 22 publications

Evaluating aircraft cockpit emotion through a neural network approach

Evaluating aircraft cockpit emotion through a neural network approach

A method to explore strategies to communicate user experience through storyboards: an automotive design case study

ValueD: a model of cognitive value determination in design

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