Abstract
Looking at technical consumer products like communication devices or pc accessory, we state high saturated markets in developed societies. This leads to a broad range of market offers not only in performance or financial aspects. The users seek for more individual products that differentiate on a subsequent, more qualitative level. User centered design approaches have been developed to handle the resulting high product variety and to keep them economically efficient. E.g., Universal Design supports the development of products for as many persons as possible, also including those with physiological or cognitive deficits. But to really raise the quality of life we also need to take other needs into account. Maslow’s hierarchy of needs states that with the fulfilment of physical needs the level shifts to psychological demands like emotional or attitudinal satisfaction. We will shortly introduce a framework that supports an emotional design optimization based on interdisciplinary findings (e.g. psychology, market research or Kansei Engineering) and statistical data analysis. For a valid forecasting, robust and transparent mathematical treatment of this data is required. To this, we give a first overview of possible approaches and their potential to ensure robust and transparent mathematical data treatment in design for emotional impressions.
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Kett, S.G., Schmitt, B., Wartzack, S. (2017). What the Statistics Tell Us—How to Use Empiric Data in Design for Emotional Impressions. In: Chakrabarti, A., Chakrabarti, D. (eds) Research into Design for Communities, Volume 2. ICoRD 2017. Smart Innovation, Systems and Technologies, vol 66. Springer, Singapore. https://doi.org/10.1007/978-981-10-3521-0_56
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DOI: https://doi.org/10.1007/978-981-10-3521-0_56
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