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A Study On Consumer's Feeling Preference Of Mobile Phone

Posted on:2009-08-16Degree:MasterType:Thesis
Country:ChinaCandidate:J MaFull Text:PDF
GTID:2189360308479241Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
As the development of science technology, individuated products become more and more popular. Consumer emphasized the feeling property when they purchased goods as the deleloping of individuation requirement and product function. There is a misunderstanding between designer and consumer. How to identify consumer's feeling preference property and conformity this property into products are still big problem for designers.There are more than one thousand different brands in mobile phone market. Consumers focus more on the appearance of phones during their purchasing process as the function diversity is not so strong now. How to design a product satisfied by consumers is the biggest problem for the producers all over the world. This paper will establish a consumers preferred model and the relationship model between semantic word and modeling elements. First, mobile phones for consumers to feel scale of assessment will be built through the semantic differences, multi-dimensional scale analysis, cluster analysis, factor analysis methods, and on this basis we will build consumer preferences feeling model regression analysis method. The preferred model is the reaction of the semantic words on the overall preferences (preferences and purchasing desire) and this model can help designers grasp the mind reaction when consumer judges products'appearance. Based on this model, as well as the design factor which was classified of qualitative rules, the relationship between design factor and semantic words will be built. This two models will be able to form an objective element of the overall response to consumer preferences, which promote better grasp the design of consumer preferences will feel a positive role.
Keywords/Search Tags:kansei engineering, semantic difference method, consumer's preference, regression analysis, design factor
PDF Full Text Request
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