Affiliation:
1. Institutes of Physical Science and Information Technology, Anhui University, Hefei 230601, China
Abstract
In the current era that consumers pursue personalized experience, in order to optimize the customer experience of new Chinese-style clothing products and improve the evaluation procedures of new Chinese-style clothing products, based on the theory of customer perceived value, this paper constructs the evaluation index and evaluation model of new Chinese-style clothing customer perceived value. This study is divided into three stages: firstly, through literature research and interview, thirty-seven elements of the evaluation index of customer perceived value of new Chinese-style clothing are defined; secondly, through questionnaire survey and exploratory factor analysis, seven dimensions of the evaluation index of the customer perceived value of new Chinese-style clothing were extracted, which were cultural and educational value, aesthetic value, creative value, green value, engineering value, social value, and quality value, respectively; thirdly, we propose a PSO-BP neural network to evaluate the customer perceived value of new Chinese-style clothing, and we choose twenty-two and eight new Chinese-style clothing as training samples and test samples, respectively. The experimental results show that the PSO-BP neural network can accurately evaluate the customer perceived value of new Chinese-style clothing, and its error is controlled by 2.5% compared with the traditional BP neural network. The research results show that enterprises can improve the quality of product design through the new Chinese-style clothing customer perceived value evaluation indicators and models, and then improve their sustainable competitive advantage, so as to achieve the sustainable development of the new Chinese-style clothing industry ultimately.
Funder
Chinese National Funding of Social Sciences
Subject
Computer Science Applications,Software
Cited by
1 articles.
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