Optimize the online shopping title of men’s plain-color shirts in e-commerce based on Kansei Engineering
Online shopping sales of men’s plain-color shirts have fallen in China. Improving the quality of shirts’ online titles can effectively increase click-through rates and transaction rates. The subjective evaluative adjectives (Kansei Words) in the online titles for styling and color design are the mos...
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| Main Authors: | , |
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| Format: | Article |
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Taylor & Francis
2022
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| Online Access: | http://psasir.upm.edu.my/id/eprint/108901/ https://www.tandfonline.com/doi/abs/10.1080/20932685.2022.2085598 |
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| Summary: | Online shopping sales of men’s plain-color shirts have fallen in China. Improving the quality of shirts’ online titles can effectively increase click-through rates and transaction rates. The subjective evaluative adjectives (Kansei Words) in the online titles for styling and color design are the most attractive to consumers. This study uses Exploratory Sequential Mixed Method combined with Kansei Engineering. First, in the phase of qualitative data collection, through interviews and documents, researchers collect 90 subjective evaluative adjectives (Kansei Words). Second, in the phase of quantitative survey research, through questionnaires, card sorting, hierarchical cluster and quick cluster, researchers got Kansei semantical space and established four evaluation dimensions: utility evaluation, symbolic evaluation, design evaluation, and occasion evaluation. Finally, in Kansei semantical space and evaluation dimensions, the final 15 Kansei Words that consumers are most interested in are gotten to optimize the online title. That is, this study finds evaluative adjectives consumers are most interested in through Kansei Engineering. Based on this, consumers’ preferences can be found, and product titles can be optimized to increase sales. Besides, through the research process of Kansei Engineering and Exploratory Sequential Mixed Method, this study provided methodological references for other clothing research categories about consumers’ preferences. |
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