Hybrid kansei engineering system for website user interface design / Mohd Yuzi Zali
Past literature on website user interface design and user experience has shown that feeling and emotion play a very important role in determining users' browsing behavior and decision in their online activity. The design elements used to construct a website had a great impact on how a user perc...
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/63715/1/63715.pdf |
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| Summary: | Past literature on website user interface design and user experience has shown that feeling and emotion play a very important role in determining users' browsing behavior and decision in their online activity. The design elements used to construct a website had a great impact on how a user perceives and responses to the website. Design that is visually appealing and emotionally attractive will make a user stay longer on a website. Kansei Engineering is a technology that aims to integrate feeling and emotion into product design. According to past literatures, there were several success story of Kansei Engineering implementations in various fields. In website development, there was a study on Kansei Engineering which produced a guideline for developing Kansei website user interface called Kansei Web Design Guideline (KWDG). Using this guideline, a user can identify related web design elements based on intended Kansei word. This research aims to extend the previous research by investigating the possibility of automating Kansei recognition from a given design specimen. Using Hybrid Kansei Engineering System (KES), this study introduced a new Kansei Web Relational Data Model (KWRDM) that served as a data model to define Kansei web design. On top of this new data model, a prototype of Kansei Web Recognition System (KWRS) was developed featuring applications for Forward KES and Backward KES. Forward KES application is capable of identifying web design elements from a given Kansei word while Backward KES application is used to automatically recognize Kansei from a set of design elements. The prototype has been tested using five website design specimens of different Kansei concepts and feedback from 40 respondents has been collected. While the result varies between the tested specimens, the analysis indicated that with certain improvements, KWRDM can be used to automate Kansei web recognition. The author recommended the inclusion of image recognition feature and the enhancement of KWRDM to improve the KWRS. The outcome of this study is significant to Kansei research on website user interface. It will open a new opportunity towards engaging and affective website user interface design which embed human feeling and emotion. ii |
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