Consumer-Driven Usability Test of Mobile Application for Tea Recommendation Service
Source abstract
Abstract
The rapidly growing interest in healthy lifestyles and the health benefit of foods and the growing tea-consuming population are driving the growth of the tea industry. In particular, the growing preference among Millennials for premium blended tea is leading the growth of the tea market. In this paper, we study the feasibility of recommendation services for blended tea, which has not been addressed well by existing recommender systems. To this end, we design TeaPickTM, a mobile application that suggests a blend of tea suited to the user’s preferences including desired health benefits. To evaluate the application and its recommendations, we conduct not only a usability test, but also a consumer acceptance test with 31 participants. Our user study shows that the participants were positive about the recommendation service provided by our application and were generally satisfied with the recommended tea.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Recommender Systems and Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Science and Technology, Kookmin University, Seoul 02707, Korea
School of Computer Science and Engineering, KOREATECH, Cheonan 31253, Korea
References (29)
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