Translated Titles

Effects of Relevance of Recommended Products on Shopping Experience



Key Words

相關性 ; 卡片分類 ; 科技接受模式 ; Relevance ; Card sorting ; Technology Acceptance Model



Volume or Term/Year and Month of Publication


Academic Degree Category




Content Language


Chinese Abstract


English Abstract

Recommended products are commonly displayed around target products on shopping websites. Most of the recommended products relate to the target products, but some advertised products may not be so relevant. Previous research has shown that the relevance of recommended products to target products affects customers’ shopping experience and attitude. The higher the relevance is, the more positive the experience and attitude will be. Therefore, the relationship between relevance of recommended products and shopping experience is important. However, insufficient research has been done to explore this relationship. The purpose of this paper is to investigate how customer’s shopping experience changes to recommended products according to different degrees of relevance to target products. To obtain the relevance of products, twenty participants were asked to sort 100 products so that a dendrogram about product relevance was constructed. Based on the dendrogram, 5 levels of relevance were identified. They were the highest relevance, high relevance, medium relevance, low relevance and the lowest relevance, and served as the 5 levels of the independent variable. Five shopping webpages were designed according to these 5 levels of relevance. For each webpage, a target product displayed on the center of the page and 4 recommended products horizontally listed below it. Another40 participants were asked to browse all the five webpages in a random order and to complete a shopping experience questionnaire for measuring participants’ shopping experience of recommendation information quality, shopping relevance and perceived usefulness. Results indicated that the declines of shopping experience from medium to low relevance and from high to medium relevance were significantly sharper than the declines from highest to high relevance and from low to the lowest relevance. A logistic function should be able to describe the relationship between the shopping experience and product relevance. Thus, through the curve estimation modeling, a logistic regression function was derived. It is expected that designers of recommendation systems can apply this function to their design decisions.

Topic Category 管理學院 > 工業工程與管理系碩士班
工程學 > 工程學總論
社會科學 > 管理學
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