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• W2892516983 abstract "Advancements in digital technology and devices enlarge dimensions of e-commerce, reforming the ways that consumers shop and purchase products and services. In particular, the mixed use of online, mobile, and offline channels and devices for shopping provides B2C firms with unprecedented challenges and opportunities to develop effective segmentation approaches that capture multitude of newly emerging consumers’ shopping patterns. This paper aims to classify consumers along with their shopping patterns and channel preferences by using rank order survey data from Korean and American consumers on their path-to-purchase behaviors. Cluster analysis and Association Rule Mining (ARM) are applied for segmentation and its characterization. Relative importance of path-to-purchase factors such as information search location, payment method, delivery option, and payment location are assessed to determine the differences in Korean and American consumers regarding their shopping patterns and preferences. Network visualization of rules shows the differences in shopping preference and patterns of Korean and US consumers both at micro and macro levels." @default.
• W2892516983 created "2018-10-05" @default.
• W2892516983 creator A5015274418 @default.
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• W2892516983 date "2018-11-01" @default.
• W2892516983 modified "2023-09-26" @default.
• W2892516983 title "A new approach to segmenting multichannel shoppers in Korea and the U.S." @default.
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• W2892516983 doi "https://doi.org/10.1016/j.jretconser.2018.09.007" @default.
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