A Study on the Repurchase Intention of Korean College Students in Cross-Border B2C e-Commerce

Kwak, Su-Young; Kim, Mie-Jung

doi:10.20462/tebs.2018.2.19.1.263

Cited by 1 publication

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“…He built a system that could handle various language support and refunds for product returns to eliminate consumer anxiety. Although the scholar saw the problems in e-commerce and established a system to increase people's repurchase rate, he did not verify whether the system was feasible [3]. Zhang B found that with the rise of emerging technologies and consumption patterns in the context of "big data," e-commerce has become mainstream.…”

Section: Related Workmentioning

confidence: 99%

Big Data Mining Method of E-Commerce Consumption Pattern Based on Mobile Platform

2022

Security and Communication Networks

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With the emergence of e-commerce, not only can people more abundantly obtain a variety of products and services and faster, but also e-commerce can also greatly improve people's quality of life. This study aims to study how to analyze the big data mining method based on the e-commerce consumption pattern of the mobile platform. In fact, it is to study the role of big data mining methods in e-commerce consumption patterns. This study proposes why we should study big data mining methods and introduces the conceptual knowledge around e-commerce and data mining. We can see that e-commerce is not only convenient but also low in cost. Ten consumers scored 65–78 points for the competitiveness of e-commerce, and 73–84 points for low cost, with the highest score for convenience. It can be seen that the biggest advantage of e-commerce is convenience. It can be seen that the percentage of Taobao in 2015 was 45.6%, and the percentage in 2018 was 79.5%, so it can be seen that e-commerce is rapidly developing. From the results of the experimental analysis, it can be seen that e-commerce is loved by the public, so it is the most important to make the healthy and sustainable development of e-commerce, and data mining can mine a large amount of data, thereby promoting the development of e-commerce.

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Section: Related Workmentioning

confidence: 99%

Big Data Mining Method of E-Commerce Consumption Pattern Based on Mobile Platform

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

A Study on the Repurchase Intention of Korean College Students in Cross-Border B2C e-Commerce

Cited by 1 publication

References 0 publications

Big Data Mining Method of E-Commerce Consumption Pattern Based on Mobile Platform

Big Data Mining Method of E-Commerce Consumption Pattern Based on Mobile Platform

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