网络购物中的消费者欺诈：通过数据挖掘检测风险指标

IF 4.2 3区管理学 Q2 BUSINESS

International Journal of Electronic Commerce Pub Date : 2022-06-24 DOI:10.1080/10864415.2022.2076199

T. Knuth, Dennis C. Ahrholdt

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引用次数: 4

摘要

摘要网络购物中的消费者欺诈已成为网络零售商面临的一个重大问题和严峻挑战。然而，对于学术界和实践来说，检测滞后，关于交易数据中风险指标的数据驱动知识仍然非常有限。因此，本研究侧重于基于实证数据识别网上购物交易数据中的消费者欺诈风险指标和组合。我们演示了使用决策树作为数据挖掘技术来分析世界上最大的在线零售商之一的数据。从而，确定了几种欺诈模式，这些模式可以将网上购物交易区分为欺诈和合法案件。因此，研究结果可以指导未来实践和理论工作中变量的选择以及欺诈预防行动和系统的设计。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Consumer Fraud in Online Shopping: Detecting Risk Indicators through Data Mining

ABSTRACT Consumer fraud in online shopping has become a major problem and severe challenge for online retailers. However, detection lags behind — for academia and practice — and data-driven knowledge about risk indicators in transaction data is still very limited. Thus, this study focuses on the empirical data-based identification of consumer fraud risk indicators and combinations in online shopping transaction data. We demonstrate the use of a decision tree as a data mining technique for analysis of data from one of the world’s largest online retailers. Thereby, several patterns of fraud that improve separation of online shopping transactions into fraudulent and legitimate cases are identified. Thus, results can guide the choice of variables and design of fraud prevention actions and systems in future practical and theoretical work.

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来源期刊

International Journal of Electronic Commerce 工程技术-计算机：软件工程

CiteScore

7.20

自引率

16.00%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Electronic Commerce is the leading refereed quarterly devoted to advancing the understanding and practice of electronic commerce. It serves the needs of researchers as well as practitioners and executives involved in electronic commerce. The Journal aims to offer an integrated view of the field by presenting approaches of multiple disciplines. Electronic commerce is the sharing of business information, maintaining business relationships, and conducting business transactions by digital means over telecommunications networks. The Journal accepts empirical and interpretive submissions that make a significant novel contribution to this field.