P-ISSN 1834-6707
E-ISSN 1834-6715
Vol. 13, Issue 2, 2019September 30, 2019 AEST
Data Analysis Techniques for Enhancing the Performance of Customs
Data Analysis Techniques for Enhancing the Performance of Customs
Danilo Desiderio,
Articles in Vol. 13, Issue 2, 2019
Vol. 13, Issue 2, 2019
- EditorialDavid Widdowson
- The Impact and Countermeasures of New Tax Policy for Cross-Border E-Commerce in ChinaBowen ShiXiang GaoLiangting JiaXiangnan Guo
- Data Analysis Techniques for Enhancing the Performance of CustomsDanilo Desiderio
- Understanding Tax and Customs Policies for Retail Import Cross-Border E-Commerce in ChinaXiangyang Li
- Establishing Risk and Targeting Profiles Using Dara Mining: Decision TreesBassem Chermiti
- Identifying Trade Mis-Invoicing Through Customs Data AnalysisYeon Soo Choi
- Revenue Maximisation Versus Trade Facilitation: The Contribution of Automated Risk ManagementChristopher Grigoriou
- Mirror Analysis as a Support for Risk Management and Valuation: A Practical StudyChristopher Grigoriou
- How Helpful Are Mirror Statistics for Customs Reform? Lessons From a Decade of Operational UseChristopher GrigoriouFrank KalizinjeGael Raballand
- Data Mining in Customs Risk Detection With Cost-Sensitive ClassificationXin Zhou
- PICARD Conference 2020PICARD Conference
Desiderio, D. (2019). Data Analysis Techniques for Enhancing the Performance of Customs. World Customs Journal, 13(2), 17–22. https://doi.org/10.55596/001c.116211