Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining

dc.Location2021 QA 76 A47
dc.SupervisorProfessor Khaled Shaalan
dc.contributor.authorAlqaryouti, Omar
dc.date.accessioned2021-08-11T05:08:24Z
dc.date.available2021-08-11T05:08:24Z
dc.date.issued2021-07
dc.description.abstractElectronic commerce (ecommerce) has penetrated every society, organization, business and household and changed consumers’ habits. It enabled businesses in some nations to trade beyond local borders and reach global proportions. This led to the explosive growth in demands for ecommerce platforms over the last few years and the increased popularity in cross-border trade interactions. The popularity became more evident in times of crisis such as COVID-19 for critical food and medical supplies and products. However, it was disrupted in other markets due to societies going on lockdown, which were further accentuated by borders being shut down. Ecommerce cross-border trade is impacted by regulations of each country. The challenges facing global trade and Customs administrations in particular cover many dimensions. Customs being tasked with protecting society and the smooth trade flow can no longer rely on traditional practices. A coordinated and consorted effort is required to disrupt illegitimate activities and support the mission of Customs. This work first aims to determine factors that drive the adoption of Blockchain technology. Blockchain is characterized for providing visibility, integrity, provenance and immutability across participants through the shared ledger capabilities. Therefore, blockchain technology is used in this study to build a framework to enhance trade facilitation and increase compliance while eliminating risks. This framework will provide advance access to information from various sources and will enable real-time discovery of risks. Accordingly, two off-chain clustering algorithms are proposed to determine value manipulation in ecommerce transactions and increase the efficiency of Customs Audit process. The Software Development Life Cycle (SDLC) methodology is adopted to build the framework. An integrated web application is developed to mock up the end-to-end process in ecommerce. Additionally, the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology is employed for modelling the two proposed clustering algorithms to identify transactional risks. The usability of the proposed framework is evaluated using the System Usability Scale (SUS) resulting in overall high acceptability levels across all users. Furthermore, accuracy measures are used to evaluate performance of the proposed clustering algorithms, reaching 86% for valuation assessment and 87% for risk identification in customs audit. The proposed framework will revolutionize the way trade supply chain is handled. It will create a shift from reactive limited visibility to proactive full visibility mode and properly manage various scenarios such as the current health hurdles and any future challenges lurching around.en_US
dc.identifier.other20171464
dc.identifier.urihttps://bspace.buid.ac.ae/handle/1234/1886
dc.language.isoenen_US
dc.publisherThe British University in Dubai (BUiD)en_US
dc.subjectblockchainen_US
dc.subjectdata miningen_US
dc.subjectclusteringen_US
dc.subjecte-Commerceen_US
dc.subjectcustomsen_US
dc.subjecttrade supply chainen_US
dc.subjectelectronic commerceen_US
dc.subjectCOVID-19en_US
dc.subjectblockchain technologyen_US
dc.titleCustoms Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Miningen_US
dc.title.alternativeتسهيل التجارة والامتثال في الإدارات الجمركية للتجارة الإلكترونية باستخدام تقنية البلوكتشين والتنقيب عن البياناتen_US
dc.typeThesisen_US
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