Theses for Computer Science

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Browsing Theses for Computer Science by Subject "blockchain technology"

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    Customs Trade Facilitation and Compliance for Ecommerce using Blockchain and Data Mining
    (The British University in Dubai (BUiD), 2021-07) Alqaryouti, Omar
    Electronic 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.
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    Examining the Factors affecting the sustainability of blockchain technology in higher education using a hybrid SEM-ANN approach
    (The British University in Dubai (BUiD), 2022-10) AL SHAMSI, MOHAMMED SALEM MATAR
    Blockchain technology has received considerable attention during the last few years. Blockchain technology permits the creation of a distributed record of a decentralized digital event in which data and related transactions are not controlled by a third party. However, little is known concerning what affects their sustainable use for educational purposes. Consequently, there are three primary goals for this research. A systematic review is conducted to address the research gaps in the literature on Blockchain adoption from the lens of information system (IS) models and theories. The systematic review included empirical studies published between January 2010 and December 2021 on the topic of blockchain adoption. Among the 918 articles, 30 articles were critically analyzed based on the inclusion criteria. This research, therefore, develops a theoretical model based on extracting constructs from the protection motivation theory (PMT) and expectation confirmation model (ECM) to understand the sustainable use of blockchain in higher education. The developed model was then tested based on data collected through an online survey from 374 university students in the UAE who used blockchain technology for educational purposes. The model was empirically validated using a hybrid structural equation modelling-artificial neural network (SEM-ANN) approach. The hypotheses testing results reinforced most of the suggested hypotheses in the developed model. The sensitivity analysis results for model 1 revealed that satisfaction has the most considerable effect on the sustainable use of blockchain technology with 100% normalized importance, followed by perceived usefulness (58.8%), perceived severity (12.1%), and response cost (9.2%). Besides, the sensitivity analysis for model 2 showed that perceived usefulness has the most considerable effect on the sustainable use of blockchain technology with 100% normalized importance. However, expectation confirmation has 29.2%. Theoretically, integrating the PMT and ECM will add significant value to the validation of the two theories in general and the blockchain in specific. Practically, understanding the impact of security factors would assist in understanding the effect of security incidents on the sustainable use of technology in higher educational institutions. In addition, governments, academia, businesses, and individuals often tend to share resources over a distributed ledger secured by means of cryptography. Blockchain technology also helps in facilitating the traceable, secure, and verifiable exchange of educational data across institutions effectively. Methodologically, the use of SEM-ANN in validating such theoretical models is rarely used, and hence, it would add value to the existing literature by measuring the non-linear relationships among the factors.