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Abstract

This dissertation studied the interlink connecting irregular human migration and five representative types of cross-border crimes (Drugs, human smuggling, human trafficking, weapons, and wildlife) impacting the security of the European Union (EU). Following the introduction, a thematic literature review of scholarly journals, books, and relevant reports identified that irregular migration and trafficking crimes are interlinked. However, a review of the evidence gathered from these sources to support the connection, proved to be mainly anecdotal information with many authors specifically stating that statistical data on the frequency of these phenomena occurring together was limited. As a result, the literature review identified an area for further investigation in addition to providing an overview of the topic.
Therefore, to investigate the interlink between these phenomena, this exploratory research collected and analysed press releases and news articles that reported on irregular migration and cross-border commodity crimes occurring together (convergence), from an online database. Articles were collected on events that occurred between 01 January 2018 – 31 December 2022 in the geographic region of countries around the Mediterranean area due to the main internationally recognised migration routes that flow into the EU. The extracted articles were manually read, and the content analysed using existing literature to validate the reported information. As a result, this study aims to contribute to the knowledge base by determining the magnitude of occurrence between trafficking crimes and irregular migration, in addition to providing contextual information.
The results found relevant news articles that reported irregular migration and at least one studied trafficking crime converged episodically depending on the date and illicit market in focus. The highest convergence rate existed between irregular migration and human smuggling with 10.6% of retrieved articles. The second highest rate was human trafficking (7.8%). The third most frequent convergence occurred with drug trafficking (5.1%). Finally, weapon and wildlife trafficking saw the lowest convergence rates (0.5%). Further, the study produced qualitative information about illicit flows, modius operandi, offenders, and routes. The implication of this research contributes to the cross-border crime knowledge base and provides an evidence-base for researchers and decision-makers on EU security. Finally, this study lays the foundation for further research opportunities. For example, harnessing the power of artificial intelligence (AI), such as large language models (i.e. ChatGPT) to scrape information from across the Inter-Web (larger dataset) for potential real-time signals intelligence for triggers of irregular migration and cross-border crime risk indicators.

Course: Risk and Security Management - BSc (Hons) - C1565

Date Deposited: 2024-11-07

URI/permalink: https://library.port.ac.uk/dissert/dis14494.html