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The debate on whether the problem of transnational crime is growing or not rages on. Yet, basic research and reliable data on which to inform this debate are lacking. As a consequence, anecdotal and incomplete information leads to analyses that focus on individual problems and neglect serious structural problems underlying the demand for illegal goods and services. Both theoretical endeavors and policy construction would thus benefit from some corrective analysis. This paper paves the ground for such analysis by focusing on the interface of legal and illegal actors. It first seeks to clarify the meaning of the terms 'international crime' and 'cross-border crime', often referred to as 'transnational crime'. Secondly, it separates for analytical purposes 'enterprise crime' from 'political crime', while recognizing that the two are often combined in practice. Thirdly, it attempts to construct a typology of legal-illegal links and associations, in order to better organize the existing knowledge and data on this subject. Fourthly, it addresses the question of whether the problem is growing, and if so, why. Finally, it outlines research and policy implications.

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As we are moving forward to the 5G era, we are witnessing a transformation in the way networks are designed and behave, with the end-user placed at the epicenter of any decision. One of the most promising contributors towards this direction is the shift from Quality of Service (QoS) to Quality of Experience (QoE) service provisioning paradigms. QoE, i.e., the degree of delight or annoyance of a service as this is perceived by the end-user, paves the way for flexible service management and personalized quality monitoring. This is enabled by exploiting parametric QoE assessment models, namely specific formula-based QoE estimation methods. In this paper, recognizing a gap in the literature between the lack of a proper manual regarding the objective QoE estimation and the ever increasing interest from network stakeholders for QoE intelligence, we provide a comprehensive guide to standardized and state-of-the-art quality assessment models. More specifically, we identify and describe parametric QoE formulas for the most popular service types (i.e., VoIP, online video, video streaming, web browsing, Skype, IPTV and file download services), indicating the key performance indicators (KPIs) and major configuration parameters (MCPs) per type. Throughout the paper, it is revealed that KPIs and MCPs are highly variant per service type, and that, even for the same service, different factors contribute with a different weight on the perceived QoE. This finding can strongly enable a more meaningful resource provisioning across different applications compared to QoE-agnostic schemes. Overall, this paper is a stand-alone, self-contained repository of QoE assessment models for the most common applications, becoming a handy tutorial to parties interested in delving more into QoE network management topics.

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