Hells Angels, positionnement stratégique et réussite criminelle : analyse des transactions monétaires d’un réseau illicite de distribution de drogues

Les travaux traditionnels sur le crime organisé indiquent que le statut d’un individu déterminerait son succès individuel. Des recherches alternatives sur les réseaux des organisations criminelles et de la réussite criminelle indiquent que le rang est moins important que la croyance générale et que les mesures de positionnement stratégique de réseau sont plus susceptibles de déterminer le succès criminel. Ce mémoire étudie les variations des gains criminels au sein de l’organisation de distribution illicite de stupéfiants des Hells Angels. Son objectif est de distinguer, à l’aide de données de comptabilité autorévélées, les éléments influençant ces différences dans le succès criminel en fonction du positionnement plus stratégique ou vulnérable d’un individu au sein de son réseau. Les résultats révèlent des moyennes de volume d’argent transigé beaucoup plus élevées que ce qui est généralement recensé. La distribution de ces capitaux est largement inégale. La disparité des chances liées à l’association criminelle se retrouve aussi dans la polarisation entre les individus fortement privilégiés et les autres qui ont une capacité de positionnement médiocre. Le croisement entre les positions et l’inégalité des gains présente que le positionnement de l’individu dans son réseau est un meilleur prédicteur de réussite criminelle que toute autre variable contextuelle ou de rang. Enfin et surtout, en contradiction avec la littérature, le fait d’atteindre de haut rang hiérarchique nuirait au succès criminel, les résultats montrant que cet état réduit l’accès au crédit, réduit les quantités de drogue par transaction et augmente le prix de la drogue à l’unité.

User Profile Management and Selection in Context-Aware Service Platforms for Networks Beyond 3G

In recent years, progress in the area of mobile telecommunications has changed our way of life, in the private as well as the business domain. Mobile and wireless networks have ever increasing bit rates, mobile network operators provide more and more services, and at the same time costs for the usage of mobile services and bit rates are decreasing. However, mobile services today still lack functions that seamlessly integrate into users’ everyday life. That is, service attributes such as context-awareness and personalisation are often either proprietary, limited or not available at all. In order to overcome this deficiency, telecommunications companies are heavily engaged in the research and development of service platforms for networks beyond 3G for the provisioning of innovative mobile services. These service platforms are to support such service attributes. Service platforms are to provide basic service-independent functions such as billing, identity management, context management, user profile management, etc. Instead of developing own solutions, developers of end-user services such as innovative messaging services or location-based services can utilise the platform-side functions for their own purposes. In doing so, the platform-side support for such functions takes away complexity, development time and development costs from service developers. Context-awareness and personalisation are two of the most important aspects of service platforms in telecommunications environments. The combination of context-awareness and personalisation features can also be described as situation-dependent personalisation of services. The support for this feature requires several processing steps. The focus of this doctoral thesis is on the processing step, in which the user’s current context is matched against situation-dependent user preferences to find the matching user preferences for the current user’s situation. However, to achieve this, a user profile management system and corresponding functionality is required. These parts are also covered by this thesis. Altogether, this thesis provides the following contributions: The first part of the contribution is mainly architecture-oriented. First and foremost, we provide a user profile management system that addresses the specific requirements of service platforms in telecommunications environments. In particular, the user profile management system has to deal with situation-specific user preferences and with user information for various services. In order to structure the user information, we also propose a user profile structure and the corresponding user profile ontology as part of an ontology infrastructure in a service platform. The second part of the contribution is the selection mechanism for finding matching situation-dependent user preferences for the personalisation of services. This functionality is provided as a sub-module of the user profile management system. Contrary to existing solutions, our selection mechanism is based on ontology reasoning. This mechanism is evaluated in terms of runtime performance and in terms of supported functionality compared to other approaches. The results of the evaluation show the benefits and the drawbacks of ontology modelling and ontology reasoning in practical applications.

Entrepreneurship, ties and relational networks: the case of a public-private cross-border tourism product

The thesis aims to understand the processes of entrepreneurship that try to create businesses or products with a high degree of complexity. This complexity comes from the fact that these products or initiatives can only be viable with the concurrence of a large number of heterogeneous actors (public, private, from different regions, etc..) which interact in a relational context. A case with these characteristics is the Camí dels Bons Homes. The thesis analyzes the evolution of the relational network from the point of view of its structure and content of its links. The results show and explain the observed changes in the network structure and the changes in the ties content. This analysis of the content of ties contributes to a new systematization and operationalization of ties’ content. Moreover this analysis takes in account negative ties, a less discussed issue in literature.

The social relations of business representation and devolved governance in the United Kingdom

The reform of regional governance in the United Kingdom has been, in part, premised on the notion that regions provide new territories of action in which cooperative networks between business communities and state-agencies can be established. Promoting business interests is seen as one mechanism for enhancing the economic competitiveness and performance of 'laggard' regions. Yet, within this context of change, business agendas and capacities are often assumed to exist 'out there, as a resource waiting to be tapped by state institutions. There is little recognition that business organisations' involvement in networks of governance owes much to historical patterns and practices of business representation, to the types of activities that exist within the business sector, and to interpretations of their own role and position within wider policymaking and implementation networks. This paper, drawing on a study of business agendas in post-devolution Scotland, demonstrates that in practice business agendas are highly complex. Their formation in any particular place depends on the actions of reflexive agents, whose perspectives and capacities are shaped by the social, economic, and political contexts within which they are operating. As such, any understanding of business agendas needs to identify the social relations of business as a whole, rather than assuming away such complexities.

Learning across business sectors: Knowledge sharing between aerospace and construction

This report addresses the extent that managerial practices can be shared between the aerospace and construction sectors. Current recipes for learning from other industries tend to be oversimplistic and often fail to recognise the embedded and contextual nature of managerial knowledge. Knowledge sharing between business sectors is best understood as an essential source of innovation. The process of comparison challenges assumptions and better equips managers to cope with future change. Comparisons between the aerospace and construction sectors are especially useful because they are so different. The two sectors differ hugely in terms of their institutional context, structure and technological intensity. The aerospace sector has experienced extensive consolidation and is dominated by a small number of global companies. Aerospace companies operate within complex networks of global interdependency such that collaborative working is a commercial imperative. In contrast, the construction sector remains highly fragmented and is characterised by a continued reliance on small firms. The vast majority of construction firms compete within localised markets that are too often characterised by opportunistic behaviour. Comparing construction to aerospace highlights the unique characteristics of both sectors and helps explain how managerial practices are mediated by context. Detailed comparisons between the two sectors are made in a range of areas and guidance is provided for the implementation of knowledge sharing strategies within and across organisations. The commonly accepted notion of ‘best practice’ is exposed as a myth. Indeed, universal models of best practice can be detrimental to performance by deflecting from the need to adapt continuously to changing circumstances. Competitiveness in the construction sector too often rests on efficiency in managing contracts, with a particular emphasis on the allocation of risk. Innovation in construction tends to be problem-driven and is rarely shared from project to project. In aerospace, the dominant model of competitiveness means that firms have little choice other than to invest in continuous innovation, despite difficult trading conditions. Research and development (R&D) expenditure in aerospace continues to rise as a percentage of turnovers. A sustained capacity for innovation within the aerospace sector depends crucially upon stability and continuity of work. In the construction sector, the emergence of the ‘hollowed-out’ firm has undermined the industry’s capacity for innovation. Integrated procurement contexts such as prime contracting in construction potentially provide a more supportive climate for an innovation-based model of competitiveness. However, investment in new ways of working depends upon a shift in thinking not only amongst construction contractors, but also amongst the industry’s major clients.

Models for evolving networks: with applications in telecommunication and online activities

Driven by a range of modern applications that includes telecommunications, e-business and on-line social interaction, recent ideas in complex networks can be extended to the case of time-varying connectivity. Here we propose a general frame- work for modelling and simulating such dynamic networks, and we explain how the long time behaviour may reveal important information about the mechanisms underlying the evolution.

Factors affecting regional SMEs progression to Digital Business Ecosystems

SMEs are widely recognized as an important driving force of economic growth, yet, their uptake of ICT is still very low. Tosupport SMEs ICT adoption and to foster regional development, in 2000, the Lisbon Strategy on the Information Society andKnowledge-based economy created a vision for 2010 towards the creation of the European Digital Business Ecosystems(DBE). This paper is positioned within that context and reports upon a project involving 6000 SMEs whose aim was tosupport ICT adoption and to encourage SME networks through the creation of a Regional Business Portal. The papere xplores factors affecting the regional SMEs participating in the DBE. An in-depth longitudinal case study approach was adopted and multiple sources of evidence were used. Many factors affecting SMEs progression to DBE were identified:including people and organization, environmental, diffusion networks, technological, regional and time factors

Social networks: evolving graphs with memory dependent edges

The plethora, and mass take up, of digital communication tech- nologies has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the ex- istence or otherwise of certain infinite products and series involving age dependent model parameters. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

An overview of the use of neural networks for data mining tasks

In the recent years, the area of data mining has been experiencing considerable demand for technologies that extract knowledge from large and complex data sources. There has been substantial commercial interest as well as active research in the area that aim to develop new and improved approaches for extracting information, relationships, and patterns from large datasets. Artificial neural networks (NNs) are popular biologically-inspired intelligent methodologies, whose classification, prediction, and pattern recognition capabilities have been utilized successfully in many areas, including science, engineering, medicine, business, banking, telecommunication, and many other fields. This paper highlights from a data mining perspective the implementation of NN, using supervised and unsupervised learning, for pattern recognition, classification, prediction, and cluster analysis, and focuses the discussion on their usage in bioinformatics and financial data analysis tasks. © 2012 Wiley Periodicals, Inc.