911 resultados para Associative network theory


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It has been suggested that, in order to maintain its relevance, critical research must develop a strong emphasis on empirical work rather than the conceptual emphasis that has typically characterized critical scholarship in management. A critical project of this nature is applicable in the information systems (IS) arena, which has a growing tradition of qualitative inquiry. Despite its relativist ontology, actor–network theory places a strong emphasis on empirical inquiry and this paper argues that actor–network theory, with its careful tracing and recording of heterogeneous networks, is well suited to the generation of detailed and contextual empirical knowledge about IS. The intention in this paper is to explore the relevance of IS research informed by actor–network theory in the pursuit of a broader critical research project as de? ned in earlier work.

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Sales leadership research has typically taken a leader-focused approach, investigating key questions from a top-down perspective. Yet considerable research outside sales has advocated a view of leadership that takes into account the fact that employees look beyond a single designated individual for leadership. In particular, the social networks of leaders have been a popular topic of investigation in the management literature, although coverage in the sales literature remains rare. The present paper conceptualizes the sales leadership role as one in which the leader must manage a network of simultaneous relationships; several types of sales manager relationships, such as the sales-manager-to-top-manager and the sales-manager-to-sales manager relationships, have received limited attention in the sales literature to date. Taking an approach based on social network theory, we develop a conceptualization of the sales manager as a "network engineer," who must manage multiple relationships, and the flows between them. Drawing from this model, we propose a detailed agenda for future sales research. © 2012 PSE National Educational Foundation. All rights reserved.

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EMBARGOED The literature on inter-organisational collaboration, although wide-ranging, offers little guidance on collaboration as process. It focuses in the main on human attributes like leadership, trust and agency, but gives little consideration to the role of objects in the development of inter-organisational collaborations. A central aim of this thesis is to understand the interaction of objects and humans in the development of a particular health and social care partnership in the North East of England. This socio-material perspective was achieved through actor-network theory (ANT) as a methodology, in which the researcher is equally sensitised to the role of human and non-human entities in the development of a network. The case study is that of the North East Lincolnshire Care Trust Plus (CTP). This was a unique health and social care collaboration arrangement between North East Lincolnshire Council and North East Lincolnshire Primary Care Trust, setup to address heath inequalities in the region. The CTP was conceived and developed at a local level by the respective organisation’s decision makers in the face of considerable opposition from regional policy makers and national regulators. However, despite this opposition, the directors eventually achieved their goal and the CTP became operational on 1st September 2007. This study seeks to understand how the CTP was conceived and developed, in the face of this opposition. The thesis makes a number of original contributions. Firstly, it adds to the current body of literature on collaboration by identifying how objects can help problematize issues and cement inter-organisational collaborations. Secondly it provides a novel account describing how two public sector organisations created a unique collaboration, despite pressing resistance from the regulatory authorities; and thirdly it extends Callon’s (1996) notion of problematization to examine how, what is rather vaguely described as ‘context’ in the literature, becomes enmeshed in decisions to collaborate. UNTIL 03/02/2016 THIS THESIS IS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

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The aim of this research is to investigate if a celebrity can be a mediator between two brands so that a negative event happening to one brand can spill over to a completely unrelated brand, which shares with the first brand only the celebrity endorser. Even though celebrity endorsement is a popular marketing strategy and celebrities often endorse multiple brands, so far there has not been any systematic study on this topic. Drawing on Associative Network Theory and the Meaning Transfer Model as theoretical framework, this research finds out that negative publicity about a brand can spill over and thereby not only hurt consumers’ attitude toward the celebrity endorser but also toward a second brand that is endorsed by the same celebrity. An unexpected finding is that celebrities can act as a protective shield for brands by weakening the direct impact of negative publicity.

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ABSTRACT : A firm's competitive advantage can arise from internal resources as well as from an interfirm network. -This dissertation investigates the competitive advantage of a firm involved in an innovation network by integrating strategic management theory and social network theory. It develops theory and provides empirical evidence that illustrates how a networked firm enables the network value and appropriates this value in an optimal way according to its strategic purpose. The four inter-related essays in this dissertation provide a framework that sheds light on the extraction of value from an innovation network by managing and designing the network in a proactive manner. The first essay reviews research in social network theory and knowledge transfer management, and identifies the crucial factors of innovation network configuration for a firm's learning performance or innovation output. The findings suggest that network structure, network relationship, and network position all impact on a firm's performance. Although the previous literature indicates that there are disagreements about the impact of dense or spare structure, as well as strong or weak ties, case evidence from Chinese software companies reveals that dense and strong connections with partners are positively associated with firms' performance. The second essay is a theoretical essay that illustrates the limitations of social network theory for explaining the source of network value and offers a new theoretical model that applies resource-based view to network environments. It suggests that network configurations, such as network structure, network relationship and network position, can be considered important network resources. In addition, this essay introduces the concept of network capability, and suggests that four types of network capabilities play an important role in unlocking the potential value of network resources and determining the distribution of network rents between partners. This essay also highlights the contingent effects of network capability on a firm's innovation output, and explains how the different impacts of network capability depend on a firm's strategic choices. This new theoretical model has been pre-tested with a case study of China software industry, which enhances the internal validity of this theory. The third essay addresses the questions of what impact network capability has on firm innovation performance and what are the antecedent factors of network capability. This essay employs a structural equation modelling methodology that uses a sample of 211 Chinese Hi-tech firms. It develops a measurement of network capability and reveals that networked firms deal with cooperation between, and coordination with partners on different levels according to their levels of network capability. The empirical results also suggests that IT maturity, the openness of culture, management system involved, and experience with network activities are antecedents of network capabilities. Furthermore, the two-group analysis of the role of international partner(s) shows that when there is a culture and norm gap between foreign partners, a firm must mobilize more resources and effort to improve its performance with respect to its innovation network. The fourth essay addresses the way in which network capabilities influence firm innovation performance. By using hierarchical multiple regression with data from Chinese Hi-tech firms, the findings suggest that there is a significant partial mediating effect of knowledge transfer on the relationships between network capabilities and innovation performance. The findings also reveal that the impacts of network capabilities divert with the environment and strategic decision the firm has made: exploration or exploitation. Network constructing capability provides a greater positive impact on and yields more contributions to innovation performance than does network operating capability in an exploration network. Network operating capability is more important than network constructing capability for innovative firms in an exploitation network. Therefore, these findings highlight that the firm can shape the innovation network proactively for better benefits, but when it does so, it should adjust its focus and change its efforts in accordance with its innovation purposes or strategic orientation.

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The study examines the internationalisation process of a contemporary SME firm and explores the impact of its business network on this development. The objective of the study is to understand SME internationalisation and its dynamics from a network perspective. The purpose of this research project is to describe and explore the development process of a firm and its business network by identifying the changes, critical events and influence factors that form this development. It is a qualitative case study, which focuses on a Finnish focal firm and its respective business network as it expands into the Greek market. It is a longitudinal research process, which covers a period of time from 1994 to 2004. The empirical study concentrates on the paper trading and converting business. The study builds on the network theory and the framework provided by Johanson and Mattsson's (1988) model on network internationalisation. The incremental internationalisation theories and network theories form the theoretical focus. The research project is organised according to a process view. The focal firm evolves from a domestically-oriented small subsidiary into an internationally experienced company, which has activities in several market areas and numerous business networks in various market segments and product categories. The findings illustrate the importance of both the domestic and foreign business network context in a firm's internationalisation process. The results of the study suggest theoretical modifications on a firm's internationalisation process by broadening the perspective and incorporating the strategic context of a firm. The findings suggest that internationalisation process is a non-linear process, which does not have a deterministic order in its development. The findings emphasise the significance of relational networks, both managerial and entrepreneurial, for establishing position in foreign markets. It implies that a firm's evolution is significantly influenced by its business network and by critical events. Business networks gain coherence due to common goals and they use accumulated capabilities to exploit market opportunities. The business network sets constraints and provides opportunities, which makes the related decision making strategically important. The firm co-evolves with its business network. The research project provides an instrumental case study with a description of an SME internationalisation process. It contributes to existing knowledge by illustrating dynamics in an international business network and by pinpointing the importance of suppliers, customers, partners, ownerships and competition to the internationalisation process.

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The use of n-tuple or weightless neural networks as pattern recognition devices has been well documented. They have a significant advantages over more common networks paradigms, such as the multilayer perceptron in that they can be easily implemented in digital hardware using standard random access memories. To date, n-tuple networks have predominantly been used as fast pattern classification devices. The paper describes how n-tuple techniques can be used in the hardware implementation of a general auto-associative network.

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We present an intuitive geometric approach for analysing the structure and fragility of T1-weighted structural MRI scans of human brains. Apart from computing characteristics like the surface area and volume of regions of the brain that consist of highly active voxels, we also employ Network Theory in order to test how close these regions are to breaking apart. This analysis is used in an attempt to automatically classify subjects into three categories: Alzheimer’s disease, mild cognitive impairment and healthy controls, for the CADDementia Challenge.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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It is currently widely accepted that the understanding of complex cell functions depends on an integrated network theoretical approach and not on an isolated view of the different molecular agents. Aim of this thesis was the examination of topological properties that mirror known biological aspects by depicting the human protein network with methods from graph- and network theory. The presented network is a partial human interactome of 9222 proteins and 36324 interactions, consisting of single interactions reliably extracted from peer-reviewed scientific publications. In general, one can focus on intra- or intermodular characteristics, where a functional module is defined as "a discrete entity whose function is separable from those of other modules". It is found that the presented human network is also scale-free and hierarchically organised, as shown for yeast networks before. The interactome also exhibits proteins with high betweenness and low connectivity which are biologically analyzed and interpreted here as shuttling proteins between organelles (e.g. ER to Golgi, internal ER protein translocation, peroxisomal import, nuclear pores import/export) for the first time. As an optimisation for finding proteins that connect modules, a new method is developed here based on proteins located between highly clustered regions, rather than regarding highly connected regions. As a proof of principle, the Mediator complex is found in first place, the prime example for a connector complex. Focusing on intramodular aspects, the measurement of k-clique communities discriminates overlapping modules very well. Twenty of the largest identified modules are analysed in detail and annotated to known biological structures (e.g. proteasome, the NFκB-, TGF-β complex). Additionally, two large and highly interconnected modules for signal transducer and transcription factor proteins are revealed, separated by known shuttling proteins. These proteins yield also the highest number of redundant shortcuts (by calculating the skeleton), exhibit the highest numbers of interactions and might constitute highly interconnected but spatially separated rich-clubs either for signal transduction or for transcription factors. This design principle allows manifold regulatory events for signal transduction and enables a high diversity of transcription events in the nucleus by a limited set of proteins. Altogether, biological aspects are mirrored by pure topological features, leading to a new view and to new methods that assist the annotation of proteins to biological functions, structures and subcellular localisations. As the human protein network is one of the most complex networks at all, these results will be fruitful for other fields of network theory and will help understanding complex network functions in general.

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Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

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This study deals with the internationalization behavior of a new and specific type of e-business company, namely the network managing e-business company (NM-EBC). The business model of such e-business companies is based on providing a platform and applications for users to connect and interact, on gathering and channeling the inputs provided by the users, and on organizing and managing the cross-relationships of the various participants. Examples are online communities, matching platforms, and portals. Since NM-EBCs internationalize by replicating their business model in a foreign market and by building up and managing a network of users, who provide input themselves and interact with each other, they have to convince users in foreign markets to join the network and hence to adopt their platform. We draw upon Rogers’ Diffusion of Innovations Theory and Network Theory to explain the internationalization behavior of NM-EBCs. These two theories originate from neighboring disciplines and have not yet been used to explain the internationalization of firms. We combine both theories and formulate hypotheses about which strategies NM-EBCs may choose to expand abroad. To test the applicability of our theory and to gain rich data about the internationalization behavior of these firms, we carried out multiple case studies with internationally active Germany-based NM-EBCs.

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In 1906, two American industrialists, John Munroe Longyear and Frederick Ayer, formed the Arctic Coal Company to make the first large scale attempt at mining in the high-Arctic location of Spitsbergen, north of the Norwegian mainland. In doing so, they encountered numerous obstacles and built an organization that attempted to overcome them. The Americans sold out in 1916 but others followed, eventually culminating in the transformation of a largely underdeveloped landscape into a mining region. This work uses John Law’s network approach of the Actor Network Theory (ANT) framework to explain how the Arctic Coal Company built a mining network in this environmentally difficult region and why they made the choices they did. It does so by identifying and analyzing the problems the company encountered and the strategies they used to overcome them by focusing on three major components of the operations; the company’s four land claims, its technical system and its main settlement, Longyear City. Extensive comparison between aspects of Longyear City and the company’s choices of technology with other American examples place analysis of the company in a wider context and helps isolate unique aspects of mining in the high-Arctic. American examples dominate comparative sections because Americans dominated the ownership and upper management of the company.

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By combining complex network theory and data mining techniques, we provide objective criteria for optimization of the functional network representation of generic multivariate time series. In particular, we propose a method for the principled selection of the threshold value for functional network reconstruction from raw data, and for proper identification of the network's indicators that unveil the most discriminative information on the system for classification purposes. We illustrate our method by analysing networks of functional brain activity of healthy subjects, and patients suffering from Mild Cognitive Impairment, an intermediate stage between the expected cognitive decline of normal aging and the more pronounced decline of dementia. We discuss extensions of the scope of the proposed methodology to network engineering purposes, and to other data mining tasks.

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We study the notion of approximate entropy within the framework of network theory. Approximate entropy is an uncertainty measure originally proposed in the context of dynamical systems and time series. We first define a purely structural entropy obtained by computing the approximate entropy of the so-called slide sequence. This is a surrogate of the degree sequence and it is suggested by the frequency partition of a graph. We examine this quantity for standard scale-free and Erdös-Rényi networks. By using classical results of Pincus, we show that our entropy measure often converges with network size to a certain binary Shannon entropy. As a second step, with specific attention to networks generated by dynamical processes, we investigate approximate entropy of horizontal visibility graphs. Visibility graphs allow us to naturally associate with a network the notion of temporal correlations, therefore providing the measure a dynamical garment. We show that approximate entropy distinguishes visibility graphs generated by processes with different complexity. The result probes to a greater extent these networks for the study of dynamical systems. Applications to certain biological data arising in cancer genomics are finally considered in the light of both approaches.