700 resultados para Strategic knowledge management


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Hollywood has dominated the global film business since the First World War. Economic formulas used by governments to assess levels of industry dominance typically measure market share to establish the degree of industry concentration. The business literature reveals that a marketing orientation strongly correlates with superior market performance and that market leaders that possess a set of six superior marketing capabilities are able to continually outperform rival firms. This paper argues that the historical evidence shows that the Hollywood Majors have consistently outperformed rival firms and rival film industries in each of those six marketing capabilities and that unless rivals develop a similarly integrated and cohesive strategic marketing management approach to the movie business and match the Major studios’ superior capabilities, then Hollywood’s dominance will continue. This paper also proposes that in cyberspace, whilst the Internet does provide a channel that democratises film distribution, the flat landscape of the world wide web means that in order to stand out from the clutter of millions of cyber-voices seeking attention, independent film companies need to possess superior strategic marketing management capabilities and develop effective e-marketing strategies to find a niche, attract a loyal online audience and prosper. However, mirroring a recent CIA report forecasting a multi-polar world economy, this paper also argues that potentially serious longer-term rivals are emerging and will increasingly take a larger slice of an expanding global box office as India, China and other major developing economies and their respective cultural channels grow and achieve economic parity with or surpass the advanced western economies. Thus, in terms of global market share over time, Hollywood’s slice of the pie will comparatively diminish in an emerging multi-polar movie business.

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This thesis consists of three related studies: an ERP Major Issues Study; an Historical Study of the Queensland Government Financial Management System; and a Meta-Study that integrates these and other related studies conducted under the umbrella of the Cooperative ERP Lifecycle Knowledge Management research program. This research provides a comprehensive view of ERP lifecycle issues encountered in SAP R/3 projects across the Queensland Government. This study follows a preliminary ERP issues study (Chang, 2002) conducted in five Queensland Government agencies. The Major Issues Study aims to achieve the following: (1) identify / explicate major issues in relation to the ES life-cycle in the public sector; (2) rank the importance of these issues; and, (3) highlight areas of consensus and dissent among stakeholder groups. To provide a rich context for this study, this thesis includes an historical recount of the Queensland Government Financial Management System (QGFMS). This recount tells of its inception as a centralised system; the selection of SAP and subsequent decentralisation; and, its eventual recentralisation under the Shared Services Initiative and CorpTech. This historical recount gives an insight into the conditions that affected the selection and ongoing management and support of QGFMS. This research forms part of a program entitled Cooperative ERP Lifecycle Knowledge Management. This thesis provides a concluding report for this research program by summarising related studies conducted in the Queensland Government SAP context: Chan (2003); Vayo et al (2002); Ng (2003); Timbrell et al (2001); Timbrell et al (2002); Chang (2002); Putra (1998); and, Niehus et al (1998). A study of Oracle in the United Arab Emirates by Dhaheri (2002) is also included. The thesis then integrates the findings from these studies in an overarching Meta-Study. The Meta-Study discusses key themes across all of these studies, creating an holistic report for the research program. Themes discussed in the meta-study include common issues found across the related studies; knowledge dynamics of the ERP lifecycle; ERP maintenance and support; and, the relationship between the key players in the ERP lifecycle.

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In sustainable development projects, as well as other types of projects, knowledge transfer is important for the organisations managing the project. Nevertheless, knowledge transfer among employees does not happen automatically and it has been found that the lack of social networks and the lack of trust among employees are the major barriers to effective knowledge transfer. Social network analysis has been recognised as a very important tool for improving knowledge transfer in the project environment. Transfer of knowledge is more effective where it depends heavily on social networks and informal dialogue. Based on the theory of social capital, social capital consists of two parts: conduits network and resource exchange network. This research studies the relationships among performance, the resource exchange network (such as the knowledge network) and the relationship network (such as strong ties network, energy network, and trust network) at the individual and project levels. The aim of this chapter is to present an approach to overcoming the lack of social networks and lack of trust to improve knowledge transfer within project-based organisations. This is to be done by identifying the optimum structure of relationship networks and knowledge networks within small and medium projects. The optimal structure of the relationship networks and knowledge networks is measured using two dimensions: intra-project and inter-project. This chapter also outlines an extensive literature review in the areas of social capital, knowledge management and project management, and presents the conceptual model of the research approach.

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We argue that the sustained successful operation of an ES is determined by, and is dependent on, multiple organizational stakeholders. The single greatest organizational barrier to EIS success and achieving widespread organizational benefits can be attributed to the way in which different subcultures treat data critical to EIS operation. Building on Lee & Strong’s (2004) data roles we incorporate Schien’s (1996) cultural framework along with DeLone and McLean’s (2003) dimensions of IS success, unpacking the underlying drivers of behaviors as they relate to EIS data. Further, we explain the origins of data based conflict resulting in poor EIS data utilization.

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Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.

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This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

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Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.

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Performance comparisons between File Signatures and Inverted Files for text retrieval have previously shown several significant shortcomings of file signatures relative to inverted files. The inverted file approach underpins most state-of-the-art search engine algorithms, such as Language and Probabilistic models. It has been widely accepted that traditional file signatures are inferior alternatives to inverted files. This paper describes TopSig, a new approach to the construction of file signatures. Many advances in semantic hashing and dimensionality reduction have been made in recent times, but these were not so far linked to general purpose, signature file based, search engines. This paper introduces a different signature file approach that builds upon and extends these recent advances. We are able to demonstrate significant improvements in the performance of signature file based indexing and retrieval, performance that is comparable to that of state of the art inverted file based systems, including Language models and BM25. These findings suggest that file signatures offer a viable alternative to inverted files in suitable settings and positions the file signatures model in the class of Vector Space retrieval models.

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In this paper, we propose a search-based approach to join two tables in the absence of clean join attributes. Non-structured documents from the web are used to express the correlations between a given query and a reference list. To implement this approach, a major challenge we meet is how to efficiently determine the number of times and the locations of each clean reference from the reference list that is approximately mentioned in the retrieved documents. We formalize the Approximate Membership Localization (AML) problem and propose an efficient partial pruning algorithm to solve it. A study using real-word data sets demonstrates the effectiveness of our search-based approach, and the efficiency of our AML algorithm.

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This research-in-progress paper reports preliminary findings of a study that is designed to identify characteristics of an expert in the discipline of Information Systems (IS). The paper delivers a formative research model to depict characteristics of an expert with three additive constructs, using concepts derived from psychology, knowledge management and social-behaviour research. The paper then explores the formation and application ‘expertise’ using four investigative questions in the context of System Evaluations. Data have been gathered from 220 respondents representing three medium sized companies in India, using the SAP Enterprise Resource Planning system. The paper summarizes planned data analyses in construct validation, model testing and model application. A validated construct of expertise of IS will have a wide range of implications for research and practice.

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Boundaries are an important field of study because they mediate almost every aspect of organizational life. They are becoming increasingly more important as organizations change more frequently and yet, despite the endemic use of the boundary metaphor in common organizational parlance, they are poorly understood. Organizational boundaries are under-theorized and researchers in related fields often simply assume their existence, without defining them. The literature on organizational boundaries is fragmented with no unifying theoretical basis. As a result, when it is recognized that an organizational boundary is "dysfunctional". there is little recourse to models on which to base remediating action. This research sets out to develop just such a theoretical model and is guided by the general question: "What is the nature of organizational boundaries?" It is argued that organizational boundaries can be conceptualised through elements of both social structure and of social process. Elements of structure include objects, coupling, properties and identity. Social processes include objectification, identification, interaction and emergence. All of these elements are integrated by a core category, or basic social process, called boundary weaving. An organizational boundary is a complex system of objects and emergent properties that are woven together by people as they interact together, objectifying the world around them, identifying with these objects and creating couplings of varying strength and polarity as well as their own fragmented identity. Organizational boundaries are characterised by the multiplicity of interconnections, a particular domain of objects, varying levels of embodiment and patterns of interaction. The theory developed in this research emerged from an exploratory, qualitative research design employing grounded theory methodology. The field data was collected from the training headquarters of the New Zealand Army using semi-structured interviews and follow up observations. The unit of analysis is an organizational boundary. Only one research context was used because of the richness and multiplicity of organizational boundaries that were present. The model arose, grounded in the data collected, through a process of theoretical memoing and constant comparative analysis. Academic literature was used as a source of data to aid theory development and the saturation of some central categories. The final theory is classified as middle range, being substantive rather than formal, and is generalizable across medium to large organizations in low-context societies. The main limitation of the research arose from the breadth of the research with multiple lines of inquiry spanning several academic disciplines, with some relevant areas such as the role of identity and complexity being addressed at a necessarily high level. The organizational boundary theory developed by this research replaces the typology approaches, typical of previous theory on organizational boundaries and reconceptualises the nature of groups in organizations as well as the role of "boundary spanners". It also has implications for any theory that relies on the concept of boundaries, such as general systems theory. The main contribution of this research is the development of a holistic model of organizational boundaries including an explanation of the multiplicity of boundaries . no organization has a single definable boundary. A significant aspect of this contribution is the integration of aspects of complexity theory and identity theory to explain the emergence of higher-order properties of organizational boundaries and of organizational identity. The core category of "boundary weaving". is a powerful new metaphor that significantly reconceptualises the way organizational boundaries may be understood in organizations. It invokes secondary metaphors such as the weaving of an organization's "boundary fabric". and provides managers with other metaphorical perspectives, such as the management of boundary friction, boundary tension, boundary permeability and boundary stability. Opportunities for future research reside in formalising and testing the theory as well as developing analytical tools that would enable managers in organizations to apply the theory in practice.

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Language Modeling (LM) has been successfully applied to Information Retrieval (IR). However, most of the existing LM approaches only rely on term occurrences in documents, queries and document collections. In traditional unigram based models, terms (or words) are usually considered to be independent. In some recent studies, dependence models have been proposed to incorporate term relationships into LM, so that links can be created between words in the same sentence, and term relationships (e.g. synonymy) can be used to expand the document model. In this study, we further extend this family of dependence models in the following two ways: (1) Term relationships are used to expand query model instead of document model, so that query expansion process can be naturally implemented; (2) We exploit more sophisticated inferential relationships extracted with Information Flow (IF). Information flow relationships are not simply pairwise term relationships as those used in previous studies, but are between a set of terms and another term. They allow for context-dependent query expansion. Our experiments conducted on TREC collections show that we can obtain large and significant improvements with our approach. This study shows that LM is an appropriate framework to implement effective query expansion.

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Information has no value unless it is accessible. Information must be connected together so a knowledge network can then be built. Such a knowledge base is a key resource for Internet users to interlink information from documents. Information retrieval, a key technology for knowledge management, guarantees access to large corpora of unstructured text. Collaborative knowledge management systems such as Wikipedia are becoming more popular than ever; however, their link creation function is not optimized for discovering possible links in the collection and the quality of automatically generated links has never been quantified. This research begins with an evaluation forum which is intended to cope with the experiments of focused link discovery in a collaborative way as well as with the investigation of the link discovery application. The research focus was on the evaluation strategy: the evaluation framework proposal, including rules, formats, pooling, validation, assessment and evaluation has proved to be efficient, reusable for further extension and efficient for conducting evaluation. The collection-split approach is used to re-construct the Wikipedia collection into a split collection comprising single passage files. This split collection is proved to be feasible for improving relevant passages discovery and is devoted to being a corpus for focused link discovery. Following these experiments, a mobile client-side prototype built on iPhone is developed to resolve the mobile Search issue by using focused link discovery technology. According to the interview survey, the proposed mobile interactive UI does improve the experience of mobile information seeking. Based on this evaluation framework, a novel cross-language link discovery proposal using multiple text collections is developed. A dynamic evaluation approach is proposed to enhance both the collaborative effort and the interacting experience between submission and evaluation. A realistic evaluation scheme has been implemented at NTCIR for cross-language link discovery tasks.

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Product Lifecycle Management has been developed as an approach to providing timely engineering information. However, the number of domain specializations within manufacturing makes such information communication disjointed, inefficient and error-prone. In this paper we propose an immersive 3D visualization of linked domain- specific information views for improving and accelerating communication processes in Product Lifecycle Management. With a common and yet understandable visualization of several domain views, interconnections and dependencies become obvious. The conceptual framework presented here links domain-specific information extracts from Product Lifecycle Management systems with each other and displays them via an integrated 3D representation scheme. We expect that this visualization framework should support holistic tactical decision making processes between domain-experts in operational and tactical manufacturing scenarios.

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The great majority of police officers are committed to honourable and competent public service and consistently demonstrate integrity and accountability in carrying out the often difficult, complex and sometimes dangerous, activities involved in policing by consent. However, in every police agency there exists an element of dishonesty, lack of professionalism and criminal behaviour. This article is based on archival research of criminal behaviour in the Norwegian police force. A total of 60 police employees were prosecuted in court because of misconduct and crime from 2005 to 2010. Court cases were coded as two potential predictors of court sentence in terms of imprisonment days, ie, type of deviance and level of deviance. Categories of police crime and levels were organised according to a conceptual framework developed for assessing and managing police deviance. Empirical findings support the hypothesis that as the seriousness of police crime increases in breadth and depth so also does the severity of the court sentence as measured by time in prison.