968 resultados para Relational Model
Resumo:
SAP and its research partners have been developing a lan- guage for describing details of Services from various view- points called the Unified Service Description Language (USDL). At the time of writing, version 3.0 describes technical implementation aspects of services, as well as stakeholders, pricing, lifecycle, and availability. Work is also underway to address other business and legal aspects of services. This language is designed to be used in service portfolio management, with a repository of service descriptions being available to various stakeholders in an organisation to allow for service prioritisation, development, deployment and lifecycle management. The structure of the USDL metadata is specified using an object-oriented metamodel that conforms to UML, MOF and EMF Ecore. As such it is amenable to code gener-ation for implementations of repositories that store service description instances. Although Web services toolkits can be used to make these programming language objects available as a set of Web services, the practicalities of writing dis- tributed clients against over one hundred class definitions, containing several hundred attributes, will make for very large WSDL interfaces and highly inefficient “chatty” implementations. This paper gives the high-level design for a completely model-generated repository for any version of USDL (or any other data-only metamodel), which uses the Eclipse Modelling Framework’s Java code generation, along with several open source plugins to create a robust, transactional repository running in a Java application with a relational datastore. However, the repository exposes a generated WSDL interface at a coarse granularity, suitable for distributed client code and user-interface creation. It uses heuristics to drive code generation to bridge between the Web service and EMF granularities.
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Infrastructure organizations are operating in an increasingly challenging business environment as a result of globalization, privatization and deregulation. In an external business environment that is constantly changing, extant literature on strategic management advocates the need to focus on factors internal to the organization such as resources and capabilities to sustain their performance. Specifically, they need to develop dynamic capabilities in order to survive and prosper under conditions of change. The aim of this paper is to explore the dynamic capabilities needed in the management of transport infrastructure assets using a multiple case study research strategy. This paper produced a number of findings. First, the empirical evidence showed that the core infrastructure asset management processes are capacity management, options evaluation, procurement & delivery, maintenance management, and asset information management. Second, the study identified five dynamic capabilities namely stakeholder connectivity, cross-functional, relational, technology absorptive and integrated information capability as central to executing the strategic infrastructure asset management processes well. These findings culminate in the development of a capability model to improve the performance of infrastructure assets in an increasingly dynamic business environment.
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Organizations today invest in collaborative IT to engage in collaborative alliances to sustain or improve their competitive positions. Effective use of this collaborative IT in an alliance requires a deeper understanding of their governance structures. This effort is to ensure the sustainability of these alliances. Through the relational view of the firm, we suggest relational lateral IT-steering committees, relational IT operational committees, and relational IT performance management systems as IT governance structures for collaborative alliances. We then incorporate these structures, develop a model for approaches to governing collaborative IT, and evaluate the effectiveness for such governance structures in the IT-dependent alliances. We suggest that IT governance efforts of an alliance should contribute to their collaborative rent. We also suggest that the collaborative rent of an alliance would relate to the business value of its alliance partners. Field survey data containing 192 responses indicates a positive influence of the suggested IT governance efforts of the alliance on the collaborative rent of the alliance. The results also suggest a positive impact of the collaborative rent of the alliance on the business value of the alliance partners.
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This paper describes the use of property graphs for mapping data between AEC software tools, which are not linked by common data formats and/or other interoperability measures. The intention of introducing this in practice, education and research is to facilitate the use of diverse, non-integrated design and analysis applications by a variety of users who need to create customised digital workflows, including those who are not expert programmers. Data model types are examined by way of supporting the choice of directed, attributed, multi-relational graphs for such data transformation tasks. A brief exemplar design scenario is also presented to illustrate the concepts and methods proposed, and conclusions are drawn regarding the feasibility of this approach and directions for further research.
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The configuration of comprehensive enterprise systems to meet the specific requirements of an organisation up to today is consuming significant resources. The results of failing or delayed enterprise system implementation projects are severe and may even threaten the organisation’s existence. One of the main drivers for implementing comprehensive enterprise systems is to streamline business processes. However, an intuitive conceptual support for business process configuration is insufficiently addressed by enterprise system vendors and inadequately researched in academia. This paper presents a model-driven approach to target this problem and proposes several configuration patterns that describe generic patterns of configuration alternatives, in order to understand what situations can occur during business process configuration. Based on these configuration patterns, a configuration notation is introduced that allows for visually highlighting configuration alternatives. Finally, we will sketch how configurable Event Driven Process Chains and the configuration of business processes can be supported using relational databases.
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This paper outlines how commercial sponsorship can be conceptualized using an item and relational information framework, and supports this with empirical data. The model presented allows for predictions about consumer memory for sponsorship information, and hence has both theoretical and practical value. Data are reported which show that sponsors considered congruent with an event benefit by providing consumers with sponsor-specific item information, while sponsors considered incongruent benefit by providing sponsor-event relational information. Overall the provision of sponsor-event relational information is shown to result in superior memory to the provision of sponsor-specific item information, which is superior to basic sponsor mentions.
Resumo:
This paper outlines how commercial sponsorship can be conceptualized using an item and relational information framework, and supports this with empirical data. The model presented allows for predictions about consumer memory for sponsorship information, and hence has both theoretical and practical value. Data are reported which show that sponsors considered congruent with an event benefit by providing consumers with sponsor-specific item information, while sponsors considered incongruent benefit by providing sponsor-event relational information. Overall the provision of sponsor-event relational information is shown to result in superior memory to the provision of sponsor-specific item information, which is superior to basic sponsor mentions.
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Given global demand for new infrastructure, governments face substantial challenges in funding new infrastructure and delivering Value for Money (VfM). As part of the background to this challenge, a critique is given of current practice in the selection of the approach to procure major public sector infrastructure in Australia and which is akin to the Multi-Attribute Utility Approach (MAUA). To contribute towards addressing the key weaknesses of MAUA, a new first-order procurement decision-making model is presented. The model addresses the make-or-buy decision (risk allocation); the bundling decision (property rights incentives), as well as the exchange relationship decision (relational to arms-length exchange) in its novel approach to articulating a procurement strategy designed to yield superior VfM across the whole life of the asset. The aim of this paper is report on the development of this decisionmaking model in terms of the procedural tasks to be followed and the method being used to test the model. The planned approach to testing the model uses a sample of 87 Australian major infrastructure projects in the sum of AUD32 billion and deploys a key proxy for VfM comprising expressions of interest, as an indicator of competition.
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Aims and objectives. To present a novel approach to nurse stress by exploring the demand–control–support model with organisational justice through the lens of relational regulation theory. Background. Nursing is often stressful due to high demands and dissatisfaction with pay, which impacts the mental well-being and productivity of nurses. Design. A cross-sectional design. Methods. A validated questionnaire was sent to the work addresses of all nursing and midwifery staff in a medium-sized general acute hospital in Australia. A total of 190 nurses and midwives returned completed questionnaires for the analyses. Results. The multiple regression analyses demonstrated that the model applies to the prototypical context of a general acute hospital and that job control, supervisor support and outside work support improve the job satisfaction and mental health of nurses. Conclusions. Most importantly, supervisor support was found to buffer the impact of excessive work demands. Fairness of procedures, distribution of resources and the quality and consistency of information are also beneficial. Relational regulation theory is applied to these findings as a novel way to conceptualise the mechanisms of support and fairness in nursing. Relevance to clinical practice. The importance of nurses’ well-being and job satisfaction is a priority for improving clinical outcomes. Practically, this means nurse managers should be encouraging nurses in the pursuit of diverse relational activities both at work and outside work.
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Database watermarking has received significant research attention in the current decade. Although, almost all watermarking models have been either irreversible (the original relation cannot be restored from the watermarked relation) and/or non-blind (requiring original relation to detect the watermark in watermarked relation). This model has several disadvantages over reversible and blind watermarking (requiring only watermarked relation and secret key from which the watermark is detected and original relation is restored) including inability to identify rightful owner in case of successful secondary watermarking, inability to revert the relation to original data set (required in high precision industries) and requirement to store unmarked relation at a secure secondary storage. To overcome these problems, we propose a watermarking scheme that is reversible as well as blind. We utilize difference expansion on integers to achieve reversibility. The major advantages provided by our scheme are reversibility to high quality original data set, rightful owner identification, resistance against secondary watermarking attacks, and no need to store original database at a secure secondary storage.
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The purpose of this paper is to review existing knowledge management (KM) practices within the field of asset management, identify gaps, and propose a new approach to managing knowledge for asset management. Existing approaches to KM in the field of asset management are incomplete with the focus primarily on the application of data and information systems, for example the use of an asset register. It is contended these approaches provide access to explicit knowledge and overlook the importance of tacit knowledge acquisition, sharing and application. In doing so, current KM approaches within asset management tend to neglect the significance of relational factors; whereas studies in the knowledge management field have showed that relational modes such as social capital is imperative for ef-fective KM outcomes. In this paper, we argue that incorporating a relational ap-proach to KM is more likely to contribute to the exchange of ideas and the devel-opment of creative responses necessary to improve decision-making in asset management. This conceptual paper uses extant literature to explain knowledge management antecedents and explore its outcomes in the context of asset man-agement. KM is a component in the new Integrated Strategic Asset Management (ISAM) framework developed in conjunction with asset management industry as-sociations (AAMCoG, 2012) that improves asset management performance. In this paper we use Nahapiet and Ghoshal’s (1998) model to explain antecedents of relational approach to knowledge management. Further, we develop an argument that relational knowledge management is likely to contribute to the improvement of the ISAM framework components, such as Organisational Strategic Manage-ment, Service Planning and Delivery. The main contribution of the paper is a novel and robust approach to managing knowledge that leads to the improvement of asset management outcomes.
Designing informal learning experiences for early career academics using a knowledge ecosystem model
Resumo:
This article presents a ‘knowledge ecosystem’ model of how early career academics experience using information to learn while building their social networks for developmental purposes. Developed using grounded theory methodology, the model offers a way of conceptualising how to empower early career academics through 1) agency (individual and relational) and 2) facilitation of personalised informal learning (design of physical and virtual systems and environments) in spaces where developmental relationships are formed including programs, courses, events, community, home and social media. It is suggested that the knowledge ecosystem model is suitable for use in designing informal learning experiences for early career academics.
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Database management systems offer a very reliable and attractive data organization for fast and economical information storage and processing for diverse applications. It is much more important that the information should be easily accessible to users with varied backgrounds, professional as well as casual, through a suitable data sublanguage. The language adopted here (APPLE) is one such language for relational database systems and is completely nonprocedural and well suited to users with minimum or no programming background. This is supported by an access path model which permits the user to formulate completely nonprocedural queries expressed solely in terms of attribute names. The data description language (DDL) and data manipulation language (DML) features of APPLE are also discussed. The underlying relational database has been implemented with the help of the DATATRIEVE-11 utility for record and domain definition which is available on the PDP-11/35. The package is coded in Pascal and MACRO-11. Further, most of the limitations of the DATATRIEVE-11 utility have been eliminated in the interface package.
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- Purpose This paper aims to investigate how direct mail consumption contributes to brand relationship quality. Store flyers and other direct mailings continue to play a significant role in many companies’ communication strategies. Research on this topic predominantly investigates driving store traffic and sales. Less is known regarding the consumer side, such as the value that consumers may derive from the consumption of direct mailings and the effects of such a value on brand relationship quality. To address this limitation, this paper tests a causal model of the contribution of direct mail value to brand commitment, drawing on a value framework that integrates social theory of engagement regimes and literature on experiential customer value. - Design/methodology/approach The empirical work of this paper is based on a rigorous four-study mixed methods design, involving qualitative study, confirmatory factor analysis and partial least squares structural modeling. - Findings The authors develop two second-order formatively designed scales – familiar value and planned value scales – that illustrate the role of engagement regimes in consumer behavior. Although both types of value contribute equally to direct mail attachment, they exert contrasting effects on other mediational consumer responses, such as reading and gratitude. Finally, the proposed theoretical model appears to be robust in predicting customers’ brand commitment. - Research limitations/implications This study provides new insights into the research on consumer value and brand relational communication. - Originality/value This study is the first to consider consumer benefits from the social perspective of engagement regimes.
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We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.