720 resultados para Accounting information


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While the importance of literature studies in the IS discipline is well recognized, little attention has been paid to the underlying structure and method of conducting effective literature reviews. Despite the fact that literature is often used to refine the research context and direct the pathways for successful research outcomes, there is very little evidence of the use of resource management tools to support the literature review process. In this paper we want to contribute to advancing the way in which literature studies in Information Systems are conducted, by proposing a systematic, pre-defined and tool-supported method to extract, analyse and report literature. This paper presents how to best identify relevant IS papers to review within a feasible and justifiable scope, how to extract relevant content from identified papers, how to synthesise and analyse the findings of a literature review and what are ways to effectively write and present the results of a literature review. The paper is specifically targeted towards novice IS researchers, who would seek to conduct a systematic detailed literature review in a focused domain. Specific contributions of our method are extensive tool support, the identification of appropriate papers including primary and secondary paper sets and a pre-codification scheme. We use a literature study on shared services as an illustrative example to present the proposed approach.

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Privacy has become one of the main impediments for e-health in its advancement to providing better services to its consumers. Even though many security protocols are being developed to protect information from being compromised, privacy is still a major issue in healthcare where privacy protection is very important. When consumers are confident that their sensitive information is safe from being compromised, their trust in these services will be higher and would lead to better adoption of these systems. In this paper we propose a solution to the problem of patient privacy in e-health through an information accountability framework could enhance consumer trust in e-health services and would lead to the success of e-health services.

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There has been an increasing interest by governments worldwide in the potential benefits of open access to public sector information (PSI). However, an important question remains: can a government incur tortious liability for incorrect information released online under an open content licence? This paper argues that the release of PSI online for free under an open content licence, specifically a Creative Commons licence, is within the bounds of an acceptable level of risk to government, especially where users are informed of the limitations of the data and appropriate information management policies and principles are in place to ensure accountability for data quality and accuracy.

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As a model for knowledge description and formalization, ontologies are widely used to represent user profiles in personalized web information gathering. However, when representing user profiles, many models have utilized only knowledge from either a global knowledge base or a user local information. In this paper, a personalized ontology model is proposed for knowledge representation and reasoning over user profiles. This model learns ontological user profiles from both a world knowledge base and user local instance repositories. The ontology model is evaluated by comparing it against benchmark models in web information gathering. The results show that this ontology model is successful.

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Each year, The Australian Centre for Philanthropy and Nonprofit Studies (CPNS) at Queensland University of Technology (QUT) collects and analyses statistics on the amount and extent of tax-deductible donations made and claimed by Australians in their individual income tax returns to deductible gift recipients (DGRs). The information presented below is based on the amount and type of tax-deductible donations made and claimed by Australian individual taxpayers to DGRs for the period 1 July 2008 to 30 June 2009. This information has been extracted mainly from the Australian Taxation Office's (ATO) publication Taxation Statistics 2008-09. The 2008-09 report is the latest report that has been made publicly available. It represents information in tax returns for the 2008-09 year processed by the ATO as at 31 October 2010.

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Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.

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Background: In the last decade, there has been increasing interest in the health effects of sedentary behavior, which is often assessed using self-report sitting-time questions. The aim of this qualitative study was to document older adults’ understanding of sitting-time questions from the International Physical Activity (PA) Questionnaire (IPAQ) and the PA Scale for the Elderly (PASE). Methods: Australian community-dwelling adults aged 65+ years answered the IPAQ and PASE sitting questions in face-to-face semi-structured interviews. IPAQ uses one open-ended question to assess sitting on a weekday in the last 7 days 'at work, at home, while doing coursework and during leisure time'; PASE uses a three-part closed question about daily leisure-time sitting in the last 7 days. Participants expressed their thoughts out loud while answering each question. They were then probed about their responses. Interviews were recorded, transcribed and coded into themes. Results: Mean age of the 28 male and 27 female participants was 73 years (range 65-89). The most frequently reported activity was watching TV. For both questionnaires, many participants had difficulties understanding what activities to report. Some had difficulty understanding what activities should be classified as ‘leisure-time sitting’. Some assumed they were being asked to only report activities provided as examples. Most reported activities they normally do, rather than those performed on a day in the previous week. Participants used a variety of strategies to select ‘a day’ for which they reported their sitting activities and to calculate sitting time on that day. Therefore, many different ways of estimating sitting time were used. Participants had particular difficulty reporting their daily sitting-time when their schedules were not consistent across days. Some participants declared the IPAQ sitting question too difficult to answer. Conclusion: The accuracy of older adults’ self-reported sitting time is questionable given the challenges they have in answering sitting-time questions. Their responses to sitting-time questions may be more accurate if our recommendations for clarifying the sitting domains, providing examples relevant to older adults and suggesting strategies for formulating responses are incorporated. Future quantitative studies should include objective criterion measures to assess validity and reliability of these questions.

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This panel discusses the impact of Green IT on information systems and how information systems can meet environmental challenges and ensure sustainability. We wish to highlight the role of green business processes, and specifically the contributions that the management of these processes can play in leveraging the transformative power of IS in order to create an environmentally sustainable society. The management of business processes has typically been thought of in terms of business improvement alongside the dimensions time, cost, quality, or flexibility – the so-called ‘devil’s quadrangle’. Contemporary organizations, however, increasingly become aware of the need to create more sustainable, IT-enabled business processes that are also successful in terms of their economic, ecological, as well as social impact. Exemplary ecological key performance indicators that increasingly find their way into the agenda of managers include carbon emissions, data center energy, or renewable energy consumption (SAP 2010). The key challenge, therefore, is to extend the devil’s quadrangle to a devil’s pentagon, including sustainability as an important fifth dimension in process change.