55 resultados para Information privacy Framework


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Cross-bred cow adoption is an important and potent policy variable precipitating subsistence household entry into emerging milk markets. This paper focuses on the problem of designing policies that encourage and sustain milkmarket expansion among a sample of subsistence households in the Ethiopian highlands. In this context it is desirable to measure households’ ‘proximity’ to market in terms of the level of deficiency of essential inputs. This problem is compounded by four factors. One is the existence of cross-bred cow numbers (count data) as an important, endogenous decision by the household; second is the lack of a multivariate generalization of the Poisson regression model; third is the censored nature of the milk sales data (sales from non-participating households are, essentially, censored at zero); and fourth is an important simultaneity that exists between the decision to adopt a cross-bred cow, the decision about how much milk to produce, the decision about how much milk to consume and the decision to market that milk which is produced but not consumed internally by the household. Routine application of Gibbs sampling and data augmentation overcome these problems in a relatively straightforward manner. We model the count data from two sites close to Addis Ababa in a latent, categorical-variable setting with known bin boundaries. The single-equation model is then extended to a multivariate system that accommodates the covariance between crossbred-cow adoption, milk-output, and milk-sales equations. The latent-variable procedure proves tractable in extension to the multivariate setting and provides important information for policy formation in emerging-market settings

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Drought is a global problem that has far-reaching impacts and especially 47 on vulnerable populations in developing regions. This paper highlights the need for a Global Drought Early Warning System (GDEWS), the elements that constitute its underlying framework (GDEWF) and the recent progress made towards its development. Many countries lack drought monitoring systems, as well as the capacity to respond via appropriate political, institutional and technological frameworks, and these have inhibited the development of integrated drought management plans or early warning systems. The GDEWS will provide a source of drought tools and products via the GDEWF for countries and regions to develop tailored drought early warning systems for their own users. A key goal of a GDEWS is to maximize the lead time for early warning, allowing drought managers and disaster coordinators more time to put mitigation measures in place to reduce the vulnerability to drought. To address this, the GDEWF will take both a top-down approach to provide global real-time drought monitoring and seasonal forecasting, and a bottom-up approach that builds upon existing national and regional systems to provide continental to global coverage. A number of challenges must be overcome, however, before a GDEWS can become a reality, including the lack of in-situ measurement networks and modest seasonal forecast skill in many regions, and the lack of infrastructure to translate data into useable information. A set of international partners, through a series of recent workshops and evolving collaborations, has made progress towards meeting these challenges and developing a global system.

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This article analyses the results of an empirical study on the 200 most popular UK-based websites in various sectors of e-commerce services. The study provides empirical evidence on unlawful processing of personal data. It comprises a survey on the methods used to seek and obtain consent to process personal data for direct marketing and advertisement, and a test on the frequency of unsolicited commercial emails (UCE) received by customers as a consequence of their registration and submission of personal information to a website. Part One of the article presents a conceptual and normative account of data protection, with a discussion of the ethical values on which EU data protection law is grounded and an outline of the elements that must be in place to seek and obtain valid consent to process personal data. Part Two discusses the outcomes of the empirical study, which unveils a significant departure between EU legal theory and practice in data protection. Although a wide majority of the websites in the sample (69%) has in place a system to ask separate consent for engaging in marketing activities, it is only 16.2% of them that obtain a consent which is valid under the standards set by EU law. The test with UCE shows that only one out of three websites (30.5%) respects the will of the data subject not to receive commercial communications. It also shows that, when submitting personal data in online transactions, there is a high probability (50%) of incurring in a website that will ignore the refusal of consent and will send UCE. The article concludes that there is severe lack of compliance of UK online service providers with essential requirements of data protection law. In this respect, it suggests that there is inappropriate standard of implementation, information and supervision by the UK authorities, especially in light of the clarifications provided at EU level.

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Purpose – This paper seeks to critically review the conceptual frameworks that have been developed for assessing the impact of information and communications technology (ICT) on real estate. Design/methodology/approach – The research is based on a critical review of existing literature and draws from examples of previous empirical research in the field. Findings – The paper suggests that a “socio-technical framework” is more appropriate to examine ICT impact in real estate than other “deterministic” frameworks. Therefore, ICT is an important part of the new economy, but must be seen in the context of a number of other social and economic factors. Research limitations/implications – The research is based on a qualitative assessment of existing frameworks, and by using examples from commercial real estate, assesses the extent to which a “socio-technical” framework can aid understanding of ICT impact. Practical implications – The paper is important in highlighting a number of the main issues in conceptualising ICT impact in real estate and also critically examines the emergence of a new economy in the information society within the general context of real estate. The paper also highlights research gaps in the field. Originality/value – The paper deconstructs the myths of the “death of real estate” and “productivity increase means jobs loss”, in relation to office real estate. Finally, it examines some of the ways in which ICT is impacting on real estate and suggests the most important components for a future research agenda in the field of ICT and real estate impact, and will be of value to property investors, facilities managers, developers, financiers, and others.

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Background. Within a therapeutic gene by environment (GxE) framework, we recently demonstrated that variation in the Serotonin Transporter Promoter Polymorphism; 5HTTLPR and marker rs6330 in Nerve Growth Factor gene; NGF is associated with poorer outcomes following cognitive behaviour therapy (CBT) for child anxiety disorders. The aim of this study was to explore one potential means of extending the translational reach of G×E data in a way that may be clinically informative. We describe a ‘risk-index’ approach combining genetic, demographic and clinical data and test its ability to predict diagnostic outcome following CBT in anxious children. Method. DNA and clinical data were collected from 384 children with a primary anxiety disorder undergoing CBT. We tested our risk model in five cross-validation training sets. Results. In predicting treatment outcome, six variables had a minimum mean beta value of 0.5: 5HTTLPR, NGF rs6330, gender, primary anxiety severity, comorbid mood disorder and comorbid externalising disorder. A risk index (range 0-8) constructed from these variables had moderate predictive ability (AUC = .62-.69) in this study. Children scoring high on this index (5-8) were approximately three times as likely to retain their primary anxiety disorder at follow-up as compared to those children scoring 2 or less. Conclusion. Significant genetic, demographic and clinical predictors of outcome following CBT for anxiety-disordered children were identified. Combining these predictors within a risk-index could be used to identify which children are less likely to be diagnosis free following CBT alone or thus require longer or enhanced treatment. The ‘risk-index’ approach represents one means of harnessing the translational potential of G×E data.

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We summarise the response of the EAA’s FRSC to Towards a Disclosure Framework for the Notes, a Discussion Paper (DP) issued jointly by EFRAG, ANC and FRC. While supportive of much of the DP, and in particular of the underlying aim to place disclosures on a sounder conceptual foundation, we identify two broad themes for further development. The first concerns the DP’s diagnosis of the problem, which is that the existing financial reporting is characterised by, on the one hand, disclosure overload and, on the other hand, an absence of a conceptual framework for organising and communicating disclosures. Our review of the literature suggests much greater support for the second of these two factors than for the first. The second broad theme is the purpose of the proposed DF, and the principles that are derived from this purpose. Here, we stress the need for the framework to better accommodate the context within which financial statement disclosures are used. In practice, this context is characterised by variation in information, incentives and enforcement, each of which has a considerable effect on the appropriate disclosure policy and practice in any given situation.

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Using a transactions costs framework, we examine the impact of information and communication technologies (mobile phones and radios) use on market participation in developing country agricultural markets using a novel transaction-level data set of Ghanaian farmers. Our analysis of the choice of markets by farmers suggests that market information from a broader range of markets may not always induce farmers to sell in more distant markets; instead farmers may use broader market information to enhance their bargaining power in closer markets. Finally, we find weak evidence on the impact of using mobile phones in attracting farm gate buyers.

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Most of studies on interoperability of systems integration focus on technical and semantic levels, but hardly extend investigations on pragmatic level. Our past work has addressed pragmatic interoperability, which is concerned with the relationship between signs and the potential behaviour and intention of responsible agents. We also define the pragmatic interoperability as a level concerning with the aggregation and optimisation of various business processes for achieving intended purposes of different information systems. This paper, as the extension of our previous research, is to propose an assessment method for measuring pragmatic interoperability of information systems. We firstly propose interoperability analysis framework, which is based on the concept of semiosis. We then develop pragmatic interoperability assessment process from two dimensions including six aspects (informal, formal, technical, substantive, communication, and control). We finally illustrate the assessment process in an example.

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Smart healthcare is a complex domain for systems integration due to human and technical factors and heterogeneous data sources involved. As a part of smart city, it is such a complex area where clinical functions require smartness of multi-systems collaborations for effective communications among departments, and radiology is one of the areas highly relies on intelligent information integration and communication. Therefore, it faces many challenges regarding integration and its interoperability such as information collision, heterogeneous data sources, policy obstacles, and procedure mismanagement. The purpose of this study is to conduct an analysis of data, semantic, and pragmatic interoperability of systems integration in radiology department, and to develop a pragmatic interoperability framework for guiding the integration. We select an on-going project at a local hospital for undertaking our case study. The project is to achieve data sharing and interoperability among Radiology Information Systems (RIS), Electronic Patient Record (EPR), and Picture Archiving and Communication Systems (PACS). Qualitative data collection and analysis methods are used. The data sources consisted of documentation including publications and internal working papers, one year of non-participant observations and 37 interviews with radiologists, clinicians, directors of IT services, referring clinicians, radiographers, receptionists and secretary. We identified four primary phases of data analysis process for the case study: requirements and barriers identification, integration approach, interoperability measurements, and knowledge foundations. Each phase is discussed and supported by qualitative data. Through the analysis we also develop a pragmatic interoperability framework that summaries the empirical findings and proposes recommendations for guiding the integration in the radiology context.

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Purpose – Today marketers operate in globalised markets, planning new ways to engage with domestic and foreign customers alike. While there is a greater need to understand these two customer groups, few studies examine the impact of customer engagement tactics on the two customer groups, focusing on their perceptual differences. Even less attention is given to customer engagement tactics in a cross-cultural framework. In this research, the authors investigate customers in China and UK, aiming to compare their perceptual differences on the impact of multiple customer engagement tactics. Design/methodology/approach – Using a quantitative approach with 286 usable responses from China and the UK obtained through a combination of person-administered survey and computer-based survey screening process, the authors test a series of hypotheses to distinguish across-cultural differences. Findings – Findings show that the collectivists (Chinese customers) perceive customer engagement tactics differently than the individualists (UK customers). The Chinese customers are more sensitive to price and reputation, whereas the UK customers respond more strongly to service, communication and customisation. Chinese customers’ concerns with extensive price and reputation comparisons may be explained by their awareness towards face (status), increased self-expression and equality. Practical implications – The findings challenge the conventional practice of using similar customer engagement tactics for a specific market place with little concern for multiple cultural backgrounds. The paper proposes strategies for marketers facing challenges in this globalised context. Originality/value – Several contributions have been made to the literatures. First, the study showed the effects of culture on the customers’ perceptual differences. Second, the study provided more information to clarify customers’ different reactions towards customer engagement tactics, highlighted by concerns towards face and status. Third, the study provided empirical evidence to support the use of multiple customer engagement tactics to the across cultural studies.

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Automatic generation of classification rules has been an increasingly popular technique in commercial applications such as Big Data analytics, rule based expert systems and decision making systems. However, a principal problem that arises with most methods for generation of classification rules is the overfit-ting of training data. When Big Data is dealt with, this may result in the generation of a large number of complex rules. This may not only increase computational cost but also lower the accuracy in predicting further unseen instances. This has led to the necessity of developing pruning methods for the simplification of rules. In addition, classification rules are used further to make predictions after the completion of their generation. As efficiency is concerned, it is expected to find the first rule that fires as soon as possible by searching through a rule set. Thus a suit-able structure is required to represent the rule set effectively. In this chapter, the authors introduce a unified framework for construction of rule based classification systems consisting of three operations on Big Data: rule generation, rule simplification and rule representation. The authors also review some existing methods and techniques used for each of the three operations and highlight their limitations. They introduce some novel methods and techniques developed by them recently. These methods and techniques are also discussed in comparison to existing ones with respect to efficient processing of Big Data.

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tWe develop an orthogonal forward selection (OFS) approach to construct radial basis function (RBF)network classifiers for two-class problems. Our approach integrates several concepts in probabilisticmodelling, including cross validation, mutual information and Bayesian hyperparameter fitting. At eachstage of the OFS procedure, one model term is selected by maximising the leave-one-out mutual infor-mation (LOOMI) between the classifier’s predicted class labels and the true class labels. We derive theformula of LOOMI within the OFS framework so that the LOOMI can be evaluated efficiently for modelterm selection. Furthermore, a Bayesian procedure of hyperparameter fitting is also integrated into theeach stage of the OFS to infer the l2-norm based local regularisation parameter from the data. Since eachforward stage is effectively fitting of a one-variable model, this task is very fast. The classifier construc-tion procedure is automatically terminated without the need of using additional stopping criterion toyield very sparse RBF classifiers with excellent classification generalisation performance, which is par-ticular useful for the noisy data sets with highly overlapping class distribution. A number of benchmarkexamples are employed to demonstrate the effectiveness of our proposed approach.

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Facility management (FM), from a service oriented approach, addresses the functions and requirements of different services such as energy management, space planning and security service. Different service requires different information to meet the needs arising from the service. Object-based Building Information Modelling (BIM) is limited to support FM services; though this technology is able to generate 3D models that semantically represent facility’s information dynamically over the lifecycle of a building. This paper presents a semiotics-inspired framework to extend BIM from a service-oriented perspective. The extended BIM, which specifies FM services and required information, will be able to express building service information in the right format for the right purposes. The service oriented approach concerns pragmatic aspect of building’s information beyond semantic level. The pragmatics defines and provides context for utilisation of building’s information. Semiotics theory adopted in this paper is to address pragmatic issues of utilisation of BIM for FM services.

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In the resource-based view, organisations are represented by the sum of their physical, human and organisational assets, resources and capabilities. Operational capabilities maintain the status quo and allow an organisation to execute their existing business. Dynamic capabilities, otherwise, allow an organisation to change this status quo including a change of the operational ones. Competitive advantage, in this context, is an effect of continuously developing and reconfiguring these firm-specific assets through dynamic capabilities. Deciding where and how to source the core operational capabilities is a key success factor. Furthermore, developing its dynamic capabilities allows an organisation to effectively manage change its operational capabilities. Many organisations are asserted to have a high dependency on - as well as a high benefit from - the use of information technology (IT), making it a crucial and overarching resource. Furthermore, the IT function is assigned the role as a change enabler and so IT sourcing affects the capability of managing business change. IT sourcing means that organisations need to decide how to source their IT capabilities. Outsourcing of parts of the IT function will also outsource some of the IT capabilities and therefore some of the business capabilities. As a result, IT sourcing has an impact on the organisation's capabilities and consequently on the business success. And finally, a turbulent and fast moving business environment challenges organisations to effectively and efficiently managing business change. Our research builds on the existing theory of dynamic and operational capabilities by considering the interdependencies between the dynamic capabilities of business change and IT sourcing. Further it examines the decision-making oversight of these areas as implemented through IT governance. We introduce a new conceptual framework derived from the existing theory and extended through an illustrative case study conducted in a German bank. Under a philosophical paradigm of constructivism, we collected data from eight semi-structured interviews and used additional sources of evidence in form of annual accounts, strategy papers and IT benchmark reports. We applied an Interpretative Phenomenological Analysis (IPA), which emerged the superordinate themes for our tentative capabilities framework. An understanding of these interdependencies enables scholars and professionals to improve business success through effectively managing business change and evaluating the impact of IT sourcing decisions on the organisation's operational and dynamic capabilities.

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We evaluate a number of real estate sentiment indices to ascertain current and forward-looking information content that may be useful for forecasting demand and supply activities. Analyzing the dynamic relationships within a Vector Auto-Regression (VAR) framework and using the quarterly US data over 1988-2010, we test the efficacy of several sentiment measures by comparing them with other coincident economic indicators. Overall, our analysis suggests that the sentiment in real estate convey valuable information that can help predict changes in real estate returns. These findings have important implications for investment decisions, from consumers' as well as institutional investors' perspectives.