88 resultados para institutional initiative


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Armed with the ‘equity’ and ‘conservation’ arguments that have a deep resonance with farming communities, developing countries are crafting a range of measures designed to protect farmers’ access to innovations, reward their contributions to the conservation and enhancement of plant genetic resources and provide incentives for sustained on-farm conservation. These measures range from the commericialization of farmers’ varieties to the conferment of a set of legally enforceable rights on farming communities – the exercise of which is expected to provide economic rewards to those responsible for on-farm conservation and innovation. The rights-based approach has been the cornerstone of legislative provision for implementing farmers’ rights in most developing countries. In drawing up these measures, developing countries do not appear to have systematically examined or provided for the substantial institutional capacity required for the effective implementation of farmers’ rights provisions. The lack of institutional capacity threatens to undermine any prospect of serious implementation of these provisions. More importantly, the expectation that significant incentives for on-farm conservation and innovation will flow from these ‘rights’ may be based on a flawed understanding of the economics of intellectual property rights. While farmers’ rights may provide only limited rewards for conservation, they may still have the effect of diluting the incentives for innovative institutional breeding programs – with the private sector increasingly relying on non-IPR instruments to profit from innovation. The focus on a rights-based approach may also draw attention away from alternative stewardship-based approaches to the realization of farmers’ rights objectives.

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The necessity and benefits for establishing the international Earth-system Prediction Initiative (EPI) are discussed by scientists associated with the World Meteorological Organization (WMO) World Weather Research Programme (WWRP), World Climate Research Programme (WCRP), International Geosphere–Biosphere Programme (IGBP), Global Climate Observing System (GCOS), and natural-hazards and socioeconomic communities. The proposed initiative will provide research and services to accelerate advances in weather, climate, and Earth system prediction and the use of this information by global societies. It will build upon the WMO, the Group on Earth Observations (GEO), the Global Earth Observation System of Systems (GEOSS) and the International Council for Science (ICSU) to coordinate the effort across the weather, climate, Earth system, natural-hazards, and socioeconomic disciplines. It will require (i) advanced high-performance computing facilities, supporting a worldwide network of research and operational modeling centers, and early warning systems; (ii) science, technology, and education projects to enhance knowledge, awareness, and utilization of weather, climate, environmental, and socioeconomic information; (iii) investments in maintaining existing and developing new observational capabilities; and (iv) infrastructure to transition achievements into operational products and services.

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Literature on comparative capitalism remains divided between approaches founded on stylized case study evidence and descriptions of broad trends, and those that focus on macro data. In contrast, this study explores the relevance of Amable’s approach to understanding differences in employment relations practice, based on firm-level micro data. The article examines employee–employer interdependence (including turnover rates) in different categories of economy as classified by Amable. The findings confirm that exit – whether forced or voluntary – remains more common in market-based economies than in their continental counterparts and that institutionalized employee voice is an important variable in reducing turnover. However, there is as much diversity within the different country categories as between them, and across continental Europe. In Denmark’s case, high turnover is combined with high unionization, showing the effects of a ‘flexicurity’ strategy. While employee voice may be stronger in Scandinavia, interdependence is weaker than in continental Europe.

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Social housing policy in the UK mirrors wider processes Associated with shifts in broad welfare regimes. Social housing has moved from dominance by state housing provision to the funding of new investment through voluntary sector housing associations to what is now a greater focus on the regulation and private financing of these not-for-profit bodies. If these trends run their course, we are likely to see a range of not-for-profit bodies providing non-market housing in a highly regulated quasi-market. This paper examines these issues through the lens of new institutional economics, which it is believed can provide important insights into the fundamental contractual and regulatory relationships that are coming to dominate social housing from the perspective of the key actors in the sector (not-for-profit housing organisations, their tenants, private lenders and the regulatory state). The paper draws on evidence recently collected from a study evaluating more than 100 stock transfer organisations that inherited ex-public housing in Scotland, including 12 detailed case studies. The paper concludes that social housing stakeholders need to be aware of the risks (and their management) faced across the sector and that the state needs to have clear objectives for social housing and coherent policy instruments to achieve those ends.

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Purpose – This paper summarises the main research findings from a detailed, qualitative set of structured interviews and case studies of private finance initiative (PFI) schemes in the UK, which involve the construction of built facilities. The research, which was funded by the Foundation for the Built Environment, examines the emergence of PFI in the UK. Benefits and problems in the PFI process are investigated. Best practice, the key critical factors for success, and lessons for the future are also analysed. Design/methodology/approach – The research is based around 11 semi-structured interviews conducted with stakeholders in key PFI projects in the UK. Findings – The research demonstrates that value for money and risk transfer are key success criteria. High procurement and transaction costs are a feature of PFI projects, and the large-scale nature of PFI projects frequently acts as barrier to entry. Research limitations/implications – The research is based on a limited number of in-depth case study interviews. The paper also shows that further research is needed to find better ways to measure these concepts empirically. Practical implications – The paper is important in highlighting four main areas of practical improvement in the PFI process: value for money assessment; establishing end-user needs; developing competitive markets and developing appropriate skills in the public sector. Originality/value – The paper examines the drivers, barriers and critical success factors for PFI in the UK for the first time in detail and will be of value to property investors, financiers, and others involved in the PFI process.

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This research examines the influence of environmental institutional distance between home and host countries on the standardization of environmental performance among multinational enterprises using ordinary least-squares (OLS) regression techniques and a sample of 128 multinationals from high-polluting industries. The paper examines the environmental institutional distance of countries using the concepts of formal and informal institutional distances. The results show that whereas a high formal environmental distance between home and host countries leads multinational enterprises to achieve a different level of environmental performance according to each country's legal requirements, a high informal environmental distance encourages these firms to unify their environmental performance independently of the countries in which their units are based. The study also discusses the implications for academia, managers, and policy makers.

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The financial crisis of 2007-2009 and the subsequent reaction of the G20 have created a new global regulatory landscape. Within the EU, change of regulatory institutions is ongoing. The research objective of this study is to understand how institutional changes to the EU regulatory landscape may affect corresponding institutionalized operational practices within financial organizations and to understand the role of agency within this process. Our motivation is to provide insight into these changes from an operational management perspective, as well as to test Thelen and Mahoney?s (2010) modes of institutional change. Consequently, the study researched implementations of an Investment Management System with a rules-based compliance module within financial organizations. The research consulted compliance and risk managers, as well as systems experts. The study suggests that prescriptive regulations are likely to create isomorphic configurations of rules-based compliance systems, which consequently will enable the institutionalization of associated compliance practices. The study reveals the ability of some agents within financial organizations to control the impact of regulatory institutions, not directly, but through the systems and processes they adopt to meet requirements. Furthermore, the research highlights the boundaries and relationships between each mode of change as future avenues of research.

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The financial crisis of 2007-2009 has precipitated large scale regulatory change. Tight deadlines for implementation require organizations to start working on remediation projects before final drafts of regulations are crystalized. Firms are faced with engaging in complex and costly change management programs at a time when profits are diminished. As a consequence of these factors, pre-crisis logics for organizing compliance practices are being questioned and new approaches introduced. Our study explores the use of Investment Management Systems (IMS) in facilitating compliance arrangements. Our motivation is to understand the new logics and the part played by IMS in supporting these approaches. The study adopts an institutional logics perspective to explore the use of such systems at eight financial organizations. The study found new logics for organizing compliance include consolidation, centralization, harmonization and consistency and that the IMS plays an important role in supporting and enabling related activities.

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Previously, governments have responded to the impacts of economic failures and consequently have developed more regulations to protect employees, customers, shareholders and the economic wellbeing of the state. Our research addresses how Accounting Information Systems (AIS) may act as carriers for institutionalised practices associated with maintaining regulatory compliance within the context of UK Asset Management Houses. The AIS was found to be a strong conduit for institutionalized compliance related practices, utilising symbolic systems, relational systems, routines and artefacts to carry approaches relating to regulative, normative and cultural-cognitive strands of institutionalism. Thus, AIS are integral to the development and dissipation of best practice for the management of regulatory compliance. As institutional elements are clearly present we argue that AIS and regulatory compliance provide a rich context to further institutionalism. Since AIS may act as conduits for regulatory approaches, both systems adopters and clients may benefit from actively seeking to codify and abstract best practices into AIS. However, the application of generic institutionalized approaches, which may be applied across similar organizations, must be tempered with each firm’s business environment and associated regulatory exposure. A balance should be sought between approaches specific enough to be useful but generic enough to be universally applied.

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Observations of Earth from space have been made for over 40 years and have contributed to advances in many aspects of climate science. However, attempts to exploit this wealth of data are often hampered by a lack of homogeneity and continuity and by insufficient understanding of the products and their uncertainties. There is, therefore, a need to reassess and reprocess satellite datasets to maximize their usefulness for climate science. The European Space Agency has responded to this need by establishing the Climate Change Initiative (CCI). The CCI will create new climate data records for (currently) 13 essential climate variables (ECVs) and make these open and easily accessible to all. Each ECV project works closely with users to produce time series from the available satellite observations relevant to users' needs. A climate modeling users' group provides a climate system perspective and a forum to bring the data and modeling communities together. This paper presents the CCI program. It outlines its benefit and presents approaches and challenges for each ECV project, covering clouds, aerosols, ozone, greenhouse gases, sea surface temperature, ocean color, sea level, sea ice, land cover, fire, glaciers, soil moisture, and ice sheets. It also discusses how the CCI approach may contribute to defining and shaping future developments in Earth observation for climate science.

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We present a Bayesian image classification scheme for discriminating cloud, clear and sea-ice observations at high latitudes to improve identification of areas of clear-sky over ice-free ocean for SST retrieval. We validate the image classification against a manually classified dataset using Advanced Along Track Scanning Radiometer (AATSR) data. A three way classification scheme using a near-infrared textural feature improves classifier accuracy by 9.9 % over the nadir only version of the cloud clearing used in the ATSR Reprocessing for Climate (ARC) project in high latitude regions. The three way classification gives similar numbers of cloud and ice scenes misclassified as clear but significantly more clear-sky cases are correctly identified (89.9 % compared with 65 % for ARC). We also demonstrate the poetential of a Bayesian image classifier including information from the 0.6 micron channel to be used in sea-ice extent and ice surface temperature retrieval with 77.7 % of ice scenes correctly identified and an overall classifier accuracy of 96 %.

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Within the SPARC Data Initiative, the first comprehensive assessment of the quality of 13 water vapor products from 11 limb-viewing satellite instruments (LIMS, SAGE II, UARS-MLS, HALOE, POAM III, SMR, SAGE III, MIPAS, SCIAMACHY, ACE-FTS, and Aura-MLS) obtained within the time period 1978-2010 has been performed. Each instrument's water vapor profile measurements were compiled into monthly zonal mean time series on a common latitude-pressure grid. These time series serve as basis for the "climatological" validation approach used within the project. The evaluations include comparisons of monthly or annual zonal mean cross sections and seasonal cycles in the tropical and extratropical upper troposphere and lower stratosphere averaged over one or more years, comparisons of interannual variability, and a study of the time evolution of physical features in water vapor such as the tropical tape recorder and polar vortex dehydration. Our knowledge of the atmospheric mean state in water vapor is best in the lower and middle stratosphere of the tropics and midlatitudes, with a relative uncertainty of. 2-6% (as quantified by the standard deviation of the instruments' multiannual means). The uncertainty increases toward the polar regions (+/- 10-15%), the mesosphere (+/- 15%), and the upper troposphere/lower stratosphere below 100 hPa (+/- 30-50%), where sampling issues add uncertainty due to large gradients and high natural variability in water vapor. The minimum found in multiannual (1998-2008) mean water vapor in the tropical lower stratosphere is 3.5 ppmv (+/- 14%), with slightly larger uncertainties for monthly mean values. The frequently used HALOE water vapor data set shows consistently lower values than most other data sets throughout the atmosphere, with increasing deviations from the multi-instrument mean below 100 hPa in both the tropics and extratropics. The knowledge gained from these comparisons and regarding the quality of the individual data sets in different regions of the atmosphere will help to improve model-measurement comparisons (e.g., for diagnostics such as the tropical tape recorder or seasonal cycles), data merging activities, and studies of climate variability.

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A comprehensive quality assessment of the ozone products from 18 limb-viewing satellite instruments is provided by means of a detailed intercomparison. The ozone climatologies in form of monthly zonal mean time series covering the upper troposphere to lower mesosphere are obtained from LIMS, SAGE I/II/III, UARS-MLS, HALOE, POAM II/III, SMR, OSIRIS, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, and SMILES within 1978–2010. The intercomparisons focus on mean biases of annual zonal mean fields, interannual variability, and seasonal cycles. Additionally, the physical consistency of the data is tested through diagnostics of the quasi-biennial oscillation and Antarctic ozone hole. The comprehensive evaluations reveal that the uncertainty in our knowledge of the atmospheric ozone mean state is smallest in the tropical and midlatitude middle stratosphere with a 1σ multi-instrument spread of less than ±5%. While the overall agreement among the climatological data sets is very good for large parts of the stratosphere, individual discrepancies have been identified, including unrealistic month-to-month fluctuations, large biases in particular atmospheric regions, or inconsistencies in the seasonal cycle. Notable differences between the data sets exist in the tropical lower stratosphere (with a spread of ±30%) and at high latitudes (±15%). In particular, large relative differences are identified in the Antarctic during the time of the ozone hole, with a spread between the monthly zonal mean fields of ±50%. The evaluations provide guidance on what data sets are the most reliable for applications such as studies of ozone variability, model-measurement comparisons, detection of long-term trends, and data-merging activities.

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Monthly zonal mean climatologies of atmospheric measurements from satellite instruments can have biases due to the nonuniform sampling of the atmosphere by the instruments. We characterize potential sampling biases in stratospheric trace gas climatologies of the Stratospheric Processes and Their Role in Climate (SPARC) Data Initiative using chemical fields from a chemistry climate model simulation and sampling patterns from 16 satellite-borne instruments. The exercise is performed for the long-lived stratospheric trace gases O3 and H2O. Monthly sampling biases for O3 exceed 10% for many instruments in the high-latitude stratosphere and in the upper troposphere/lower stratosphere, while annual mean sampling biases reach values of up to 20% in the same regions for some instruments. Sampling biases for H2O are generally smaller than for O3, although still notable in the upper troposphere/lower stratosphere and Southern Hemisphere high latitudes. The most important mechanism leading to monthly sampling bias is nonuniform temporal sampling, i.e., the fact that for many instruments, monthly means are produced from measurements which span less than the full month in question. Similarly, annual mean sampling biases are well explained by nonuniformity in the month-to-month sampling by different instruments. Nonuniform sampling in latitude and longitude are shown to also lead to nonnegligible sampling biases, which are most relevant for climatologies which are otherwise free of biases due to nonuniform temporal sampling.