Selecting crop models for decision making in wheat insurance

In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES- Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Intelligent Decision-Making System Frameworks for a Digital Plan of Work: A Theoretical Investigation for the Construction Industry

The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.

European Union and its member states as a collective actor in WTO decision-making process. ACES Cases No. 2010.3

This paper will outline and analyze the decision-making process in WTO matters. First, the players of the decision-making process -- the Council of the European Union (Council), the Trade Policy Committee, the Commission, and the European Parliament -- will be examined. Then the distinction will be made between decision-making in initiating WTO disputes and decision-making conducting trade agreement negotiations in the WTO. Then, decision-making practices in WTO matters will be assessed against constitutional principles of transparency, accountability, and legitimacy. After this assessment, conclusions will be drawn.

The EU’s Decision-Making Process Changes in the Constitutive Treaties

Since the beginning of its existence in the form of communities, the European Union’s decision-making process underwent constant evolution. There were continuous adjustments that transformed a pure intergovernmental process into one having rather federal features. Based on the hypothesis that changes have occurred at the decision level in regards to the actors, procedures, influence and ways of taking decisions in order for the new realities, needs and will at the European level to be properly addressed, this paper aims to present the reforms performed through the adoption of new treaties and the modification of the existing ones. The reality is that in order for the European dream and integration to go on and also for further development of the European Union, finally becoming an entity far beyond the founders expectations, decision makers had to constantly and carefully adapt the decision-making process. The purpose of this paper will be achieved by conducting a research based on the qualitative method, analyzing the related researches on this topic and the consolidated versions of the treaties. Thus, we will finally validate our research hypothesis that there was an evolution in what the EU’s decision-making process and decision procedures are concerned.

Reactive, Slow and...Innovative? Decision-making Structures and Policy Outputs

Consensus democracies like Switzerland are generally known to have a low innovation capacity (Lijphart 1999). This is due to the high number of veto points such as perfect bicameralism or the popular referendum. These institutions provide actors opposing a policy with several opportunities to block potential policy change (Immergut 1990; Tsebelis 2002). In order to avoid a failure of a process because opposing actors activate veto points, decision-making processes in Switzerland tend to integrate a large number of actors with different - and often diverging - preferences (Kriesi and Trechsel 2008). Including a variety of actors in a decision-making process and taking into account their preferences implies important trade-offs. Integrating a large number of actors and accommodating their preferences takes time and carries the risk of resulting in lowest common denominator solutions. On the contrary, major innovative reforms usually fail or come only as a result of strong external pressures from either the international environment, economic turmoil or the public (Kriesi 1980: 635f.; Kriesi and Trechsel 2008; Sciarini 1994). Standard decision-making processes are therefore characterized as reactive, slow and capable of only marginal adjustments (Kriesi 1980; Kriesi and Trechsel 2008; Linder 2009; Sciarini 2006). This, in turn, may be at odds with the rapid developments of international politics, the flexibility of the private sector, or the speed of technological development.

The decision-making process: experimental findings and implications.

"Paper to be read at the 1963 convention of the Society of Technical Writers and Publishers."

Factors influencing Hong Kong Chinese patients' decision-making in seeking early treatment for acute myocardial infarction

The purpose of this study was to identify, through in-depth interview, factors that influenced 27 Hong Kong Chinese patients' decision-making in seeking early treatment for acute myocardial infarction (AMI). The median delay time from the onset of symptoms to arrival at the hospital was 15.6 hours for men and 53.7 hours for women. Three major categories emerged from the data: (a) becoming aware of the threat, (b) maintaining a sense of normality, and (c) struggling to mobilize resources. A variety of decisions were made by patients from the onset of chest Pain to seeking help. These decisions were heavily influenced by healthcare factors (access to emergency medical service (EMS) and treatment), personal factors (cognitive interpretations of symptoms), sociocultural factors (family situation, cultural beliefs, and practices), and coping strategies. (c) 2006 Wiley Periodicals, Inc.

Collaborative decision-making processes for maintaining biodiversity: Two Australian case studies

There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

Improving the economic decision making capability and viability of Chinese wool textile mills

The successful restructuring of Chinese industries is of immense importance not only for the continued development of China but also to the stability of the world economy. The transformation of the Chinese wool textile industry illustrates well the many problems and pressures currently facing most Chinese industries. The Chinese wool textile industry has undergone major upheaval and restructuring in its drive to modernize and take advantage of developments in world textile markets. Macro level ownership and administrative reforms are well advanced as is the uptake of new technology and equipment. However, the changing market and institutional environment also demands an increasing level of sophistication in mill management decisions including product selection, input procurement, product pricing, investment appraisal, cost analysis and proactive identification of new market and growth opportunities. This paper outlines a series of analyses that have been integrated into a decision-making model designed to assist mill managers with these decisions. Features of the model include a whole-of-mill approach, a design based on existing mill structures and information systems, and the capacity for the model to be tailored to individual mills. All of these features facilitate the adoption of the model by time and resource constrained managers seeking to maintain the viability of their enterprises in the face of extremely dynamic market conditions.