This thesis considered the potential benefits of employing linear programming in cheese manufacturing plants as a decision tool for management. Its potential has been enhanced by the recent approval of acid orange 12 as a chemical for testing the percent protein in milk; therefore, a practical test is now available for monitoring protein as well as milk fat in milk manufacturing and fluid milk plants. Seven models, each one differing only in the milk fat and protein percentages or means of standardizing the cheese milk, were manipulated individually and simultaneously to test the managerial benefits of linear programming under various plant and market conditions. Each model consisted of five cheese activities or variables, two butter activities, three powder activities, and a selling activity for each product produced. The maximum price that could be paid the farm producer per hundred-weight of milk and the minimum wholesale rice per pound of manufactured product, to cover variable costs were determined for each variety of cheese and composition of milk. There was a definite interaction between each of the activities. This caused the cost to produce a Pound of cheese to vary according to the alternative uses for milk, cream, skim milk, and whey. When the simulated plant was being utilized at or near full capacity and the cheese milk was standardized with non fat dry milk powder, total cheese yield increased as did total profits. When the plant was not being utilized to full capacity, profits were higher by not standardizing.

There is presently no wildfire model developed for Swedish conditions, only a fire danger rating system (FWI) has been developed for Swedish conditions. The demand for a wildfire model has not been great in the past in Sweden but the climate changes now taking place increases the risk of large and intensive wildfires in Sweden. The need for additional and better tools for sizing-up wildfires will be in great demand in the future. This pre-study is aimed at: - Presenting what has been done in the wildfire modeling field during the years and mainly the last twenty years. - Giving recommendations on the continued work with developing a Swedish wildfire model. The method that was used was literature and article survey. The study also looks into the required input data for a wildfire model and the input data available at the moment. This issue is highly crucial as the quality of the output of a wildfire model is depending upon the quality of the input data. During the study, a primitive wildfire model was constructed and refined in order to get an insight in the complexities and problems with developing an operational model. The following characterization of wildfire models was used during the study: - Statistical models: based primarily on statistics from earlier or experimental fires. They do not explicitly consider the controlling physical processes. - Semi-empirical models: based on physical laws, but enhanced with some empirical factors, often by lumping all physical mechanisms for heat transfer together. - Physical models: based on physical principles and distinguishing between physical mechanisms for heat transfer. The statistical models make no attempt to involve physical processes, as they are merely a statistical description of test fires. Thus the lack of a physical basis means that statistical models must be used carefully outside the test conditions. Semi-empirical models are often based on conservation of energy principles but do not make any difference between conduction, convection and radiation heat transfer. The semi-empirical model has low computational requirements and includes variables that are generally easy to measure in the field. So despite the issue with limited accuracy, the speed and simplicity of these models make them useful for operational use. Physical models have the advantage that they are based on known relationships and thus facilitating their scaling. Thus we can expect that physical models would provide the most accurate predictions and have the widest applicability. But the work on physical models is suffering of for example the lack of understanding of several processes, such as the characterization of the chemical processes taking place during combustion, the resulting flame characteristics and the isolation and quantification of physical processes governing heat transfer. The input data available today are generally not detailed enough for physical models. As a result, a very detailed physical model will still only give imprecise predictions. As better and more detailed input will be available, the use of physical models will be more justified. A semi-empirical model is recommended being developed in Sweden. This conclusion is based upon the following factors: - The accuracy of a semi-empirical model is generally much better than for a statistical model, also the use of a semi-empirical model is much wider than the use of a statistical model. - The amount of work required for developing a semi-empirical model will not differ much from the amount of work required for a statistical model. In both cases a number of test fires will have to be conducted to define and calibrate a number of fuel models representative of Sweden. - Presently the performance and application of physical models is not at an acceptable level (due to for example the complexity which they are to model and the computational capabilities of the PC’s of today) for operational use. The semi-empirical model for Sweden is recommended to be built upon Swedish conditions (i.e. built upon the type of vegetation found in Sweden) instead of trying to retrofit the local Swedish conditions into an existing model. This would most likely give the best output for Swedish conditions. A system for better input data - weather and fuel data – should be worked on as well. This could for example take advantage of the results of the very promising “Alarm”-project that is being conducted in western part of Sweden. Regarding the issue on better fuel data, new technology for satellite images or aerial photos and image classification techniques must be monitored as one major problem to be solved is distinguishing between the canopy fuel and the ground fuel. For more specific conclusions and reflections, please see the analysis and discussion, and conclusions sections of this report.

Master of Agribusiness / Department of Agricultural Economics / Keith Harris / For an Evergreen Seed Agent, making the financial decision to invest in bulk infrastructure is a large capital investment and requires a great deal of considerations. This thesis determines the soybean sales volume required for an investment in bulk soybean infrastructure to become financially feasible. A total of 1,456 soybean sales data points were used to run a regression model. Based on the results of the regression model, a correlation was determined between those agents that have bulk soybeans and soybean sales growth in comparison to those agents that did not have bulk soybeans. A “Bulk Soybean Decision Tool” was constructed and demonstrates costs and earnings of an Evergreen Seed Agent over a five-year period. The financial feasibility analysis concluded that the soybean volume required to consider investing in bulk soybeans is 8,488 units. In addition to a break-even analysis, three other base year volume scenarios were demonstrated. At the 3,233 unit base soybean sales volume, it is not financially feasible to invest in bulk. At the 10,265 unit base soybean sales volume, it is finically feasible to invest in bulk soybeans. Lastly, at the 18,912 unit base soybean sales volume, it is finically feasible to invest in bulk soybean infrastructure. The capabilities of the “Bulk Soybean Decision Tool” are significant for any Evergreen Seed Agent considering investing in bulk soybean infrastructure. Ensuring that an Evergreen Seed Agent is making a sound financial investment in bulk soybean infrastructure will allow for an increased adoption in infrastructure, resulting in increased soybean sales volume across the distribution network.

Syncope is a common Emergency Department (ED) presentation. An important proportion of syncope patients are at risk of developing serious adverse events (SAEs), such as deaths or arrhythmias following ED disposition. Currently, no clinically-useful decision tool exists to reliably identify high-risk patients. This study derived a clinical decision tool to identify syncope patients at risk of developing SAEs after ED disposition. This study also examined key methodological considerations involved in deriving decision tools by comparing two different methodological approaches: a traditional and modern approach. The traditional approach led to an eight-variable decision tool that allowed simple clinical interpretation and use. The modern approach, which aims to avoid data-driven methodology and statistical overfitting, was used to derive a ten-variable decision tool. Both decision tools displayed acceptable and comparable performance in internal validation studies (c-statistic 0.87, 95% confidence interval 0.84-0.89). A future external validation study is required to comprehensively compare the methods.

Bakgrund: Outsourcing är ett fenomen och ett strategiskt styrinstrument som har utvecklats till att benämnas som en global trend. Outsourcing utgör även ett ständigt förekommande område inom den moderna forskningen. Förklaringen till utvecklingen är dels på grund av den globaliserade och konkurrenskraftiga värld som idag föreligger för företagen, dels på grund av de fördelar som kans uppnås med styrinstrumentet. Syfte: Vårt syfte med studien är att utifrån ett brett perspektiv kartlägga och tolka vilka faktorer som figurerar i beslutsunderlaget när ett företag fattar ett outsourcingbeslut. Kartläggningen vill vi sedan utveckla och översätta till ett praktiskt gångbart beslutsverktyg som ämnar möjliggöra ett mer effektivt och medvetet beslutsfattande hos verkliga företag. Vårt syfte är således att bemöta den problematik vi har identifierat i den tidigare forskningen, och samtidigt bidra till att framtida företag kan bemöta sina outsourcingbeslut på ett mer framgångsrikt sätt. Teoretisk referensram: Vår teoretiska referensram utgörs av de tre stora teoretiska inriktningarna Core vs. Peripheral, Transaction Cost Economics och Resource Based View. Till detta integreras vad forskningen lyfter avseende fördelar, nackdelar och risker med outsourcing. Tillsammans framhäver dessa teorier en uppsättning faktorer som belyser vad företag beaktar vid ett outsourcingbeslut. Metod: Vi utför en intervjustudie på fem svenska företag belägna i södra Sverige. Företagen är Husqvarna AB, Lammhults Design Group AB, Lantmännen ek. för., Tetra Pak AB och VIDA AB. I vår studie appliceras ett kvalitativt angreppssätt för att analysera och tolka det insamlade materialet. Resultat: Studien har resulterat till ett egenutvecklat beslutsverktyg vilket är förankrat i både forskning och företags erfarenheter. I analysen framkommer att vissa teoretiska faktorer visade sig ha starkt empiriskt stöd hos de studerade företagen, medan andra faktorer lös med sin frånvaro. Företagen kunde även tillföra sex unika faktorer vilka inte framkom ur teorierna. Sammantaget resulterade beslutsverktyget till 26 olika faktorer, samt en bilaga för att tydliggöra vad samtliga dessa faktorer innebär för ett outsourcingbeslut. Vår förhoppning är att vårt beslutsverktyg kommer att tillämpas av företag i framtiden, och att vi kan bidra till en mer effektiv verksamhetsstyrning hos företag. / Background: Outsourcing is a phenomenon and a strategic tool which have turned into a global trend. Outsourcing does also frequently occur as a subject of study within the modern research. The explanation behind the development of outsourcing are partly due to the globalized and competitive world which today exist for companies, and because of the advantages which can be achieved with the strategic tool. Purpose: Our purpose is to identify and interpret from a broad perspective which factors a company take into account while making an outsourcing decision. We then want to develop and translate this identification to a practical viable decision tool that intends to enable more efficient and conscious decision making within businesses. Our purpose is thus to address the problems we have identified in the previous research, while contributing to future companies so that they can meet their outsourcing decision in a more successful way. Theoretical framework: Our theoretical framework consists of the three major theories Core vs. Peripheral, Transaction Cost Economics and Resource Based View. In addition to this, we integrate what the research highlight regarding advantages, disadvantages and risks of outsourcing. Together these theories form a set of factors that illustrate what companies take into account while they make their outsourcing decisions. Method: We conduct an interview study of five Swedish companies located in the southern Sweden. The companies are Husqvarna AB, Lammhults Design Group AB, Lantmännen ek. för., Tetra Pak AB och VIDA AB. In our study we applied a qualitative approach to analyse and interpret our material. Findings: The study has led to a decision tool which has been developed upon both research and corporate experience. The analysis shows that some factors were found to have strong empirical support of the companies studies, while other where absent. The companies could also provide six unique factors which did not emerge from the theories. Overall, our decision tool resulted in 26 different factors, as well as an appendix to clear what all of these factors mean for an outsourcing decision. We hope that our decision tool will be applied by companies in the future, and that we can contribute to more efficient management of future businesses.

Despite the fact that unguided decision making might lead to inefficient and nonoptimal decisions, decisions made at organizational levels seldom utilise decisionanalytical tools. Several gaps between the decision-makers and the computer baseddecision tools exist, and a main problem in managerial decision-making involves the lack of information and precise objective data, i.e. uncertainty and imprecision may be inherent in the decision situation. We believe that this problem might be overcome by providing computer based decision tools capable of handling the uncertainty inherent in real-life decision-making. At present, nearly all decision analytic software is only able to handle precise input, and no known software is capable of handling full scale imprecision, i.e. imprecise probabilities, values and weights, in the form of interval and comparative statements. There are, however, some theories which are able to handle some kind of uncertainty, and which deal with computational and implementational issues, but if they are never actually operationalised, they are of little real use for a decision-maker. Therefore, a natural question is how a reasonable decision analytical framework can be built based on prevailing interval methods, thus dealing with the problems of uncertain and imprecise input? Further, will the interval approach actually prove useful? The framework presented herein handles theoretical foundations for, and implementations of, imprecise multi-level trees, multi-criteria, risk analysis, together with several different evaluation options. The framework supports interval probabilities, values, and criteria weights, as well as comparative statements, also allowing for mixing probabilistic and multi-criteria decisions. The framework has also been field tested in a number of studies, proving the usefulness of the interval approach.

Lameness and mastitis are the two most costly diseases in the dairy industry. Reduction of these diseases through housing and management is beneficial. Compost bedded pack (CBP) and sand freestall barns were compared in a long-term, on-farm study to assess the effect of housing on each disease. Another research objective was to evaluate the effects of ambient weather conditions on moisture and 20 cm internal temperature of CBP. Compost bedded pack moisture, C:N ratio, and internal temperature effects on cleanliness, mastitis, and bedding bacterial counts were also considered. The last research objective was to evaluate the economics of bedding material decisions in CBP and provide a user-friendly decision support tool to predict bedding costs and usefulness.

<p>How is research and science being used in political debate? An idea analysis of the debate about försäkringsmedicinskt beslutsstöd (decision tool in healthcare security)</p><p>This is a case study on different types of research use (utilization) The aim of this paper is to examine how the politicians make use of expertise and research in the parliamentary debate surrounding the decision tool in healthcare security (försäkringsmedicinskt beslutsstöd). The aim is also to find out to what extent different types of research use are present in this debate. In this case study the qualitative method of idea analysis is being used on the empirical material. The tool of analysis is based upon the theories of research use by Amara et al. (building on Beyer) and Carol Weiss. My conclusion is that the most common type of research use in this debate is the symbolic, followed by the conceptual type. The instrumental type of research use is the least frequent one in this debate.</p>

In almost all supply chains, materials need to be stored or buffered, implying that manufacturing companies need effective replenishment methods. However, this is challenging, since companies must balance inventory costs and customer service in complex and different situations. Therefore, it is important to choose replenishment methods carefully. One well-known and widespread method is Material Requirements Planning (MRP). But the method has problems, such as regarding volume flexibility. There are other methods, but the literature lacks case studies and detailed descriptions and analysis of them, especially for visually oriented methods. Therefore, it is important to explore different methods for materials supply. The purpose of this study is to analyze the application of visually oriented replenishment methods in manufacturing industry and further to design a tentative decision tool for selecting methods. The research aims to provide some answers to three key questions. The first research question concerns general factors that are important for evaluating how effective replenishment methods are. From the literature review, different factors emerged such as product characteristics (fit in the Kraljic matrix, volume issues, size, etc.); information, trust, and geographical proximity between supplier and customer; and different logistics goals (delivery service elements, tied-up capital, use of resources, inventory accuracy). It is also import to include the basic principles methods are related to. The factors were summarized in an analysis model, which is structured with three main areas (planning environment/conditions, basic principles, and effects). The model is used to analyze four case studies. The  second research  question focuses  on  the  characteristics for  visually orientedreplenishment methods. Examples of characteristics are: easy to understand and operate, offers uncomplicated flows, substantially applicable for noncritical and leverage parts with high yearly requirement and fairly even consumption, provides potential for  reduced  errors  in  stores/flows, potential for  providing high  delivery service and low levels of tied-up capital and resource utilization. The third research question focuses on what a tentative decision tool for selecting replenishment methods might look like, based on the factors that emerged from the other research questions and studies by others. In order to achieve an efficient materials supply, companies need to consider these factors when selecting replenishment methods. The decision tool consists of different steps, considering aspects of the planning environment/conditions in relation to the product and the supplier. The importance of the companies’ goals/motives for materials supply must also be assessed. The output from the decision tool is appropriate replenishment methods. / <p>QC 20130603</p>

L’étude et le choix des stratégies décisionnelles en santé animale nécessite de disposer d’informations sur l’efficacité des outils disponibles, qu’il s’agisse d’un test unique, d’une association de plusieurs tests ou d’un ensemble de critères cliniques et épidémiologiques. La validation des tests de dépistage ou de diagnostic constitue donc un prérequis à la conception de protocoles d’aide à la prise de décisions sanitaires. Lorsqu’il existe une référence fournissant une information sur le statut infectieux des individus étudiés, l’estimation des caractéristiques des tests peut être effectuée de manière directe. En santé animale, il est toutefois fréquent de ne pas disposer de cette information, lorsqu’aucun test ne référence n’est disponible ou lorsqu’il n’a pas pu être mis en œuvre, pour des raisons pratiques, économiques ou éthiques. Dans ce cas, l’étude des tests requiert l’utilisation de méthodes statistiques adaptées, telles l’utilisation de modèles à classe latente implémentés par une approche bayésienne. Nous avons choisi, au cours de nos travaux, de nous intéresser à l’estimation de la part d’incertitude liée à l’utilisation de tests en tant qu’outils d’aide à la prise de décision. Nous exposons dans un premier chapitre les enjeux et les modalités de la lutte contre les maladies animales, les outils épidémiologiques disponibles pour l’élaboration de stratégies décisionnelles et les méthodes permettant l’évaluation de ces outils et leur comparaison. Les trois chapitres suivants constituent une application de ces méthodes, dans des contextes différents correspondant à trois types de situations dans lesquelles il existe un besoin d’aide à la décision sanitaire en santé animale : le dépistage de la brucellose porcine chez les porcs reproducteurs, le dépistage de l’épididymite contagieuse du bélier chez les béliers destinés à l’export et le dépistage de la tuberculose bovine dans les départements de Côte d’Or et de Dordogne et dans la région camarguaise. Le dernier chapitre de ce manuscrit consiste en une discussion générale sur les modalités de choix d’un outil d’aide à la décision sanitaire. / Knowing the efficacy of a diagnostic tool, whether it is a test used alone, a sequence of several tests or a group of clinical criteria, is essential to study and choose decision strategies. The validation of diagnostic and screening tests is thus necessary to conceive decision schemes. When a gold standard is available, the characteristics of a test can be estimated directly. However, the true individual disease status of the animals is often unknown, particularly in absence of a gold standard or when the gold standard cannot be used because of economical, practical or ethical constraints. In these cases, specific statistical methods like latent class models implemented through a Bayesian approach must be used. Our work aimed at estimating the uncertainty due to the use of diagnostic tests as decision tools. The first chapter presents the issues and practical details of the struggle against animal disease and the epidemiological tools available to estimate the characteristics of the tests and to compare them. In the three following chapters, these methods are applied to three different contexts in which the conception and the evaluation of decision tools are needed: the screening of porcine brucellosis in breeding hogs, the screening of Brucella ovis infection in exported rams and the screening of bovine tuberculosis in Côte d’Or, Dordogne and Camargue (France). The last chapter consists in a global discussion about how to choose a decision tool.