635 research outputs found

    ENHANCING THE FINANCIAL AND MARKETING PERFORMANCE OF FIRMS IN THE SMOKED AND PROCESSED MEAT INDUSTRY

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    Small smoked and processed meat manufacturers constitute a unique cottage industry in Texas. This paper assesses ways for such firms to improve their financial performance through better marketing strategies. The results indicate that, on average, small firms tend to be the most profitable. This is true whether size is measured in terms of dollars, pounds, or number of employees. The more profitable firms tend to be those that are located in rural areas or in shopping centers; those that make the majority of their sales at their own stores; those that do less of their own distribution; and those that emphasize fresh meat sales and de-emphasize jerky sales.Agribusiness,

    SUIZA FOODS CORPORATION: BEST MANAGEMENT STRATEGY IN THE FLUID MILK INDUSTRY

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    Suiza Foods has rapidly grown to become the largest company in the U.S. fluid milk industry. This teaching case is designed to familiarize students with the challenges which confront Suiza in its quest for further growth and, in turn, high profitability. Interviews with top executives describe the history of Suiza as well as the rationale behind Suiza's strategies. Information is presented on both economic and financial trends so as to allow the student to asses Suiza's past, present and future performance.Agribusiness, Livestock Production/Industries,

    ENHANCING THE FINANCIAL PERFORMANCE OF SMALL MEAT PROCESSORS

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    The small firms examined produce meats in the State of Texas and emphasize such products as sausage, jerky, brisket, and fresh meats. The authors test hypotheses with the intent to identify operational factors associated with firm financial success. A quartile model and an econometric model are both used for this purpose. Results generally suggest important factors for firms to be profitable include product selection, pricing strategies, special equipment, and location.Agribusiness, Agricultural Finance,

    Formulating genome-scale kinetic models in the post-genome era

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    The biological community is now awash in high-throughput data sets and is grappling with the challenge of integrating disparate data sets. Such integration has taken the form of statistical analysis of large data sets, or through the bottom–up reconstruction of reaction networks. While progress has been made with statistical and structural methods, large-scale systems have remained refractory to dynamic model building by traditional approaches. The availability of annotated genomes enabled the reconstruction of genome-scale networks, and now the availability of high-throughput metabolomic and fluxomic data along with thermodynamic information opens the possibility to build genome-scale kinetic models. We describe here a framework for building and analyzing such models. The mathematical analysis challenges are reflected in four foundational properties, (i) the decomposition of the Jacobian matrix into chemical, kinetic and thermodynamic information, (ii) the structural similarity between the stoichiometric matrix and the transpose of the gradient matrix, (iii) the duality transformations enabling either fluxes or concentrations to serve as the independent variables and (iv) the timescale hierarchy in biological networks. Recognition and appreciation of these properties highlight notable and challenging new in silico analysis issues

    Communications Biophysics

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    Contains a summary of research publications and reports on four research projects.National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-04)National Aeronautics and Space Administration (Grant NsG-496

    Statistical Communication Theory

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    Contains research objectives and reports on six research projects
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