Evaluating Optimal Product Mix Using Dynamic Simulation: A Tomato Processing Case
AbstractTechnology-driven change is everywhere and value-capture from new technology is challenging for business managers. Also rival firms may use technology as part of major success strategies. This situation leads managers to be keenly interested in evaluation of alternative technologies prior to making a sunk investment in physical facilities. In contemplating new or added-capacity processing facilities, managers and investors must evaluate return on investment (ROI). Evaluation of ROI is complex because it varies by alternative technology and the resultant potential product mix alternatives associated with that technology at the time the investment capital is committed to build the processing plant. This research examines optimal alternative product mix from a processing plant technology that is fixed at the time of commitment to building or adding capacity. Evaluating the optimal product mix is of vital concern in any start-up processing environment. In this research the optimal product mix is evaluated by using a sophisticated evaluative tool known as PowerSim. This economic simulation software is used to model a start-up tomato processing plant in Ohio. The model evaluates the effects of various output, or tomato product mix, on plant profitability measured by ROI. Results indicate that an increase in plant profitability is expected when the tomato product mix consists of products that have a lower soluble solids concentration. The lower the soluble solids concentration of a tomato product, the less the processor will benefit from tomato varieties with high soluble solids. The processing operation achieves a RIO of 26.5 percent when the plant'ï¿½s product mix is 50 percent tomato paste (31 degrees brix) and 50 percent diced tomatoes. This product mix optimizes processor net income and realizes a plant return on equity of 50.6 percent.
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Bibliographic InfoArticle provided by Food Distribution Research Society in its journal Journal of Food Distribution Research.
Volume (Year): 32 (2001)
Issue (Month): 01 (March)
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