FARM BUSINESS GOALS AND COMPETITIVE ADVANTAGE

This paper investigates empirically the relationship between both farm business goals and sources of competitive advantage, and various farm and producer characteristics using new primary data collected from a survey of Ohio farmers. Results show that most farmers do not recognize sources of competitive advantage and practice strategy implementation beyond reliance on longstanding paradigms for success within the context of government farm program support and the use of traditional risk management tools. However, several key insights emerge. Farmers who engage in cost leadership strategies are more profitable. Farmers who suggest that the goal of their farming operation is to enhance profitability/efficiency use more management tools, while lifestyle farmers use fewer. Larger farmers are more apt to engage in a cost leadership strategy, while those with higher debt-to-asset ratios and those that are more livestock oriented are more likely to engage in differentiation or focus strategies. Smaller farmers and those that produce specialty or value-added crops are more likely to focus on a particular niche market. Lastly, the use of the Internet as part of the farming operation does not influence the probability of engaging in any particular business strategy. It is apparent that the government farm program has contributed to a strategic where few producers have an explicit or implicit farm business strategy beyond "working the program" and acting as price takers. Or if a strategic choice is apparent, it rests primarily with cost leadership.Farm Management,

DETERMINANTS OF PRICE ELASTICITIES FOR STORE BRANDS AND NATIONAL BRANDS OF CHEESE

A two-stage modeling process is developed to estimate factors that determine price sensitivities for store and national brands of cheese. Results show that several factors affect price sensitivities. AIDS and LA/AIDS models are used in the analyses and meta-regression results show no difference in own-price elasticities for these two models.Demand and Price Analysis,

A SOCIOECONOMIC APPROACH TO ASSESSING PRICE COMPETITION BETWEEN PRIVATE LABELS AND NATIONAL BRANDS: THE CASE OF SHREDDED CHEESE

An LA/AIDS model is developed to estimate demand elasticities for packages of 8-oz shredded cheese for higher- and lower-income consumers. Data used in this study are scanner data for six supermarket stores in two distinct socioeconomic areas. Results show that: (1) lower-income shoppers are more price-sensitive than higher-income shoppers for both private labels and national brands; (2) compared with private labels, consumers are very sensitive to national brands price changes even in higher-income areas; (3) cross-price elasticities between private labels and national brands are all positive, i.e., private labels and national brands are substitutes in both lower- and higher-income stores; and (4) the number of promoted items does not have a statistically significant impact on sales; instead, the percentage of price discount affects sales for both private labels and national brands.Demand and Price Analysis,

A Continuum of Consumer Attitudes Toward Genetically Modified Foods in the United States

A national telephone survey was conducted in the United States in April 2002 to study the consumer acceptance of genetically modified (GM) foods. Attitudes toward GM foods were examined through the use of a multiple correspondence analysis (MCA), analyzing the interrelationships among many categorical variables. This method was combined with a cluster analysis to construct a typology of consumers' attitudes. Four distinct classes of attitudes were finally extracted, denoted as: Proponents, Non-Opponents, Moderate Opponents, and Extreme Opponents. It was estimated that only 35% of the surveyed population was opposed to GM foods.consumer acceptance, correspondence analysis, GM foods, telephone survey, Consumer/Household Economics, Research and Development/Tech Change/Emerging Technologies,

1982 Ohio Agribusiness Compensation Survey

Exact date of working paper unknown

EVALUATING OPTIMAL PRODUCT MIX USING DYNAMIC SIMULATION: A TOMATO PROCESSING CASE

Technology-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'Â’s 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.Agribusiness,