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英文文献：Development Of A Stochastic Model To Evaluate Plant Growers' Enterprise Budgets-建立了一个评估种植者企业预算的随机模型
英文文献作者：Ludena, Carlos E.,McNamara, Kevin T.,Hammer, P. Allen,Foster, Kenneth A.
英文文献摘要：
Increased domestic concentration and international competition in the floricultural industry are forcing growers to improve resource management efficiency. Cost management and cost accounting methods are becoming key tools as growers attempt to reduce costs. These tools allow growers to allocate costs for each crop, increasing their greenhouse planning abilities. Growers have a relative high degree of risk due to potential crop and market failure. Individual growers have different tolerance for risk and risk bearing capacity. Growers need a cost accounting system that incorporates production and market risk, a system that allows them to make informed business decisions. The research reported in this paper developed a greenhouse budgeting model that incorporated risk to allow growers to compare production costs for flowers with different genetics and production technologies. This enables greenhouse growers to make production management decisions that incorporate production and market risk. The model gives growers the option of imputing their own production data to evaluate how various yield and price assumptions influence income and expense projections, and ultimately, profit. The model allows growers to compare total production cost and revenue varying grower type, production time, geographical location, operation size, and cost structure. The model evaluates budgets for growers who market to mass-market retail operations or wholesale intermediaries who sell to merchandisers or flower shops distribution channels. The model was demonstrated with sample data to illustrate how incorporating risk analysis into a grower's greenhouse budget model effects resource allocation and production decisions as compare to a budget model that does not incorporate risk. Deterministic and stochastic models were used to demonstrate differences in production decisions under various assumptions. The stochastic model introduced prices and flowering characteristics variability. The @Risk software was used to generate the random number simulation of the stochastic model, and stochastic dominance analysis was used to rank the alternatives. The result for both the deterministic and stochastic models identified the same cultivar as most profitable. However, there were differences in crop profits levels and rankings for subsequent cultivars that could influence growers' production choice decisions. The grower's risk aversion level influenced his/her choice of the most profitable cultivars in the stochastic model. The model summarizes the sources of variability that affect cost and revenue. The model enables the grower to measure effects that change in productivity might have on profit. Growers can identify items in their budget that have a greater effect on profitability, and make adjustments. The model can be used to allocate cost across activities, so the grower would be able to measure the economic impact of an item on the budget.
国内花卉业集中度的提高和国际竞争迫使种植者提高资源管理效率。成本管理和成本会计方法正在成为种植者试图降低成本的关键工具。这些工具允许种植者为每种作物分配成本，提高他们的温室规划能力。由于潜在的作物和市场失灵，种植者有较高的风险。个体种植者对风险的容忍度和风险承受能力不同。种植者需要一个包含生产和市场风险的成本核算系统，一个允许他们做出明智的商业决策的系统。这篇论文中报道的研究开发了一个温室预算模型，该模型将风险纳入其中，使种植者能够比较不同基因和生产技术的花卉的生产成本。这使得温室种植者能够结合生产和市场风险做出生产管理决策。该模型为种植者提供了估算自己生产数据的选择，以评估各种产量和价格假设如何影响收入和支出预测，并最终影响利润。该模型允许种植者比较不同种植类型、生产时间、地理位置、经营规模和成本结构的总生产成本和收入。该模型评估了向大众市场零售经营的种植者或向商人或花店分销渠道销售的批发中间商的预算。该模型使用样本数据进行了演示，以说明与不包含风险的预算模型相比，将风险分析纳入种植者的温室预算模型如何影响资源分配和生产决策。用确定性模型和随机模型论证了不同假设下生产决策的差异。随机模型引入了价格和开花特征的变异性。利用@Risk软件生成随机模型的随机数模拟，采用随机优势度分析对备选方案进行排序。确定性模型和随机模型的结果都认为同一品种最有利可图。然而，随后品种的作物利润水平和排名存在差异，这可能影响种植者的生产选择决策。在随机模型中，栽培者的风险厌恶程度影响其对最盈利品种的选择。该模型总结了影响成本和收入的可变性的来源。该模型使种植者能够衡量生产力的变化可能对利润产生的影响。种植者可以在他们的预算中找出对利润有较大影响的项目，并做出调整。该模型可用于在各个生产活动之间分配成本，这样种植者就能够衡量某一项目对预算的经济影响。
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