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Qualitative decision-making model of investment into start-up companies

机译:对初创公司的投资的定性决策模型

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摘要

The investments into start-up companies are often unique. The results are difficult to forecast. These investments are based on sparse and vague information, which is why statistical modelling methods are not applicable. Therefore, this paper applies qualitative modelling and qualitative decision tree to support investment decision-making into start-up companies. A team of experts was asked to describe start-up investment and 12 characteristics (variables) were chosen, e.g., profitability, market potential, etc. These variables were divided to two sets, variables that are under the management control - decision variables - and variables that are not under managerial control - lottery variables. The 12-dimensional models were developed; a common-sense analysis identifies 18 qualitative equationless relations and the model generated 20 scenarios. A subset of scenarios was transferred into a qualitative decision tree. The tree was evaluated to identify the best possible sequence of decisions using heuristics based on common-sense reasoning.
机译:对初创公司的投资通常是独一无二的。结果很难预测。这些投资基于稀疏和模糊的信息,这就是为什么统计建模方法不适用的原因。因此,本文运用定性建模和定性决策树来支持对初创公司的投资决策。要求一个专家团队描述启动投资,并选择了12个特征(变量),例如盈利能力,市场潜力等。这些变量分为两组,在管理控制下的变量-决策变量-和不受管理控制的变量-彩票变量。开发了12维模型;常识分析确定了18个定性的无方程关系,并且该模型生成了20个场景。方案的子集被转移到定性决策树中。使用基于常识推理的启发式方法对树进行评估,以确定最佳的决策顺序。

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