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# 统计代写|SPSS代考|GEDU724 Models of Decision-Making

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## 统计代写|SPSS代考|Models of Decision-Making

In the classic rational model, economic man as the decision-maker has a clear goal, perfect information about all possible options, can assess all possible consequences of these options, can rank all options based on the consequences, and can choose the option that ranks highest. When the choice can result in different outcomes, and each outcome has a given probability, the decision-maker will choose based on a combination of probability and the utility (total satisfaction) of each possible outcome. This is called expected utility theory (Von Neumann \& Morgenstern, 1944). In simple terms, a decision-maker will always choose the option that gives the highest expected benefit. Two distinctive assumptions of this model are that (a) the decisionmaker only considers the statistical probability of the various outcomes, which implies risk neutrality, and (b) the decision-maker is not influenced by the way the options are presented. While the original theory was formulated using objective probability (based on data), later versions included subjective probability (intuition or judgment-based). It is a normative theory intended to suggest how decisions should be made, rather than a descriptive theory of how decisions are actually made (Plous, 1993).

The bounded rationality model, on the other hand, attempts to describe how individuals actually decide. It does not assume that decision-makers have perfect information about all alternatives and their consequences. Herbert Simon (1955) was central to developing this model. He argued that decision-makers, as a rule, seek an alternative that is satisfying and suffices (is good enough), or what he called, “satisficing.” When a decision-maker finds a satisfactory option, he or she chooses it without seeking better possible alternatives. This means that the order in which alternatives are discovered or presented affects the choice, which contradicts the assumptions of the classic rational model.

The third model we consider, developed by Kahneman and Tversky (1979) and called prospect theory, describes how individuals have different starting points and make choices under conditions of uncertainty. Decision-makers start with a set of options, called prospects. Each prospect has potential losses or gains. The decision is a function of weighing the gains against the losses from the given starting point, which is an important distinction from expected utility theory. People are more influenced by potential losses than gains, even when the expected value is identical. Experiments show that most people prefer a certain prize of $\$ 500$to a$50 \%$chance of winning$\$1000$, while most people prefer a $50 \%$ chance of losing $\$ 1000$to a certain loss of$\$500$. Expected utility theory values these two outcomes as equal, whereas prospect theory recognizes human nature’s aversion to losses. This implies that the way gains and losses are framed (presented) influences choice (Plous, 1993). Richard Thaler won the 2017 Nobel Prize for his theory of nudging (Thaler, 2015). Nudging could be described as subtle framing, a little push, on the decision process that can have substantial ramifications for choice.

## 统计代写|SPSS代考|Models of Politics and Power

The second main type of decision models focuses on organizational decision-making embedded in the context of politics and power. Decisions are reached through a struggle between different interest groups in the organization (Pfeffer \& Salancik, 1978). This struggle is similar to the conflicts in national politics. Decisions are often the result of conflicts where different interest groups apply pressure, and the outcome depends on who has the most power. This perspective says little on how the individual interest groups choose the alternatives they prefer, though it is reasonable to assume that they are a result of individual decision processes taking place prior to the political processes.

## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。