The Economics of Experimentation in the Design of New Products and Processes

新产品和新工艺设计中的实验经济学

• 批准号: 9416177
• 负责人: Eric Von Hippel
• 金额: --
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-08-01 至 1997-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9416177&HistoricalAwards=false
• 关键词: Economics; Experimentation; Design; New; Products

Proposal #9416177 In many fields, researchers have traditionally found it economical to do research by creating and testing a few, well though-out experiments in the expectation of a high successful rate. Nature takes a different approach -creating many experiments and then screening for the few successful ones (random mutation and survival of the fittest). The cost-effectiveness of each experimental strategy depends on the relative cost of designing experiments versus "running" them and analyzing the results. Today, the relative costs of experimental steps associated with the design of new products and processes is being radically affected in many fields due to the use of new or greatly improved experimental methods such as simulation, mass screening and genetic algorithm techniques. Often, the effect of these techniques is to make "nature's" experimental approach increasingly cost-effective. This, in turn, is changing the way experimentation is being (or should be) done in many fields. This research examines the economics of the new forms of (often, computer assisted) experimentation in a number of fields, and to compare them with the economics of more traditional experimental methods. The findings of this research will provide academics with new insight into the economics of experimentation in the design of new products and processes. The findings will also enable developers of new products and processes and governmental decision makers to make better judgments with respect to the cost-effectiveness of experimentation strategies they may use during the development of new products and processes. For purposes of analysis, the execution of an experiment as involving a four-step cycle: (1) one conceives of or designs an experiment; (2) one builds the (physical or virtual) apparatus needed to conduct that experiment; (3) one runs the experiment; (4) one analyzes the result. Each of these four steps has a cost. The absolute and relative magnitude of these costs can affect exp erimental strategies. Thus, experimenters might logically strive to replace expensive experimental methods with cheaper ones. And, if step (1) - design of an experiment- is much cheaper than step (3) - running that experiment- one might logically expect an experimenter to invest more in step 4 -design- if by doing so he or she can reduce the cost or frequency of required experimental runs. Recently-developed experimental techniques such as simulation, mass screening and genetic algorithm techniques can radically affect the absolute and relative cost of the four steps involved in experimentation. 15 pairs of experiments (30 cases total) are studied. Each pair will contain one experiment performed in a manner that is traditional for the filed studied, and one experiment of a very similar type performed using a novel experimental technique such as those mentioned just above. Analyses of cost and benefits of these experimental pairs are followed by the creation and testing of hypotheses as to which techniques will be most effective in experimental conditions characterized by known levels of key variables such as the cost of generating materials or designs to be used as experimental inputs.

提案＃9416177在许多领域中，研究人员传统上发现，通过创建和测试一些实验来进行研究是经济的研究，这是在预期高成功率的情况下进行的。 大自然采用了不同的方法 - 创建许多实验，然后筛选少数成功的实验（合适的随机突变和生存）。 每个实验策略的成本效益取决于设计实验的相对成本与“运行”它们并分析结果的相对成本。 如今，由于使用了新的或大大改进的实验方法，例如模拟，质量筛选和遗传算法技术，与新产品和过程设计相关的实验步骤的相对成本正在受到根本影响。 通常，这些技术的效果是使“自然”的实验方法越来越具有成本效益。 反过来，这改变了在许多领域（或应该）进行实验的方式。 这项研究检查了许多领域（通常，计算机协助）实验的新形式的经济学，并将其与更传统的实验方法的经济学进行比较。 这项研究的结果将为学者提供新的产品和过程设计实验经济学的新见解。 这些发现还将使新产品和流程和政府决策者的开发人员就他们在开发新产品和流程期间可能使用的实验策略的成本效益做出更好的判断。 出于分析的目的，执行实验涉及四步周期：（1）一个人的想法或设计实验； （2）人们建立了进行该实验所需的（物理或虚拟）设备； （3）一个运行实验； （4）一个分析结果。这四个步骤中的每一个都有一个成本。 这些成本的绝对和相对大小会影响实验策略。 因此，实验者可能在逻辑上努力用便宜的实验方法代替昂贵的实验方法。 而且，如果步骤（1） - 实验的设计 - 比步骤（3）便宜得多 - 在逻辑上可能会期望实验者在步骤4 -Design -deSign-如果这样做可以降低所需的实验运行的成本或频率。 最近开发的实验技术，例如模拟，质量筛查和遗传算法技术，可以从根本上影响实验中涉及的四个步骤的绝对和相对成本。 研究了15对实验（总共30例）。 每对将包含一个以传统的研究方式进行的实验，以及使用新颖的实验技术进行的非常相似类型的实验，例如上面提到的实验技术。 这些实验对的成本和收益的分析之后，对假设的创建和检验是在实验条件下最有效的，以已知水平的关键变量（例如生成材料的成本或设计用作实验输入）为特征的实验条件。