G2TT
来源类型Discussion paper
规范类型论文
来源IDDP17392
DP17392 Microfoundations of Low-Frequency High-Impact Decisions
Arnaldo Camuffo; Alfonso Gambardella; Fabio Maccheroni; Massimo Marinacci; Andrea Pignataro
发表日期2022-06-17
出版年2022
语种英语
摘要We argue that for low-frequency high-impact strategic decisions under uncertainty decision makers define, experiment with and choose models before defining, experimenting and choosing actions. Framing decisions are choices of attributes, logical links and theories that enable decision makers to rank models by concentrating probability distributions. We develop a model that shows that decision makers with a high prior on their models do not experiment, but when the prior is lower than a threshold, they benefit from experimenting with more uncertain models in less familiar domains. As the prior on the less uncertain models declines, decision-makers are more likely to search for alternative models in less familiar domains, and either run larger scale more informative experiments (if they are not resource-constrained) or pick a decision rule that is less likely to reject the alternative decision problem (if they are resource-constrained). Our framework explains how and why decision-makers can make better strategic decisions from a wider exploration. We provide examples that illustrate the application of our framework.
主题Organizational Economics
关键词Decision problem Experiments Exploration Framing Strategy Theory Uncertainty
URLhttps://cepr.org/publications/dp17392
来源智库Centre for Economic Policy Research (United Kingdom)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/546453
推荐引用方式
GB/T 7714
Arnaldo Camuffo,Alfonso Gambardella,Fabio Maccheroni,et al. DP17392 Microfoundations of Low-Frequency High-Impact Decisions. 2022.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Arnaldo Camuffo]的文章
[Alfonso Gambardella]的文章
[Fabio Maccheroni]的文章
百度学术
百度学术中相似的文章
[Arnaldo Camuffo]的文章
[Alfonso Gambardella]的文章
[Fabio Maccheroni]的文章
必应学术
必应学术中相似的文章
[Arnaldo Camuffo]的文章
[Alfonso Gambardella]的文章
[Fabio Maccheroni]的文章
相关权益政策
暂无数据
收藏/分享

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。