Advances in behavioral decision analytics: Theory, Applications, and Training

该项目旨在帮助下一代数字版权管理系统研究减少对技术建模假设的依赖，这些假设可能会偏向或危及其研究结果的可解释性和可复制性。关键的想法是利用行为的异质性作为一种资产，而不是将其视为一种讨厌的东西。将理论与随时间、跨背景和决策者之间的可变性直接联系起来，将更好地使管理和政策与数亿人行为的共性和差异相协调，从而带来更大的社会相关性。该基金还旨在更好地概念化、定义和理解决策理论的范围。扩大理论范围意味着扩大政策覆盖范围：更广泛和更深入的视角为应用DRMS相关专业人员在更多时间和更多背景下支持更多人口的福祉铺平了道路。该项目具有理论、分析、经验和培训部分。拟议的研究开发了新的工具和模型来更好地理解偏好的强度，新的开源公共领域分析软件，在数据收集期间动态调整决策实验的新方法，以及概念化、定义和评估决策理论范围的创新方法。这些创新既为实证工作提供了信息，也建立在实证工作的基础上，这些工作更密切地关注行为的异质性和上下文依赖。该项目考虑了伦理/道德基础如何与证据权衡相互作用，框架如何与概率推理相互作用，风险和时间如何协同，以及比较个人和集体决策的新方法。培训部分侧重于下一代DRMS学者，在暑期学校培训初级学者，与他们的家庭实验室合作开展基于研究的培训，并促进受训人员研究项目的专门传播。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to help next-generation DRMS research reduce its reliance on technical modeling assumptions that could bias or jeopardize the interpretability and replicability of its findings. The key idea is to leverage heterogeneity of behavior as an asset rather than treating it as a nuisance. Directly connecting theories to variability over time, across contexts, and between decision makers, will better attune management and policy to both commonalities and differences in behavior across hundreds of millions of people, leading to greater societal relevance. The grant also aims to better conceptualize, define, and understand the scope of decision theories. Enhancing theoretical scope means expanding policy coverage: A broader and deeper perspective paves the way for applied DRMS-related professionals to support the well-being of a larger portion of the population at more times and in more contexts.The project features theoretical, analytical, empirical, and training components. The proposed research develops new tools and models to better understand strength of preference, new open-source public-domain analytics software, novel methods for adapting decision-making experiments dynamically during data collection, and innovative approaches toward conceptualizing, defining, and assessing the scope of decision theories. These innovations both inform and build on empirical work that looks more closely at heterogeneity of behavior and context-dependence. The project considers how ethical/moral foundations interact with evidence weighing, how framing interacts with probabilistic inference, how risk and time synergize, as well as novel ways to compare individual and collective decision making. The training component focuses on next-generation DRMS scholars by training junior scholars in summer schools, following-up with collaborative, research-based training jointly with their home labs, and facilitating dedicated dissemination of the trainees’ research projects.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.