I-Corps: D-Ready Mobile Guide
I-Corps:D-Ready 移动指南
基本信息
- 批准号:1550507
- 负责人:
- 金额:$ 5万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-08-01 至 2017-01-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project focuses on techniques for survey analysis that can inform decision making -- potentially in a broad range of areas.D-Ready will use contemporary machine learning techniques to process and filter the data the team will collate regarding such areas as choice preferences. The proposed technology will be deployed with two goals in mind. A survey design methodology will be used to help ensure that decision-selection guidelines are unbiased for individual user. This is important because the more unbiased the decision support product, the more widely it will be trusted and used. The team will also use cursor-tracking technology to develop an in-depth statistical picture of how individual users view decision-support site-apps. This will allow for the team to use nonlinear regression and classification methods to segment users into distinct types. The insights learned from these analyses will be valuable to support decision makers in a broad range of applications. Applying the customer discovery process during the I-Corps curriculum, the team intends to come up with a more complete value proposition that it will provide and refine the product features that will be most useful.D-Ready is envisioned as an online and mobile decision support guide that creates customized information for users that is simple, convenient and unbiased. The proposed technology has potentially broad applications in several areas including marketing, for example, where a three-step strategy of 1) defining an attraction for a certain population, 2) harvesting detailed interactive behavior data while users react to that attraction, and finally 3) analyzing that data for the purpose of market segmentation, represents a powerful new form of survey collection.
这个项目的重点是调查分析技术,这些技术可以为决策提供信息--可能在广泛的领域。D-Ready将使用现代机器学习技术来处理和过滤团队将整理的关于选择偏好等领域的数据。这项拟议的技术在部署时将考虑到两个目标。将使用一种调查设计方法,以帮助确保决策选择准则对个人用户没有偏见。这一点很重要,因为决策支持产品越公正,它就越受信任和使用。该团队还将使用光标跟踪技术,开发关于个人用户如何查看决策支持网站应用程序的深入统计图片。这将使团队能够使用非线性回归和分类方法将用户划分为不同的类型。从这些分析中学到的洞察力将对支持决策者在广泛的应用中发挥重要作用。在i-Corps课程中应用客户发现流程,该团队打算提出一个更完整的价值主张,它将提供和完善最有用的产品功能。D-Ready被设想为一个在线和移动决策支持指南,为用户创建简单、方便和公正的定制信息。建议的技术在包括市场营销在内的几个领域具有潜在的广泛应用,例如,三步策略:1)为特定人群定义吸引力,2)在用户对该吸引力做出反应时收集详细的互动行为数据,最后3)出于市场细分的目的对数据进行分析,这代表了一种强大的新调查收集形式。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Ethan Bueno de Mesquita其他文献
From Investiture to Worms: A Political Economy of European Development and the Rise of Secular Authority∗
从任命权到蠕虫:欧洲发展的政治经济学和世俗权威的崛起*
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
B. B. D. Mesquita;Ethan Bueno de Mesquita - 通讯作者:
Ethan Bueno de Mesquita
Multitask , Accountability , and Institutional Design ∗
多任务、问责制和制度设计*
- DOI:
10.2139/ssrn.2463425 - 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Scott Ashworth;Ethan Bueno de Mesquita - 通讯作者:
Ethan Bueno de Mesquita
Optimal Retrospective Voting
最佳回顾性投票
- DOI:
- 发表时间:
2006 - 期刊:
- 影响因子:0
- 作者:
Ethan Bueno de Mesquita;A. Friedenberg - 通讯作者:
A. Friedenberg
Accountability, Selection, and Term Limits: Theory and Evidence from U.S. State Elections
问责制、选拔和任期限制:来自美国各州选举的理论和证据
- DOI:
10.2307/2297593 - 发表时间:
2006 - 期刊:
- 影响因子:0
- 作者:
J. Alt;Ethan Bueno de Mesquita;Shanna Rose - 通讯作者:
Shanna Rose
The Propaganda of the Deed: Terrorism, Counterterrorism, and Mobilization
行动的宣传:恐怖主义、反恐和动员
- DOI:
10.1111/j.1540-5907.2007.00256.x - 发表时间:
2007 - 期刊:
- 影响因子:4.2
- 作者:
Ethan Bueno de Mesquita;Eric S. Dickson - 通讯作者:
Eric S. Dickson
Ethan Bueno de Mesquita的其他文献
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{{ truncateString('Ethan Bueno de Mesquita', 18)}}的其他基金
RAPID: Higher Order Beliefs during a Pandemic: Theory and Evidence to Test the Effects of Public Health Campaigns
RAPID:大流行期间的更高阶信念:测试公共卫生运动效果的理论和证据
- 批准号:
2035682 - 财政年份:2020
- 资助金额:
$ 5万 - 项目类别:
Standard Grant
Collaborative Research on the Nature of Electoral Accountability
选举问责性质的合作研究
- 批准号:
0819152 - 财政年份:2008
- 资助金额:
$ 5万 - 项目类别:
Continuing Grant
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