CIVIC-PG Track B: Economic Resiliency through Mechanism Design and Secure Computing: MainStreetPulse: An Early Warning Platform for Monitoring and Supporting Main Street Businesses

该项目旨在利用加密技术、激励措施和公开数据更好地了解波士顿个体小企业和主要商业区的健康状况。利用这些技术，城市可以改善主要街道区的规划建议，并积极主动地确定有针对性的干预和支持陷入困境的企业。该项目的最终目标是创建可复制的工具，供所有城市使用，以保护和发展作为美国经济支柱的小企业部门，根据美国劳工统计局的数据，占所有经济活动的44%和美国所有员工的47%。它还将提供工具，以防止和减轻企业关闭对主要街道地区的影响。在SARS-CoV-2大流行的最初几个月里，这一挑战变得更加严峻，当时估计有10万家企业被迫关闭，远远高于每年退出的约60万家企业。为了实现这一目标，研究团队将开发一个预测模型和一个用户友好的应用程序，使用机制设计和安全计算。城市规划者和个体企业可以使用设想的云原生工具来做出关键决策，例如位置引用，租金和工资预算以及利用预计人口变化的销售预测。第1阶段的研究课题主要是围绕设计一种机制的可行性，以预测小企业的困境或关闭，根据现有的数据源的应用程序沿着的敏感数据由企业主贡献的结果，作为机制设计和安全计算技术的应用程序。该模型将在第二阶段试点中以社区规模进行测试。参与者将被激励贡献业务数据，因为安全的多方计算将允许团队在不访问原始数据的情况下开发模型。该项目是对公民创新挑战计划-轨道B的回应。弥合基本资源和服务社区需求之间的差距-是NSF、国土安全部和能源部之间的合作。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The project seeks to better understand the health of individual small businesses and Main Street business districts in Boston using cryptography, incentives, and publicly available data. Using these techniques, the city can improve planning recommendations for Main Street Districts and proactively identify distressed businesses for targeted interventions and support. The project ultimately aims to create replicable tools that can be used by all cities to protect and grow the small business sector which serves as the backbone of the American economy, accounting for 44% of all economic activity and 47% of all U.S. employees, according to the U.S. Bureau of Labor Statistics. It will also provide tools to prevent and mitigate the impact of business closures on Main Street districts. This challenge became even more acute during the first months of the SARS-CoV-2 pandemic when an estimated 100,000 businesses were forced to close, a volume much higher than the approximately 600,000 business that exit each year.To achieve this, the research team will develop a predictive model and a user-friendly application using mechanism design and secure computation. The envisioned cloud-native tool can be used by city planners and by individual businesses to make critical decisions such as location citing, rent and payroll budgets, and sales forecasts that leverage projected population shifts. The research questions for Stage 1 are primarily centered around the feasibility of designing a mechanism to predict the distress or closure of small businesses, based on the application of existing data sources along with sensitive data contributed by business owners as a result of the application of mechanism design and secure computation techniques. This model will be tested at the neighborhood scale in the Stage 2 pilot. Participants will be incentivized to contribute business data, because secure multi-party computation will allow the team to develop the model without ever having access to the original data.This project is in response to the Civic Innovation Challenge program—Track B. Bridging the gap between essential resources and services & community needs—and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.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.