Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy
نویسندگان
چکیده
Big data and predictive analytics have the potential to make cities more efficient. Yet cities often lack the resources to use new data and methods effectively, and private researchers often lack the incentives to help solve the problems that cities face. New platforms—such as Kaggle, TopCoder, and DrivenData—now enable governments and other organizations to outsource large-scale prediction problems via open tournaments. But can open tournaments really help solve public problems? In this paper, we theoretically and empirically explore the potential of prediction tournaments to improve city operations and translate data science insights into practice. In Section I, we present a formal model
منابع مشابه
Nber Working Paper Series Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy
Can open tournaments improve the quality of city services? The proliferation of big data makes it possible to use predictive analytics to better target services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to crowdsource competence by making data public and ...
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