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Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

Citations

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Cited by:

  1. Galdo, Virgilio & Li, Yue & Rama, Martin, 2021. "Identifying urban areas by combining human judgment and machine learning: An application to India," Journal of Urban Economics, Elsevier, vol. 125(C).
  2. Juan Manuel Ponce Romero & Stephen H. Hallett & Simon Jude, 2017. "Leveraging Big Data Tools and Technologies: Addressing the Challenges of the Water Quality Sector," Sustainability, MDPI, vol. 9(12), pages 1-19, November.
  3. Gaglianone, Wagner Piazza & Giacomini, Raffaella & Issler, João Victor & Skreta, Vasiliki, 2022. "Incentive-driven inattention," Journal of Econometrics, Elsevier, vol. 231(1), pages 188-212.
  4. Suying Gao & Xiangshan Jin & Ye Zhang, 2021. "User Participation Behavior in Crowdsourcing Platforms: Impact of Information Signaling Theory," Sustainability, MDPI, vol. 13(11), pages 1-19, June.
  5. Stevenson, Megan T. & Doleac, Jennifer, 2019. "Algorithmic Risk Assessment in the Hands of Humans," IZA Discussion Papers 12853, IZA Network @ LISER.
  6. Kevin J. Boudreau, 2018. "Amateurs Crowds & Professional Entrepreneurs as Platform Complementors," NBER Working Papers 24512, National Bureau of Economic Research, Inc.
  7. David R. Agrawal & William F. Fox, 2026. "The Smarter State? Artificial Intelligence and Modern State and Local Public Finance," CESifo Working Paper Series 12716, CESifo.
  8. Hayakawa, Kazunobu & Keola, Souknilanh & Urata, Shujiro, 2022. "How effective was the restaurant restraining order against COVID-19? A nighttime light study in Japan," Japan and the World Economy, Elsevier, vol. 63(C).
  9. Jane Andrew & Max Baker, 2021. "The General Data Protection Regulation in the Age of Surveillance Capitalism," Journal of Business Ethics, Springer, vol. 168(3), pages 565-578, January.
  10. Fiona Burlig & Christopher Knittel & David Rapson & Mar Reguant & Catherine Wolfram, 2020. "Machine Learning from Schools about Energy Efficiency," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 7(6), pages 1181-1217.
  11. Araz Taeihagh, 2017. "Crowdsourcing, Sharing Economies and Development," Journal of Developing Societies, , vol. 33(2), pages 191-222, June.
  12. Hyunjin Kim & Edward L. Glaeser & Andrew Hillis & Scott Duke Kominers & Michael Luca, 2024. "Decision authority and the returns to algorithms," Strategic Management Journal, Wiley Blackwell, vol. 45(4), pages 619-648, April.
  13. SJ, Balaji & Babu, Suresh Chandra & Pal, Suresh, 2021. "Understanding Science and Policy Making in Agriculture: A Machine Learning Application for India," 2021 Conference, August 17-31, 2021, Virtual 315227, International Association of Agricultural Economists.
  14. Xiaoyan Wang & Xi Lin & Meng Li, 2021. "Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles," Papers 2102.07147, arXiv.org.
  15. Ho-Yin Mak, 2022. "Enabling Smarter Cities with Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 24(1), pages 24-39, January.
  16. Maria R. Ibanez & Michael W. Toffel, 2020. "How Scheduling Can Bias Quality Assessment: Evidence from Food-Safety Inspections," Management Science, INFORMS, vol. 66(6), pages 2396-2416, June.
  17. Susan Athey, 2018. "The Impact of Machine Learning on Economics," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 507-547, National Bureau of Economic Research, Inc.
  18. Elliott Ash & Sergio Galletta & Tommaso Giommoni, 2025. "A Machine Learning Approach to Analyze and Support Anticorruption Policy," American Economic Journal: Economic Policy, American Economic Association, vol. 17(2), pages 162-193, May.
  19. Josh Matti & Jane E. Ruseski, 2024. "The location of urban healthcare services: Evidence from Phoenix Yelp reviews," Southern Economic Journal, John Wiley & Sons, vol. 91(1), pages 92-117, July.
  20. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
  21. Brandt, Tobias & Wagner, Sebastian & Neumann, Dirk, 2021. "Prescriptive analytics in public-sector decision-making: A framework and insights from charging infrastructure planning," European Journal of Operational Research, Elsevier, vol. 291(1), pages 379-393.
  22. Andersson, Magnus & Hayakawa, Kazunobu & Keola, Souknilanh & Yamanouchi, Kenta, 2025. "Impacts of international transport infrastructure: Evidence from Laotian households," Journal of Asian Economics, Elsevier, vol. 97(C).
  23. Edward L. Glaeser & Scott Duke Kominers & Michael Luca & Nikhil Naik, 2018. "Big Data And Big Cities: The Promises And Limitations Of Improved Measures Of Urban Life," Economic Inquiry, Western Economic Association International, vol. 56(1), pages 114-137, January.
  24. Juan Carlos Perdomo, 2023. "The Relative Value of Prediction in Algorithmic Decision Making," Papers 2312.08511, arXiv.org, revised May 2024.
  25. Araz Taeihagh, 2017. "Crowdsourcing: a new tool for policy-making?," Policy Sciences, Springer;Society of Policy Sciences, vol. 50(4), pages 629-647, December.
  26. Susan Athey & Michael Luca, 2019. "Economists (and Economics) in Tech Companies," Journal of Economic Perspectives, American Economic Association, vol. 33(1), pages 209-230, Winter.
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