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Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

Citations

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Cited by:

  1. Gaglianone, Wagner Piazza & Giacomini, Raffaella & Issler, João Victor & Skreta, Vasiliki, 2022. "Incentive-driven inattention," Journal of Econometrics, Elsevier, vol. 231(1), pages 188-212.
  2. 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.
  3. Lu, Yi & Yan, Haosheng & Zhang, Zebang, 2026. "Compliance under in-between monitoring: evidence from a national land inspection system," Journal of Economic Behavior & Organization, Elsevier, vol. 245(C).
  4. 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.
  5. 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.
  6. 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.
  7. Chiara Farronato & Georgios Zervas, 2026. "Consumer Reviews and Regulation: Evidence from New York City Restaurants," Marketing Science, INFORMS, vol. 45(4), pages 752-772, July.
  8. Stevenson, Megan T. & Doleac, Jennifer, 2019. "Algorithmic Risk Assessment in the Hands of Humans," IZA Discussion Papers 12853, IZA Network @ LISER.
  9. 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).
  10. 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).
  11. 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).
  12. 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.
  13. Ho-Yin Mak, 2022. "Enabling Smarter Cities with Operations Management," Manufacturing & Service Operations Management, INFORMS, vol. 24(1), pages 24-39, January.
  14. 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.
  15. 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.
  16. 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.
  17. Kevin J. Boudreau, 2018. "Amateurs Crowds & Professional Entrepreneurs as Platform Complementors," NBER Working Papers 24512, National Bureau of Economic Research, Inc.
  18. 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.
  19. Araz Taeihagh, 2017. "Crowdsourcing, Sharing Economies and Development," Journal of Developing Societies, , vol. 33(2), pages 191-222, June.
  20. 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.
  21. 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.
  22. 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.
  23. Juan Carlos Perdomo, 2023. "The Relative Value of Prediction in Algorithmic Decision Making," Papers 2312.08511, arXiv.org, revised May 2024.
  24. Araz Taeihagh, 2017. "Crowdsourcing: a new tool for policy-making?," Policy Sciences, Springer;Society of Policy Sciences, vol. 50(4), pages 629-647, December.
  25. 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.
  26. Xiaoyan Wang & Xi Lin & Meng Li, 2021. "Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles," Papers 2102.07147, arXiv.org.
  27. 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.
  28. 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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