IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v30y2019i4p1363-1386.html
   My bibliography  Save this article

A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections

Author

Listed:
  • Jorge Mejia

    (Kelley School of Business, Indiana University, Bloomington, Indiana 47405)

  • Shawn Mankad

    (Samuel Curtis Johnson Graduate School of Management, Cornell University, Ithaca, New York 14853)

  • Anandasivam Gopal

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20742)

Abstract

From an upset stomach to a life-threatening foodborne illness, getting sick is all too common after eating in restaurants. Although health inspection programs are designed to protect consumers, such inspections typically occur at wide intervals of time, allowing restaurant hygiene to remain unmonitored in the interim periods. Information provided in online reviews may be effectively used in these interim periods to gauge restaurant hygiene. In this paper, we use textual information from online reviews of restaurants to effectively identify cases of hygiene violations in restaurants, even after the restaurants have been inspected and certified, thereby identifying moral hazard. Using a data set of restaurant hygiene inspections in New York City from 2010 through 2016 and the associated set of online reviews for the same set of restaurants from Yelp, we use supervised machine learning techniques to develop a hygiene dictionary specifically crafted to identify hygiene-related concerns. The use of this dictionary and the related word counts in online reviews allows us to identify systematic instances of moral hazard, wherein restaurants with positive hygiene inspection scores are seen to regress in their hygiene maintenance within 90 days of receiving the inspection scores. To the extent that social media provide some visibility into the hygiene practices of restaurants, we argue that the effects of information asymmetry that lead to moral hazard may be partially mitigated in this context. Based on our work, we also provide strategies for how cities and policymakers may design effective restaurant inspection programs, through a combination of traditional inspections and the appropriate use of social media.

Suggested Citation

  • Jorge Mejia & Shawn Mankad & Anandasivam Gopal, 2019. "A for Effort? Using the Crowd to Identify Moral Hazard in New York City Restaurant Hygiene Inspections," Information Systems Research, INFORMS, vol. 30(4), pages 1363-1386, December.
    • Handle: RePEc:inm:orisre:v:30:y:2019:i:4:p:1363-1386
    DOI: 10.1287/isre.2019.0866
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/isre.2019.0866
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2019.0866?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Martin Bichler & Alok Gupta & Wolfgang Ketter, 2010. "Research Commentary ---Designing Smart Markets," Information Systems Research, INFORMS, vol. 21(4), pages 688-699, December.
    2. S. Andrew Starbird, 2005. "Moral Hazard, Inspection Policy, and Food Safety," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(1), pages 15-27.
    3. Sinan Aral & Chrysanthos Dellarocas & David Godes, 2013. "Introduction to the Special Issue ---Social Media and Business Transformation: A Framework for Research," Information Systems Research, INFORMS, vol. 24(1), pages 3-13, March.
    4. Starbird S. Andrew & Amanor-Boadu Vincent, 2007. "Contract Selectivity, Food Safety, and Traceability," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 5(1), pages 1-22, February.
    5. Tobias J. Klein & Christian Lambertz & Konrad O. Stahl, 2016. "Market Transparency, Adverse Selection, and Moral Hazard," Journal of Political Economy, University of Chicago Press, vol. 124(6), pages 1677-1713.
    6. Michael C. Lovell, 1963. "Seasonal Adjustment of Economic Time Series and Multiple Regression," Cowles Foundation Discussion Papers 151, Cowles Foundation for Research in Economics, Yale University.
    7. Jonah Berger & Alan T. Sorensen & Scott J. Rasmussen, 2010. "Positive Effects of Negative Publicity: When Negative Reviews Increase Sales," Marketing Science, INFORMS, vol. 29(5), pages 815-827, 09-10.
    8. Joshua D. Angrist & Jörn-Steffen Pischke, 2009. "Mostly Harmless Econometrics: An Empiricist's Companion," Economics Books, Princeton University Press, edition 1, number 8769.
    9. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    10. Ginger Zhe Jin & Phillip Leslie, 2003. "The Effect of Information on Product Quality: Evidence from Restaurant Hygiene Grade Cards," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(2), pages 409-451.
    11. Decker, Reinhold & Trusov, Michael, 2010. "Estimating aggregate consumer preferences from online product reviews," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 293-307.
    12. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    13. Paul C. Tetlock & Maytal Saar‐Tsechansky & Sofus Macskassy, 2008. "More Than Words: Quantifying Language to Measure Firms' Fundamentals," Journal of Finance, American Finance Association, vol. 63(3), pages 1437-1467, June.
    14. Valerio Filoso, 2013. "Regression anatomy, revealed," Stata Journal, StataCorp LP, vol. 13(1), pages 92-106, March.
    15. Martin Gaynor & Deborah Haas-Wilson & William B. Vogt, 2000. "Are Invisible Hands Good Hands? Moral Hazard, Competition, and the Second-Best in Health Care Markets," Journal of Political Economy, University of Chicago Press, vol. 108(5), pages 992-1005, October.
    16. Francine Lafontaine, 1992. "Agency Theory and Franchising: Some Empirical Results," RAND Journal of Economics, The RAND Corporation, vol. 23(2), pages 263-283, Summer.
    17. Anonymous, 2013. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 8(3), pages 243-243, December.
    18. David J. Hand & Heikki Mannila & Padhraic Smyth, 2001. "Principles of Data Mining," MIT Press Books, The MIT Press, edition 1, volume 1, number 026208290x, April.
    19. Bruce E. Hansen, 2016. "The Risk of James--Stein and Lasso Shrinkage," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1456-1470, December.
    20. Susan Athey & Guido W. Imbens, 2006. "Identification and Inference in Nonlinear Difference-in-Differences Models," Econometrica, Econometric Society, vol. 74(2), pages 431-497, March.
    21. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    22. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    23. Steven Shavell, 1979. "On Moral Hazard and Insurance," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 93(4), pages 541-562.
    24. Hal R. Varian, 2014. "Big Data: New Tricks for Econometrics," Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 3-28, Spring.
    25. Marianne Bertrand & Esther Duflo & Sendhil Mullainathan, 2004. "How Much Should We Trust Differences-In-Differences Estimates?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 119(1), pages 249-275.
    26. Benjamin Balsmeier & Mohamad Assaf & Tyler Chesebro & Gabe Fierro & Kevin Johnson & Scott Johnson & Guan‐Cheng Li & Sonja Lück & Doug O'Reagan & Bill Yeh & Guangzheng Zang & Lee Fleming, 2018. "Machine learning and natural language processing on the patent corpus: Data, tools, and new measures," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(3), pages 535-553, September.
    27. Joseph E. Stiglitz, 2002. "Information and the Change in the Paradigm in Economics," American Economic Review, American Economic Association, vol. 92(3), pages 460-501, June.
    28. John M. Crespi & St)phan Marette, 2001. "How Should Food Safety Certification be Financed?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(4), pages 852-861.
    29. George A. Akerlof, 1970. "The Market for "Lemons": Quality Uncertainty and the Market Mechanism," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 84(3), pages 488-500.
    30. Feng Li, 2010. "The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 48(5), pages 1049-1102, December.
    31. Matthew Gentzkow & Bryan T. Kelly & Matt Taddy, 2017. "Text as Data," NBER Working Papers 23276, National Bureau of Economic Research, Inc.
    32. Jon Kleinberg & Jens Ludwig & Sendhil Mullainathan & Ziad Obermeyer, 2015. "Prediction Policy Problems," American Economic Review, American Economic Association, vol. 105(5), pages 491-495, May.
    33. John P Schomberg & Oliver L Haimson & Gillian R Hayes & Hoda Anton-Culver, 2016. "Supplementing Public Health Inspection via Social Media," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-21, March.
    34. Anonymous, 2013. "Introduction to the Issue," Journal of Wine Economics, Cambridge University Press, vol. 8(2), pages 129-130, November.
    35. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    36. Patrick Bajari & Denis Nekipelov & Stephen P. Ryan & Miaoyu Yang, 2015. "Machine Learning Methods for Demand Estimation," American Economic Review, American Economic Association, vol. 105(5), pages 481-485, May.
    37. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    38. Antonio Moreno & Christian Terwiesch, 2014. "Doing Business with Strangers: Reputation in Online Service Marketplaces," Information Systems Research, INFORMS, vol. 25(4), pages 865-886, December.
    39. Carl Shapiro, 1986. "Investment, Moral Hazard, and Occupational Licensing," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 53(5), pages 843-862.
    40. Jon Kleinberg & Himabindu Lakkaraju & Jure Leskovec & Jens Ludwig & Sendhil Mullainathan, 2018. "Human Decisions and Machine Predictions," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(1), pages 237-293.
    41. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    42. Ginger Zhe Jin & Phillip Leslie, 2009. "Reputational Incentives for Restaurant Hygiene," American Economic Journal: Microeconomics, American Economic Association, vol. 1(1), pages 237-267, February.
    43. Oded Netzer & Ronen Feldman & Jacob Goldenberg & Moshe Fresko, 2012. "Mine Your Own Business: Market-Structure Surveillance Through Text Mining," Marketing Science, INFORMS, vol. 31(3), pages 521-543, May.
    44. Irwin, K. & Ballard, J. & Grendon, J. & Kobayashi, J., 1989. "Results of routine restaurant inspections can predict outbreaks of foodborne illness: The Seattle-King County experience," American Journal of Public Health, American Public Health Association, vol. 79(5), pages 586-590.
    45. Tim Loughran & Bill Mcdonald, 2011. "When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks," Journal of Finance, American Finance Association, vol. 66(1), pages 35-65, February.
    46. Rubinstein, Ariel & Yaari, Menahem E., 1983. "Repeated insurance contracts and moral hazard," Journal of Economic Theory, Elsevier, vol. 30(1), pages 74-97, June.
    47. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Abderahman Rejeb & Alireza Abdollahi & Karim Rejeb & Mohamed M. Mostafa, 2023. "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2183-2209, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    2. Mochen Yang & Gediminas Adomavicius & Gordon Burtch & Yuqing Rena, 2018. "Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining," Information Systems Research, INFORMS, vol. 29(1), pages 4-24, March.
    3. Christoph Schneider & Markus Weinmann & Peter N.C. Mohr & Jan vom Brocke, 2021. "When the Stars Shine Too Bright: The Influence of Multidimensional Ratings on Online Consumer Ratings," Management Science, INFORMS, vol. 67(6), pages 3871-3898, June.
    4. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers Dissertations 13, Paderborn University, Faculty of Business Administration and Economics.
    5. Daniel Kaimann & Joe Cox, 2014. "The Interaction of Signals: A Fuzzy set Analysis of the Video Game Industry," Working Papers CIE 84, Paderborn University, CIE Center for International Economics.
    6. Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
    7. Pei-Yu Chen & Yili Hong & Ying Liu, 2018. "The Value of Multidimensional Rating Systems: Evidence from a Natural Experiment and Randomized Experiments," Management Science, INFORMS, vol. 64(10), pages 4629-4647, October.
    8. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R, Cowles Foundation for Research in Economics, Yale University, revised Sep 2020.
    9. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
    10. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    11. Colmekcioglu, Nazan & Marvi, Reza & Foroudi, Pantea & Okumus, Fevzi, 2022. "Generation, susceptibility, and response regarding negativity: An in-depth analysis on negative online reviews," Journal of Business Research, Elsevier, vol. 153(C), pages 235-250.
    12. Yipu Deng & Jinyang Zheng & Warut Khern-am-nuai & Karthik Kannan, 2022. "More than the Quantity: The Value of Editorial Reviews for a User-Generated Content Platform," Management Science, INFORMS, vol. 68(9), pages 6865-6888, September.
    13. Tobias Reckmann, 2017. "Verwendung von Word of Mouth-Daten zur Identifikation von Asymmetrie im Wettbewerb: Eine textbasierte Analyse am Beispiel deutscher Automobilmarken [Identification of asymmetric competition by usin," Schmalenbach Journal of Business Research, Springer, vol. 69(2), pages 173-201, June.
    14. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.
    15. Heeseung Andrew Lee & Angela Aerry Choi & Tianshu Sun & Wonseok Oh, 2021. "Reviewing Before Reading? An Empirical Investigation of Book-Consumption Patterns and Their Effects on Reviews and Sales," Information Systems Research, INFORMS, vol. 32(4), pages 1368-1389, December.
    16. Steffen Zimmermann & Philipp Herrmann & Dennis Kundisch & Barrie R. Nault, 2018. "Decomposing the Variance of Consumer Ratings and the Impact on Price and Demand," Information Systems Research, INFORMS, vol. 29(4), pages 984-1002, December.
    17. Mochen Yang & Yuqing Ren & Gediminas Adomavicius, 2019. "Understanding User-Generated Content and Customer Engagement on Facebook Business Pages," Information Systems Research, INFORMS, vol. 30(3), pages 839-855, September.
    18. Ishita Chakraborty & Minkyung Kim & K. Sudhir, 2019. "Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection," Cowles Foundation Discussion Papers 2176R2, Cowles Foundation for Research in Economics, Yale University, revised Jun 2021.
    19. Hui, Xiang & Klein, Tobias & Stahl, Konrad, 2022. "Learning from Online Ratings," CEPR Discussion Papers 17006, C.E.P.R. Discussion Papers.
    20. Natalia Levina & Manuel Arriaga, 2014. "Distinction and Status Production on User-Generated Content Platforms: Using Bourdieu’s Theory of Cultural Production to Understand Social Dynamics in Online Fields," Information Systems Research, INFORMS, vol. 25(3), pages 468-488, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:orisre:v:30:y:2019:i:4:p:1363-1386. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.