How Scheduling Can Bias Quality Assessment: Evidence from Food-Safety Inspections

Maria R. Ibanez () and Michael W. Toffel ()
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Maria R. Ibanez: Kellogg School of Management at Northwestern University, Evanston, Illinois 60208
Michael W. Toffel: Harvard Business School, Boston, Massachusetts 02163

Management Science, 2020, vol. 66, issue 6, 2396-2416

Abstract: Accuracy and consistency are critical for inspections to be an effective, fair, and useful tool for assessing risks, quality, and suppliers—and for making decisions based on those assessments. We examine how inspector schedules could introduce bias that erodes inspection quality by altering inspector stringency. Our analysis of thousands of food-safety inspections reveals that inspectors are affected by the inspection outcomes at their prior-inspected establishment ( outcome effects ), citing more violations after they inspect establishments that exhibited worse compliance levels or trends. Moreover, consistent with negativity bias, the effect is stronger after observing compliance deterioration than improvement. Inspection results are also affected by when the inspection occurs within an inspector’s day ( daily schedule effects ): Inspectors cite fewer violations after spending more time conducting inspections throughout the day and when inspections risk prolonging their typical workday. Overall, our findings suggest that currently unreported violations would be cited if the outcome effects—which increase scrutiny—were triggered more often and if the daily schedule effects—which erode scrutiny—were reduced. For example, our estimates indicate that if outcome effects were doubled and daily schedule effects were fully mitigated, 11% more violations would be detected, enabling remedial actions that could substantially reduce foodborne illnesses and hospitalizations. Understanding and addressing these inspection biases can help managers and policymakers improve not only food safety but also process quality, environmental practices, occupational safety, and working conditions.

Keywords: quality; scheduling; bias; discretion; inspection; behavioral operations; empirical; regulation; public health (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (12)

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