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Effectiveness of Planning Prompts on Organizations’ Likelihood to File Their Overdue Taxes: A Multi‐Wave Field Experiment

Nicole Robitaille (), Julian House () and Nina Mazar ()
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Nicole Robitaille: Smith School of Business, Queens University, Kingston, Ontario K7L 3N6, Canada
Julian House: Behavioural Insights Unit, Treasury Board Secretariat, Government of Ontario, Toronto, Ontario M7A 1Y7, Canada
Nina Mazar: Questrom School of Business, Boston University, Boston, Massachusetts 02215

Management Science, 2021, vol. 67, issue 7, 4327-4340

Abstract: This paper investigates the effectiveness of planning prompts on organizations’ tax compliance behavior. We conducted a large-scale, multi‐wave field experiment examining the tax-paying behavior of all organizations that failed to file timely annual returns for a payroll tax in the province of Ontario. Organizations were randomly assigned to receive one of two letters: Ontario’s standard late notice (control) and a revised experimental late notice, which included step-by-step instructions of when, where, and how to file a return. Our data indicate that planning prompts are effective at increasing organizations’ timely tax payment. In addition to replicating these findings across two waves, we demonstrate that, although our intervention did not appear to have effects that persisted across tax years, organizations also did not habituate to our manipulation and its effects were consistent across repeated exposures. Our study is among the first to demonstrate that a simple behavioral intervention that has typically been applied to individuals to help them to act upon their existing motivations can be effective in the realm of tax compliance and organizational behavior.

Keywords: government tax policy; economics behavior and behavioral decision making; organizational studies behavior; organizational studies decision making; field experiment (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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http://dx.doi.org/10.1287/mnsc.2020.3744 (application/pdf)

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