When and Why Randomized Response Techniques (Fail to) Elicit the Truth

Leslie K. John; George   Loewenstein; Alessandro   Acquisti; Joachim  Vosgerau

Article | Organizational Behavior and Human Decision Processes | September 2018

When and Why Randomized Response Techniques (Fail to) Elicit the Truth

by Leslie K. John, George Loewenstein, Alessandro Acquisti and Joachim Vosgerau

Abstract

By adding random noise to individual responses, randomized response techniques (RRTs) are intended to enhance privacy protection and encourage honest disclosure of sensitive information. Empirical findings on their success in doing so are, however, mixed. In nine experiments, we show that the noise introduced by RRTs can make respondents concerned that innocuous responses will be interpreted as admissions, and, as a result, yield prevalence estimates that are lower than direct questioning (Studies 1–4, 5A, & 6), less accurate than direct questioning (Studies 1, 3, 4B, & 5A), and even nonsensical (i.e., negative, Studies 3–6). Studies 2A and 2B show that the paradox is eliminated when the target behavior is socially desirable, even when it is merely framed as such. Study 3 shows the paradox is driven by respondents’ concerns over response misinterpretation. A simple modification designed to reduce concerns over response misinterpretation reduces the problem (Studies 4 & 5), particularly when such concerns are heightened (Studies 5 & 6).

Keywords: truth-telling; Lying; privacy; information disclosure; survey research; Surveys; Attitudes; Behavior;

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Citation:

John, Leslie K., George Loewenstein, Alessandro Acquisti, and Joachim Vosgerau. "When and Why Randomized Response Techniques (Fail to) Elicit the Truth." Organizational Behavior and Human Decision Processes 148 (September 2018): 101–123.

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The case describes a program that CVS Health recently implemented to improve medication adherence, an important problem from a societal, public policy, and firm perspective. A test of the program, costing hundreds of thousands of dollars to implement, increased the proportion of adherent customers by 1.4 percentage points. Students are asked to quantify the system-wide economic benefit of this improvement and draw upon insights from behavioral science to examine approaches for boosting medication adherence.

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By the time Dan Doctoroff, CEO of Sidewalk Labs, began hosting a Reddit “Ask Me Anything” session in January 2018, he had only nine months remaining to convince the people of Toronto, their government representatives, and presumably his parent company Alphabet, Inc., that Sidewalk Labs’ plan to construct “the first truly 21st-century city” on the Canadian city’s waterfront was a sound one. Along with much excitement and optimism, strains of concern had emerged since Doctoroff and partners first announced their intentions for a city “built from the internet up” in Toronto’s Quayside district. As Doctoroff prepared for yet another milestone in a year of planning and community engagement, it was almost certain that of the many questions headed his way, digital privacy would be among them.

In their commentary, Wilson & Stolarz-Fantino argue that specific design features of our research mean that it cannot have policy implications and that researchers “need to consider profit maximization in menu design or studies are likely to suggest ill-informed implementations.” In this reply, we respond to the specific critiques of our work with empirical data and conceptual arguments. We agree with Wilson and Stolarz-Fantino that researchers seeking to understand a policy’s influence on consumers should test predictions about which strategies firms will likely use when implementing a policy. Research, however, that demonstrates the effectiveness (or lack thereof) of an intervention even without perfectly predicting a firm’s response still has enormous value for setting policy.

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When and Why Randomized Response Techniques (Fail to) Elicit the Truth

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