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Research Note ---Applying the Randomized Response Technique to Elicit Truthful Responses to Sensitive Questions in IS Research: The Case of Software Piracy Behavior

Samuel S. K. Kwan (), Mike K. P. So () and Kar Yan Tam ()
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Samuel S. K. Kwan: Department of Information Systems, Business Statistics and Operations Management, Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Hong Kong
Mike K. P. So: Department of Information and Systems, Business Statistics and Operations Management, Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Hong Kong
Kar Yan Tam: Department of Information and Systems, Business Statistics and Operations Management, Hong Kong University of Science and Technology (HKUST), Clear Water Bay, Hong Kong

Information Systems Research, 2010, vol. 21, issue 4, 941-959

Abstract: Research on software piracy often relies on self-reports by individual users and thus suffers from possible response distortion attributable to a variety of human motivations. Conclusions drawn directly from distorted self-reports may misguide managerial and policy decisions. The randomized response technique (RRT) was proposed as a remedy to response distortion. In this paper, a model based on RRT was used to illustrate how truthful responses to sensitive questions can be empirically estimated. The model was tested in two empirical studies on software piracy. Consistent with our expectations, respondents responding to RRT were more willing to disclose sensitive information about their attitudes, intentions, and behaviors on software piracy. Nontrivial distortions were demonstrated in causal relationships involving sensitive and nonsensitive variables. The study extends RRT to multivariate analysis and illustrates the feasibility and usefulness of the method in studying sensitive behavioral issues in the information systems (IS) domain.

Keywords: response distortion; software piracy; randomized response technique; unrelated question design; method of moments; socially desirable responding; structural equation modeling (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (4)

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