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Matching survey responses with anonymity in environments with privacy concerns: A practical guide

Dominik Vogel (Faculty of Business, Economics and Social Sciences, University of Hamburg, Hamburg, Germany)

International Journal of Public Sector Management

ISSN: 0951-3558

Article publication date: 4 June 2018

Issue publication date: 24 July 2018




In many cases, public management researchers’ focus lies in phenomena, embedded in a hierarchical context. Conducting surveys and analyzing subsequent data require a way to identify which responses belong to the same entity. This might be, for example, members of the same team or data from different organizational levels. It can be very difficult to collect such data in environments marked by high concerns for anonymity and data privacy. The purpose of this paper is to suggest a procedure for matching survey data without compromising respondents’ anonymity.


The paper explains the need for data collection procedures, which preserve anonymity and lays out a process for conducting survey research that allows for responses to be clustered, while preserving participants’ anonymity.


Survey research, preserving participants’ anonymity while allowing for responses to be clustered in teams, is possible if researchers cooperate with a custodian, trusted by the participants. The custodian assigns random identifiers to survey entities but does not get access to the data. This way neither the researchers nor custodians are able to identify respondents. This process is described in detail and illustrated with a factious research project.


Many public management research questions require responses to be clustered in dyads, teams, departments, or organizations. The described procedure makes such research possible in environments with privacy concerns; this is the case with many public administrations.



Vogel, D. (2018), "Matching survey responses with anonymity in environments with privacy concerns: A practical guide", International Journal of Public Sector Management, Vol. 31 No. 7, pp. 742-754.



Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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