Are future bureaucrats more prosocial?
| Author | Markus Tepe,Pieter Vanhuysse |
| Date | 01 December 2017 |
| Published date | 01 December 2017 |
| DOI | http://doi.org/10.1111/padm.12359 |
SYMPOSIUM ARTICLE
Are future bureaucrats more prosocial?
Markus Tepe
1
|Pieter Vanhuysse
2
1
Institute for Social Sciences, University of
Oldenburg, Oldenburg, Germany
2
Department of Political Science and Public
Management, University of Southern
Denmark, Odense, Denmark
Correspondence
Markus Tepe, Institute for Social Sciences,
University of Oldenburg, Ammerlaender
Heerstr. 114–118, Oldenburg, Lower Saxony,
D-26111, Germany.
Email: markus.tepe@uni-oldenburg.de
Funding information
Fritz Thyssen Foundation, Grant/Award
number: 10.13.1.113
This article explores the associations between self-reported Public
Service Motivation (PSM) and preferred job traits, study choice,
and observable prosocial behaviour. We studied three subject
pools covering over 250 university students in Germany. We used
laboratory experiments with monetary rewards to measure altru-
ism, fairness, strategic fairness, and cooperativeness, and a post-
experimental survey on subjects’PSM. Higher levels of PSM were
not associated with studying public administration but were posi-
tively associated with altruism and negatively with strategic fair-
ness. The experimental data reveal robust subject pool effects.
After controlling for PSM, public administration students behaved
more altruistically and displayed less merely strategic fairness than
business students. And they behaved more cooperatively than
business and law students. These behavioural findings about
future bureaucrats corroborate cumulative earlier survey evidence
about the higher prosocial tendencies of public sector employees.
They point to the danger of crowding out such tendencies through
overly extrinsic management tools.
1|INTRODUCTION
Public administration debates since the 1980s have been dominated by the New Public Management paradigm
(henceforth NPM). NPM aims to complement or sometimes replace traditional bureaucratic practices of human
resource management with incentive-based practices, partly borrowed from private sector settings and based on
material self-interest maximizing behavioural assumptions (Hood and Dixon 2015). Yet a large literature shows that
the desire to work in the public sector is positively correlated with prosocial motives that are largely ignored by
NPM. These include public interest, civic duty, and self-sacrifice (e.g., Perry 1996; Brewer 2003; Houston 2006;
Vandenabeele 2008; Perry et al. 2010; Coursey et al. 2011; Georgellis et al. 2011). Public sector motivation (hence-
forth PSM), it appears, is a ‘particular form of altruism or prosocial motivation that is animated by specific disposi-
tions and values arising from public institutions and missions ... (and) more prevalent in government than other
sectors’(Perry et al. 2010, p. 682).
If the actions of public employees are significantly based on such prosocial motives, this is likely to have impor-
tant consequences for the fit and effectiveness within public administration of NPM and other instruments based
DOI: 10.1111/padm.12359
Public Administration. 2017;95:957–975.wileyonlinelibrary.com/journal/padm© 2017 John Wiley & Sons Ltd957
on self-interest assumptions. For instance, prosocial behaviour could be crowded out or depleted after being
exposed to monetary or other extrinsic rewards, or group-oriented action might become the subject of performance
comparison (Frey and Jegen 2001; Georgellis et al. 2011; Bowles 2016). This would be counterproductive in impor-
tant ways. Prosocial behaviour significantly benefits groups and organizations through a lesser need for monitoring
of agents by principals (Gailmard 2010; Perry et al. 2010) and through higher levels of cooperation for collective
goals (Bowles and Gintis 2011; Gaechter 2014).
This article explores the link between PSM and the choice to study public administration, as compared to busi-
ness sciences or law, on observable prosocial behaviour. It offers new insights regarding the behavioural conse-
quences of self-reported PSM (differentiating the latter also by exploring subjectively preferred job characteristics)
and the effect of studying public administration on prosocial behaviour (Bozeman and Su 2015). Of course, public
administration and social psychology research has long been concerned with public/private behavioural differences
(Nalbandian and Edwards 1983; Wittmer 1991). But few studies have used behavioural experiments to identify pub-
lic administration-specific subject pool effects (e.g., Alatas et al. 2008). In a sense, we are thus tackling a question at
least as old as Rhinehart et al. (1969) with new experimental tools. In so doing, we respond to repeated calls for
experimental research in, and better behavioural foundations for, public administration (Bozeman 1992; Bozeman
and Su 2015, p. 706; Grimmelikhuijsen et al. 2017).
Despite the growing use of experimental designs in public administration research, laboratory experiments are
still rare (Tepe and Prokop 2017). To measure prosocial behaviour, we conduct three classic experimental games
(dictator game, ultimatum game and public goods game) with monetary rewards among three different subject pools
in Germany: university students of public administration, law, and business sciences and economics. Self-reported
PSM and preferred job characteristics are measured in a post-experimental survey. Our experimental design aims
less to identify causal relationships than to obtain appropriate measures of actual prosocial behaviour—revealed
rather than stated preferences—to explore the behavioural consequences of subjective variables such as PSM and
preferred job characteristics.
Our main findings can be summarized as follows: (1) PSM does not predict the choice to study public adminis-
tration, but it is associated with more altruistic and less strategically fair behaviour. (2) Subjects who consider secu-
rity as a more important job characteristic than monetary rewards are more likely to study public administration
than business sciences or law. But such preferences are not associated with actual prosocial behaviour. (3) Public
administration students both behave more altruistically and display less merely strategic fairness than business stu-
dents. And they behave more cooperatively than students of both business and law.
2|THEORETICAL FRAMEWORK
2.1 |Self-interested or cooperative norm-oriented motivations?
The debate on public employees’motivations is dominated by two paradigmatic action-theoretical ideal types: self-
interested bureaucrats and cooperative norm-oriented public servants. The first paradigm holds that bureaucrats are
not primarily interested in promoting the public interest or achieving public bureau goals, but instead try to maxi-
mize their personal goals (Downs 1967; Niskanen 1971). Given that bureaucrats have little influence on their salary
(e.g., because of career tracks), their incentives are predominantly non-pecuniary, such as the number of subordi-
nates, budget size, or office size. The NPM paradigm largely draws on this framework and on related principal–agent
theories to model the delegation problem in public organizations (Hood and Dixon 2015). But existing evidence on
the empirical validity of these self-interested behaviour assumptions is ambiguous at best (e.g., Zamir and
Sulitzeanu-Kenan 2017).
After more than 20 years of NPM reforms, even the precursors of principal–agent theory in public administra-
tion research (Miller and Whitford 2002, p. 233) are sceptical about its predictive power. This raises the concern
958 TEPE AND VANHUYSSE
Get this document and AI-powered insights with a free trial of vLex and Vincent AI
Get Started for FreeStart Your 3-day Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your 3-day Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your 3-day Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your 3-day Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting
Start Your 3-day Free Trial of vLex and Vincent AI, Your Precision-Engineered Legal Assistant
-
Access comprehensive legal content with no limitations across vLex's unparalleled global legal database
-
Build stronger arguments with verified citations and CERT citator that tracks case history and precedential strength
-
Transform your legal research from hours to minutes with Vincent AI's intelligent search and analysis capabilities
-
Elevate your practice by focusing your expertise where it matters most while Vincent handles the heavy lifting