We draw on behavioral science to investigate a set of decisions that may have an impact on public human resource management, thus affecting public service provision. Our survey-in-the-field-experiment with the nursing personnel of a local health authority showed that respondents’ decisions in the area of health care operations management were affected by social pressures (bandwagoning), the presence of a decoy option, and the framing of alternatives. Anchoring and halo effects severely biased the assessment of subordinates’ performance. Decisions in the domain of health policies were influenced by denominator neglect and zero-risk bias. Debiasing interventions eliminated the bandwagoning and framing effects. Being midway between abstract and un-testable grand theories and data-driven testable hypotheses, our findings advance behavioral human resource (HR) as a fruitful middle range theory in public personnel administration. Normative implications for scholars and practitioners about the power of the architecture of choices are discussed.
AbnerG. B.KimS. Y.PerryJ. L. (2017). Building evidence for public human resource management: Using middle range theory to link theory and data. Review of Public Personnel Administration, 37, 139-159.
2.
AlonsoD.Fernandez-BerrocalP. (2003). Irrational decisions: Attending to numbers rather than ratios. Personality and Individual Differences, 35, 1537-1547.
3.
AndersenS. C.HjortskovM. (2015). Cognitive biases in performance evaluations. Journal of Public Administration Research and Theory, 26, 647-662.
4.
ArielyD. (2010). Predictably irrational, revised and expanded edition: The hidden forces that shape our decisions. London, England: HarperCollins.
5.
BaekgaardM.SerritzlewS. (2016). Interpreting performance information: Motivated reasoning or unbiased comprehension. Public Administration Review, 76, 73-82.
6.
BaronJ.GowdaR.KunreutherH. (1993). Attitudes toward managing hazardous waste: What should be cleaned up and who should pay for it?Risk Analysis, 13, 183-192.
7.
BarrowsS.HendersonM.PetersonP. E.WestM. R. (2016). Relative performance information and perceptions of public service quality: Evidence from American school districts. Journal of Public Administration Research and Theory, 26, 571-583.
8.
BattaglioR. P. (2014). Public human resource management: Strategies and practices in the 21st century. Thousand Oaks, CA: SAGE.
9.
BelleN. (2013). Experimental evidence on the relationship between public service motivation and job performance. Public Administration Review, 73, 143-153.
10.
BelleN. (2014). Leading to make a difference: A field experiment on the performance effects of transformational leadership, perceived social impact, and public service motivation. Journal of Public Administration Research and Theory, 24, 109-136.
11.
BelleN.CantarelliP.BelardinelliP. (2017). Cognitive biases in performance appraisal: Experimental evidence on anchoring and halo effects with public sector managers and employees. Review of Public Personnel Administration, 37, 275-294. doi:10.1177/0734371X17704891
12.
BernoulliD. (1954). Exposition of a new theory on the measurement of risk. Econometrica: Journal of the Econometric Society, 22, 23-36.
13.
Blumenthal-BarbyJ. S.KriegerH. (2015). Cognitive biases and heuristics in medical decision making: A critical review using a systematic search strategy. Medical Decision Making, 35, 539-557.
14.
BolinoM. C.GrantA. M. (2016). The bright side of being prosocial at work, and the dark side, too: A review and agenda for research on other-oriented motives, behavior, and impact in organizations. Academy of Management Annals, 10, 599-670.
15.
BormanW. C. (1975). Effects of instructions to avoid halo error on reliability and validity of performance evaluation ratings. Journal of Applied Psychology, 60, 556-560.
16.
CharbonneauÉ.van RyzinG. G. (2015). Benchmarks and citizen judgments of local government performance: Findings from a survey experiment. Public Management Review, 17, 288-304.
CohenL.RothschildH. (1979). The bandwagons of medicine. Perspectives in Biology and Medicine, 22, 531-538.
20.
ColmanA. (2003). Group think: Bandwagon effect. In ColmanAndrew (Ed.), Oxford dictionary of psychology (p. 77). Oxford, UK.
21.
CornelissenJ. P.WernerM. D. (2014). Putting framing in perspective: A review of framing and frame analysis across the management and organizational literature. Academy of Management Annals, 8, 181-235.
22.
Denes-RajV.EpsteinS. (1994). Conflict between intuitive and rational processing: When people behave against their better judgment. Journal of Personality and Social Psychology, 66, 819-829.
23.
DiMaggioP.PowellW. (1983). The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields. American Sociological Review, 48, 147-160.
24.
EpsteinS. (1994). Integration of the cognitive and the psychodynamic unconscious. American Psychologist, 49, 709-724.
25.
FurnhamA.BooH. C. (2011). A literature review of the anchoring effect. The Journal of Socio-Economics, 40, 35-42.
26.
Garcia-RetameroR.GalesicM.GigerenzerG. (2010). Do icon arrays help reduce denominator neglect?Medical Decision Making, 30, 672-684.
27.
GardnerD. (2009). Risk: The science and politics of fear. Random House. London, UK: Virgin Books.
28.
GilovichT.GriffinD.KahnemanD. (Eds.). (2002). Heuristics and biases: The psychology of intuitive judgment. Cambridge, UK: Cambridge university press.
29.
GrantA. M. (2007). Relational job design and the motivation to make a prosocial difference. Academy of Management Review, 32, 393-417.
30.
GrimmelikhuijsenS.JilkeS.OlsenA. L.TummersL. (2017). Behavioral public administration: Combining insights from public administration and psychology. Public Administration Review, 77, 45-56.
31.
HolzbachR. L. (1978). Rater bias in performance ratings: Superior, self-, and peer ratings. Journal of Applied Psychology, 63, 579-588.
32.
HuberJ.PayneJ. W.PutoC. (1982). Adding asymmetrically dominated alternatives: Violations of regularity and the similarity hypothesis. Journal of Consumer Research, 9, 90-98.
33.
IngrahamP. W.Rubaii-BarrettN. (2007). Foundations of Public Administration Series: Human resource management as a core dimension of public administration. Washington, DC: American Society for Public Administration.
34.
JacobsR.KozlowskiS. W. (1985). A closer look at halo error in performance ratings. Academy of Management Journal, 28, 201-212.
35.
JamesO. (2010). Performance measures and democracy: Information effects on citizens in field and laboratory experiments. Journal of Public Administration Research and Theory, 21, 399-418.
36.
JilkeS.Van RyzinG. G.Van de WalleS. (2016). Responses to decline in marketized public services: An experimental evaluation of choice overload. Journal of Public Administration Research and Theory, 26, 421-432.
37.
JonesB. D. (2003). Bounded rationality and political science: Lessons from public administration and public policy. Journal of Public Administration Research and Theory, 13, 395-412.
KahnemanD. (2011). Thinking, fast and slow. New York, NY: Macmillan.
40.
KahnemanD.TverskyA. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 47, 263-292.
41.
KingL. M.HunterJ. E.SchmidtF. L. (1980). Halo in a multidimensional forced-choice performance evaluation scale. Journal of Applied Psychology, 65, 507-516.
42.
KirkpatrickL. A.EpsteinS. (1992). Cognitive-experiential self-theory and subjective probability: Further evidence for two conceptual systems. Journal of Personality and Social Psychology, 63, 534-544.
43.
LarrickR. P. (2004). Debiasing. In PowsnerRachel A.PowsnerEdward R. (Eds.), Blackwell handbook of judgment and decision making (pp. 316-338).
44.
LevinI. P.SchneiderS. L.GaethG. J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76, 149-188.
45.
LilienfeldS. O.AmmiratiR.LandfieldK. (2009). Giving debiasing away: Can psychological research on correcting cognitive errors promote human welfare?Perspectives on Psychological Science, 4, 390-398.
46.
MarvelJ. D. (2015). Public opinion and public sector performance: Are individuals’ beliefs about performance evidence-based or the product of anti–public sector bias?International Public Management Journal, 18, 209-227.
47.
MarvelJ. D. (2016). Unconscious bias in citizens’ evaluations of public sector performance. Journal of Public Administration Research and Theory, 26, 143-158.
48.
McNeilB. J.PaukerS. G.SoxH. C.Jr.TverskyA. (1982). On the elicitation of preferences for alternative therapies. The New England Journal of Medicine, 306, 1259-1262.
49.
MoynihanD. P.LavertuS. (2012). Does involvement in performance management routines encourage performance information use? Evaluating GPRA and PART. Public Administration Review, 72, 592-602.
50.
NielsenP. A. (2014). Learning from performance feedback: Performance information, aspiration levels, and managerial priorities. Public Administration, 92, 142-160.
51.
NisbettR. E.WilsonT. D. (1977). The halo effect: Evidence for unconscious alteration of judgments. Journal of Personality and Social Psychology, 35, 250-256.
52.
OkanY.Garcia-RetameroR.CokelyE. T.MaldonadoA. (2012). Individual differences in graph literacy: Overcoming denominator neglect in risk comprehension. Journal of Behavioral Decision Making, 25, 390-401.
53.
OlsenA. L. (2015a). Citizen (dis)satisfaction: An experimental equivalence framing study. Public Administration Review, 75, 469-478.
54.
OlsenA. L. (2015b, September). Negative performance information causes asymmetrical evaluations and elicits strong responsibility attributions. San Francisco, California: Annual meeting of the American Political Science Association.
55.
OlsenA. L. (2017a). Compared to what? How social and historical reference points affect citizens’ performance evaluations. Journal of Public Administration Research and Theory, 27, 562-580.
56.
OlsenA. L. (2017b). Human interest or hard numbers? Experiments on citizens’ selection, exposure, and recall of performance information. Public Administration Review, 77, 408-420.
57.
Organization for Economic Cooperation and Development. (2017). Behavioural insights and public policy: Lessons from around the world. Paris, France: Author. doi:10.1787/9789264270480-en
58.
PaciniR.EpsteinS. (1999). The interaction of three facets of concrete thinking in a game of chance. Thinking & Reasoning, 5, 303-325.
59.
PedersenR. T. (2017). Ratio bias and policy preferences: How equivalency framing of numbers can affect attitudes. Political Psychology, 38, 1103-1120.
60.
PerryJ. L. (1993). Strategic human resource management. Review of Public Personnel Administration, 13(4), 59-71.
61.
PerryJ. L. (2010). A strategic agenda for public human resource management research. Review of Public Personnel Administration, 30, 20-43.
62.
PerryJ. L.HondeghemA.WiseL. R. (2010). Revisiting the motivational bases of public service: Twenty years of research and an agenda for the future. Public Administration Review, 70, 681-690.
63.
ReynaV. F.BrainerdC. J. (2008). Numeracy, ratio bias, and denominator neglect in judgments of risk and probability. Learning and Individual Differences, 18, 89-107.
64.
SaposnikG.RedelmeierD.RuffC. C.ToblerP. N. (2016). Cognitive biases associated with medical decisions: A systematic review. BMC Medical Informatics and Decision Making, 16(1), Article 138.
65.
SimonH. A. (1956). Rational choice and the structure of the environment. Psychological Review, 63, 129-138.
66.
TaberC. S.LodgeM. (2006). Motivated skepticism in the evaluation of political beliefs. American Journal of Political Science, 50, 755-769.
67.
ThalerR. (2015). Misbehaving: The making of behavioral economics. New York, NY: W.W. Norton.
ViscusiW. K.MagatW. A.HuberJ. (1987). An investigation of the rationality of consumer valuations of multiple health risks. The RAND Journal of Economics, 18, 465-479.
76.
YamagishiK. (1997). When a 12.86% mortality is more dangerous than 24.14%: Implications for risk communication. Applied Cognitive Psychology, 11, 495-506.
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