Studies of victim number effects in charitable giving consistently find that people care more and help more when presented with an appeal to help an individual compared with an appeal to help multiple people in need. Across three online experiments (N = 1,348), Bayesian estimation revealed the opposite pattern when people responded to multiple appeals to help targets of different sizes (1, 2, 5, 7, and 12). In this joint evaluation context, participants donated more to larger groups, when appeals were presented in both ascending order (Study 1) and random order (Study 2). The pattern held whether or not participants saw an overview of all appeals at the start of the study and when a single individual was added to the array (Study 3). These results clarify how compassion fade findings typical of separate evaluations may not generalize to contexts in which people encounter multiple appeals within a short temporal window.
BaronJ.GreeneJ. (1996). Determinants of insensitivity to quantity in valuation of public goods: Contribution, warm glow, budget constraints, availability, and prominence. Journal of Experimental Psychology: Applied, 2(2), 107–125.
2.
BazermanM. H.TenbrunselA. E.Wade-BenzoniK. (1998). Negotiating with yourself and losing: Making decisions with competing internal preferences. Academy of Management Review, 23(2), 225–241.
3.
BrooksS. P.GelmanA. (1998). General methods for monitoring convergence of iterative simulations. Journal of Computational and Graphical Statistics, 7(4), 434–455.
4.
BürknerP. C. (2017). brms: An R package for Bayesian multilevel models using Stan. Journal of Statistical Software, 80(1), 1–28. https://doi.org/10.18637/jss.v080.i01
5.
BürknerP. C.CharpentierE. (2018). Monotonic effects: A principled approach for including ordinal predictors in regression models. Available from https://osf.io/kvrsg/
6.
ButtsM. M.LuntD. C.FrelingT. L.GabrielA. S. (2019). Helping one or helping many? A theoretical integration and meta-analytic review of the compassion fade literature. Organizational Behavior and Human Decision Processes, 151, 16–33.
7.
CameronC. D.PayneB. K. (2011). Escaping affect: How motivated emotion regulation creates insensitivity to mass suffering. Journal of Personality and Social Psychology, 100(1), 1–15.
8.
DesvousgesW.MathewsK.TrainK. (2012). Adequate responsiveness to scope in contingent valuation. Ecological Economics, 84, 121–128.
9.
DickertS.KleberJ.VästfjällD.SlovicP. (2016). Mental imagery, impact, and affect: A mediation model for charitable giving. PLOS ONE, 11(2), Article e0148274.
10.
DickertS.VästfjällD.KleberJ.SlovicP. (2015). Scope insensitivity: The limits of intuitive valuation of human lives in public policy. Journal of Applied Research in Memory and Cognition, 4(3), 248–255. https://doi.org/10.1016/j.jarmac.2014.09.002
11.
ErlandssonA.BjörklundF.BäckströmM. (2015). Emotional reactions, perceived impact and perceived responsibility mediate the identifiable victim effect, proportion dominance effect and in-group effect respectively. Organizational Behavior and Human Decision Processes, 127, 1–14.
12.
FaulF.ErdfelderE.BuchnerA.LangA. G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160.
13.
FestingerL. (1957). A theory of cognitive dissonance. Stanford University Press.
14.
GelmanA.CarlinJ. B.SternH. S.RubinD. B. (2004). Bayesian data analysis (2nd ed.). Chapman & Hall.
15.
GinoF.ShuL. L.BazermanM. H. (2010). Nameless + harmless = blameless: When seemingly irrelevant factors influence judgment of (un) ethical behavior. Organizational Behavior and Human Decision Processes, 111(2), 93–101.
16.
HoffmanM. D.GelmanA. (2014). The No-U-Turn sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research, 15(1), 1593–1623.
17.
HseeC. K.ZhangJ.LuZ. Y.XuF. (2013). Unit asking: A method to boost donations and beyond. Psychological Science, 24(9), 1801–1808. https://doi.org/10.1177/0956797613482947
18.
KahnemanD.FrederickS. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In GilovichT.GriffinD.KahnemanD. (Eds.), Heuristics of intuitive judgment: extensions and applications. Cambridge University Press.
19.
KahnemanD. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58(9), 697–720.
20.
KahnemanD.RitovI.SchkadeD. (1999). Economic preferences or attitude expressions? An analysis of dollar responses to public issues. Journal of Risk and Uncertainty, 19(1/3), 203–235.
21.
KogutT.RitovI. (2005a). The “identified victim” effect: An identified group, or just a single individual?Journal of Behavioral Decision Making, 18(3), 157–167.
22.
KogutT.RitovI. (2005b). The singularity effect of identified victims in separate and joint evaluations. Organizational Behavior and Human Decision Processes, 97(2), 106–116.
23.
RubaltelliE.HysenbelliD.DickertS.MayorgaM.SlovicP. (2020). Asymmetric cost and benefit perceptions in willingness-to-donate decisions. Journal of Behavioral Decision Making, 33(3), 304–322. https://doi.org/10.1002/bdm.2164
24.
SaldanaJ. (2009). The coding manual for qualitative researchers. SAGE.
25.
SimonD.HolyoakK. J. (2002). Structural dynamics of cognition: From consistency theories to constraint satisfaction. Personality and Social Psychology Review, 6(4), 283–294.
26.
SlovicP. (2007). “If I look at the mass I will never act”: Psychic numbing and genocide. Judgment and Decision Making, 2(2), 79–95.
27.
SlovicS.SlovicP. (2015). Numbers and nerves: Information, emotion, and meaning in a world of data. Oregon State University Press. Retrieved March 18, 2018, from Project MUSE database
28.
SmallD. A.LoewensteinG.SlovicP. (2007). Sympathy and callousness: The impact of deliberative thought on donations to identifiable and statistical victims. Organizational Behavior and Human Decision Processes, 102(2), 143–153.
29.
SmithR. W.FaroD.BursonK. A. (2013). More for the many: The influence of entitativity on charitable giving. Journal of Consumer Research, 39(5), 961–976.
30.
TetlockP. E.MellersB. A. (2002). The great rationality debate. Psychological Science, 13(1), 94–99.
VästfjällD.SlovicP.MayorgaM. (2015). Pseudoineffacy: Negative feelings from children who cannot be helped reduce warm glow for children who can be helped. Frontiers in Psychology, 6, Article 616. https://doi.org/10.3389/fpsyg.2015.00616
33.
VästfjällD.SlovicP.MayorgaM.PetersE. (2014). Compassion fade: Affect and charity are greatest for a single child in need. PLOS ONE, 9(6), Article e100115. https://doi.org/10.1371/journal.pone.0100115
34.
WendorfC. A. W. (2004). Primer on multiple regression coding: Common forms and the additional case of repeated contrasts. Understanding Statistics, 3(1), 47–57.
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