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\title{How decision context changes the balance between cost and benefit increasing charitable donations}

\author{
Marta Caserotti\thanks{University of Padova}
\and
Enrico Rubaltelli\thanks{Corresponding author: University of Padova,
  Department of Developmental and Socialization Psychology,
Via Venezia, 8--35131 Padova, Italy. Email: enrico.rubaltelli@unipd.it.}
\and
Paul Slovic\thanks{Decision Research and University of Oregon}
}

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\newcommand{\jref}{http://journal.sjdm.org/vol14.2.html}
\newcommand{\jhead}{Judgment and Decision Making, Vol.~14, No.~2}
\newcommand{\jdate}{March 2019}
\pagestyle{myheadings} \markright{\protect\small \href{\jref}{\jhead}, \jdate \hfill Perceived cost and benefit in prosocial behavior \qquad}
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\href{\jref}{\jhead}, \jdate, pp.\ 187-198
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{\small \href{\jref}{\jhead}, \jdate, pp.\ 187--198}
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\begin{onecolabstract}
%\end{latexonly}
  Recent research on charitable donations shows that donors evaluate both
  the impact of helping and its cost. We asked whether these evaluations
  were affected by the context of alternative charitable causes. We found
  that presenting two donation appeals in joint evaluation, as compared to
  separate evaluation, increased the perceived benefit of the cause ranked
  as more important (Study 1), and decreased its perceived cost, regardless
  of the relative actual costs (Study 2).  Finally, we try to reconcile an
  explanation based on perceived cost and benefit with previous work on
  charitable donations.

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\smallskip
\noindent
Keywords: prosocial behavior, altruism, decision context, charity
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]
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{\renewcommand{\thefootnote}{}

\footnotetext{

This material is based upon work supported by the National Science
Foundation under Grant Nos.~1227729 and 1427414. Any opinions,
findings, and conclusions or recommendations expressed in this material
are those of the authors and do not necessarily reflect the views of
the National Science Foundation.

Copyright: \copyright\ 2018.
The authors license this article under the terms of the
\href{http://creativecommons.org/licenses/by/3.0/}{Creative Commons
  Attribution 3.0 License.}
}}

\saythanks

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\section{Introduction}
People trying to determine whether to make a donation to a given cause
are likely to consider several factors. Many potential donors feel so moved by a
specific charitable cause that they perceive that cause as important
enough to merit action (Batson, Batson, Slingsby, et al., 1991; Slovic,
2007). Such donors may also rely on their feelings to help them ascertain
the extent to which their actions are needed, and evaluate how they
feel about the prospect of helping those in need (Kogut \& Ritov,
2005a, 2005b; Cameron \& Payne, 2011; Dickert, Sagara \& Slovic, 2011;
Genevsky, Västfjäll, Slovic \& Knutson, 2013; Slovic, Ziontis, Woods,
Goodman \& Jinks, 2013; Västfjäll, Slovic, Mayorga \& Peters, 2014;
Västfjäll, Slovic \& Mayorga, 2015; Agnoli, Pittarello, Hysenbelli \&
Rubaltelli, 2015). Moreover, making a donation entails the sacrifice of
personal resources, whether money or time, that are frequently limited,
and as such, could easily be put to a different use.

The present paper focuses on how people, deciding whether to make a
donation, tend to balance the use of their resources against their
appraisal of a particular cause or group’s need for help. We suggest that
this decision can be influenced by how donors perceive the appeal for
help. In particular, we demonstrate that contextual factors are likely to
affect the tradeoff between the use of donors' resources and the perceived
need to act. We are not suggesting that potential donors rely on an
objective cost-benefit analysis, to render a “technical” assessment of the
relative merits of assisting victims of a given crisis or humanitarian
emergency. Instead, we ask whether identical quantities of money or help
are perceived differently, depending on the context in which the appeal for
a donation is presented.

\subsection{Perceived cost for the donor and benefit to the recipients }
Despite the important role that emotions play in driving donation
decisions, prior research has overlooked other significant factors that may
ultimately prove useful in understanding donation behavior. In particular,
we hypothesize that a decision to donate will also depend on subjective
judgments about the cost and benefit associated with a particular
fundraising campaign. By cost, we refer to people’s perceptions of the
monetary cost involved in contributing to a charitable organization. We
define benefit in terms of people’s perceptions of the value of providing
help to individuals in need. For instance, people are less willing to
donate when they perceive their donation to be a mere “drop-in-the-bucket”,
which occurs when they regard their contribution as unlikely to have a
significant impact on solving the problem (Fetherstonhaugh, Slovic, Johnson
\& Friedrich, 1997; Västfjäll et al., 2015).

Cryder, Loewenstein and Scheines (2013) found that an important predictor
of willingness to help is the donor’s perception of the impact that a given
contribution will have on the provision of assistance to people in
need. Cryder and colleagues’ conclusion is also based on past work
demonstrating the importance of perceived impact as a motivator of donation
decisions (Duncan, 2004). Similarly, past research has identified a
proportionality effect, which refers to the preference for interventions
that make a proportionally large impact over interventions likely to have a
relatively smaller impact, even when the overall impact does not vary
across the two conditions (Baron, 1997; Fetherstonhaugh et al., 1997;
Friedrich, Barnes, Capin, Dawson et al., 1999; Erlandsson, Bjorklund \&
Backstrom, 2014, 2015). We take these results as evidence that people are
more willing to donate when they perceive higher benefits resulting from
the donation.

We also consider donors' perception of the costs associated with the
donation, as well as their perception of benefits. In particular, we expect
people to decide whether it is worth making a donation on the basis of a
subjective assessment of the balance between sacrificing personal resources
and the amount of help provided thanks to their donation. People should
therefore be likelier to donate when the perceived balance is tilted in
favor of high benefit for the recipients, relative to the cost for the
donor. Past research has shown that prosocial behavior and donations
decrease with increased costs (Dovidio, Piliavin, Gaertner, et al., 1991;
Shaw, Batson, \& Todd, 1994; Rubaltelli \& Agnoli, 2012). Similarly,
reducing the perceived costs can result in larger donations (Breman, 2011;
De Bruyn \& Prokopec, 2013; Richman, DeWall, \& Wolff, 2015; Sussman,
Sharma \& Alter, 2015).

Our research question is consistent with the literature just
reviewed. Perceived costs and benefits should show inverse (relative to
each other) effects on willingness to give, so that an increase in the
perceived benefit for the recipient of a donation, relative to an increase
in the perceived cost for the donor, should lead to an increase in
donations. However, an increase in the perceived benefit should not affect
behavior if it is accompanied by an equally large increase in perceived
cost. This hypothesis is consistent with previous research conducted on
people's subjective evaluations of the impact of an aid intervention and
the costs for the donor (Rubaltelli \& Agnoli, 2012; Cryder et al., 2013;
Erlandsson et al., 2014, 2015), but it has, to date, not been properly
tested.

\subsection{Outline of the studies}
Previous studies showed an inconsistency between preferences elicited in
joint evaluation (JE) and separate evaluation (SE; Hsee, 1996, 1998; Hsee,
Zhang \& Chen, 2004; Rubaltelli \& Slovic, 2008; Hsee \& Zhang, 2010). For
instance, Hsee (1996) found that, in SE, people are willing to pay more for
a second-hand dictionary with a lower number of entries that looks like new
rather than for a dictionary with a higher number of entries and a torn
cover. Conversely, in JE, people were willing to pay more for the
dictionary with a higher number of entries. The explanation for this
inconsistency is based on the evaluability hypothesis, which states how some
attributes are hard to evaluate independently (Hsee, 1996). To explore the
role of the balance between the perceived cost for the donor and the
perceived benefit for the recipients in predicting prosocial behavior, we
will describe two studies wherein we compared joint versus separate
evaluations of different donation appeals. Doing this enabled us to assess
how donors’ subjective perceptions of cost and benefit are influenced by
decision context and also to determine whether presenting identical
fundraising appeals in JE or in SE would result in different evaluations of
the same appeal.

In Study 1, we show that donors perceive benefits differently, based on
the presentation mode (JE vs.\ SE). The presence of a second appeal
should modify the balance between perceived cost and benefit, thereby
affecting donation decisions. To assess whether these changes operate
independently of the relative costs of each cause, in Study 2, we
manipulated the donation amount associated with one cause, while
keeping the amount required for the second cause constant. We show that
participants demonstrate a preference for supporting the charity they
perceive as more important, regardless of the relative costs. In Study
2, we also measured, for each cause, affective reactions, perceived
impact, and warm glow, to determine how perceived cost and benefit
relate to variables that have traditionally been assessed in the
literature on charitable donations.

\section{Study 1}
In Study 1, we manipulated the decision context, by seeking contributions
to charitable causes, from potential donors, either in JE or in SE. Based
on the literature on JE/SE differences (Hsee, 1996, 1998; Hsee \& Zhang,
2010), we expected that perceived cost and benefit associated with
contributing to a given cause could change, depending on the presence or
absence of an opportunity for comparison. We conducted a pre-test, to
select two charitable causes, one that people regarded as highly important
and one regarded as relatively less important. A group of Amazon Mechanical
Turk (MTurk) workers (distinct from the actual study participants) rated
several causes, according to their importance and their perceived benefits
for people in need of their advocacy.  Selecting from a vast array of
causes, we focused on the advancement of healthcare and the support of
amateur sports, because they represented the largest disparity in perceived
importance: respectively, \textit{t}(29) = 9.00; \textit{p} {\textless}
.01; \textit{d} = 3.34, for the ratings of importance
(M\textsubscript{HEALTH} = 6.00, SD\textsubscript{HEALTH} = 1.29 vs.\
M\textsubscript{SPORT} = 3.30, SD\textsubscript{SPORT} = 1.95); and
\textit{t}(29) = 4.75; \textit{p} {\textless} .01; \textit{d} = 1.76, for
the ratings of the perceived benefit associated with each of the two causes
(M\textsubscript{HEALTH} = 5.37, SD\textsubscript{HEALTH} = 1.54 vs.\
M\textsubscript{SPORT} = 3.57, SD\textsubscript{SPORT} = 2.00; scales
ranged from 1 to 7).

Based on previous literature showing that positive stimuli acquire value
when paired with stimuli that are slightly more negative or less positive
(Bateman, Dent, Peters, Slovic \& Starmer, 2007), we expect that presenting
an important cause alongside a less important one (JE) should make the
benefit of contributing to that cause stand out and, as a result, increase
people’s willingness to support it compared to when it is presented in
isolation (SE). Therefore, we expected that, in JE, the presence of a less
important cause would produce, among potential donors, a heightened
awareness of the benefits associated with the important cause.\footnote{Our
  work is unlike previous tests of the JE/SE inconsistency in charitable
  giving. For instance, Kogut and Ritov (2005b), in studying the
  single-identifiable-victim effect, presented information regarding the
  benefit in terms of the number of children that could be helped (paired
  with their pictures), whereas we used qualitative rather than
  quantitative information (that is, the labels describing an important and
  an unimportant cause). And we examine perceived cost.}

\subsection{Method}

\paragraph{Subjects.} Three hundred and twenty seven Mturk workers (37.9\%
female; mean age 32 years, ranging from 18 to 69 years) participated in
Study 1. Participants were paid \$0.30 for participation. All participants
were from the United States and had minimum completion rates of 95\% on
past surveys. Use of Mturk has been validated by Buhrmester, Kwang and
Gosling (2011), as well as Paolacci, Chandler, and Ipeirotis (2010; see
also, Mason \& Suri, 2012; Goodman, Cryder \& Cheema, 2013; Chandler,
Mueller \& Paolacci, 2014). We used TurkGate (Goldin \& Darlow, 2013), a
system that prevents repeated participation, to filter out individuals who
had taken part in similar studies (and in our own pre-test).

\paragraph{Materials and procedure.} Participants were presented with a scenario
wherein they were provided with the opportunity to make a donation. In
JE, the scenario presented two causes; in the two SE conditions,
participants were presented with only one of the two causes at a time.
In accordance with the pre-test results, one cause was related to
healthcare: participants were asked to contribute to a charity
supporting research seeking a cure for cancer. The other cause was
related to amateur sport: participants were asked to contribute to a
charity supporting an amateur baseball league. Further, we assigned
distinct amounts for the requested donations for each of the two
charities: the cost of donating to cancer research was \$75, whereas
for the amateur baseball league it was \$15. In this way, it was
possible to test the extent to which people were willing to accept a
higher cost, to help the more important of the two causes. In JE, the
important cause (cancer research) was always presented first and the
other cause (amateur baseball league) second.

After reading the scenario, participants were asked to respond to a
series of questions. In JE, each question was repeated for both
causes. An early question measured motivation to help on a scale
ranging from 1 (“\textit{not at all motivated}”) to 7 (“\textit{very
motivated}”). Subsequently, they were asked to decide whether they
wanted to make a donation. After participants made their decision about
whether to donate, they were asked to rate both perceived cost for the
donor and benefit for the recipients, using two 7-point scales. At the
end, they were presented with a manipulation check, where they rated
the importance, value, and perceived benefit associated with each
cause. Participants gave their ratings, using a scale ranging from 1
(“\textit{not at all}”) to 7 (“\textit{very}”).

\subsection{Results}

\subsubsection{Manipulation check}
For both causes, we averaged the three items that measured importance,
value, and perceived benefit of the causes (${\alpha}$ = .86 for cancer
research, and ${\alpha}$ = .92 for the amateur baseball league; see Table 1
for descriptive analyses). A first t-test analysis showed that the
importance of the cancer research cause was rated as significantly higher
in JE than in SE, \textit{t}(217) = 3.28, \textit{p} = .001, \textit{d} =
.45. Similarly, the importance of the amateur baseball league cause was
rated as significantly higher in JE than in SE, \textit{t}(205) = 2.20,
\textit{p} = .03, \textit{d} = .31. Furthermore, cancer research was rated
significantly more important than the amateur baseball league in both JE
(\textit{t}(212) = 10.63, \textit{p} {\textless} .001, \textit{d} = 1.46)
and SE (\textit{t}(210) = 9.90, \textit{p} {\textless} .001, \textit{d} =
1.37). Finally, the interaction between condition and cause, tested using a
formula previously described by Hsee (1996)\footnote{According to Hsee
  (1996) the interaction effect in a design where one condition is between
  subjects (JE) and the other is within-subjects (SE) should be tested with
  this formula: $t = [(M_{JA} - M_{JB}) - (M_{SA} - M_{SB})]/sqrt(S_J^2/N_J +
  S_{SA}^2/N_{SA} + S_{SB}^2/N_{SB})$, where $M_{JA}$, $M_{JB}$, $M_{SA}$,
  and $M_{SB}$ are the respective means for joint ($J$) and separate ($S$)
  presentation of options A and B; $S$ is the variance of the
  within-subject difference in JE and $S_{SA}^2$ and $S_{SA}^2$ are the
  variances for options $A$ and $B$ in separate evaluation; $N_J$,
  $N_{SA}$, and $N_{SB}$ are the respective numbers of subjects in the
  three conditions.}, was not significant, \textit{t}(316) = .60,
\textit{p} = .55, \textit{d} = .07.

%Table 1. 
\begin{table}[t]\centering
\caption{Descriptive statistics (Study 1).}
\begin{tabular}{l*{4}{C{.35in}}}\toprule
  & \mc{2}{c}{JE} & \mc{2}{c}{SE}\\\cmidrule(lr){2-3}\cmidrule(lr){4-5}
  & M & SD & M & SD\\\midrule
\mc{5}{l}{Cancer research}\\
 Cost for the donors & 4.84 & 1.71 & 5.17 & 1.70\\
 Benefit for recipients & 5.60 & 1.57 & 4.55 & 1.83\\
 Importance of the cause & 5.68 & 1.27 & 5.09 & 1.42\\\midrule
\mc{5}{l}{Amateur baseball league}\\
 Cost for the donors & 3.73 & 1.83 & 4.41 & 1.86\\
 Benefit for recipients & 4.20 & 1.67 & 4.35 & 1.62\\
 Importance of the cause & 3.59 & 1.60 & 3.12 & 1.46\\\bottomrule
\end{tabular}
\end{table}

We then assessed the correlations between perceived cost, perceived
benefit, and motivation to help for the two causes in both JE and
SE. Results showed that, in JE, the perceived cost of giving to cancer
research was negatively correlated with the perceived benefit for the
recipients, but the correlation was not significant (\textit{r} = $-$.18,
\textit{p} = .07). In SE, the cost for the donor and the benefit for the
recipients were negatively correlated, but again the relationship was weak
(\textit{r }= $-$.15, \textit{p} = .12). Both dimensions were significantly
correlated with the motivation to help and this relationship was negative
for cost (\textit{r} = $-$.28, \textit{p} {\textless} .01 in JE and
\textit{r }= $-$.25, \textit{p} {\textless} .01 in SE) and positive for
benefit (\textit{r} = .53, \textit{p} {\textless} .001 in JE and \textit{r}
= .55, \textit{p} {\textless} .001 in SE). For the baseball amateur league,
in JE, cost and benefit were not correlated (\textit{r} = $-$.09,
\textit{p} = .35). In SE, the correlation between cost for the donor and
benefit for recipients was a little higher but still not significant
(\textit{r} = $-$.13, \textit{p} = .19). The correlations with motivation
to help were significant: this relationship was negative for cost
(\textit{r }= $-$.41, \textit{p} = .02 in JE and \textit{r} = $-$.41,
\textit{p} {\textless} .001 in SE) and positive for benefit (\textit{r }=
.58, \textit{p} {\textless} .001 in JE and \textit{r} = .40, \textit{p}
{\textless} .001 in SE).

\subsubsection{Effect of decision context on perceived costs and benefits}

We subsequently analyzed how the perceived cost for donor and benefit for
recipient varied across causes (cancer research vs.\ amateur baseball
league) and conditions (JE vs.\ SE). For cancer research, ratings of
perceived cost for the donor were non-significantly higher in SE than in JE
(Table 1; \textit{t}(222) = 1.45, \textit{p} = .15, \textit{d} = .20),
whereas, for the amateur baseball league, perceived cost was significantly
higher in SE (\textit{t}(210) = 2.70, \textit{p} = .01, \textit{d} =
.37). In addition, for cost, a significant cost difference between the two causes
(cancer higher) emerged both in JE (\textit{t}(216) = 4.63, \textit{p}
{\textless} .001, \textit{d} = .63) and in SE (\textit{t}(216) = 3.15,
\textit{p} = .002, \textit{d} = .43). Finally, the interaction between
condition and cause was not significant (\textit{t}(324) = 1.37, \textit{p}
= .17, \textit{d} = .15).

Ratings for the benefit of cancer research were significantly higher in JE
than in SE (\textit{t}(222) = 4.60, \textit{p} {\textless} .001, \textit{d}
= .62), whereas this difference was not significant for the amateur
baseball league (\textit{t}(210) = .65, \textit{p} = .51, \textit{d }=
.09).  Furthermore, cancer benefit was significantly higher than baseball
benefit in JE (\textit{t}(216) = 6.36, \textit{p} {\textless} .001,
\textit{d} = .87), but not in SE (\textit{t}(216) = .84, \textit{p} = .40,
\textit{d }= .11). Finally, the difference between the two causes was
significantly greater in JE than in SE (\textit{t}(324) = 4.21 for the
interaction, \textit{p} {\textless} .001, \textit{d} = .47).

\subsubsection{Motivation to help} 

We repeated the same analyses for participants’ motivation to help. For
cancer research, motivation was higher in JE than in SE (Figure 1;
\textit{t}(222) = 6.98, \textit{p} {\textless} .001, \textit{d} =
.94). This was also true for the amateur baseball league (\textit{t}(210) =
2.14, \textit{p} = .03, \textit{d} = .30). When comparing motivation to
help the two causes, motivation was higher for cancer in both JE
(\textit{t} (216) = 8.20, \textit{p} {\textless} .001, \textit{d} = 1.12)
and SE (\textit{t}(216) = 3.36, \textit{p} {\textless} .001, \textit{d} =
.46).  Finally, the effect of condition was greater for cancer than for
baseball (\textit{t}(324) = 4.63 for the interaction, \textit{p}
{\textless} .001, \textit{d} = .52).

%Figure 1. 
\begin{figure}[t]
\includegraphics[width=\columnwidth]{fig1.eps}
\caption{Motivation to help by condition (JE vs.\ SE) and type
of cause (cancer research vs.\ amateur baseball league). Error bars
indicate standard errors.}
\end{figure}

\subsubsection{Donation decisions}

For cancer research, 71\% of participants (N = 77 out of 109) chose to give
in JE, whereas only 44\% (N = 50 out of 115) did so in SE. A Wilcoxon test
showed that the difference was significant, \textit{Z }= 4.10, \textit{p}
{\textless} .0001. For the amateur baseball league, 39\% of participants (N
= 43 out of 109) chose to make a donation in JE, and 32\% (N = 33 out of
103) chose to give in SE. This difference was not significant, \textit{Z }=
1.13, \textit{p} = .26 (Figure 2).

% can this be tested?

\subsubsection{Mediation analyses}

For each cause, we tested mediation models for the effect of condition (JE
vs.\ SE) using the lavaan package (Rosseel, 2012) for R (R Development Core
Team, 2015).  We first ran a model with motivation to help as the dependent
variable (condition coded: JE = 0; SE = 1). For the cancer research cause,
results showed an indirect effect of perceived benefit for the recipient
(\textit{B} = $-$.53, \textit{SE }= .14, \textit{z }= $-$3.88, \textit{p}
{\textless} .001) but no indirect effect of perceived cost for the donor
(\textit{B} = $-$.06, \textit{SE }= .05, \textit{z }= $-$1.22, \textit{p} =
.22). When both mediators were included in the model the effect of
condition was still significant, indicating a partial mediation effect
(\textit{B} = $-$.99, \textit{SE }= .20, \textit{z }= $-$4.91, \textit{p}
{\textless} .001; the mediation model was significant, \textit{p}
{\textless} .001). For the amateur baseball league, results showed an
indirect effect of perceived cost for the donor (\textit{B} = $-$.17,
\textit{SE }= .08, \textit{z }= $-$2.19, \textit{p} = .03), but no indirect
effect of perceived benefit for the recipient (\textit{B} = .07, \textit{SE
}= .12, \textit{z }= .62, \textit{p} = .53). When both mediators were
included in the model the effect of condition was still significant,
indicating a partial mediation effect (\textit{B} = $-$.41, \textit{SE }=
.20, \textit{z }= $-$2.08, \textit{p} = .046; the mediation model was
significant, \textit{p} = .04).

%Figure 2. 
\begin{figure}[t]
\includegraphics[width=\columnwidth]{fig2.eps}
\caption{Percentage of hypothetical donations by condition (JE
vs.\ SE) and type of cause (cancer research vs.\ amateur baseball
league). Error bars indicate standard errors.}
\end{figure}

We then repeated the mediation analysis with participants’ decisions as the
dependent variable. For cancer research, we found again an indirect effect
of perceived benefit (\textit{B} = $-$.13, \textit{SE }= .03, \textit{z }=
$-$3.91, \textit{p} {\textless} .001) but not of perceived cost (\textit{B}
= $-$.03, \textit{SE }= .02, \textit{z }= $-$1.35, \textit{p} = .18). When
both mediators were included in the model the effect of condition was
almost significant (\textit{B} = $-$.11, \textit{SE }= .06, \textit{z
}= $-$1.94, \textit{p} = .05; the mediation model was significant,
\textit{p} {\textless} .001).  For the amateur baseball league, the
mediation model was not significant (\textit{p} = .27), therefore we do not
discuss it further.

\subsection{Discussion}

Study 1 examined the extent to which the method of presenting a fundraising
campaign influenced people’s perceptions of cost for the donor and benefit
for the recipients. Specifically, we manipulated the way the two causes
were presented and the possibility of comparing them. We selected two
causes that were clearly different in the importance that people attach to
them. We also set the cost associated with the causes in a way that the
more important cause (cancer research) had the higher cost.  Consistent
with our hypothesis, results showed that people perceived a higher benefit
for the recipients when the \$75 donation to cancer research was presented
alongside a \$15 donation associated with a less important cause (amateur
baseball league). As a result, participants demonstrated a higher level of
motivation to help cancer research in JE, relative to SE and similar
results were observed for the hypothetical donations. Interestingly, in SE,
the perceived benefit for recipients was lower than the cost for the donor
when participants were presented with the more important cause (cancer
research).  Consequently, in SE, fewer than half of the participants were
willing to support even the important cause. By contrast, in JE, the
perceived benefit was higher than the perceived cost, so that most
participants were willing to make a donation supporting cancer
research. Further, and consistent with the above results, a mediation
analysis indicated that, for cancer research, perceived benefit for the recipients
partially mediated the effect of decision context
both on motivation to help and hypothetical donations.

It would be reasonable to assume that cancer is sufficiently important
to merit and receive widespread support from people, given how often
they hear about it in the media and how likely they are to personally
know someone who has suffered from it. Consistent with the above
conclusion regarding the importance of cancer research, as a cause that
merits support, it was perceived as significantly more important than
the amateur baseball league; this was true both in JE and SE. Still, in
spite of that, people’s willingness to support a clearly more important
charity, engaged in a fight against such a deadly disease, varied
significantly depending on the decision context, which affected the
perceived benefit of the donation. This result reflects the importance
of further probing how people perceive the balance between perceived
cost and benefit in deciding to support a charitable cause.

Although cancer research was generally perceived to entail a higher cost
to the donor, thereby showing the sum of money to be assessable even in
SE, its benefit was judged to be higher in JE than in SE. When each
cause was presented in SE, the difference in the percentage of people
who decided to donate to each was far smaller. These findings are
consistent with the literature regarding JE/SE inconsistencies (Hsee,
1996, 1998; Hsee \& Zhang, 2010) and suggest that the perceived impact
of a cause is significantly influenced by the context in which the
fundraising appeal is presented. Sometimes, the presence of a less
important cause can effectively boost donations, by amplifying the
disparity between perceived benefit for recipients and cost for the
donor. Again, these data support our claim that people are likelier to
donate when the perceived benefit outweighs the perceived cost. 

\section{Study 2}
To evaluate whether the findings from Study 1 are independent of the
relative cost associated with each of the two causes, in Study 2 we
manipulated only the donation amount associated with the less important
cause in JE, but we kept the donation amount constant for the more
important cause. Consistent with the results of Study 1, we expected
that participants would prefer to support the more important charity,
regardless of the relative cost of the two causes. As in the previous
study, we hypothesized that participants’ perception of benefit
associated with the donation and their willingness to give to the more
important charity would increase in JE (vs.\ SE).

\subsection[Method ]{Method }
\paragraph{Subjects.} Six hundred and eighty-six Mturk participants (56 \%
female, mean age 34.67 years, ranging from 18 to 80 years) participated in
Study 2.  Participants were randomly assigned to one of seven experimental
conditions. Participants were paid \$0.20 for their participation. We used
TurkGate (Goldin \& Darlow, 2013) to filter out people who had previously
participated in similar studies.

\paragraph{Materials and procedure.} In Study 2, each participants read a
scenario presenting them with the chance to make a donation. In the SE
condition, participants were presented with only one of the two causes:
either cancer research or the amateur baseball league. Further, in SE, the
amateur baseball league was presented to three different groups, and in
each case, it was associated with different donation amounts: \$20, \$50,
and \$80, respectively. By contrast, cancer research was presented to only
one group, and associated with a constant donation amount of \$50. In the
three JE conditions, participants were presented with the same two causes
tested in the SE condition, and again, we manipulated the amount required
to support the amateur baseball league.  While cancer research was always
associated with a \$50 donation, depending on the specific JE condition,
the amateur baseball league cause was associated with donation amounts of
either \$20 (i.e., baseball less expensive), \$50 (equal cost for both
causes), or \$80 (baseball more expensive). In this way, it was possible to
ascertain the increased willingness to support the more important cause
(cancer research), independently of the relative cost of the two causes.
Similarly, we aimed to test whether the changing cost of the less important
cause (baseball amateur league) would influence participants’ willingness
to support it.

After reading the scenario, participants were asked to report their
motivation to help, whether they wanted to make a donation, and their
perception of both cost and benefit of the donation. These variables
were measured with the same questions that we used in Study 1. Further,
in Study 2, participants were asked to rate each cause on the following
7-point scales: how positively or negatively they felt about the cause,
from 1 ( “\textit{absolutely negative}”) to 7 (“\textit{absolutely
positive}”); how good they felt about giving to the cause, from 1 (
\textit{“not good at all}”) to 7 (“\textit{very good}”); and how they
perceived the impact of their donation, from 1 ( “\textit{no impact at
all}”) to 7  (“\textit{very large impact}”). Finally, participants were
asked two additional questions about potential alternative uses of
their money: the first question asked whether they would rather use the
same amount of money of the donation cost to support a different
charity; the second question asked whether they would rather use that
amount of money to do something else entirely. Participants answered
both questions on 7-point scales, ranging from 1 (“\textit{not at
all}”) to 7 (“\textit{absolutely}”). 

\subsection[Results]{Results}

\subsubsection{Descriptive analysis}

%Table 2.  
\begin{table}[t]\centering
\caption{Descriptive statistics for donation decision and motivation to
help in Study 2.}
\begin{tabular}{@{}L{.9in}L{.75in}C{.5in}C{.35in}C{.35in}@{}}\toprule
 &  & Donation decision & \mc{2}{C{.7in}}{Motivation to help}\\\cmidrule{4-5}
 &  & \% & M & SD\\\midrule
\multirow{2}{.9in}{JE – Baseball less expensive} & Cancer \$50 & 80.61 & 5.29 & 1.60\\
 & Baseball \$20 & 26.53 & 2.58 & 1.59\\\midrule
\multirow{2}{.9in}{JE – Equal cost for both causes} & Cancer \$50 & 81.63 & 5.39 & 1.76\\
 & Baseball \$50 & 20.40 & 2.48 & 1.60\\\midrule
\multirow{2}{.9in}{JE – Baseball more expensive} & Cancer \$50 & 86.73 & 5.64 & 1.42\\
 & Baseball \$80 & 21.42 & 2.56 & 1.35\\\midrule
SE & Cancer \$50 & 50.00 & 4.02 & 1.78\\
 & Baseball \$20 & 33.33 & 2.91 & 1.81\\
 & Baseball \$50 & 21.78 & 2.41 & 1.63\\
 & Baseball \$80 & 33.33 & 3.02 & 1.79\\\bottomrule
\mc{5}{@{}p{3.1in}@{}}{Note: The percentage of people choosing to give to the two causes in JE
does not add up to 100\% because participants were presented with two
different questions, one for each cause. As a result, they could
support both causes if they decided to do so.}
\end{tabular}
\end{table}

In all three JE conditions, regardless of the relative price of the two
causes, the percentage of people willing to give to cancer research was
higher than the percentage of people who decided to make a donation in
support of the amateur baseball league (Table 2). In addition,
participants were more willing to donate to cancer research in JE than in
SE.

Similarly, motivation to help the more important cause (cancer research)
was higher when it was presented alongside the less important one
(amateur baseball league), which was not particularly influenced by the
decision context. Moreover, the different donation amounts associated
with the amateur baseball league did not seem to influence
participants’ willingness to donate to this cause. A similar pattern of
results was identified regarding hypothetical donations.

Before proceeding further with the analysis, we ascertained whether the
amount of money associated with the donation to the amateur baseball league
affected willingness to donate.  First, an analysis of variance, using only
the baseball league cause showed that neither in JE nor in SE was
motivation influenced by the amount of money required for a donation
(\textit{F} (5, 582) = 2.20, \textit{p} = .05). Tukey multiple comparisons
showed no significant difference (\textit{p} = .09 or higher). For cancer
research, we analyzed only the three JE conditions in which support for
this cause could be affected by the different amounts associated with the
less important cause. Again, results did not show any effect on motivation
(\textit{p }= .29 or higher). Based on these results, in the following
analyses, we collapsed the three JE conditions, as well as the three
baseball-only SE conditions.

\subsubsection{Effect of decision context on cost and affective reactions}

%Table 3
\begin{table}[t]\centering
\caption{Descriptive statistics for affective reactions and cost (Study
2).}
\begin{tabular}{llllll}\toprule
 &  & \mc{2}{l}{Affective reactions} & \mc{2}{l}{Cost}\\
 &  & M & SD & M & SD\\\midrule
JE & Cancer & 5.66 & 1.26 & 3.57 & 1.55\\
 & Baseball & 3.90 & 1.33 & 5.20 & 1.39\\
SE & Cancer & 4.86 & 1.33 & 4.39 & 1.37\\
 & Baseball & 4.15 & 1.37 & 5.17 & 1.37\\\bottomrule
\end{tabular}
\end{table}

Based on a factor analysis that used a Varimax rotation and factor loadings
selected on the basis of eigenvalues {\textgreater}1 (see Appendix), for
each cause, we combined several variables (affect, benefit for recipients,
warm glow, and impact) into a single factor that we labeled “affective
reactions”. Similarly, for each cause, we combined several variables (cost
to the donor, desire to use money to support a different cause, and desire
to use money to do something else entirely) into a single factor that we
labeled “cost”.  Together, the two factors explained 69\% of the variance
for the cancer research cause, and 71\% of the variance for the amateur
baseball league. For both causes, the affective reactions and cost factors
reached good reliability (always ${\alpha}$ {\textgreater} .70).

We went on to analyze the effect of decision context on the cost factor.
For cancer research, the cost factor was higher in SE than in JE (Table 3;
\textit{t}(388) = 4.61, \textit{p }{\textless} .001, \textit{d} = .47),
whereas, for the amateur baseball league, the effect of condition was not
significant (\textit{t}(588) = .25, \textit{p }= .81, \textit{d} =
.02). Furthermore, ratings of cost for baseball were higher than those for
cancer in both JE (\textit{t}(586) = 13.40, \textit{p }{\textless} .001,
\textit{d} = 1.11) and SE (\textit{t}(390) = 4.48, \textit{p }{\textless}
.001, \textit{d} = .45). Finally, the interaction between condition and
cause was significant (Table 3; \textit{t }(682) = 5.20, \textit{p
}{\textless} .001, \textit{d} = .40).

We repeated the same analysis with affective reactions as the dependent
variable. In this case, for cancer research, ratings of affective reactions
were higher in JE than SE, whereas the opposite was true for the amateur
baseball league (Table 3; \textit{t}(388) = 4.21, \textit{p}{\textless}
.001, \textit{d} = .43 for cancer research and \textit{t}(588) = 2.25,
\textit{p }= .03, \textit{d} = .19 for baseball). In addition,
affective reactions were higher for cancer than for baseball in both JE
(\textit{t}(586) = 14.87, \textit{p }{\textless} .001, \textit{d} = 1.23)
and SE (\textit{t}(390) = 4.86, \textit{p }{\textless} .001, \textit{d }=
.49).  Finally, JE/SE difference was greater for cancer than for baseball
(\textit{t}(682) = 5.07 for the interaction, \textit{p }{\textless} .001,
\textit{d} = .39).

%Figure 3. 
\begin{figure}[t]
\includegraphics[width=\columnwidth,clip=true]{fig3.eps}
\caption{Motivation to help by condition (JE vs.\ SE) and type
of cause (cancer research vs.\ amateur baseball league). Error bars
indicate standard errors.}
\end{figure}

\subsubsection{Motivation to help}

For cancer research, we found stronger motivation in JE than in SE (Figure
3; \textit{t}(388) = 7.34, \textit{p }{\textless} .001, \textit{d} = .75),
whereas the effect of condition was not significant for the amateur
baseball league (\textit{t}(586) = 1.69, \textit{p }= .09, \textit{d} =
.14). Furthermore, motivation to help was higher for cancer research than
the amateur baseball league in both JE (\textit{t}(584) = 22.48, \textit{p
}{\textless} .001, \textit{d} = 1.86) and SE (\textit{t}(390) = 4.86,
\textit{p }{\textless} .001, \textit{d} = .49), and this difference was
greater for cancer than for baseball (\textit{t}(681) = 9.15 for the
interaction, \textit{p }{\textless} .001, \textit{d} = .70).

\subsubsection{Donation decisions}

For cancer research, 83\% of participants (N = 244 out of 294) chose to
give in JE, whereas only 50\% (N = 48 out of 96) did so in SE. A Wilcoxon
test showed that the difference was significant (\textit{Z }= 6.47,
\textit{p} {\textless} .0001). For the amateur baseball league, 23\% of
participants (N = 67 out of 294) chose to make a donation in JE and 29\% (N
= 87 out of 296) chose to give in SE. This difference was not significant
(\textit{Z }= 1.83, \textit{p} = .07; Figure 4).

\subsubsection{Mediation analyses} 

For each cause, we tested a first mediation model with motivation to help
as the dependent variable and condition as the main predictor (JE = 0; SE = 1). For the cancer
research cause, results showed both an indirect effect of the factor cost
(\textit{B} = $-$.33, \textit{SE }= .08, \textit{z }= $-$4.28, \textit{p}
{\textless} .001) and an indirect effect of the factor affective reactions
(\textit{B} = $-$.44, \textit{SE }= .12, \textit{z }= $-$3.68, \textit{p}
{\textless} .001). When both mediators were included in the model the effect
of condition was still significant, indicating a partial mediation effect
(\textit{B} = $-$.66, \textit{SE }= .17, \textit{z }= $-$3.93, \textit{p}
{\textless} .001); the mediation model was significant (\textit{p}
{\textless} .001). For the amateur baseball league, the mediation model was
not significant (\textit{p} = .08), therefore we do not discuss it further.

%Figure 4. 
\begin{figure}[t]
\includegraphics[width=\columnwidth,clip=true]{fig4.eps}
\caption{Percentage of hypothetical donations by condition (JE
vs.\ SE) and type of cause (cancer research vs.\ amateur baseball
league). Error bars indicate standard errors.}
\end{figure}

We then repeated the same analysis with participants’ donation decisions as
the dependent variable. For cancer research, we found again an indirect
effect of both the cost factor (\textit{B} = $-$.07, \textit{SE }= .02,
\textit{z }= $-$4.18, \textit{p} {\textless} .001) and affective reactions
(\textit{B} = $-$.09, \textit{SE }= .02, \textit{z }= $-$3.53, \textit{p}
{\textless} .001). When both mediators were included in the model the effect
of condition was still significant (\textit{B} = $-$.18, \textit{SE }= .05,
\textit{z }= $-$3.46, \textit{p} = .001; the mediation model was
significant, \textit{p} {\textless} .001). Once again, for the amateur
baseball league, the mediation model was not significant (\textit{p} =
.07).

\subsection[Discussion ]{Discussion }
Study 2 examined whether results showing that, in JE, the more important
cause is favored over the less important one, are independent of the
relative cost of supporting the two charities. In the JE conditions of
Study 2, we manipulated the donation amount associated with the amateur
baseball league, while keeping constant the amount required to support
cancer research. Accordingly, we also ran three different SE conditions
for the amateur baseball league, varying the donation amount associated
with this cause. Results showed that participants were more motivated
to help and decided to donate more frequently to cancer research than
to the cause that they regarded as less important, and this was
significantly more notable in JE than it was in SE. People motivation
to help and hypothetical donations in support of cancer research were
higher in JE (vs.\ SE), but this was not true for the amateur baseball
league.

Importantly, participants’ increased willingness to support cancer
research (relative to amateur sport) was observed across all JE
conditions, indicating that the increased propensity to support the
more important cause was independent of the relative difference in
donation amounts required to support each of the two causes. Moreover,
mediation analyses showed that, for cancer research, the effect of
decision context on motivation to help and hypothetical donations was
partially mediated by cost and affective reactions.

Our results also showed a significant effect of affective reactions,
indicating that people had a more positive reaction to cancer research
and especially in JE. In terms of the perceived cost of a donation in
support of cancer research, we found that it was perceived as lower in
JE than it was in SE, indicating that the presence of a less important
cause tended to reduce the perceived cost associated with supporting
the more important one.

An important result from Study 2 is that, in JE, people were more willing
to support the more important cause, regardless of the cost of the less
important one. Indeed, when it was less expensive to support baseball than
cancer, participants were still significantly likelier to support the more
important cause than the less important one. Moreover, even when donations
in support of baseball were objectively less expensive, the perceived cost
of supporting amateur baseball was higher than that perceived in relation
to cancer research (see Appendix). This finding shows the
importance of subjective evaluation of cost for the donor and the extent to
which the decision context can influence such evaluations. Finally, in JE,
people always perceived the affective reactions toward cancer research as
higher than the perceived cost, while the opposite was true for the amateur
baseball league.

\section{General discussion}
In the present studies, we hypothesized that donations would increase when
the perceived benefit for recipients outweighed the relative cost donors are
asked to face, but they should decrease when the difference between these
two dimensions is minimal or cost is perceived to be higher than
benefit. In agreement with this hypothesis, the way that an appeal for
donations is presented influences how people perceive the cost and benefit
of giving. Some causes, as important as they may seem, come to seem even
more valuable, with even greater perceived benefits, when presented
alongside causes of relatively less importance. This type of effect was
demonstrated in Study 1 by presenting an important cause and a less
important one in either JE or SE. Further, in Study 2, we replicated these
results while manipulating relative cost of the two causes.

Our studies revealed that, in JE relative to SE, people demonstrate
increased motivation to help and donate to cancer research despite
perceiving it to be a more important cause in both conditions. In other
words, in JE, the presence of the amateur baseball league amplified the
perceived benefit of cancer research, which came to appear even
worthier of help than it did in SE. This result is consistent with
previous work showing that positive stimuli can be perceived even more
favorably when presented alongside negative or less positive ones
(Bateman et al., 2007).

However, the decision context (JE vs.\ SE) had little or no effect on the
less important cause (amateur baseball league).  Although the present work
focused on how the JE versus SE presentation influences people’s decision
to support an important cause, results for the less important one were a
little surprising and, maybe, worth additional research. We could have
expected a decrease in willingness to help and also a reduction in the
ratings of perceived benefit when the amateur baseball league was presented
alongside cancer research, but this did not happen. A possible explanation
is that donors need reasons to give their money and the JE condition is
more likely to make a worthy cause look even worthier rather than hit
negatively a less worthy cause. In other words, the comparison made
available in JE should give donors additional reasons to give to cancer
research and to perceive the benefit for recipients higher than in SE,
whereas the unimportant cause is simply used as a benchmark that helps the
evaluation of the important one. It is worth noting that, for the less
important cause, perceived cost for the donor is always higher than
perceived benefit for the recipients. As a result, people’s perception of
the benefit associated with this cause is unlikely to decrease since the
starting point is already fairly low. Therefore, results may be different
if a slightly more important cause is used instead of the amateur baseball
league. In this case, perceived benefit might be closer to perceived cost
in SE leaving enough room for a lower rating of benefit in JE.

The paper contributes to the literature on prosocial behavior and
charitable giving in multiple ways. One contribution is that it offers a
way to link divergent research paths that have been investigated thus
far. Some studies have already demonstrated the important role of perceived
cost for the donor, but without clearly highlighting the link between this
dimension and people’s perception of benefits for recipients (Breman, 2011;
De Bruyn \& Prokopec, 2013; Rubaltelli \& Agnoli, 2012; Richman et al.,
2015; Sussman et al., 2015). Other studies have investigated the perceived
impact and effectiveness of the donation, but often without accounting for
the perceived cost people face when deciding to donate (Cryder et al.,
2013; Erlandsson et al., 2014, 2015). However, there are situations in
which variations on how a donation appeal is presented can be targeted to
modify the perceived benefit for recipients, whereas, under different
conditions, it may be possible to target and modify the perceived cost for
the donor. As a result, it is important to assess both dimensions at once,
to investigate how the tradeoff between benefit and cost develops, and the
extent to which such changes affect giving.

Yet another of this paper’s contributions is the fact that, in Study 2, we
assessed both cost and benefit, alongside other dimensions that have
traditionally been associated with prosocial behavior, such as warm glow,
affective reactions, and impact. Results showed that perceived benefit for
the recipients did cluster into the same factor as the above-mentioned
dimensions. This is a reasonable result, given that all such variables
pertain to people’s perception of the donation and the cause, rather than
centering on the donor. Even the dimension of warm glow, which relates to
people’s experience of positive feelings when they decide to donate, is
largely focused on the act of giving (Andreoni, 1990). However, we did find
that cost is still an independent factor that is worth being considered
separately from these variables. This conclusion is also reasonable if we
acknowledge that cost is not necessarily or solely focused on the act of
giving and on the value of the cause, but also on how people prefer and
then decide to use their own resources. This is especially true as, in
Study 2, we added questions that asked participants to rate whether they
would have liked to spend their money in other ways than giving it in
support of the cause(s) they considered. As a result, Study 2 supported our
main hypothesis that we should consider several dimensions at once when
analyzing people’s charitable giving decisions.  In particular, these
dimensions should facilitate the development of a way of measuring the
tradeoff between how donors perceive the benefit for the recipients and how
they perceive the cost of funding that cause. As the present work
demonstrates, this tradeoff is critical to understanding people’s
willingness to give, and it also depends on how information about a given
cause is presented; therefore, it cannot be regarded as an obvious
conclusion based on objective information but requires careful
consideration.

In line with the above conclusion, we demonstrated the importance of
contextual factors in comprehending the balance between perceived cost
and benefit people face when they are deciding whether to make a
donation. In fact, in Study 2, we showed that, by presenting two causes
in JE, it was possible to increase donations to the cause regarded as
more important without increasing the perceived cost and irrespective
of the donation amounts associated with the less important cause. This contribution
could also stimulate an additional series of hypotheses with
considerable applied value.

We have showed one of the many ways in which perceived benefit and cost can
be affected so as to promote increased giving, but many other solutions to
the same problem exist. For instance, another potential approach could rely
on presenting donations in a foreign currency, if the fundraising is
intended to help people abroad. In this case, the dimension of perceived
cost is expressed in an unfamiliar format that might render donors less
sensitive to the amount of money spent and therefore inclined to give it
less weigh in making a decision. Alternatively, presenting a single
well-identified person in need, rather than a group, could increase the
perceived benefit, because it triggers more intense affective reactions and
a closer connection with the recipient (Kogut \& Ritov, 2005a, 2005b;
Slovic, 2007; Västfjäll et al., 2015). Study 2 seems to support this
conclusion, as the perceived benefit was correlated with the affective
reactions that participants experienced toward the two causes.

A limitation of the present work relates to the fact that donations were
always and only tested in a hypothetical setting. Although donations
were hypothetical, we found that perceived cost did, in fact, have an
impact on participants’ decisions. Still, field studies (or
experimental studies with real donations) aimed at assessing the role
of perceived cost and benefit are required to further strengthen the
validity of our conclusions and increase the applied value of the
present findings. 

Despite several questions and research directions that remain open to
investigation, we believe that the findings reported here are crucial
to a better understanding of prosocial behavior and what drives
people’s decisions to give. We have shown that the decision to donate
can be strongly influenced by how people perceive the balance between
the cost of sacrificing personal resources and the help such resources
represent to individuals in need. Finally, we believe that clarifying
how the presentation of the donation appeal shapes this tradeoff is a
critical aspect that can be used to increase the effectiveness of
fundraising campaigns.

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\bigskip
\section*{Appendix: Factor analysis}
Before assessing the effect of our manipulation on cost, benefit,
affect, warm glow, perceived impact, and the items asking about
alternative uses of the donation amount, we ran a factor analysis. We
started by looking at the correlations between our main variables.
Correlations were calculated separately for each cause, and showed
positive relationships between affect, perceived benefit for the
recipients, warm glow, and impact (\textit{r }between .48 and .77; Table S1), as
well as between perceived cost to the donor, preference to use money in
support of a different cause, and preference to use the money to do
something else entirely (\textit{r }between .33 and .70).
Based on these two sets of correlations, it appeared reasonable to
expect that a two-factor structure could be found, given that all
variables related to the outcome for the recipients and donors’
feelings toward the cause correlated with each other. At the same time,
the three questions regarding the cost of the donation or donors’
preferred use of their money correlated with each other, too.

We then proceeded with the factor analysis, which we ran separately for
the two causes. In both cases, we used a Varimax rotation and factor
loadings selected on the basis of eigenvalues ({\textgreater}1).
Results from the factor analysis are summarized in Table S2 and show
that, for both causes, the expected two-factor structure was confirmed.
The factor that includes affect, perceived benefit for the recipients,
warm glow, and impact loaded to a first factor (affective reactions),
whereas the perceived cost to the donor, along with the items regarding
the alternative uses of money, loaded to a second factor (perceived
cost).

Together, these two factors explained 71\% of variance for the cancer
research cause, and 69\% of the variance for the amateur baseball
league cause. All factors showed good reliability (see Table S2).

Finally, in Table S3, we report the descriptive statistics for both
affective reactions and cost, divided by cause and condition, without
collapsing the data across the three JE conditions and the three
baseball-only SE conditions. In JE, the affect induced by cancer
research was always higher than the perceived cost of the donation,
irrespective of the different donation amounts associated with amateur
baseball league. The opposite was found for the baseball league cause
(cost was consistently higher than affect) with little difference
across different JE conditions. In SE, the affect and the cost
participants associated with cancer research were approximately the
same, and this result is consistent with the 50\% rate of hypothetical
donations we found in this condition. For the baseball league, in SE,
the perceived cost was still higher than affect, irrespective of the
donation amount associated with this cause.\bigskip

\begin{table}[h]\centering
\caption*{Table S1. Correlation matrix for Study 2. Correlations for the cancer
research cause are reported on the top half of the table; correlations
for the amateur baseball league cause are reported in the bottom half
of the table.}
\begin{tabular}{@{}L{1in}@{}*{7}{d{1.2}}@{}}\toprule
 & \mc{1}{c}{1} & \mc{1}{c}{2} & \mc{1}{c}{3} & \mc{1}{c}{4} & \mc{1}{c}{5} & \mc{1}{c}{6} & \mc{1}{c}{7}\\\midrule
1.\ Affect & . & -.17 & .68 & .72 & .48 & -.42 & -.45\\
2.\ Perceived cost & -.12 & . & -.26 & -.23 & -.23 & .33 & .43\\[-.8ex]
\mc{8}{@{\quad}l}{to the donor}\\
3.\ Perceived & .60 & -.10 & . & .77 & .63 & -.43 & -.46\\[-.8ex]
\mc{8}{@{\quad}l}{benefit for the recipients}\\
4.\ Warm glow & .67 & -.19 & .67 & . & .62 & -.41 & -.48\\
5.\ Impact & .55 & -.14 & .64 & .66 & . & -.33 & -.44\\
6.\ Support a & -.35 & .26 & -.28 & -.34 & -.32 & .& .69\\[-.8ex]
\mc{8}{@{\quad}l}{different cause}\\
7.\ Do something  & -.38 & .34 & -.32 & -.42 & -.34 & .70 & .\\[-.8ex]
\mc{8}{@{\quad}l}{else with the money}\\\bottomrule
\mc{8}{@{}L{\columnwidth}@{}}{All correlations are significant at $p<.001$ except $-.10$ ($p<.05$) and $-.12$ ($p<.01$).}
\end{tabular}
\end{table}

\begin{table}[h]\centering
\caption*{Table S2. Factor analysis for both causes (cancer research and amateur
baseball league) for Study 2.}
\begin{tabular}{@{}L{1in}*{4}{C{.5in}}@{}}\toprule
 & \mc{2}{c}{Cancer research} & \mc{2}{c}{Baseball league}\\\cmidrule(lr){2-3}\cmidrule(lr){4-5}
Items & Affective reactions & Perceived cost & Affective reactions &
Perceived cost\\\midrule
Affect & .83 &  & .80 & \\
Benefit & .86 &  & .86 & \\
Warm glow & .89 &  & .85 & \\
Impact  & .75 &  & .82 & \\
Cost  &  & .78 &  & .67\\
\mc{2}{@{}L{1.55in}}{Use money to support a different cause} & .75 &  & .80\\
\mc{2}{@{}L{1.55in}}{Use money to do something else}  & .78 &  & .83\\\midrule
Proportion of variance & .43 & .28 & .42 & .27\\
Cumulative variance & .43 & .71 & .42 & .69\\
Cronbach’s $\alpha$ & .74 & .88 & .87 & .70\\\bottomrule
\end{tabular}\bigskip
\end{table}

\begin{table}[h]\centering
\caption*{Table S3. Descriptive statistics for the affect and cost factors in
Study 2.}
\begin{tabular}{@{}L{1in}@{}c*{4}{C{.45in}}@{}}\toprule
 &  & Affect cancer & Affect b-ball & Cost cancer & Cost b-ball \\\midrule
\multirow{2}{1in}{JE baseball less expensive} & M & 5.57 & 3.87 & 3.52 & 5.05\\
 & SD & 1.23 & 1.42 & 1.47 & 1.51\\\midrule
JE equal cost & M & 5.58 & 3.90 & 3.92 & 5.39\\
 & SD & 1.38 & 1.19 & 1.58 & 1.22\\\midrule
\multirow{2}{1in}{JE baseball more expensive} & M & 5.80 & 3.90 & 3.25 & 5.13\\
 & SD & 1.15 & 1.37 & 1.52 & 1.40\\\midrule
\multirow{2}{1in}{SE cancer research} & M & 4.86 & {}- & 4.38 & {}-\\
 & SD & 1.32 & {}- & 1.37 & {}-\\\midrule
\multirow{2}{1in}{SE baseball less expensive} & M & {}- & 4.10 & {}- & 5.02\\
 & SD & {}- & 1.41 & {}- & 1.37\\\midrule
SE equal cost & M & {}- & 3.96 & {}- & 5.33\\
 & SD & {}- & 1.30 & {}- & 1.40\\\midrule
\multirow{2}{1in}{SE baseball more expensive} & M & {}- & 4.39 & {}- & 5.15\\
 & SD & {}- & 1.38 & {}- & 1.33\\\bottomrule
\end{tabular}\bigskip
\end{table}

\end{document}
