(IR)RATIONAL DECISION MAKING FOR CHARITIES: IS IT MORE EFFECTIVE TO PREVENT OR TO CURE AT THE END?
University of Groningen Faculty of Economics and Business
Msc Marketing
1st Supervisor: Marijke Leliveld 2nd supervisor: Sebastian Sadowski
By Nando Velis June 2017
Petrus Campersingel 147a 9713 AH Groningen
Effective altruism suggests that we should focus on having the biggest societal impact. This societal impact can be established but often implies higher overhead costs. However, we also know that people prefer a less effective charity over a more effective one when the overhead is high. This was found in a context of saving people in need. We want to test whether people make decisions more in line with EA when the charities involve preventing people to become needy. We expected that people in a preventing setting would accept a higher overhead than people in a curing setting. Therefore, we manipulated the two so that people had a curing or preventing message before the question for help to test this. It was expected that people in the preventing condition would have a higher preference for the cost-effective charity. However, there was no significant effect between charity type and choice between a high and low cost-effective charity. Furthermore, we tested if people that with a high importance of rationality and moralized rationality would have a higher preference for high cost-effectiveness. However, this was not related to choice between low and high cost-effectiveness and participants rated the low cost-effective charity as more appropriate. Young people had a higher score on the importance of rationality and moralized rationality. Future research should investigate why people with a high moralized rationality do prefer a low cost-effective charity instead of a high cost-effective charity which can do more good and have a higher societal impact.
1. INTRODUCTION ... 3
2. LITERATURE REVIEW ... 6
2.1 Curing vs Preventing ... 6
2.2 Moralized Rationality Scale (MRS) ... 9
3.RESEARCH METHODS ... 10
4.RESULTS ... 13
4.1 Preference for curing vs preventing charity ... 14
4.2 Manipulation of charity type on preference for low vs high cost-effective charity ... 13
4.3 Appropriateness of both charities ... 16
4.4 Moralized Rationality Scale ... 17
4.4.1 Importance of Rationality & choice for charity ... 17
4.4.2 Moralized Rationality & choice for charity... 18
4.4.3 Importance of Rationality & preventing lives from getting infected vs saving lives of those infected 19 4.4.4 Moralized Rationality & preventing lives from getting infected vs saving lives of those infected ... 20
4.5 Age ... 20
4.6 Gender ... 22
5. CONCLUSION & RECOMMENDATIONS ... 23
5.1 Discussion ... 23
5.2 Theoretical implications ... 26
5.3 Managerial implications ... 28
5.4 Limitations & Future Research ... 29
6. REFERENCES... 31
7. APENDIX ... 39
7.1 Part 1 Survey about Moralized Rationality and Importance of Rationality... 39
7.2 Part 2 Survey (24 hours after part 1) ... 41
1. INTRODUCTION
In the news we regularly hear negative news about charities and how they spend money, and for example how much they pay their employees. With the word ‘charity’ people are thinking about volunteer work, or at least low salary costs for employees. More than fifty percent of Americans think that a non-profit organization needs an overhead ratio of twenty percent or less. In addition, they even emphasize that overhead ratio and financial
transparency are more important factors than the successfully fulfillment of the goals of a non-profit organization, when determining their willingness to give for a charity (BBB Wise Giving Alliance, 2001). People are overhead averse (Gneezy et al., 2014) and tend to give less to a charity where the director and other employees earning substantial wages, even when this charity is more cost-effective than another organization where total labor costs are lower (Balsam & Harris, 2014). People are so overhead averse that some people even have a list with wages of charity directors ready at home, to use this as an argument for not giving any money to the charity during a door-to-door campaign. But what is the cause of this behavior? It seems that donors compare the overhead costs of charities when taking the decision to choose between different charities. American organization Charity Watch rates charities with a label based on overhead costs to make it clear how much money will go directly to the goal and what percentage of overhead costs a charity has. However, overhead costs do not say how cost-effective a charity is. One charity can have 50% of overhead costs, while they can be more cost-effective than a charity with 10% overhead costs. How? Low salary cost and low organizational infrastructure can lead to low overhead costs but also to low returns, were highly experienced and qualified people can operate more effective and therefore bring better results with them (Urban Institute Center on Philanthropy, 2004).
charities based on comparison between overhead costs and incomes. This group tries to change the way of thinking of philanthropists and donors to a more rational and scientific approach. Effective altruists combine donating with the heart and the head (Singer, 2013). Effective altruism consists of two parts: First, altruism means ‘’improving the lives of others’’. Second effectiveness means ‘’doing the most good with whatever resources you have’’ In other words, the movement is about trying to be as effective as possible (MacAskill, 2015). According to Ord (2013), there is an astounding difference between charities, some charities do 1.000 times as good than other charities. Therefore, EA suggests that it is important to give money to the most effective charities to have the biggest impact and influence (Ord, 2013). To illustrate the differences in effectiveness between charities, the following example by Singer (2013) will make this clear. There are two options to donate, where the first charity will provide guide dogs to blind people in the US, which costs about $40.000 because of the training required for the dog and its recipient. The second charity will pay for surgeries to reverse the effects of trachoma in Africa, which costs about $20 per patient cured. The latter will help 2.000 persons to cure from blindness, while the first will help one person. In this example the money could have been invested 2.000 times more beneficial. While the second option is the best rationally speaking, the majority of the people will choose the first one (Singer, 2013).
A lot of people feel more need to help someone they can identify with, than with a large number of people we don’t know (Small, Loewenstein, & Slovic, 2007). They feel more urge to cure someone they know from a disease than preventing two others from getting the same disease. This seems not rational, since donating to the larger group at risk could be more cost-effective. Prevention is way more cost effective than curing as we can see in the
diseases like malaria and diarrhea have also been saving more than 2.5 million lives per year with little costs, making it very cost-effective (Fenner, 1988). These are examples of very cost-effective prevention methods, suggesting it is very important for charities to put emphasis on prevention solutions if they want to create the biggest societal impact with as little as possible, i.e., to be very cost-effective.
Can our society increase the chance on donating to a high- rather than low cost-effective charity to create a bigger societal impact?
2. LITERATURE REVIEW 2.1 Curing vs Preventing
There are several ways you can distinguish charities from each other. In this study we focus on the differences in the way of helping, namely: prevention or cure. Leliveld et al., (2015) showed that people donating to a curing charity preferred low cost-effectiveness over high cost-effectiveness, therefore in this study we investigate if this is the same for a
spontaneous emotional reactions (see Schwarz & Clore, 1983; Slovic, Finucane, Peters, & MacGregor, 2002).
The effective altruists try to maximize the effectiveness of charities in the way of $/life saved. Recent estimates make clear that in the case of HIV/AIDS condom distribution is far more effective in minimizing the harm than the provision of anti-retrovirals. Moreover, there is also evidence that anti-retroviral drug availability could lead to riskier sexual behavior and therefore increase HIV transmission. Therefore it could become even less effective in
comparison to prevention programs (Jamison, 2006). The condom distribution is an example of a prevention way of helping, while retroviral is a curing way of helping people who already have HIV/AIDS. Based on efficiency, the entire donation amount should be spent on condom distribution.
However, so far most governments and populations affected by the pandemic have rejected strategies that leave people with HIV/AIDS untreated. Even governments seem to prefer curing methods. Research about health care expenditures shows that EU governments have declined their expenditures on prevention services over the last couple of years.
Therefore, this study will test if there is a indeed a difference in preference between curing and preventing. If people indeed prefer curing while preventing may be better, the EA should bring this under more attention. When people prefer preventing, it is interesting why
governments do not bring more focus on prevention methods at the moment.
Besides the preference for curing or preventing, is it interesting to investigate whether people who prefer curing differ in their choice for a low/high cost-effective charity from people who prefer preventing. Prior research showed that people prefer a low-cost effective charity above a high cost-effective charity, because they do not like the overhead costs in a charity in a curing context (Gneezy, Keenan, & Gneezy, 2014; Leliveld, Bolderdijk, & Blinde-Leerentveld, 2015). However, Vasall et al. (2014), claimed that HIV prevention is very cost-effective and therefore we can assume that when someone in a prevention condition thinks more about cost-effectiveness than someone in a curing condition, since there are no sad little children involved. People who feel sympathy with the victim and prefer curing methods, could be more obliged by the overhead costs. They are motivated to donate because they think their money goes directly to the help of the person in need and not to cover the overhead costs (Gneezy, Keenan & Gneezy, 2014). We expect that people in a preventing condition do feel less sympathy for the victims, because they prevent people from getting infected so they cannot identify with the victims and they will donate with the reason to help the most people, thus based on a high cost-effectiveness.
H1:People in a curing condition will have a lower preference for a high cost-effective charity than people in a preventing condition. (-)
2.2 Moralized Rationality Scale (MRS)
The MRS evaluates the attitudes and beliefs that are based on logical reasoning and evidence (Ståhl, Zaal & Skitka, 2016). People who score high on this MRS scale, claim that a lack of logical reasoning or rationality is seen as a mistake. Moralized Rationality is high for people who score high on the MRS scale, and they feel anger or are upset about people who score low on the MRS, because they feel it as a need to behave rational and therefore ask others to do the same. People who score high on the MRS scale, have a higher willingness to donate for rational oriented charities compared to more irrational oriented based charities (Ståhl, Zaal & Skitka, 2016). In their study they designed a charity with the objective to stop the spread of irrational beliefs that reflected the societal commitment to rationality and morality. This charity got the highest willingness to donate, compared to other charities with irrational-oriented traits that were seen as a prototype of immorality.
Effective Altruism is about doing the most good possible, and therefore the cost-effectiveness of a charity will be an important measure to compare between two charities. Prior research by Leliveld, Bolderdijk and Blinde-Leerentveld (2015), showed that people preferred a low cost-effective charity above a high cost-effective charity in a curing condition. However, in this study we also focus on cost-effectiveness in a preventing condition.
Therefore it is interesting to investigate whether the MRS and IRS will influence this
curing condition, since the people in the preventing condition already prefer high cost-effectiveness.
H3a: People who score high on the moralized rationality scale will give more to a cost-effective charity than people who score low on the moralized rationality scale. (+)
H3b: The moralized rationality scale will have a moderating effect between type of charity and preference for charity.
Figure 1: conceptual model.
3.RESEARCH METHODS
In this research a self-administered survey was composed with Qualtrics. Qualtrics is a free survey website that is available for all internet users and therefore very user-friendly. We used Mturk, an online panel platform to gather participants. The advantage of this online research method is that it was easy to reach a large sample size, and it took little time to conduct. Another advantage was the option to test the moralized rationality and importance of rationality 24 hours before the rest of the survey with the same respondents because of their MTurk ID. All respondents came from the USA, which is ranked second on the World Giving Index (Cafonline, 2016). This could be a limitation, because the results are not a worldwide representation and have a low external validity. The advantage of Mturk is that the sample is
Type of Charity (curing vs preventing)
Preference for charity (high vs low
more diverse compared to other sampling techniques, e.g. asking students at a college. Mturk reaches a higher variance in age and has a higher average age (Paolacci, Chandler and
Ipeirotis, 2010; Buhrmester et al, 2011), which increases the external validity. The survey started with an introduction text to make clear where the survey is about (the whole survey is available in the appendix). It also indicated the survey consisted of two parts. The first part had to be filled in 24 hours before the second part. The first part measured the MRS by means of a Likert scale (1-7). By using the 9 items for moralized rationality and the 6 items for importance of rationality of the MRS scale (cf. Ståhl, Zaal and Skitka (2016), questions were already validated (see appendix for questions). After these questions respondents had to fill in their MTurk ID, so that they could link the first part of the survey with their answers in the second part of the survey 24 hours later. Then, after 24 hours they got the next part of the survey which started with their Mturk ID. This raw dataset had to be adjusted before it was available to use for analysis. This was done by combining the two parts of the survey with the MTurk ID’s of the respondents. Since the first part had 250
respondents and the second part 200, only 200 respondents were usable for this study. Furthermore, for unknown reason one Mturk ID was three times used, so these three set of answers had to be excluded. This resulted in a sample of 197 participants (Mean age: 39.19, SD =10.85; 57,4% female,
42,6% male). Figure 2: Gender
After the descriptive statistics, a Cronbach’s alpha analysis was used to test if the questions that will test the same variable have a Cronbach alpha of above 0.7 together, so that they were testing the same variable and they were internal consistent (George & Mallery, 2003). All items in Table 1 (next page) made a Cronbach Alpha of around .9 which is excellent.
43% 57%
Gender
Variable Cronbach’s Alpha N of Items
Moralized Rationality 0.893 9
Importance of Rationality 0.896 6
Charity A Appropriateness 0.940 4
Charity B Appropriateness 0.961 4
Table 1: Cronbach’s alpha’s
Participants learned they would receive information about two humanitarian charities. Here is where we manipulated curing vs prevention. Half of the people saw a text with ‘In Africa, many people will get infected by HIV. With your help charities can save the lives of those infected!’, whereas the other half saw a text with ‘In Africa, many people are getting infected by HIV. With your help charities can prevent people from getting infected! ‘We then gave participants information about two charities, in which we manipulated the
cost-effectiveness (within-subjects). See table 2 for the exact information.
Table 2: Cost-effectiveness between Charity A and Charity B.
The comparison between charity A and charity B’s cost-effectiveness did not use official numbers, but numbers that were made up to show the differences between the charities. Also no official charity name was used so that both scenarios had the same structure to avoid biases of the respondents and in order to prevent participants from having an opinion in advance on the attractiveness and familiarity of the charity. The respondents had to make a preference between charity A and B, answering the question ’If you were to donate money to one of the two charities, which charity would you prefer to donate to?’ After respondents made a
Donations raised per year
% spent on salary Bonus system for individual employees of charity
Charity A 300.000 23 No
preference between charity A and B, they had to answer questions about how appropriate, moral, acceptable and unselfish (Appropriateness) the charities were in their opinion (7 points Likert scale were: 1=Inappropriate, 7=Appropriate). Furthermore, questions were asked about how important preventing lives from getting infected and saving lives of those infected were for respondents (1=Not at all important, 7=Very important) and after that a question where they had to choose between the two options (1=Preventing lives from getting infected, 7 = Saving lives of those infected). Additionally, an attention check, to test if respondents did pay full attention by reading all the questions correctly, some general demographics and
respondents opinion about the survey were asked at end of the questionnaire.
4.RESULTS
4.1 Manipulation of charity type on preference for low vs high cost-effective charity The first hypothesis tested if people in a curing condition had a lower preference for a high cost-effective charity than people in a preventing condition. A chi-square test of
independence was performed to examine the relation between type of charity (cure vs prevent) and preference for charity (A: low overhead/ low cost-effective or B: high
Figure 3: Type of charity vs choice for charity
Although the chi square was not significant we conducted this test to understand the relation between type of charity and choice for charity A or B. Therefore, charity type did not have a significant effect on the choice between charity A and B, b=-.259, t(197)=0.374, p=0.489 with a Nagelkerke R2 = of 0.004 , F(1,197)= 0.479 p=0.489. Furthermore, to test if there was a significant difference between type of charity on preference for charity A or B a repeated measures Anova test with a Greenhouse-Geisser correction was conducted (F(1, 195)= 306.650, p=0.000). Since the main ANOVA was significant, this means that there is a difference between people’s preference for Charity A and B. However, there was no difference between the conditions curing and preventing (F (1, 195)= 0.044, p=0.835).
4.2 Preference for saving lives vs preventing lives
The second hypothesis tested if people had a higher preference for a charity that saves lives of those infected than a charity that prevents people from getting infected.A chi square test was conducted to compare the effect of charity type on choice between preventing lives from getting infected and saving lives of those infected. There was no difference in choice between preventing lives from getting infected or saving lives of those infected for the curing and preventing conditions, c2(1, N = 166) = 0.141, p =0 .708.
Figure 4: Type of charity vs choice between preventing lives from getting infected or saving lives of those infected.
26,8% of people in the prevention condition preferred saving lives of those infected, while 57,7% of people preferred preventing lives from getting infected and 15,5% of people rated the two equally important. While 23% of people in the curing condition preferred saving lives of those infected and 62% of people in the curing condition preferred preventing lives from getting infected and 15% of people rated the two equally important. In contrary to the prediction, the curing condition had a higher percentage of preference for preventing lives. However, the relation between type of charity and preventing or saving lives was not
significant X2 (2, N = 197) = 0.443, p=0.801). Furthermore, a binary logistic regression was performed with charity type as IV and the choice between preventing people from getting infected and saving lives of those infected as DV, b=-.224, t(197)=0.340, p=0.510 with a Nagelkerke R2 = of 0.004, suggesting the manipulation did not affect people’s indicated preference.
After the choice between saving or preventing, people had to rate the importance of both constructs separately. A 2x2 mixed Anova was conducted to test if there were
differences between subjects (curing and preventing) and within subjects (the importance of saving and preventing). These results showed that people rated saving lives almost equally
62 56 15 15 23 26 0 10 20 30 40 50 60 70 CURE PREVENT
important (M = 6.13, SD=1,09) as preventing lives (M = 6.12, SD=1.12) and therefore this was not significant (F(1, 195)=0.011, p = 0.917). However, when comparing the means of importance of preventing and saving for the curing and preventing conditions, there was a difference between the curing and preventing conditions (F(1,195)= 4.659, p= 0.032). Importance for preventing lives had a mean of 5.89 (SD=1.25) for the curing and 6.36 (SD=0.90) for the preventing condition. Importance for saving lives had a mean of 6.07 (SD=1.16) for the curing and 6.20 (SD=1.02) for the preventing.
4.3 Appropriateness of both charities
4.4 Moralized Rationality Scale
The study by Stahl, Zaal and Skitka (2016) divided the MRS into two subscales, so in this study we did the same. After performing a linear regression with both subscales
(Moralized Rationality and Importance of Rationality), it became clear that neither the
Importance of Rationality (IR) had a significant effect on the preference for charity A(dummy coded to 0) or B(dummy coded to 1), (b= -.017, t(195) =-0.243, p=0.808), nor does Moralized Rationality (MR) (b=-.078, t(195) = -1.088, p =.278). We tested the direct and moderating effects of IR and MR separately to avoid multicollinearity and performed different chi square tests with the two subscales (IR &MR) divided into two groups by median split (low and high). The paragraphs 4.4.1 t/m 4.4.4 and figure 5 t/m 8 below show the results that were found:
4.4.1 Importance of Rationality & choice for charity
83,9% of the low IR group preferred charity A and 80,6% of the high IR group preferred charity A. 16,1% of the low IR group preferred charity B and 19,4% of the of the high IR group preferred charity B. It seems that there are no differences in choice between charities between both groups, since the percentages are almost similar. Therefore, the relation between IR groups and preference for charity was not significant, X2 (1, N = 196) = 0.360, p=0.548.
Furthermore, a binary logistic regression with IR and preference for charity was conducted. MR did not have a significant effect on choice between charity A and B (b=0.987,
t(197)=0.181, p=0.941 with a Nagelkerke R2 = of 0.003). Furthermore, the interaction
between IR and charity type did not have a significant effect on the choice between charity A and B, b=0.965, t(197)=0.066, p=0.583. Therefore, IR did not moderate the effect between charity type and choice for charity.
4.4.2 Moralized Rationality & choice for charity
78,0% of the low MR group preferred charity A and 85,7% of the high MR group preferred charity A. 22,0% of the low MR group preferred charity B and 14,3% of the of the high MR group preferred charity B. It seems that there are no differences in choice between charities between both groups, since the percentages are almost similar. Therefore, the
relation between MR groups and preference for charity was not significant, X2 (1, N = 196) = 1.967, p=0.161).
Figure 6: Moralized Rationality vs choice for charity.
Furthermore, a binary logistic regression with MR and preference for charity was conducted. MR did have a significant effect on choice between charity A and B (b=0.840, t(197)=0.168, p=0.840 with a Nagelkerke R2 = of 0.001). Furthermore, the interaction between MR and charity type did not have a significant effect on the choice between charity A and B,
(b=1.009, t(197)=0.106, p=0.932). Therefore, it did not moderate the effect between charity type and choice for charity.
4.4.3 Importance of Rationality & preventing lives from getting infected vs saving lives of those infected
19,4% of the high IR group preferred saving lives of those infected, 67,0% of the high IR group preferred preventing lives from getting infected and 13,6% rated the two equally important. 30,6% of the low IR group preferred saving lives of those infected, 52,1% of the low IR group preferred preventing lives from getting infected and 17,0% rated the two equally important. As seen in figure 7 there is some difference between IR groups and choice between preventing or saving lives, although this was not significant on a 0.05 significance level X2 (2, N = 197) = 4.775, p=0.092).
Figure 7: Importance of Rationality vs Preference between preventing lives from getting infected or saving lives of those infected
49 69 16 14 29 20 0 20 40 60 80 LOW IMPORTANCE OF RATIONALITY HIGH IMPORTANCE OF RATIONALITY
4.4.4 Moralized Rationality & preventing lives from getting infected vs saving lives of those infected
23,8% of the high MR group preferred saving lives of those infected, 60,0% of the high MR group preferred preventing lives from getting infected and 16,2% rated the two equally important. 26,1% of the low MR group preferred saving lives of those infected, 59,8% of the low MR group preferred preventing lives from getting infected and 14,1% rated the two equally important. However, the relation between MR groups and choice between preventing or saving lives, was not significant X2 (2, N = 197) = 0.239, p=0.887.
Figure 8: Moralized Rationality vs Preference between preventing lives from getting infected or saving lives of those infected.
4.5 Age
When dividing the Age into two subgroups by median-split (Young=below 36 and Old =36 or above), it became clear that there was a significant difference between these two groups in rating the importance of preventing people from getting infected M(Young) = 5.93, SD (1,20) to M(Old)= 6.30, (SD 1.01), p=.018). The old age group rated the importance of preventing people from getting infected higher than the young age group. The previous effect did not occur with the importance of saving infected people, where the difference in mean
55 63 13 17 24 25 0 10 20 30 40 50 60 70 LOW MORALIZED RATIONALITY HIGH MORALIZED RATIONALITY
M(Young) = 6,01, (SD = 1.10) and M(Old)= 6.24, (SD = 1.07), p=.136 was not significant. Testing the effect of Age on Moralized Rationality and Importance of Rationality, showed that IR had no significant effect (X2 (1, N = 197) = 2.974, p=0.095), while MR did have a significant effect (X2 (2, N = 197) = 3.890, p=0.049). Figure 10 shows that the young age group had a higher MR than the old age group.
Figure 9: Age vs Importance of Rationality Figure 10: Age vs Moralized Rationality
Furthermore, age was tested on preference for a less/more effective charity.
65,7% of people who chose for the high effective charity were from the old age group, and 34,3% were from the young age group. The chi square was not significant on a 0.05
significance level, it still has some effect when tested on a .10 significance level (X2 (1, N = 196) = 2.961, p=0.085). It seems that the older age group has a slightly higher preference for the more-effective charity than the young age group.
Figure 11: Age vs cost-effectiveness charity 39 55 55 48 0 10 20 30 40 50 60 YOUNG OLD
Age x Importance of Rationality
High Importance of Rationality Low Importance of Rationality
37 55 57 48 0 20 40 60 YOUNG OLD
Age x Moralized Rationality
High Moralized Rationality Low Moralized Rationality
81 80 12 23 0 20 40 60 80 100 YOUNG OLD Age x cost-effectiveness
4.6 Gender
Male and female were compared on their appropriateness ratings of charity A and B. Table 3 on the next page shows that the ratings of charity B for men (4.06) and women (3.64) differed and they were almost significant (F(1, 195) = 3.084, p = 0.081). This explained that male respondents rated charity B, although it had more overhead costs as more moral
(p=0.054) acceptable (0.088) and unselfish (0.079) than their female counterparts. The ratings of Charity A did not have a significant difference between male and female ( F(1, 195) = 0.358, p = 0.550). Furthermore, there was no significant difference between male and female on IR (p=0.144), MR (0.278), preference for prevent vs save (0.591), and preference for charity A or B (p=0.414).
(on a 1-7 scale) Mean Male Mean Female SD Male SD Female Significantie(Anova) Charity A appropriateness 5.99 6.15 1.035 0.899 0.242 Charity A morality 6.02 6.14 1.086 0.962 0.422 Charity A acceptability 6.17 6.24 1.096 0.928 0.618 Charity A selfishness 6.07 6.04 1.128 1.097 0.865 Charity B appropriateness 4.17 3.85 1.559 1.910 0.215 Charity B morality 4.4 3.94 1.576 1.734 0.054 Charity B acceptability 4.12 3.66 1.745 1.911 0.088 Charity B selfishness 3.54 3.12 1.639 1.662 0.079
5. CONCLUSION & RECOMMENDATIONS 5.1 General Discussion
The goal of this research was to investigate if our society can increase the chance on donating to a high- rather than low cost-effective charity to create a bigger societal impact. This is important because people evaluate charities more on overhead-ratio than the
effectiveness of organizations, because it is easier to evaluate compared to cost-effectiveness (Baron & Szymanska, 2011). EA tries to change the focus on cost-effectiveness, so that donations will have a bigger societal impact and more people can be helped. Prior research showed that people prefer low cost-effective charities over high-effective ones in a curing context. We tested if people in a preventing context had a higher preference for a high effective charity, since preventing is in nature more effective than curing (Kerns, 1996). However, we did not find support for our prediction that people in a preventing condition have a higher preference for a high-effective charity. We only found that people preferred the less effective charity over the more effective charity, regardless of whether they were
comparing two curing charities or two prevention charity. Thus, it could be concluded that the cure/prevent condition had no influence on people’s choice. One reason could be that people, did not feel enough sympathy for the ones infected, because the study did not have any pictures or moving videos to feel more compassioned with the victims.
acceptability, while the ones who chose for charity A were more obliged by the fact that charity B had way more overhead costs and salary than charity A and therefore rated charity B significantly lower. Combining the results of the choice between the more/less effective charity and the rating on appropriateness of both charities, shows that in accordance with the study of Caviola, Faulmüller, Everett, Savulescu & Kahane (2014),people prefer a low overhead ratio and therefore people prefer the less effective charity and rate the less effective charity as more appropriate than the more effective charity.
We also predicted that people prefer a charity that saves lives of those infected over a charity that prevents people from getting infected. In general people did not have a higher preference for saving lives than preventing lives, however we found a significant difference between charity type and importance of preventing lives from getting infected. People in a preventing condition had more importance for preventing lives than people in the curing condition. The importance of saving lives was not different for both conditions. It is interesting to see that people in the preventing condition had a higher importance for preventing lives than the people in the curing condition.
prediction, IR and MR did not have a significant effect on preference for a cost-effective charity or a preference between preventing vs saving lives. There was no direct effect, but there was also no moderating effect of IR and MR between type of charity and preference for a more/less effective charity. It is quite interesting to see that people who claim to have high importance for rationality did not have a significantly higher preference for the high cost-effective charity. Apparently they could not see the link between more money for the charity and the amount of people that could have been helped. One reason could be the fact that most people scored relatively high on the importance of rationality score, and therefore there was no big difference between the low vs high IR group. As mentioned earlier in this chapter, the study by Baron & Szymanska (2011), showed that this irrational decision could also occur because of the evaluability of the overhead and salary compared to the cost-effectiveness. The percentage of salary and bonus yes or no could have been more clear compared to the
effectiveness were people only saw the amount of donations raised and forgot to link this with more/less effectiveness. Stahl et al. (2016), showed that people with a high MR/IR prefer a rational charity over an irrational one, however in their study it was mentioned that the charities goal was to prevent the spread of irrational beliefs. In our study most people chose the less-effective charity which is irrational. The reason for this could be that when choosing between two charities, it could have been unclear for the respondents what the rational choice was. However, our results are not completely abnormal compared to previous studies of Gneezy et al. (2014) and Leliveld et al. (2015), who also found that people prefer a less effective charity, although this was only in a curing context.
conclude that when becoming older, preventing diseases becomes more important. However, these results are contradicting with the results that showed the young age group had a higher MR. Assuming rational thinking should lead to a high importance for preventing, these results are contradicting. However, research by Kohlberg (1984) showed that when becoming older, moral rationality increases. One learns during his life and the older one become the more cognitive learning takes place and morality becomes more important. His research compared moral rationality at different ages, where higher stages of moralized reasoning are positively associated with age. The higher importance for preventing and preference for the more-effective charity for the older age group confirm the theory of Kohlberg, however the higher MR for the younger age group can not be explained.
Gender did not differ on MR and IR scores and preference for charity. On the other hand, male respondents rated charity B, while it had more overhead costs, as more moral, acceptable and unselfish than their female counterparts. This was not significant on a 0.05 significance level, but it seems that male respondents had less problems with the overhead costs in a charity, since it was significant when tested on a 0.10 significance level.
5.2 Theoretical implications
decision. This can be explained by the fact that affective reactions can be made sooner than cognitive encoding and therefore people use their emotions and feelings instead of using rational decisions which takes longer time (Zajonc, 1980). Furthermore, Kahneman and Tversky (1984) showed that the value of losing something is greater than the value of gaining the same, this is called the endowment effect. In our study this endowment effect can explain that people see the extra money on salary costs as a higher loss than they value the higher effectiveness of the charity and the increase in donations raised by this charity. We predicted that in a prevention condition people would prefer cost-effectiveness more than in a curing condition, however our study showed the same results as Leliveld et al. (2015), and Gneezy et al. (2014), people choose the low-effective option. Even for the group with a high importance for rationality, there was no higher preference for a cost-effective charity. This finding
suggests that people choose for a less effective option, even when they know that the other option raised more money and could do more good in the end. Small and Loewenstein (2007), showed earlier that people donate more to one identifiable person than a large number of people who are unknown. Therefore, maybe we can conclude that altough we expect people to act rational, this effect takes not place for altruism and charities where we act more affective and irrational. When we take the comments of respondents (see appendix 7.3, p45) into account, we can conclude that people see it as a taboo trade-off to choose between preventing or curing, since they think it is both important. According to Tetlock (2000) a taboo trade-off occurs when people have to choose between something people consider sacred, for example a human life, with a monetarized value. Most people think it is offensive to trade sacred values for money. In our study people had to decide between more donations raised with a higher salary or less donations raised with less salary costs. This can be
negative word of mouth and boycotts take place to punish communal organizations that adopt commercial strategies (McGraw, Schwartz, & Tetlock, 2011), e.g. salary and fundraising in charities. In our study most people were disgusted by the higher salary, so that they boycotted this and prefered the less-effective charity altough the high effective charity would have a higher societal impact and could help more people. This moral cleansing is caused by moral amplification. Moral amplification is the separation of good and bad in the explanation of behavior (Haidt & Algoe, 2004). When high salary is seen as bad behavior, people will engage in motivated reasoning, were people choose the conclusion they want without further evidence or rational thinking (Kunda, 1990). They feel the higher salary is a bad thing and therefore they will not look at the other (good) aspects of a charity and choose the less-effective charity. It seems that most people make irrational decisions based on their own emotional toughts, caused by taboo trade-offs, moral amplification and moral cleansing when choosing between two charities. Maybe it is rational to behave irrational if lives are at stake.
5.3 Managerial implications
assign more weight to it. If this can be achieved, charities can focus on their effectiveness instead of emphasizing low overhead ratios, which even leads to more low overhead
expectations of donors (Lecy & Searing, 2015). Furthermore, this low overhead expectactions leads to cutting on overhead which leads to less organizational effectiveness and insufficient infrastructure and because of that to lower donations raised on the long term (Wing & Hager, 2004). Besides that the vast majority chose for the low-effective charity, it is interesting to see that people in the preventing condition had more importance for preventing lives than the people in the curing condition. If the overhead problem can be solved, it is worthwhile to frame people in a preventing environment, so that they increase their importance for
preventing lives and donate money for this. When this cost-effectiveness gets more attention, people will value prevention higher and donate more. More donations leads to more money to create an even higher cost-effectiveness, so that it becomes a vicious circle.
5.4 Limitations & Future Research
influence on the difference between curing and preventing.
Secondly, the fact that the two conditions curing and preventing did not significantly produce different results, may be an indication that the manipulation was not strong enough and the respondents did not base their opinion on these two conditions. However, it can also be an indication that people only take a look at the overhead, whether they are in a curing or preventing context. Future studies can test if our study had these outcomes because of a weak manipulation or that the manipulation had no influence on people’s preference for a more/less effective charity. In doing so, we suggest using for example a longer introduction text, or repeating the message of the manipulation, so that the curing or preventing intention keeps longer in mind of the respondents. Bornstein (2016) found that people’s liking rating of a merely exposed stimulus shift by 1 to 2 points on a 9 point Likert scale and Likert scales are the most sensitive to the merely exposure effect. Therefore, mere exposure can lead to a higher influence of the curing or preventing condition, which could lead to a higher importance for saving lives or preventing lives.
In addition, the contradicting results between age related to IR/MR and age related to preference for prevention may be interesting for future research. It was expected that the more IR and MR someone had, the more preference for prevention one had. The younger group had a higher IR and MR, but the older group had a higher preference for prevention. Furthermore, the older age group had a slight preference for the more effective charity. Research by
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7. APENDIX
7.1 Part 1 Survey about Moralized Rationality and Importance of Rationality Introduction
Questions about Importance of Rationality
7.2 Part 2 Survey (24 hours after part 1) Introduction
Preventing condition
Questions about charity B
Questions about importance of saving lives of those infected and importance of preventing lives from getting infected.
Question about choosing between preventing lives from getting infected or saving lives of those infected.
Age/Gender
Question to check if people payed attention
Mturk ID
Debriefing
7.3 Comments of respondents
These are the comments of respondents that motivated their choices, or interesting views that give something to think about.
- Why would a charity give bonuses to employees? With HIV or AIDS people need to be told how to prevent it because it does not have a real cure yet.
- When I heard "preventing illness" I thought of vaccines and not HIV. I think giving free condoms as prevention is great, but we still need to help those who were infected unknowingly. Not all things can be prevented, and I think -some- vaccines are more harmful than helpful, which influenced my answers.
- This survey honestly made me think! Prevention and curing are both important, so it was tough to choose.
- Preventing a disease is "easy", while curing someone is much more difficult and to me, more important.
- Many charities spend a disproportionate amount of their donations on salaries and general bureaucracy. One should not be coming into such a position with the aim of being well off, but to help others. And yes, I have worked for a charity in the past. - It's tough to think about prevention vs. cure. I suppose in the long run, prevention
would save more lives than a cure, wouldn't it? I feel conflicted about this.
- It's hard to decide which way to go with preventing or healing because they're both equally as important. They both have different purposes and needs.
- It always bothers me when I see charities offering bonuses to their employees. It also prevents me and people like me from donating to them.
- If I had to choose, I'd rather prevent people from getting a currently incurable disease, but healing and preventing are both important.
- I mostly picked the charity based on amount spent on salaries. Information of preventing or curing was not given.
- I agree that prevention is more important than working on curing after the fact - but when I give money I think I would give to the organization working on helping those already affected (paradoxical, I know, but there you have it). Good luck with your work
