No evidence that a range of artificial monitoring cues influence online donations to charity in an MTurk sample

Abstract

Monitoring cues, such as an image of a face or pair of eyes, have been found to increase prosocial behaviour in several studies. However, other studies have found little or no support for this effect. Here, we examined whether monitoring cues affect online donations to charity while manipulating the emotion displayed, the number of watchers and the cue type. We also include as statistical controls a range of likely covariates of prosocial behaviour. Using the crowdsourcing Internet marketplace, Amazon Mechanical Turk (MTurk), 1535 participants completed our survey and were given the opportunity to donate to charity while being shown an image prime. None of the monitoring primes we tested had a significant effect on charitable giving. By contrast, the control variables of culture, age, sex and previous charity giving frequency did predict donations. This work supports the importance of cultural differences and enduring individual differences in prosocial behaviour and shows that a range of artificial monitoring cues do not reliably boost online charity donation on MTurk.

The Effect of Expressive Biosignals on Empathy and Closeness for a Stigmatized Group Member

“…Given that we did not observe significant effects on empathic concern, this aligns with prior work about empathic concern and its related effects [7,8]. Additionally, our analysis yielded a mean of $0.22 in donations, 7% of the amount they could donate (their payment for the task), as compared to 13% in the low empathy condition in Batson's original study [7], or roughly 10% in some studies on charitable giving [59,60]. This is potentially due to limitations in our donation measure.…”

Watching Eyes and Living up to Expectations: Unkind, Not Kind, Eyes Increase First Mover Cooperation in a Sequential Prisoner’s Dilemma

“…The data we present indicates that eyes are unlikely to increase prosocial behavior through involvement in forming expectations of reciprocity, in which case we hypothesized that unkind eyes would generate the idea of an untrustworthy interaction partner. In fact, we observe the opposite pattern, as unkind eyes boost cooperation in the first 2 We note that a recent study found no effect of the valence of surveillance cues on online donations in a MTurk sample [39]. However, it is hard to compare both studies, since we measure different dependent variables, do a laboratory study with substantial monetary incentives, and offer only the region around the eyes as a cue, not the entire face.…”

“…To further validate this hypothesis, we believe that, for example, objectively measuring arousal and fear in participants exposed to eyes of differing emotional valence would be a promising new avenue for research. From a methodological perspective, the finding that valence matters is an important one: previous studies (with exception of the recent online study [39]) had not yet rigorously distinguished between eyes of different valence 3 , yet this might in its own account for variation between studies. We therefore suggest that the valence of the cues should be factored into the design of future studies on the eye effect.…”

Predictive models for charitable giving using machine learning techniques

“…The factors that have been reported to drive charitable giving are awareness of need [ 10 ], solicitation [ 11 , 12 ], mode of communication [ 13 ], donor characteristics [ 14 ] including age [ 4 , 15 , 16 ], sex [ 17 ], ethnicity [ 4 , 17 ], personal income [ 4 , 15 ] and tax itemizing [ 15 ], education [ 4 , 15 ], volunteerism/civic-minded donor [ 4 , 18 ], moral norms/values & guilt [ 11 , 12 ], religiosity [ 4 , 16 , 19 , 20 ], obligation (wealthy) [ 21 ] or lack of family need [ 11 ], and attitudes toward charitable organizations [ 22 ], historical data on donation [ 16 ], size of request [ 23 ], altruism [ 10 , 11 ], reputation of individual/charity [ 24 ], psychological benefits [ 10 ], and efficacy [ 10 ]. Bekkers and Wiepking [ 25 ] performed an extensive literature review on how age, education, religion, and solicitation are correlated with the amount of charitable giving.…”