ABSTRACT
We examined whether enhancing (vs. not enhancing) the emotionality of a referent public good influences the subsequent valuation of a target public good. We predicted that it would and that the directionality of its impact would depend on a fundamental cognitive process – categorisation. If the target and referent goods belong to the same domain, we expected that the effect on the target would be in the same direction as the emotional enhancement of the referent (assimilation effect). However, if the target and referent goods belong to different domains, we expected that the effect on the target would be either negligible or in the opposite direction to that of the emotional enhancement of the referent (null or contrast effect). In Experiment 1 we examined the impact of emotionally enhancing a referent public good on feelings towards a target public good, whereas in Experiment 2 on the willingness to contribute towards a target public good. The results support the predicted interaction, which was driven by an assimilation effect for same-domain goods and a null effect for different-domain goods. In doing so, the present findings highlight the interplay between cognition and emotion in the valuation of public goods. We discuss theoretical and practical implications.
Acknowledgement
All authors contributed equally to this work.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 Research suggests that the joint valuation of same-domain goods (e.g. two endangered species) is different and that it resembles more separate valuation (see Bonini, Ritov, & Graffeo, Citation2008). We return to this point in the General discussion.
2 We conducted an a-priori power analysis using G*power (Faul, Erdfelder, Lang, & Buchner, Citation2007) for “ANOVA: Fixed effects, special, main effects and interaction” with the following settings: effect size f = 0.30 (medium effect, estimated), alpha level = .05, power = .90, numerator df = 1, number of groups = 4 (two factors, two levels each). The calculation indicated a minimum sample size of 119 participants. No interim analyses or stopping rules were applied.
3 We conducted an a-priori power analysis similar to that of Experiment 1. In light of the results of Experiment 1, we adjusted the effect size to f = .20. The calculation indicated a minimum sample size of 265 participants. No interim analyses or stopping rules were applied.
4 We thank Prof. Dr Spruyt for pointing our attention to this link.