Preferences and strategic behavior in public goods games

Grandjean, Gilles; Lefèbvre, Mathieu; Mantovani, Marco

doi:10.1016/j.jebo.2022.01.007

Cited by 3 publications

(9 citation statements)

References 37 publications

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“…Which groups are most inclined to converge? The analysis of Grandjean et al ( 14 ) suggests that group homogeneity matters (see Fig. 3 A).…”

Section: Resultsmentioning

confidence: 93%

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Separating individual and group-level cooperation in the Public Goods Game

Nielsen,

Pfattheicher

2024

PNAS Nexus

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Cooperation in the Public Goods Game (PGG) is determined by a mixture of individual differences (e.g., personality, social preferences) and group dynamics (e.g., reciprocation, social norms). However, to our knowledge, no thorough attempt has been made to separate individual and group levels of cooperation and quantify the variance in cooperation that can be attributed to the group level. In an analysis of ten open datasets (total N = 4,556, 1003 groups, 7–50 rounds), we chart the trajectory of individual and group-level variance across rounds of repeated PGGs. We find that the portion of group-level variance increases initially and plateaus around the fifth round, typically at a level between 20% and 50%. In addition, we identify four factors that increase the portion of group-level variance: (1) punishment opportunities; (2) detailed feedback including all group members’ decisions; (3) small groups (≤4 players); and (4) groups with homogenous social preferences.

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“…Which groups are most inclined to converge? The analysis of Grandjean et al ( 14 ) suggests that group homogeneity matters (see Fig. 3 A).…”

Section: Resultsmentioning

confidence: 93%

“…B) Diederich et al ( 13 ). C) Grandjean et al ( 14 ). D) Gächter et al ( 15 ) excluding the condition with stranger matching.…”

Section: Resultsmentioning

confidence: 99%

Separating individual and group-level cooperation in the Public Goods Game

Nielsen,

Pfattheicher

2024

PNAS Nexus

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“…Like in [ 22 , 47 , 48 ], we use the results from the first Strategy Method (referred to as 1st SM hereafter) to classify subjects into preference types. We define four types: free-rider, strong conditional cooperator, weak conditional cooperator, and “other” type:…”

Section: Methodsmentioning

confidence: 99%

“…In the event that a subject does not match any of the above-mentioned type classifications, we categorize the subject as “other” type. Our classification follows more or less [ 48 ]. We introduce a new “weak conditional cooperator” status that allows us to differentiate by degree of cooperation in the results.…”

Section: Methodsmentioning

confidence: 99%

“…We introduce a new “weak conditional cooperator” status that allows us to differentiate by degree of cooperation in the results. As pointed by [ 48 ], while the chosen thresholds may appear arbitrary, they allow to identify clearly distinct types. See also [ 49 ]’s meta-analysis of preference types in public good games who adopt a similar procedure.…”

Section: Methodsmentioning

confidence: 99%

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Long-lasting effects of incentives and social preference: A public goods experiment

2022

Self Cite

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This paper addresses the question of the effectiveness and permanence of temporary incentives to contribute to a public good. Using a common experimental framework, we investigate the effects of a recommendation that takes the form of an exhortative message to contribute, a monetary punishment and a non-monetary reward to sustain high levels of contributions. In particular, we shed light on the differential impact these mechanisms have on heterogeneous types of agents. The results show that all three incentives increase contributions compared to a pre-phase where there is no incentive. Monetary sanctions lead to the highest contributions, but a sudden drop in contributions is observed once the incentive to punish is removed. On the contrary, Recommendation leads to the lowest contributions but maintains a long-lasting impact in the Post-policy phase. In particular, it makes free-riders increase their contribution over time in the post-incentive phase. Finally, non-monetary reward backfires against those who are weakly conditional cooperators. Our findings emphasize the importance of designing and maintaining incentives not only for free-riders, but for strong and weak conditional cooperators as well, depending on characteristics of the incentives.

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