Disentangling the Sources of Pro-social Behavior in the Workplace: A Field Experiment

where the marginal return of effort is increased by the fact that the worker enjoys the act of
contributing to the production of the public good. Note that the properties of c (∙) and 7(∙) imply
that ê ≥ e*. This case corresponds to Treatment A in our experimental design, as in that context
workers’ effort contributes to a charitable cause but has no impact on the total amount that gets
transferred. We summarize the first main behavioral prediction:

Prediction 1 Any difference in the amount of effort supplied in Treatment A relative to the Base-
line Treatment, ê — e*, is due to the worker’s action-oriented altruism.

Third, the complete case, where worker’s effort takes place in an environment that is associated
with the production of the public good and is directly linked to the amount of the public good
produced, so both kinds of pro-social motivations are potentially induced. Then equilibrium effort
is given by:

(4)                              è s.t. c' (ê) = p + 7' (e) + φ' [g (è; ε)] ^dg(' ’^g)

de

where the marginal return of effort is augmented by its impact on public good provision. Note that
^' (∙) ≥ θ implies that è ≥ e. This case corresponds to Treatment B in our experimental design, as
in that context workers’ effort contributes to a charitable cause and it does not lead to crowding
out of the experimenter’s contribution.

We can now state the second main behavioral prediction of this framework:

Prediction 2 Any difference in the amount of effort supplied in Treatment B relative to Treatment
A, è — ê, is due to the worker’s output-oriented altruism.

This simple framework provides us with some predictions regarding how we should expect that
a worker will respond to each of these settings that involve a monetary compensation and induce
different combinations of altruistic motivations (action and output oriented). In the next section
we present the results of the study.

3 Results

We are going to evaluate both behavioral predictions by assessing the change in productivity be-
tween the two sessions across the different treatments. In particular, we look at the percentage

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