Subjects have to provide demographic information (age, gender, education). Furthermore, we elicit information on subjects’ preferences through the global preference module (Falk et al. 2018), Big-5 personality traits, and other scales. Precisely, we will elicit the subjects’ preferences on risk, altruism, reciprocity, social comparison, loss aversion, and competition.
In a next step, subjects have to work for 10 minutes on a real-effort task similar to DellaVigna and Pope (2018). In this task, subjects have to press the buttons “a” and “b” alternately on their keyboard. For each correct alternation of button presses, they receive one point. Subjects are randomly assigned to a control group or to one of six different incentive schemes: (1) a piece rate (2) social incentive (3) goal (4) gift (5) bonus loss (6) real time feedback. The data for the real time feedback has been obtained from a pilot experiment (n=209) which was conducted to ensure clarity of instructions and to test code quality of the experimental software.
In the second step, we will run a second round of experiments on MTurk with a different set of subjects where we first again elicit the respective workers’ characteristics (the same characteristics as in the first experiment). In a control group, all workers will work under the scheme that generated the highest average performance in the experiment of the first round. In the two treatment groups, workers will be exposed to the scheme that is predicted to yield the highest performance conditional on the specific characteristics of each individual worker. The treatment groups differ in the algorithm used for the prediction. The key expected insights of the experiment are thus (i) whether and (ii) to what extent algorithmic assignment of the specific incentive scheme adopted can improve performance. Details regarding the algorithms used will be preregistered before the start of the second experiment.
General Experimental Design:
Before participating, subjects will be provided with a brief description of the task (complete a survey and a working task) as well as with the technical requirements (a physical keyboard) and guaranteed payment upon successful submission ($1 flat-pay + $1.50 guaranteed minimum bonus). Furthermore, they will be asked for their consent to participate in the study from which they know they can withdraw at any time.
The final sample will exclude subjects that:
(1) do not complete the MTurk task within 90 minutes of starting;
(2) are not approved;
(3) do not score at least one point;
(4) scored 4000 or more points (since this would indicate cheating)
(5) scored 400 or more points in 1 minute (since this would indicate cheating)
Restriction (2)-(4) are the same as in DellaVigna and Pope (2018). Restriction (1) is similar to the restriction in DellaVigna and Pope (2018), however, the maximum completion time is longer due to the survey included in our study. Restriction (5) is equivalent to restriction (4) broken down to individual minutes for which we will collect data as well.