Procedure and design. The experiment had two, high and low effort treat-
ments, with two types of tasks, routine and creative. Hence, there were four conditions (see Table 2.2). The experiment was conducted in two phases. That is, for example, in the low effort treatment participants earned their endowments through a routing task, made their contributions in a standard PGG, then they earned through a creative effort task and again made their contributions to the standard PGG without getting feedback in between. To eliminate order effects the sequence of the tasks were switched in different sessions. Similar design was applied in the high effort treatments. The only difference was the amount of effort needed to solve the tasks. The number of observations in different treatments and different sequences of the tasks were balanced. LTR1 and HTR1 means low and high effort treatments with the task sequence: routine task - creative task. LTR2 and HTR2 denote the opposite sequence: creative task - routine task (see Table 2.1).
LTR1 HTR1 LTR2 HTR2
N of obs. 27 36 27 33
Table 2.1: Number of observations in different sessions with varied sequence of tasks
After reading the instructions on how the experiment is organized and how they are supposed to play the game, the subjects had the opportunity to ob- serve how hypothetical contributions can be redistributed using PGG calcula- tor (see instructions in Appendix 2.8.1). There were three person groups. The participants were informed that they would earn twice and contribute to PGG twice, however only one of their decisions would be pay-off relevant. Any positive contribution was doubled and redistributed among the three group members. πi = pi+ 1/2P N i=1(ji) Where, • πi - Earnings of i
• ji - allocation to joint account
• N - number of group members
In this PG experiment marginal per capital return (MPCR) was 0.66. This is higher than usually used range between 0.4 - 0.5. The reason to opt for somewhat higher MPCR is that the research goal of the current project was to observe probable decline in contributions across different treatments. The higher MPCR makes it more likely to detect treatment effects if there are any. As in most PG experiments, here it is socially optimal if everyone contributes everything. However, for individuals the dominant strategy is to contribute zero in all of the treatments (Thaler and Johnson, 1990). After getting to know how the PGG works, the subjects answered control questions. The subjects earned 50 ECU in all treatments, i.e. there was no inequality between group members and across groups. After the control questions they solved real effort tasks.
Real-effort task N of obs.
Treatment "R.L.eff" Counting a letter 54 Treatment "R.H.eff" Counting two letters 69
Treatment "C.L.eff" Creating words 54
Treatment "C.H.eff" Creating more words 69 Table 2.2: Experimental conditions
Real effort tasks. Examples from the previous literature comparing be-
haviour in PGG after effort exertion include: Graduate Management Admis- sion Tests (GMAT) (Cherry et al., 2005, Spraggon and Oxoby, 2009); and answering questions about plot and visual images from a 6 minute episode of TV cartoon (Muehlbacher and Kirchler, 2009).
In this experiment, in the routine effort treatments, the participants had to count one or two letters within given strings of letters.2 For example, count how
many times a letter “a” appears in characters strings with different lengths, the longer the letter strings were, the more points subjects received. After surpassing a certain threshold of points participants would earn 50 ECUs and automatically proceed to the next stage (see Figure in Appendix 2.8.2).
In the psychological creativity research literature, authors often ask sub- jects to think of creative stories or creative solutions to open questions, which are modifications of the Torrence Test (Torrance, 1968). Other examples of creative or innovative tasks include: Writing three line poems; Paint paintings (Amabile, 1979, 1985, Buccafusco and Sprigman, 2010); Designing an Auto- mobile (Cantner et al., 2009); Word creation task (Eckartz et al., 2012) and word extension (modified scrabble) tasks (Crosetto, 2010).
In this experiment I applied a word creation task3 similar to the task, used
by Eckartz et al. (2012). The main reasons behind are that it has many aspects of a creative task and it mimics quite well a creative innovation. Moreover, it is one way to avoid using the most widely applied consensual assessment technique (CAT) (Amabile, 1979). The CAT method, which requires selection of judges for assessment of creative outputs is time consuming and impractical (Amabile, 1996). In addition to the fact that the task, that I use, takes less time than other options, it is easy to program, objectively assesses creativity and makes it possible to count efforts exerted by players (see Figure in Appendix 2.8.2).
The longer words the participants built, the more points were granted (see Table 2.3). After getting more than a threshold level4students earned 50 ECUs
and proceeded to the next stage. The difference between low and high effort routine tasks was that in the high effort treatment subjects had to count two letters in the same letter strings and collect twice more points. In the high effort creative task subjects had to create words from the same letter string, however they had to collect one and half times more points than in the low effort creative task. It has to be emphasized that effortfulness of routine and creative tasks were maximally approximated: In the low effort routine task solving the longest letter string would suffice to proceed. Likewise, creating the longest words (which students could usually come up with) was enough to collect the necessary points. While doing the high effort treatment students had to solve minimum of three letter strings and find about three words to proceed.
Finally, after making the second contribution decision, the subjects were
3I am thankful to Diego d’Andria and Igor Asanov for providing a code, implemented in the programming languages Ruby and R, to generate the letter string and the list of possible words for the creative effort task.
4Students could collect up to 600 points with the given letter string. However, thresholds were 18 points in low effort treatment and 27 points in high effort treatment to keep the task sufficiently effortful, but not too difficult.
Words from the letter set " a c c d e e e g i n s t " ad 1 + 2 = 3 points and 1 + 2 + 3 = 6 points cats 1 + 2 + 3 + 4 = 10 points ... ... teasing 1 + 2 + 3 + 4 + 5 + 6 + 7 = 28 points
Table 2.3: Measuring creativity: Longer words generate more points (Eckartz et al., 2012)
asked manipulation-check questions. Then, they were informed which of their contribution decisions was pay-off relevant, about the amounts of the contri- butions by their group members and their total profit. As a last step, they answered SVO (Murphy et al., 2011) and personality (Gosling et al., 2003) questionnaires. They were remunerated and released.
The experiment was conducted in Z-tree (Fischbacher, 2007). The partici- pants were recruited by Online Recruitment System for Economic Experiments (ORSEE) (Greiner, 2015).