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Introduction --- The study aims to test the level of external validity of experiments investigating dishonesty. Our project uses an experimental design enabling self-selection of participants into environments allowing more or less deception (Bless, & Burger, 2016); for a theoretical framework see Houdek (2017, p. 2): “An experimental approach measuring a causal effect of an observed factor just by randomized assignments of participants into experimental/control groups has a limited external relevance due to the assumption that the influence of sorting is negligible in real life. But people tend not to be randomly assigned to a contest, profession, team, a certain boss, or randomly get in charge of a process (although it can happen). Rather, they strive to work in environments they perceive as suitable for themselves or are assigned into environments they fit into. An experiment which uses randomized assignment of participants can come to a potential conclusion that an observed factor does not influence dishonesty. Such conclusion is of course causally valid; however, it does not imply that this factor does not have an observable influence in a comparable real-world situation where people can self-select into their preferred environments.” **Expectations and hypotheses:** We expect that in the third round, participants will report a higher number of correct guesses in the version of the task that enables cheating if they chose the version by themselves than if they were assigned to it. We expect that participants who chose the version of the task that enables cheating will report a higher number of correct guesses in the third round of the task than participants who chose a random assignment and were assigned to the same version of the task. We will also examine whether participants who can choose the version of the task will overall earn more in the third round of the task than participants who are not able to choose. We will also explore a potential relationship between preference for cheating enabling environments as well as the actual cheating with risk and social preferences. Furthermore, we will explore whether preference for cheating enabling environments and cheating itself can be predicted by personality characteristics, morality measures, impression management tendencies and life values. We will look at the differences in these relationships between Czech and Chinese samples as well. Methods --- **Participants** We ran experiments with Czech and Chinese subjects from November to December 2018. The data from Chinese participants will be also collected in 2019. The planned sample size is 300 for each nationality. The Czech and Chinese subjects are mostly university students. Therefore, neither sample is representative of the respective population. On average, the subjects are younger, more educated, and come from higher-income households than the general population. The fact that most of the Chinese subjects are business students can be a source of additional biases (e.g. Carter & Irons 1991; Marwell & Ames 1981). **Design and procedure** The study was conducted in a laboratory setting. Participants, in groups of up to 17 (in the Czech Republic) and up to 45 (in China), were working individually on workstations separated by dividers. The whole experiment was administered in English (as a non-native language for both groups) using a custom written Python program. Participants first signed an informed consent and read a short overview of all parts of the experiment. Then, they continued to work, self-paced, according to the instructions shown on their computer screen. The first part of the experiment is a modified mind game (Jiang, 2013). In our variant of the game, participants earn money when they correctly predict whether the outcome of a fair die roll will be odd or even. Rules of the game are explained before it begins and participants’ understanding is checked using a short quiz. There are two different versions of the game: in the BEFORE version, participants state their predictions before the die is rolled and then they see the outcome. Therefore, no cheating is possible. In the AFTER version, participants are asked to make their predictions in their mind and remember it. Then a roll is made and they are shown the outcome and they have to state whether they predicted it correctly or not. As the actual prediction is only in participants’ minds, they can cheat and misreport even their incorrect predictions as correct. Participants play three rounds of the game, with ten rolls in each round. They are informed beforehand that one round will be selected at random and they only get money earned in the selected round. In the first two rounds, every participant plays one round of the game in the AFTER and one in the BEFORE version, in a random order. Then, a half of participants is randomly assigned one of the versions for the third round. The remaining participants are offered a choice before the third round – they read short descriptions of both versions of the game and then they choose whether they want to play the last round in the BEFORE or AFTER version or whether they want to have one of the versions assigned to them at random. After the third round, participants are informed which round was selected for payoff and how much they earned. In the second part of the experiment a simplified HL task is used to elicit participants’ risk preferences (Holt & Laury, 2002; Teubner, Adam, & Niemeyer, 2015). That is, participants make several choices between pairs of options: for each pair, one option represents a certain amount of money and the second one is a lottery with increasing expected outcome for each subsequent pair. At the end of the experiment, one of the pairs is chosen at random and participants get money according to their choice – either they get the certain amount or, in case they choose a lottery, the lottery is played and they get money based on its result. The risk parameter of a lottery for which a participant switches from certain option to the lottery serves as a measure of risk preferences. Additionally, participants can earn money in this task and therefore it is not possible to tell whether their earnings are based on cheating in the first task or on luck in the second task. At the beginning of the experiment, participants are informed that it will be impossible to tell how much they earned in different parts of the experiment. In the third part of the experiment, participants are given an option to give a part (from zero to the whole amount) of their earnings from the first part to a charitable organization of their choosing (from a predetermined set of four respected charities from the country where the experiment takes place). The willingness to share earnings with charity serves as a measure of social preferences. In the last part of the experiment, participants answer socio-demographic questions and fill several questionnaires, namely 60-items HEXACO scale (Ashton & Lee, 2009), work deception scale (Gunia & Levine, 2016), prosocialness scale (Caprara, Steca, Zelli, & Capanna, 2005), BIDR-16 (Hart, Ritchie, Hepper, & Gebauer, 2015), moral agency scale (Black, 2016), measure of moral disengagement (Shu, Gino, Bazerman, 2011), and PVQ (Schwartz, 2012). Participants are informed before the questionnaires that there are attention check items in the questionnaires and that they can earn an additional reward if they manage to answer all of them correctly. They also answer questions about how they perceived the two versions of the first task and complete a short debriefing in which they answer open-ended questions about the aims of the different parts of the experiment. Finally, participants are thanked for their participation, informed of the total earned sum of money, paid, and dismissed. **Materials** The program used to run the experiment is in Files. Analysis plan --- Except for cases of technical difficulties during the administration, we do not plan to exclude any participants from the main analyses. For analyses using questionnaire data, we will exclude participants who did not answer all the attention checks correctly. For comparisons of Czech and Chinese participants, we will exclude a few participants who were not of either nationality. To test whether participants cheated at all, we will compare the number of reported correct predictions in the AFTER version of the task with the number expected by chance (i.e., 5) using a t-test. To compare the rate of cheating between Czech and Chinese participants, we will compare their number of reported correct predictions in the AFTER version of the task using a t-test. To compare cheating of participants who chose the AFTER version of the task themselves in the third round with those who were assigned to the AFTER version of the task at random, we will compare their number of reported correct predictions using a t-test. To compare cheating of participants who chose the AFTER version of the task themselves in the third round with those who were assigned to the AFTER version of the task at random after they chose the random selection of the version, we will compare their number of reported correct predictions using a t-test. To compare earnings of participants who could choose the version of the task with those who could not choose the version of the task, we will compare the number of reported correct predictions (in both versions of the task) in the third block using a t-test. We will do the above described tests with pooled data of Czech and Chinese participants as well as with including the nationality as a predictor. In the latter case, we will conduct a regression instead of a t-test and nationality and its interaction with the studied factor will be included as predictors. References --- Ashton, M. C., & Lee, K. (2009). The HEXACO-60: A short measure of the major dimensions of personality. Journal of Personality Assessment, 91(4), 340-345. doi: 10.1080/00223890902935878 Black, J. E. (2016). An Introduction to the Moral Agency Scale. Social Psychology, 47, 295-310. doi: 10.1027/1864-9335/a000284 Bless, H., & Burger, A. M. (2016). A Closer Look at Social Psychologists’ Silver Bullet. Perspectives on Psychological Science, 11(2), 296-308. doi: 10.1177/1745691615621278 Caprara, G. V., Steca, P., Zelli, A., & Capanna, C. (2005). A new scale for measuring adults' prosocialness. European Journal of Psychological Assessment, 21(2), 77-89. doi: 10.1027/1015-5759.21.2.77 Carter, J. R., and M. D. Irons. (1991). “Are Economists Different, and If So, Why?” Journal of Economic Perspectives, 5(2), 171-77. doi: 10.1257/jep.5.2.171 Gunia, B. C., and Levine, E. E. (2016). Deception as competence: the effect of occupation on ethical judgment and behavior. Academy of Management Proceedings, 2016, 10780. doi: 10.5465/AMBPP.2016.10780abstract Hart, C. M., Ritchie, T. D., Hepper, E. G., & Gebauer, J. E. (2015). The balanced inventory of desirable responding short form (BIDR-16). Sage Open, 5(4), doi: 10.1177/2158244015621113 Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. American Economic Review, 92(5), 1644-1655. doi: 10.1257/000282802762024700 Houdek, P. (2017). A Perspective on Research on Dishonesty: Limited External Validity Due to the Lack of Possibility of Self-Selection in Experimental Designs. Frontiers in Psychology, 8(1566), 1-6. doi: 10.3389/fpsyg.2017.01566 Jiang, T. (2013). Cheating in mind games: The subtlety of rules matters. Journal of Economic Behavior & Organization, 93, 328-336. doi: 10.1016/j.jebo.2013.04.003 Marwell, G., and R. E. Ames. (1981). Economists Free Ride, Does Anyone Else? Journal of Public Economics, 15(3), 295-310. doi: 10.1016/0047-2727(81)90013-X Shu, L. L., Gino, F., & Bazerman, M. H. (2011). Dishonest deed, clear conscience: When cheating leads to moral disengagement and motivated forgetting. Personality and Social Psychology Bulletin, 37(3), 330-349. doi: 10.1177/0146167211398138 Schwartz, S. H., Cieciuch, J., Vecchione, M., Davidov, E., Fischer, R., Beierlein, C., ... & Dirilen-Gumus, O. (2012). Refining the theory of basic individual values. Journal of personality and social psychology, 103(4), 663-688. doi: 10.1037/a0029393 Teubner, T., Adam, M., & Niemeyer, C. (2015). Measuring risk preferences in field experiments: Proposition of a simplified task. Economics Bulletin, 35(3), 1510-1517.