|M.Sc Student||Yona Lilach|
|Subject||Learning to Cheat: The Effect of Experience on Dishonest|
|Department||Department of Industrial Engineering and Management||Supervisors||DR. Kinneret Tedorescu|
|DR. Ori Plonsky|
|Full Thesis text|
Cheating and dishonest behaviors have become an interesting subject with a growing body of studies. Since this topic is relatively new, there are some conflicting findings such as whether people are sensitive to the probability of being caught. Most experimental investigations of dishonest behaviors used “one-shot decisions” paradigms in which participants make only one relevant decision during the experiment. The current work aims to expand our understanding of dishonest behavior under repeated ethical decisions from experience. For this purpose, we used a repeated decisions paradigm designed in such a way that it places participants in a dilemma, whether to report an honest answer and receive a lower reward (or none) or to report a dishonest answer and receive a larger reward. We examined the effect of two opposing enforcement policies on the cheating rate, and whether the magnitude of the incentive has an effect on the cheating rate (Study 1). In addition, we examined how the addition of enforcement policies affect cheating rates, and the effect of those policies on different types of cheaters (Study 2). The results reveal that under ethical decisions with feedback from experience, people are more sensitive to the probability of enforcement rather than to the magnitude of the fine if caught. That is, when there are high probability enforcement policies with low fines people cheat or learn to cheat less compared to when there are low probability enforcement policies with high fines. We also found that among people who tend to cheat more, the differences between enforcement policies are even greater. The study findings suggest that in order to minimize cheating behaviors it is better to increase the number of fines compared to the magnitude.