We followed up on previous results showing increased cheating under the threat of potential losses compared to the promise of equivalent gains, as well as inconsistent findings in this literature. Our studies used diverse paradigms, including random number reporting, binary number reporting, performance-level reporting, and reliance on illicit resources. In seven studies of online workers (n = 3,803), we found that participants tended to cheat, though the effect size of cheating (Cohen’s d) varied from 0.14 to 1.18 in different settings. However, in all studied paradigms, we observed no significant effect of gain and loss framing, with an overall effect size of d = 0.004, and with the variance in different studies accounted for by sampling error. Examining the moderating effect of stake size did not yield significant findings. At the individual level, higher cheating was predicted by loss aversion, but, on average, participants did not exhibit loss aversion for the obtained incentives. Thus, we cannot overrule the possibility that the inconsistencies in the literature might simply be due to sampling noise around an extremely small (or zero) effect.

Everyone is talking about bots. Much of the discussion has focused on downsides. It is too easy to use bots to cheat, but there are also many ways to use bots to improve your writing. Good writers use thesauruses. It is not cheating to use bots as a modern version of a thesaurus. It is also not cheating to use recommendation systems in a responsible way.

We conducted an experiment in a high-immersive virtual reality environment to study the effect of the presence of a virtual observer on cheating behavior. Participants were placed in a virtual room and played 30 rounds of a cheating game without a chance of their cheating being detected. We varied whether or not a virtual observer (an avatar) was present in the room, and, if so, whether the avatar was actively staring at the decision maker or passively seated in a corner watching his smartphone. Results display significantly less cheating with an active than with a passive avatar, but not less cheating than in a control condition without an avatar. This suggests that an active (virtual) observer can intensify reputational concerns, but that the presence of someone passive and uninterested may actually alleviate such concerns.

We use different incentive schemes to study truth-telling in a die-roll task when people are asked to reveal the number rolled privately. We find no significant evidence of cheating when there are no financial incentives associated with the reports, but do find evidence of such when the reports determine financial gains or losses (in different treatments). We find no evidence of loss aversion in the standard case in which subjects receive their earnings in a sealed envelope at the end of the session. When subjects manipulate the possible earnings, we find evidence of less cheating, particularly in the loss setting; in fact, there is no significant difference in behavior between the non-incentivized case and the loss setting with money manipulation. We interpret our findings in terms of the moral cost of cheating and differences in the perceived trust and beliefs in the gain and the loss frames.

Households are frequently subject to income and asset shocks. We performed a lab experiment, inducing losses on a real effort task, after which we measured cognitive performance, loss aversion and cheating behavior. We found that asset losses, but not income losses, act as a cognitive load, by decreasing accuracy and increasing response times. We did not detect any change in dishonesty or loss aversion.

People frequently engage in dishonest behavior, which entails costs to society. A common advice to increase honesty is to enhance observability. However, previous research produced conflicting findings, making it unclear when and why observability increases honesty. Here we show that observability enhances honesty when observers can gossip to relevant others (i.e., to future interaction partners who can influence the gossip target’s outcome), because it increases reputational concern. In 2 incentivized and pre-registered studies, participants privately rolled a die 30 times and were informed that reporting higher numbers would lead to higher outcomes (total N = 1608; 28650 observations). We manipulated observability and gossip. Both studies revealed that gossip to relevant others decreased dishonest reporting, whereas mere observation did not. Importantly, reputational concern partly mediated the impact of gossip on dishonesty. Moreover, gossip influenced recipients’ trust in gossip targets, with messages denoting dishonesty swaying trust more than messages denoting honesty. Our findings demonstrate when and why observability promotes honesty.

Randomized response (RR) is a well-known method for measuring sensitive behavior. Yet this method is not often applied because: (i) of its lower efficiency and the resulting need for larger sample sizes which make applications of RR costly; (ii) despite its privacy-protection mechanism the RR design may not be followed by every respondent; and (iii) the incorrect belief that RR yields estimates only of aggregate-level behavior but that these estimates cannot be linked to individual-level covariates. This paper addresses the efficiency problem by applying item randomized-response (IRR) models for the analysis of multivariate RR data. In these models, a person parameter is estimated based on multiple measures of a sensitive behavior under study which allow for more powerful analyses of individual differences than available from univariate RR data. Response behavior that does not follow the RR design is approached by introducing mixture components in the IRR models with one component consisting of respondents who answer truthfully and another component consisting of respondents who do not provide truthful responses. An analysis of data from two large-scale Dutch surveys conducted among recipients of invalidity insurance benefits shows that the willingness of a respondent to answer truthfully is related to the educational level of the respondents and the perceived clarity of the instructions. A person is more willing to comply when the expected benefits of noncompliance are minor and social control is strong.

In order to identify aberrant response-time patterns on educational and psychological tests, it is important to be able to separate the speed at which the test taker operates from the time the items require. A lognormal model for response times with this feature was used to derive a Bayesian procedure for detecting aberrant response times. Besides, a combination of the response-time model with a regular response model in an hierarchical framework was used in an alternative procedure for the detection of aberrant response times, in which collateral information on the test takers’ speed is derived from their response vectors. The procedures are illustrated using a data set for the Graduate Management Admission Test® (GMAT®). In addition, a power study was conducted using simulated cheating behavior on an adaptive test.

We examine how monetary incentives and information about others’ dishonesty affect lying decisions and whether these two dimensions interact with each other. Our experiment consists of a repeated cheating game where we vary the monetary incentives (Low, High, and Very High) and information about others’ dishonesty (With or Without information). We find that dishonesty decreases when payoffs are Very High. Information has only a weak positive effect on average. Conditioning on beliefs, we find that those who overestimate (underestimate) cheating reduce (increase) dishonesty. Information and payoffs do not interact with each other.

The Deterministic, Gated Item Response Theory Model (DGM, Shu, Unpublished Dissertation. The University of North Carolina at Greensboro, 2010) is proposed to identify cheaters who obtain significant score gain on tests due to item exposure/compromise by conditioning on the item status (exposed or unexposed items). A “gated” function is introduced to decompose the observed examinees’ performance into two distributions (the true ability distribution determined by examinees’ true ability and the cheating distribution determined by examinees’ cheating ability). Test cheaters who have score gain due to item exposure are identified through the comparison of the two distributions. Hierarchical Markov Chain Monte Carlo is used as the model’s estimation framework. Finally, the model is applied in a real data set to illustrate how the model can be used to identify examinees having pre-knowledge on the exposed items.

We explored how the perspective through which individuals view their actions influences their ethicality, comparing a narrow perspective that allows for evaluation of each choice in isolation, to a broad perspective that promotes an aggregate view of one’s choices. To examine unethical behavior we employed a computerized variation of a trivia game that challenges the player’s integrity because, rather than choosing the correct answer, players indicate whether the correct highlighted answer is the answer they had in mind. In Experiment 1 perspective was modified through the choice procedure: broad perspective evoked by an aggregate decision regarding the upcoming test items and narrow perspective evoked by a segregated decision regarding each upcoming test item. In Experiment 2 perspective was evoked through differential priming. Across both experiments, when given a monetary incentive to succeed, the adoption of a narrow perspective increased cheating, as evidenced by overall higher reported success rates.

Current theories of dishonest behavior suggest that both individual profits and the availability of justifications drive cheating. Although some evidence hints that cheating behavior is most prevalent when both self-profit and social justifications are present, the relative impact of each of these factors is insufficiently understood. This study provides a fine-grained analysis of the trade-off between self-profit versus social justifiability. In a non-student online sample, we assessed dishonest behavior in a coin-tossing task, involving six conditions which systematically varied both self-profit and social justifiability (in terms of social welfare), such that a decrease in the former was associated with the exact same increase in the latter. Results showed that self-profit outweighed social justifiability, but that there was also an effect of social justifications.

In many situations people behave ethically, while elsewhere dishonesty reigns. Studies of the determinants of unethical behavior often use random assignment of participants in various conditions to identify contextual or psychological factors influencing dishonesty. However, in many real-world contexts, people deliberately choose or avoid specific environments. In three experiments (total N = 2,124) enabling self-selection of participants in two similar tasks, one of which allowed for cheating, we found that participants who chose the task where they could lie for financial gain reported a higher number of correct predictions than those who were assigned it at random. Introduction of financial costs for entering the cheating-allowing task led to a decrease in interest in the task; however, it also led to more intense cheating. An intervention aimed to discourage participants from choosing the cheating-enabling environment based on social norm information did not have the expected effect; on the contrary, it backfired. In summary, the results suggest that people low in moral character are likely to eventually dominate cheating-enabling environments, where they then cheat extensively. Interventions trying to limit the preference of this environment may not have the expected effect as they could lead to the selection of the worst fraudsters.

Previous research has established that higher levels of trait Honesty-Humility (HH) are associated with less dishonest behavior in cheating paradigms. However, only imprecise effect size estimates of this HH-cheating link are available. Moreover, evidence is inconclusive on whether other basic personality traits from the HEXACO or Big Five models are associated with unethical decision making and whether such effects have incremental validity beyond HH. We address these issues in a highly powered reanalysis of 16 studies assessing dishonest behavior in an incentivized, one-shot cheating paradigm (N = 5,002). For this purpose, we rely on a newly developed logistic regression approach for the analysis of nested data in cheating paradigms. We also test theoretically derived interactions of HH with other basic personality traits (i.e., Emotionality and Conscientiousness) and situational factors (i.e., the baseline probability of observing a favorable outcome) as well as the incremental validity of HH over demographic characteristics. The results show a medium to large effect of HH (odds ratio = 0.53), which was independent of other personality, situational, or demographic variables. Only one other trait (Big Five Agreeableness) was associated with unethical decision making, although it failed to show any incremental validity beyond HH.

In the light of the potential negative consequences of dishonest behaviors for individuals and societies, researchers from different disciplines have aimed to investigate situation and person factors shaping the occurrence and extent of such behaviors. The present study investigates the roles of a situation factor, the baseline probability of observing a favorable outcome, and a person factor, trait Honesty-Humility from the HEXACO Model of Personality, in shaping dishonest behavior. Next to main effects, a person-situation interaction between these factors was tested. Across three studies with 5,297 participants overall, we find that a higher baseline probability of observing a favorable outcome and lower levels in Honesty-Humility are linked to more dishonest behavior, whereas there was no strong evidence for an interaction between these factors. By testing the assumed effects in two different cheating paradigms, this study additionally allows to disentangle previously found effects of (a) the distance between an observed and the favorable outcome and (b) the baseline probability of observing a favorable outcome.

Do people cheat more when they have something to gain, or when they have something to lose? The answer to this question isn’t straightforward, as research is mixed when it comes to understanding how unethical people will be when they might acquire something good versus avoid something bad. To wit, research has found that people cheat more in a loss (vs. gain) frame, yet research on regulatory focus has found that people cheat more in a promotion focus (where the focus is on acquiring gains) than in a prevention focus (where the focus is on avoiding losses). Through a large-scale field study containing 332,239 observations including 27,350 transgressions, we address the contradictory results of gain/loss frames and regulatory focus on committing unethical behavior in a context that contains a high risk of detecting unethical behavior (NFL football games). Our results replicated the separate effects of more cheating in a loss frame, and more cheating in a promotion focus. Furthermore, our data revealed a heretofore undocumented crossover interaction, in accordance with regulatory fit, which could disentangle past results: Specifically, we found promotion focus is associated with more cheating in a loss (vs. gain) frame, whereas prevention focus is associated with more cheating in a gain (vs. loss) frame. In gridiron football, this translates to offensive players fouling more when their team is losing (vs. winning) and defensive players fouling more when their team is winning (vs. losing).

Commercial practices such as drip pricing, reference pricing and best-price guarantee can be used to set higher prices and mislead consumers, but protective measures can restore efficiency. In a placebo-controlled market experiment, we examined a treatment allowing for the use and misuse of commercial practices. Three additional treatments tested the effects of formal sanctions, informal sanctions and a regret nudge. We found that commercial practices led to higher prices, cheating was systematic and regret nudging was ineffective. Furthermore, formal and informal sanctions reduced both the likelihood of using commercial practices and the likelihood of cheating, leading to welfare increases.