Testing the effectiveness and endorsement of collective punishment

Abstract

Collective punishment has been applied to sanction and mitigate unethical or illegal behavior. While the use of this controversial mode of punishment might be justifiable from a consequentialist perspective, its effectiveness as well as factors affecting individuals’ endorsement of its use are largely unexplored. Focusing on dishonesty and rule breaking as two prominent examples of unethical and often illegal behavior, we herein address these gaps by testing the effectiveness and endorsement of collective punishment across six preregistered experiments and survey studies with samples from three countries (overall N = 11,020). Exploring the role of inter-individual differences, we tested whether the HEXACO dimensions and the Dark Factor of Personality (D) interact with the implementation of collective punishment in predicting dishonesty and relate to the endorsement of collective punishment (in context of the COVID-19 pandemic). Our results provide substantive evidence for the effectiveness of collective punishment. Further, both honesty-humility and D predicted dishonesty irrespective of the presence of collective punishment, while individuals high (vs. low) in emotionality reacted more to the implementation of collective punishment and more strongly endorsed its use. Combined, these results provide important implications for the evaluation and consideration of collective punishment, including the role of individual differences.

Plain language summary

Sometimes, when one person breaks the rules, everyone in the group gets punished. This approach, called collective punishment, is used to stop bad behavior. But can it be considered fair and is it even effective? And what makes some people agree with this method more than others? We looked into these questions by conducting six studies with over 11,000 participants from three different countries overall. We were interested in two main aspects: Does collective punishment actually discourage dishonest behavior (in terms of cheating for financial benefits) and rule-breaking, and which personality traits are related to whether people think collective punishment is a good idea. We considered a wide range of personality traits, including ones that describe how honest or manipulative someone is, and how they might influence reactions to collective punishment. Our findings show that collective punishment can work to reduce dishonest actions. However, we also discovered that how honest or manipulative someone is affects their likelihood to cheat, regardless of whether collective punishment is present or not. People who are more emotional tend to be more responsive to and supportive of collective punishment. These insights could help decide whether collective punishment is a useful or fair strategy (note that it should only be applied, if at all, when the individual transgressors cannot be identified), taking into account how different people might react differently.

Keywords

collective punishment dishonesty HEXACO personality unethical behavior

The use of collective punishment—that is, sanctioning a group of individuals when it is impossible to identify or sanction the individual offenders (Pereira et al., 2015)—is a controversial issue that has sparked discussions across disciplines (e.g., Heckathorn, 1988; Klocker, 2020; Levinson, 2003; White, 1994). Whereas collective punishment can be considered an unfair and illegitimate form of punishment because it violates the principle of individual responsibility (Pereira et al., 2015), it has been widely applied to sanction and mitigate unethical and illegal behavior. For example, in ancient times, the Code of Hammurabi (1795–1750 BC) stated that a victim of robbery was entitled to collect compensation from the community in which the robbery occurred if the guilty party could not be captured (Horne, 2015). Current examples of collective punishment include banning all football supporters of a team due to the wrongdoings of a few of them (UEFA, 2024); the suspension of the Russian Olympic Team from the 2018 PyeongChang Olympic winter Games due to allegations that many Russian athletes were, supported by a state-run doping program, on performance-enhancing substances (Pound et al., 2015); and strict visa or immigration rules for individuals with a specific nationality due to former violent (terrorist) attacks of individuals from that nation (Pyle et al., 2018). A more indirect form of collective punishment may be economic sanctions toward organizations and nations in response to the misconduct of some employees, citizens, or leaders (Levinson, 2003; Taylor, 2020; Weisbrot & Sachs, 2019).

The moral debate concerning collective punishment is fundamentally rooted in the question of what makes punishment justifiable in the first place. In this respect, two dominant perspectives have been presented: retributivism and consequentialism (Bedau & Kelly, 2019; Shariff et al., 2014). According to retributivism, offenders should be punished in proportion to the harm they have caused simply because they deserve it (Walen, 2020). The moral justification for punishment is thus based on norms of fairness and reciprocity (Shariff et al., 2014). From this point of view, collective punishment is inherently unjustifiable because it inflicts harm on innocent individuals who, under no circumstances, deserve to be punished (Walen, 2020).

According to consequentialism, by contrast, the moral justification for punishment is based on the benefits it produces (Sinnott-Armstrong, 2019). The moral justification for punishment thus lies in its effectiveness to reduce future transgressions (Carlsmith et al., 2002), and the severity of punishment is selected in accordance with what is considered most beneficial to society at large (Shariff et al., 2014). From this point of view, collective punishment can be justified and might be used as an alternative to individual punishment if it is impossible to identify, capture, or punish the actual offender(s), and if the societal benefits provided by collective punishment outweigh the overall harm collective punishment inflicts on both the offender(s) and the innocent (Bentham, 1830).

While collective punishment might be justifiable from a consequentialist point of view, one necessary condition is that it does provide societal benefits such as effectively mitigating unethical and illegal behavior. Importantly, though, research testing its effectiveness is scarce, limited by important methodological shortcomings, and has produced inconclusive results. More precisely, Zhao et al. (2021) observed a reduction in academic cheating when implementing (a version of) collective punishment, whereas Chapkovski (2021) did not observe a significant effect of (a version of) collective punishment for contributions to a public good. Notably, both studies implemented a version of collective punishment in terms of that the individual offenders could actually be identified—thus violating the notion that collective punishment should, even from a consequentialist perspective, only be considered when it is impossible to identify or exclusively punish the individual offenders. Further contributing to the inconclusive evidence concerning the effectiveness of collective punishment, Siniver et al. (2022) found an increase (not a decrease) in dishonesty when collective punishment was introduced in a cheating paradigm in which the individual cheaters could not be identified. However, as also noted by the authors, relatively small sample sizes (Ns ≤ 57) in the reported studies might undermine the robustness of these findings as sensitivity analyses suggest that the studies were powered (1 – β = .90, α = .05) for relatively large effects only (ds > .44), which are relatively uncommon in dishonesty research (Bartoš, 2024).

Here, we address this lack of robust evidence on the effectiveness of collective punishment when individual offenders cannot be identified and thus individually punished. In addition, we not only examine the importance of some situational factors that might affect the effectiveness of collective punishment, but also explore the role of individual differences for the effectiveness and endorsement of collective punishment. Indeed, research has suggested that some individuals are more sensitive toward punishment than others. For example, Hilbig et al. (2012) found that especially individuals low (vs. high) in (HEXACO) honesty-humility changed their contributions to a public good depending on the absence vs. presence of potential punishment.

Beyond identifying who is more likely to be affected by punishment (threats), research has also delved into understanding who is more inclined to execute (peer-)punishment and view it as a justifiable mean. For instance, individuals low (vs. high) in (Big Five) agreeableness have been found to be more punitive towards others (Roberts et al., 2013) and more supportive of peer-punishment as a practice (Klama & Egan, 2011). These and other studies (e.g., Chung et al., 2022; Franklin-Luther & Volk, 2021; Robbers, 2006) point to an interplay between personality traits and reactions or attitudes toward punishment (threats), indicating that some individual differences may shape the effects of punitive measures and/or the likelihood of their endorsement. Importantly, the existing body of research that connects personality traits with responses to punishment has primarily investigated institutional or peer-punishment targeted at individuals. In contrast, relations between personality traits and collective punishment remain virtually unexplored.

Seeking to expand existing knowledge, the objective of our investigation is two-fold. Firstly, we rigorously test the effectiveness of collective punishment for reducing (self-serving financial) dishonesty, including whether some conditions affect its effectiveness. Secondly, we explore the role of personality traits in moderating the impact of collective punishment on dishonesty as well as in affecting the endorsement of collective punishment as a means to reduce rule-breaking.

To investigate the effectiveness and endorsement of collective punishment, we focus on the criteria of dishonesty and rule-breaking. Both represent clear forms of unethical (and often illegal) behavior that can easily be studied using both experimental and survey methods. In particular, to critically examine the effectiveness of collective punishment, we introduce a modified version of the Mind Game (Schild et al., 2019) in Studies 1–3. This modified version closely mirrors situations in which collective punishment, from a consequentialist perspective, could be justifiable—namely, situations in which it is impossible to detect, capture, and only punish individuals who engage in unethical behavior. This part of our investigation contributes to existing research testing the effects of situational factors for reducing dishonesty (e.g., Ayal et al., 2015; Hertwig & Mazar, 2022; Pierce & Balasubramarian, 2015) by providing robust evidence with regard to a largely underexplored situational factor, namely, collective punishment.

Going beyond testing the effectiveness of collective punishment, we further explore whether inter-individual differences interact with the implementation of collective punishment in predicting dishonesty. To this end, we consider the basic dimensions of the HEXACO model of personality (Ashton et al., 2014; Ashton & Lee, 2007; Zettler et al., 2020)—honesty-humility, emotionality, extraversion, agreeableness vs. anger, conscientiousness, and openness to experience—as well as the dark factor of personality (Moshagen et al., 2018) (Study 3). By delving into the interplay between these dimensions and collective punishment, this part of our investigation contributes to past research linking the HEXACO dimensions (Houdek et al., 2021; Zettler et al., 2020) and D (Moshagen et al., 2018, 2020) to dishonesty, as well as to research considering potential interaction effects between the HEXACO dimensions and situational factors in predicting dishonest behavior (e.g., Kleinlogel et al., 2018; Schild et al., 2020) and anti- or prosocial behavior more broadly (e.g., Wiltshire et al., 2014; Zettler et al., 2013).

Lastly, capitalizing on the particular situation created by the outbreak of the coronavirus disease (COVID-19), we tested the relations between the aforementioned personality dimensions and the endorsement of the use of collective punishment on rule-breaking (Studies 4a and 4b). This part of our investigation contributes to existing research on how personality characteristics affect the endorsement of punishment (e.g., Franklin-Luther & Volk, 2021; Klama & Egan, 2011), by focusing on a very specific and morally rather controversial mode of punishment.

Importantly, the purpose of this investigation was not to draw any conclusions about the moral defensibility of collective punishment (for discussions around this, see, e.g., Klocker, 2020; Levinson, 2003; White, 1994), but rather to provide important, previously missing information necessary for evaluating the moral defensibility from a consequentialist perspective.

Open science statement

All studies were preregistered prior to data collection.¹ In the Supplemental Material, we provide links to the preregistrations, an overview of all preregistered hypotheses and whether they were supported (Table S1), as well as the experimental instructions and power analyses for Studies 1–3. Data and analysis scripts are accessible via the Open Science Framework (OSF; https://osf.io/8smyb/). Data for Study 4 cannot be shared publicly but we provide the analysis script and the analysis output.

Study 1

We started our investigation by testing whether collective punishment is effective in mitigating unethical behavior in the form of self-serving financial dishonesty at all. In doing so, we also tested whether there is a difference in the effectiveness of collective punishment if applied with a lenient versus a strict threshold for observed dishonesty. We hypothesized that collective punishment would only be effective when implemented with a strict threshold (Table S1).

Method

Procedure

We conducted an online experiment with three between-participants conditions—control, strict threshold, and lenient threshold—using formr (Arslan et al., 2020). The experiment took 5 minutes to complete, and participants were paid a flat participation fee of £0.40. Participants in the control condition played a version of the Mind Game (Schild et al., 2019) without collective punishment. Specifically, participants were first asked to write down a number between 1 and 8 in private. Next, a random number between 1 and 8 was displayed, and participants were asked to report whether there was a match between this number and the number they had written down. If a match was reported, participants received a bonus incentive of £0.40. Participants thus had an opportunity to lie (i.e., report a match even if they did not observe one) to maximize their profit. Given that only 1 out of 8 participants should report a match under the assumption of full honesty, it is possible to infer if, and to what extent, participants were dishonest on the aggregate level. In the strict and lenient threshold conditions, participants played the same version of the Mind Game, but collective punishment was introduced. Specifically, we informed participants that no one would receive their £0.40 bonus incentive if the total number of reported matches exceeded a certain threshold. The threshold was set to 18% and 50% of reported matches in the strict and lenient threshold conditions, respectively. The threshold levels were set to these levels to be considerably lower (strict threshold) or higher (lenient threshold) than typical levels of dishonesty in Prolific samples (d = ∼.20–.36; Jaffé et al., 2019; Schild et al., 2021).

Analytical framework

An important feature of the Mind Game is that the proportion of alleged matches is conflated with legitimate matches, precluding the immediate interpretations of reported matches as an indicator of dishonesty (Moshagen & Hilbig, 2017). However, given that the baseline probability p for legitimate matches is conclusively known, one can precisely estimate the proportion of dishonest individuals given the following assumptions: (1) dishonest respondents always claim to have obtained a match, (2) honest respondents only report having obtained a match if this is truly the case, and (3) respondents never lie to their disadvantage by denying having obtained a match.² Given these assumptions, the probability of observing a match response is a function of the proportion of honest and dishonest respondents and the baseline probability p, such that:

p (m a t c h) = d + (1 - d) \cdot p

(1)

where d denotes the proportion of dishonest individuals (Moshagen & Hilbig, 2017). Solving for d,

d = \frac{p (m a t c h) - p}{(1 - p)}

(2)

One can obtain an unbiased estimate of the proportion of dishonest respondents by replacing p (match) with the observed proportion of reported matches. To estimate d along with its standard error, and, more importantly, to allow for pairwise comparisons of the proportion of dishonest individuals between conditions, we relied on a multinomial processing tree model (Erdfelder et al., 2009). See Lilleholt et al. (2020) or Thielmann and Hilbig (2018) for a similar approach.

Participants

Aiming to collect data from 900 participants, a total of 903 participants (self-identified 61.57% females, 38.21% males, 0.22% other; M_age = 36.08, SD_age = 12.27 years) from the United Kingdom (UK) were recruited via Prolific (https://www.prolific.com/).³ Eight participants started but did not complete the study and were excluded before data analysis.

Results

As shown in Figure 1, the proportion of dishonest individuals, d, was estimated to be .23, .14, and .19 for the control, strict, and lenient threshold conditions, respectively. Dishonesty was thus observed in all three conditions with estimates of d significantly differing from zero (all ps < .001). Collective punishment with a strict threshold reduced the prevalence of dishonesty compared to the control condition (Cohen’s ω = .08, p = .039)⁴. In contrast, collective punishment with a lenient threshold had a descriptive, but no statistically significant effect on the overall level of dishonesty (Cohen’s ω = .03, p = .415). No significant difference was observed between the strict and the lenient threshold conditions (Cohen’s ω = .05, p = .211). Combined, these results indicate that collective punishment is effective in reducing dishonesty when a strict threshold is applied. However, the data do not support evidence for the effectiveness of a lenient threshold in reducing dishonesty.

Figure 1.

Estimated proportion of dishonest individuals with 95% CIs in Study 1.

Study 2a

In Study 2a, we compared the independent and joint effects of collective punishment and collective reward, herein defined as rewarding all members of a group for not engaging in too much unethical behavior together. Comparing the effectiveness of collective punishment to that of collective reward is important, given that collective reward may constitute a viable alternative to collective punishment from a consequentialist perspective. In fact, it follows from the maxim of consequentialism that collective reward should always be preferred to collective punishment if collective reward and collective punishment are equally effective and if the costs of collective reward do not outweigh the harm that would be inflicted (on both the guilty and innocent parties) if collective punishment is applied. To further examine the effectiveness of collective punishment, we tested its deterrence efficiency at different levels of punishment severity.

We expected collective punishment, collective reward, and a combination of both to be effective in mitigating unethical behavior in the form of financial dishonesty. Furthermore, we hypothesized that an increase in punishment severity would make collective punishment more effective (see e.g., Thielmann & Hilbig, 2018) and that a combination of collective punishment and collective reward would be more effective than collective punishment or collective reward (see e.g., Cressman et al., 2013; Góis et al., 2019) alone (Table S1).

Method

Procedure

We conducted an online experiment with five between-participants conditions—control, collective punishment, collective reward, severe collective punishment, and combined collective punishment and collective reward—using the formr survey software (Arslan et al., 2020). The experiment took 5 minutes to complete, and participants were paid a flat participation fee of £0.40. As in Study 1, participants in the control condition played a version of the Mind Game without collective punishment or collective reward. In the remaining conditions, participants played the same version of the Mind Game, in which different interventions of collective punishment, collective reward, and a combination of collective punishment and collective reward were applied at an implementation threshold of 16% reported matches. Specifically, we informed participants in the collective punishment condition that no one would receive a bonus incentive of £0.40 for reporting a match if the total number of reported matches exceeded the 16% implementation threshold. Similarly, we informed participants in the severe collective punishment condition that no one would receive a bonus incentive of £0.40 for reporting a match, and that they would be banned from any future study conducted by us if the total number of reported matches exceeded the 16% threshold. Further, we informed participants in the collective reward condition that everyone would receive a bonus of £0.07 in addition to their participation fee and the potential £0.40 bonus for reporting a match if the total number of reported matches was lower than the 16% threshold. Finally, we informed participants in the combined collective punishment and collective reward condition that everyone would receive a bonus of £0.07 if the total number of reported matches was lower than the 16% threshold, but that neither this nor the £0.40 bonus for reporting a match would be paid to anyone if the total number of reported matches exceeded the 16% threshold. Given that we recruited a considerably larger sample in Study 2a as compared to Study 1, we reduced the threshold from 18% to 16%.

Participants

Aiming to collect data from 4,250 individuals, N = 4,272 participants from the United States were recruited via Prolific. The sample comprised self-identified 52.69% females, 45.88% males, and 1.43% other (M_age = 34.53, SD_age = 12.31 years). A total of 243 participants started but did not complete the study and were excluded before data analysis.

Results

As shown in Figure 2, the proportion of dishonest individuals d was estimated to be .23, .16, .12, .13, and .14 for the control, collective punishment, severe collective punishment, collective reward, and combined collective punishment and collective reward condition, respectively. Dishonesty was thus observed in all conditions with estimates of d significantly differing from zero (all ps < .001). Compared to the control condition, collective punishment (Cohen’s ω = .07, p = .007), collective reward (Cohen’s ω = .09, p < .001), and a combination of collective punishment and collective reward (Cohen’s ω = .08, p < .001) all reduced dishonesty. Collective punishment and collective reward did not significantly differ in their effectiveness to mitigate dishonesty (Cohen’s ω = .03, p = .210). Increasing the severity of punishment did only descriptively, but not statistically, result in an increase in the effectiveness of collective punishment (Cohen’s ω = .04, p = .063). Similarly, combining collective punishment and collective reward did not result in a significantly increased effectiveness compared to either collective punishment (Cohen’s ω = .02, p = .516) or collective reward alone (Cohen’s ω = .01, p = .550). Controlling for age and gender did not change the direction or significance of the reported effects.

Figure 2.

Estimated proportion of dishonest individuals with 95% CIs in Studies 2a and 2b.

Study 2b

In Study 2b, we tested whether the effectiveness of collective punishment, collective reward, and their combination continued when the interventions were reapplied to the same population. This is particularly important because the usefulness and moral justifiability of collective punishment is severely limited if it is only effective on one occasion or if it is less effective than collective reward in a repeated setting.

Method

Procedure

To explore this question, we re-invited all participants from Study 2a to another round of exactly the same experiment two days after the end of Study 2a—except those in the severe collective punishment condition who, as part of their punishment, were banned from all future studies conducted by us. That is, all participants were assigned to the same condition to which they were randomly allocated in Study 2a. In the invitation letter (sent one day before commencing Study 2b), participants were provided with feedback about their group performance in the Mind Game in Study 2a. Specifically, participants in the control condition were informed of the total number of reported matches in their group (condition). In contrast, participants in the collective punishment, collective reward, and combined collective punishment and collective reward conditions were not only informed about the total number of reported matches in their respective groups, but also whether they exceeded the implementation threshold of 16% reported matches, together with the consequences following from this. Finally, all participants were made aware that the subsequent experiment would involve the same participants as in Study 2a, implying that participants would be part of the same group of individuals as in Study 2a.

Participants

In total, 3,240 participants (self-identified 52.22% females, 46.27% males, 1.51% other; M_age = 34.49, SD_age = 12.33 years) participated in Study 2b, representing 94.93% of the originally invited participants (excluding those that were in the severe punishment condition). Sensitivity analyses suggest that we had power = .90 to detect small effects (Cohen’s ω = .05, α = .05) across conditions (ns > 778). A total of 139 participants started but did not complete the study and were excluded before data analysis.

Results

As shown in Figure 2, the proportion of dishonest individuals d was estimated to be .30, .15, .25, and .12 for the control, collective punishment, collective reward, and combined collective punishment and collective reward condition, respectively. Again, dishonesty was observed in all conditions (all ps < .001). Compared to the control condition, collective punishment (Cohen’s ω = .15, p < .001) and a combination of collective punishment and collective reward (ω = .17, p < .001) were shown to be effective in mitigating dishonesty, whereas collective reward was only descriptively, but not statistically effective (Cohen’s ω = .05, p = .066). Moreover, both collective punishment (Cohen’s ω = .10, p < .001) and a combination of collective punishment and collective reward (Cohen’s ω = .13, p < .001) decreased dishonesty more than collective reward alone. There was no evidence that either collective punishment or a combination of collective punishment and collective reward was statistically superior to the other (Cohen’s ω = .03, p = .264). Notably, a significant increase in dishonesty between Studies 2a and 2b was found in the control (Cohen’s ω = .07, p = .006) and the collective reward (Cohen’s ω = .12, p < .001) conditions, whereas there was no significant increase in dishonesty in the collective punishment (Cohen’s ω = .01, p = .579) and the combined collective punishment and collective reward (Cohen’s ω = .03, p = .299) conditions. Overall, these results suggest that only collective punishment and a combination of collective punishment and collective reward continued to be effective in repeated settings.

Study 3

Whereas Studies 1 and 2 primarily focused on whether and under which circumstances collective punishment influences dishonest behavior, in Study 3 we investigated whether some individuals are more or less responsive to the implementation of collective punishment. Understanding inter-individual differences in individuals’ responsiveness to the implementation of collective punishment is important because it cannot be morally justifiable from a consequentialist perspective to use collective punishment as a deterrent if those who are being targeted are largely non-responsive to it. We considered individual differences in terms of the basic dimensions of the HEXACO model of personality: honesty-humility, emotionality, extraversion, agreeableness vs. anger, conscientiousness, and openness to experience (HEXACO; Ashton & Lee, 2007). In addition, we considered D, the common core of all aversive personality characteristics (Bader et al., 2023; Moshagen et al., 2018; Zettler et al., 2021).

In line with previous research, we expected a negative relationship between honesty-humility and dishonesty (Zettler et al., 2020) as well as a positive relationship between D and dishonesty (Moshagen et al., 2018). More importantly, we expected to find an interaction between both honesty-humility and D on the one hand and the implementation of collective punishment on the other (see Table S1). In this regard, we tested two competing hypotheses: Prior research has shown that individuals low in honesty-humility are more responsive to the presence of potential punishment in economic games (e.g., Hilbig et al., 2012). Thus, one might expect that those low in honesty-humility might also be more responsive to the implementation of collective punishment and might therefore be less dishonest when collective punishment is present. In contrast, individuals high in honesty-humility do not only have a preference for honesty but also to be cooperative, fair, and genuine towards others (Ashton & Lee, 2007; Ścigała et al., 2021). As cheating in the adapted mind game is dishonest but also comes with potential unfair consequences for other participants (i.e., honest winners might get punished as part of the collective punishment), one might expect that the implementation of collective punishment might especially influence the behavior of those high in honesty-humility, who might even more strongly refrain from dishonest behavior.

Method

Procedure

We conducted an online experiment with two measurement occasions and two between-participants conditions—control and collective punishment—using formr (Arslan et al., 2020). The first measurement occasion took approximately 10 minutes, and the second took approximately 5 minutes to complete. Participants were paid a flat fee of £1.00 for participating at the first measurement occasion and £0.45 for participating at the second. At the first occasion, all participants filled out the HEXACO-60 (Ashton & Lee, 2009) and the D16 (Moshagen, Zettler, & Hilbig, 2020) questionnaires. All items were answered on a 5-point Likert-type scale (ranging from 1 = strongly disagree to 5 = strongly agree). Descriptive statistics including reliability metrics for the six HEXACO dimensions and D can be found in Table S2. At the second measurement occasion, which took place one week after the first one, participants played the Mind Game with or without collective punishment. Specifically, we informed participants in the collective punishment condition that no one would receive a bonus incentive of £0.40 for reporting a match if they reported more than 15% of matches as a group altogether.

Analytical framework

Again, we relied on the analytical framework put forward by Moshagen and Hilbig (2017) to compare the overall proportion of dishonest individuals, d, across conditions. To investigate the link between dishonesty and the six HEXACO dimensions and D, as well as the interaction between, on the one hand, honesty-humility and D, and, on the other hand, the presence or absence of collective punishment, we used a modified logistical regression analysis, as recommended by Heck and Moshagen (2018).

Participants

Targeting a final sample size of 4,000, 4,001 participants from the UK recruited via Prolific participated on both measurement occasions of Study 3. We excluded 48 participants because they either experienced technical issues or failed to answer at least one of two attention check items (“If you are reading this, please press ‘five’.” and “If you are reading this, please press ‘two’.“) correctly, resulting in a final sample of 3,953 participants (self-identified 61.47% females, 37.97% males, 0.56% other; M_age = 34.96, SD_age = 12.94 years). A total of 213 participants started but did not complete the study and were excluded before data analysis.

Results

The proportion of dishonest individuals, d, was estimated to be .32 and .17 for the control and collective punishment conditions, respectively. Thus, collective punishment again decreased dishonesty (Cohen’s ω = .14, p < .001). Across models, honesty-humility, openness to experience, and age were negatively related to dishonesty, and D was positively related to dishonesty (Table 1). For all dimensions except emotionality (see Figure 3), we found no statistically significant interaction effect regarding the presence of collective punishment. Combined, these results do not provide evidence that individuals across different trait levels differ in their sensitivity to the implementation of collective punishment except for those high in emotionality, who appear to react more strongly to collective punishment. That is, individuals with high levels of emotionality are more likely to refrain from dishonesty in the presence vs. absence from collective punishment, whereas individuals with low levels of emotionality do not differ in their dishonesty depending on the presence or absence of collective punishment.

Table 1.

Modified logistic regression predicting the proportion of dishonest individuals in study 3.

	Model 1		Model 2
Variable	OR	95% CI	OR	95% CI
Intercept	0.42^***	[0.36, 0.49]	0.43^***	[0.36, 0.51]
Age	0.70 ^***	[0.63, 0.79]	0.74 ^***	[0.64, 0.85]
Gender (Male)	1.18	[0.95, 1.47]	1.11	[0.84, 1.45]
Honesty-humility	0.78 ^***	[0.70, 0.88]	0.76 ^***	[0.66, 0.88]
Emotionality	1.07	[0.95, 1.20]	1.16^*	[1.01, 1.34]
Extraversion	1.09	[0.98, 1.21]	1.06	[0.94, 1.20]
Agreeableness vs. Anger	1.16^**	[1.04, 1.30]	1.14	[0.99, 1.31]
Conscientiousness	1.04	[0.94, 1.15]	1.04	[0.92, 1.19]
Openness to experience	0.87 ^**	[0.79, 0.95]	0.85 ^*	[0.76, 0.96]
Dark factor of personality	1.28 ^***	[1.13, 1.45]	1.26 ^**	[1.07, 1.47]
Condition (CP)	0.42 ^***	[0.34, 0.51]	0.37 ^***	[0.27, 0.50]
Condition (CP): Age			0.84	[0.64, 1.10]
Condition (CP): Gender (Male)			1.12	[0.70, 1.80]
Condition (CP): Honesty-humility			1.11	[0.87, 1.41]
Condition (CP): Emotionality			0.77 ^*	[0.60, 0.98]
Condition (CP): Extraversion			1.06	[0.85, 1.33]
Condition (CP): Agreeableness vs. Anger			1.11	[0.87, 1.42]
Condition (CP): Conscientiousness			0.97	[0.79, 1.20]
Condition (CP): Openness to experience			1.04	[0.85, 1.27]
Condition (CP): Dark factor of personality			1.06	[0.82, 1.38]
n	3,931		3,931
Log-likelihood	−2409.68		−2403.33

Note. Continuous predictors are mean-centered and scaled by 1 standard deviation.

CP: Collective punishment; OR: odds ratio; CI: confidence interval.

***p < .001; **p < .01; *p < .05.

All p-values are two-tailed. Significant predictors across both models are bolded.

Figure 3.

Relations between emotionality and the proportion of dishonest individuals in the control condition and the collective punishment condition in Study 3 (N = 3,953).

Studies 4a and 4b

In Studies 4a and 4b, we tested which inter-individual differences relate to individuals’ endorsement of collective punishment, given that previous research has shown that the perceived legitimacy of different punishment modes can affect their overall effectiveness (Faillo et al., 2013; Zheng & Nie, 2013). Further, inter-individual differences, such as justice concerns (Berent et al., 2017) and utilitarian motives (Confino et al., 2024), have already been linked to the endorsement of collective punishment. Specifically, we capitalized on the fact that the Danish government, like many others (Cheng et al., 2020), imposed several restrictions in response to the COVID-19 pandemic to curb the spread of the disease and continuously warned the public that additional restrictions would be applied if too many individuals failed to comply (Bohr, 2020). Notably, this strategy conceptually mirrored a nationwide implementation of collective punishment (under the assumption that the authorities could and/or would not aim to identify, capture, and punish each individual citizen not following the restrictions; e.g., because this would be too effort-intensive or might undermine the idea of a democratic, non-authoritarian state). We asked two samples of adult Danish citizens to indicate whether they would endorse the imposition of additional and more serious restrictions if some (but not all) Danish citizens failed to comply with the restrictions. Then, we linked participants’ responses to demographic information and personality dimensions (i.e., HEXACO dimensions and D) to gain some initial insights as to what relates to individuals’ endorsement of collective punishment.

Method

Procedure and participants

The data used in Studies 4a and 4b was collected as part of a large study assessing Danish citizens’ perceptions and behavioral responses to the COVID-19 pandemic; namely, COSMO-Denmark (Böhm et al., 2020). In particular, data for Study 4a was derived from the fourth wave (April 14^th −19^th, 2020) of a repeated cross-sectional survey, and data for Study 4b was derived from the first four weeks of a panel survey (March 25^th –April 19^th, 2020). In both cases, the survey was set up in formr (Arslan et al., 2020) and invitations were sent via the official digital mail system in Denmark, called e-Boks (https://www.e-boks.com/danmark/en/). In total, 5,000 Danish citizens were invited to the fourth wave of the repeated cross-sectional survey, of whom 599 responded (self-identified 52.25% females, 47.41% males, 0.33% other; M_age = 54.74, SD_age = 15.80 years). In the first week of the panel survey, 15,000 Danish citizens were invited, of whom 2,546 responded. Of these, 1,293 also participated in the three subsequent weeks of the panel survey (based on official registers, 56.77% females, 43.23% males; M_age = 53.90, SD_age = 15.54 years).

Measures

Across Studies 4a and 4b, we assessed participants’ endorsement of collective punishment as a means of mitigating rule-breaking in the context of the COVID-19 pandemic, together with their self-reported adherence to COVID-19 restrictions, their perceived risk of COVID-19, and their concerns about the societal consequences of COVID-19. Furthermore, we assessed participants’ levels in the HEXACO personality dimensions using the Brief HEXACO Inventory (BHI; De Vries, 2013) in both Studies 4a and 4b. In Study 4b, we also assessed participants’ levels in D via the D16. The BHI and the D16 were answered using a 5-point Likert-type scale (ranging from 1 = strongly disagree to 5 = strongly agree), whereas all other items were answered on a 7-point Likert-type scale with different anchors. Descriptive statistics for each of the measures used in Studies 4a and 4b can be found in Tables S3–S5. Importantly, the internal consistencies of the BHI were relatively low (alphas <.62), which is, however, in line with prior research using this measure (see De Vries, 2013). An overview of all items and scales used in Studies 4a and 4b can be found in Table S5. A full overview of all variables assessed in COSMO is available at https://docs.google.com/spreadsheets/d/10TvgDYpPqIu0O5s8jx4TL0KF1NcfR9AUqm4AqNU2Tyc/edit?usp=sharing.

Results

Results from Studies 4a (r (597) = .17, p < .001) and 4b (r (1,291) = .20, p < .001) indicate that individuals who themselves adhered to the COVID-19 restrictions were more likely to endorse the use of collective punishment as a means of reducing noncompliance. As shown in Table 2, this result even holds after controlling for all other variables considered in both Studies 4a and 4b. Furthermore, citizens who were very concerned about the potential societal consequences of the COVID-19 pandemic and individuals high in D were more likely to endorse the use of collective punishment. Lastly, individuals high in emotionality were more likely to endorse the use of collective punishment (see Figure 4).

Table 2.

OLS regressions predicting the endorsement of collective punishment in studies 4a and 4b.

	Study 4a		Study 4b
Variable	Model 1 β (SE)	Model 2 β (SE)	Model 1 β (SE)	Model 2 β (SE)
Intercept	.00 (.06)	−.04 (.06)	.02 (.04)	.04 (.05)
Age	.09 (.05)	.09 (.05)	.05 (.03)	.08^* (.04)
Gender (Male)	−.01 (.09)	.08 (.10)	−.04 (.06)	−.10 (.08)
Adherence	.18 ^*** (.04)	.19 ^*** (.05)	.15 ^*** (.03)	.15 ^*** (.04)
Perceived risk	.11^* (.05)	.12^* (.05)	.09^** (.03)	.07 (.04)
Concerns for society	.24 ^*** (.04)	.25 ^** (.05)	.25 ^*** (.03)	.25 ^*** (.04)
Honesty-humility	–	−.12^* (.05)	–	.00 (.04)
Emotionality	–	.10^* (.05)	–	.09 ^* (.04)
Extraversion	–	−.01 (.05)	–	−.00 (.04)
Agreeableness vs. Anger	–	.15^** (.05)	–	.05 (.04)
Conscientiousness	–	−.01 (.05)	–	.06 (.04)
Openness to experience	–	−.18^*** (.04)	–	−.05 (.04)
Dark factor of personality	–	–	–	.13 ^** (.04)
n	472	441	1,246	751
R ²	0.15	0.21	0.13	0.16

Note. Continuous predictors are mean-centered and scaled by 1 standard deviation.

SE: standard error.

^***p < .001; ^**p < .01; ^*p < .05.

All p-values are two-tailed. Significant predictors across both models are bolded. Across all models we only use data from participants with no missing data in the independent and dependent variables of interest.

Figure 4.

Relations between emotionality and the endorsement of collective punishment in Study 4a (A; N = 599) and 4b (B; N = 1,293).

General discussion

Across six well-powered studies, we tested the effectiveness of collective punishment in reducing (self-serving financial) dishonesty. Furthermore, we explored whether personality dimensions moderate the effectiveness of collective punishment (for reducing dishonesty) as well as relate to the endorsement of collective punishment (for reducing rule-breaking). Results provide substantive evidence for the effectiveness of collective punishment in mitigating unethical behavior in the form of dishonesty. Focusing on inter-individual differences, we further found that honesty-humility and D predicted dishonesty irrespective of the absence or presence of collective punishment. Yet, individuals with higher (vs. lower) levels in emotionality showed lower levels of dishonesty when collective punishment was present (vs. absent). Using survey data, we also found that personality dimensions, especially D and emotionality, were related to individuals’ endorsement of collective punishment as an instrument for mitigating rule-breaking behavior in the context of the COVID-19 pandemic. Taken together, the present investigation provides robust evidence for the evaluation of collective punishment as an instrument for (sanctioning and) mitigating unethical and illegal behavior, and dishonesty in particular.

The effectiveness of collective punishment

Using a novel paradigm which ensures that collective punishment can be applied to a group while individual transgressors cannot be identified, we tested under which circumstances collective punishment is effective in reducing (self-serving) dishonesty. Our results suggest that collective punishment is effective when applied with a strict threshold, but we did not find support for its effectiveness when the criterion for its implementation is more lenient. Further, the fact that collective punishment and collective reward appeared to be equally effective in a one-shot setting raises the question of whether collective punishment should be preferred to collective reward when the goal is to reduce unethical behavior at a single point in time. Conversely, our results indicate that collective punishment continues to be effective in a repeated setting, whereas there was no support for such a claim concerning collective reward. Hence, from a consequentialist perspective, collective punishment could be considered to be morally defensible as an instrument for mitigating unethical behavior in the same population over time. More precisely, our results show that collective punishment can provide societal benefits in terms of reducing unethical behavior (here, dishonesty) and does so in a repeated setting for the same population. At the same time, whether the societal benefits at hand outweigh the costs (e.g., for implementation or on the innocent) is a crucial question that has to be considered extremely carefully when thinking about implementing collective punishment (for larger discussions on this, see, e.g., Heckathorn, 1988; Klocker, 2020; Levinson, 2003; White, 1994).

We did not find support that increasing the severity of punishment enhanced the effectiveness of collective punishment, which contrasts with previous findings on individual punishment (Laske et al., 2018; Thielmann & Hilbig, 2018). However, it could be argued that in our study the penalty of being banned from future studies by our lab may have been too weak, because future studies by our lab represent only a very small fraction of the subsequent available jobs on Prolific. Therefore, our insights into how punishment severity impacts dishonesty remain somewhat limited.

While our findings align with the finding that collective punishment can effectively reduce academic cheating (Zhao et al., 2021), they stand in contrast to investigations which found no significant reduction of rule following in a public goods game (Chapkovski, 2021), and even increased dishonesty in a cheating paradigm (Siniver et al., 2022). Next to methodological differences (e.g., we provide results across several experiments with a priori defined sample sizes, the design used herein does not allow for detecting individual transgressors), another potential explanation for these differences might be that the severity of the punishment in our study was relatively strong in terms of that all participants who rightfully won in the (adapted Mind Game) paradigm did not receive a bonus incentive. This explanation is in line with findings suggesting that dishonesty is strongly reduced with increased punishment severity on the individual level (Thielmann & Hilbig, 2018). Thus, our research may offer valuable insights for assessing the effectiveness of real-world interventions that share similar structural features.

In line with prior research (Garrett et al., 2016; Reis et al., 2023), we found that participants in the control condition of Study 2b were more dishonest in the second session as compared to the first session. There are likely several non-exclusive explanations for this finding. First, more participants may have realized (learned) that they could actually cheat in the paradigm. Second, more participants may have perceived that there are no negative consequences for cheating (e.g., study submissions were still approved, signaling that cheating is tolerated). Third, participants may have learned that cheating is widespread (having been informed of the total number of reported matches in their group), or perhaps more common than they initially thought. Future research might aim to disentangle the exact mechanisms here.

Different perspectives and the endorsement of collective punishment

In our studies, the perspective of respondents varied notably between Studies 1–3 and Studies 4a and 4b, which may have influenced their perceptions of and responses to collective punishment—next to the obvious differences that Studies 1–3 investigated participants’ behavioral responses to collective punishment threats, whereas Studies 4a and 4b investigated participants’ endorsement of collective punishment. In Studies 1–3, participants were positioned primarily as potential victims of collective punishment. This setup naturally elicits a perspective where individuals are more sensitive to the fairness and impact of being unjustly punished due to the actions of others. From this viewpoint, participants’ behavioral responses to collective punishment are likely influenced by their personal experience of potential injustice and the desire to avoid harm. Conversely, in Studies 4a and 4b, the context differed as participants were both potential victims and beneficiaries of collective punishment. Here, the additional COVID-19 restrictions served as a collective measure to protect public health, meaning that participants might perceive themselves as beneficiaries of these measures, potentially especially if they valued safety over freedom (see Costantini et al., 2021). This dual role complicates the perception of collective punishment, as individuals must balance their personal inconvenience against the broader benefit to public health. Further, this dual perspective can lead to a more nuanced evaluation of collective punishment, where individuals may simultaneously recognize the necessity of such measures while also feeling the impact of the restrictions on their personal freedom.

Baumert and Schmitt (2016) distinguish four perspectives from which one can be sensitive to (in)justice: beneficiary, observer, perpetrator, and victim. These perspectives can significantly influence how individuals perceive the legitimacy and fairness of collective punishment. For instance, individuals with high levels of D, who hold “the tendency to maximize one’s individual utility—disregarding, accepting, or malevolently provoking disutility for others” (Moshagen et al., 2018, p. 656), may be more likely to endorse collective punishment from the perspective of a beneficiary. Conversely, from the victim’s perspective, high levels of D might lead to lower endorsement due to a heightened sensitivity to personal injustice. Understanding these perspectives might help explain variations in endorsement levels.

Social bonds and the effectiveness of collective punishment

In our experimental studies, the connection between participants was relatively weak, as they were all crowdworkers on Prolific. However, the effectiveness of collective punishment may be significantly shaped by the strength of social bonds among group members. In tightly-knit groups, stronger connections can amplify accountability, peer pressure, empathy, and collective responsibility. When individuals strongly identify with their group, they are more likely to adhere to group norms to avoid disappointing or harming their peers (e.g., Masson & Fritsche, 2014; Rathbone et al., 2023; Täuber & Sassenberg, 2012). Additionally, empathy for innocent group members affected by collective punishment may increase the psychological cost of dishonest behavior (e.g., Thielmann & Hilbig, 2018). Thus, in settings where group bonds are stronger than in our studies, one might expect collective punishment to be even more effective.

Inter-individual differences and collective punishment

Although we hypothesized that honesty-humility and D would interact with the implementation of collective punishment in predicting dishonesty, our results did not support either of these hypotheses. Instead, we found that honesty-humility and D were related to dishonesty regardless of whether or not collective punishment was present. One explanation is that our implementation of collective punishment shifted the incentive structure uniformly, making the external costs of cheating more salient for everyone, rather than selectively engaging the motivational pathways tied to honesty-humility or D. These findings add to the literature showing a negative relation between honesty-humility and dishonesty (e.g., Heck & Moshagen, 2018; Zettler et al., 2020) and a positive relation between D and dishonesty (Moshagen et al., 2018, 2020), respectively. Next to these direct relations, previous studies already investigated potential interaction effects between honesty-humility and situational factors on dishonesty or anti- and prosocial behavior more broadly. Interestingly, several studies found support for such interaction effects (e.g., Hilbig & Zettler, 2009), while others did not (e.g., Schild et al., 2020). From this perspective, another explanation is that further variables might affect the interplay between honesty-humility/D, collective punishment, and (self-serving financial) dishonesty, masking any interaction effects between honesty-humility/D and collective punishment. Future research might thus aim to further specify the conditions under which honesty-humility (or other personality dimensions) are expected to interact with which kind of other factors in predicting dishonesty or related criteria. In this regard, further specifications of the affordance framework for prosocial behavior (Columbus et al., 2019; Popov & Thielmann, 2025 in press; Thielmann et al., 2020) might help in the design of future studies on collective punishment.

In addition to continued focus on honesty-humility and D as important predictors for dishonesty (alone or in combination with other factors), future research might delve more deeply into the role of emotionality for dishonesty-related outcomes. More precisely, our exploratory analyses suggest that individuals high (vs. low) in emotionality reacted more strongly to the presence of collective punishment by being less dishonest. While a large body of research has indicated that emotionality is not related to dishonesty in classic cheating paradigms (e.g., Heck & Moshagen, 2018) or dishonesty more broadly (Zettler et al., 2020), this finding is conceptually in line with a recent study suggesting that emotionality is related to prosocial lies (i.e., cheating for the benefit of another person; Thielmann et al., 2023). Because individuals high in emotionality tend to show a stronger empathic concern for others (which might also explain why they show more prosocial lies), they might refrain from dishonest behaviors if this would imply direct, negative consequences for others, including innocent others—as in the case of collective punishment. Another, potentially complementary line of argumentation is that individuals high in emotionality are also more anxious, fearful, and worrisome (Ashton & Lee, 2007) and might thus refrain from dishonesty in the presence of collective punishment because they are afraid of getting sanctioned. Clearly, future research should more strongly consider the role of emotionality for specific forms of dishonesty or anti- and prosocial behavior, as increasing evidence points at a high relevance of this dimension for respective outcomes (e.g., Bader et al., 2025).

Results across both Studies 4a and 4b further showed that especially D and emotionality were also related to endorsing the use of collective punishment. Concerning D, these findings align with research showing that spitefulness is an important ingredient of D (even if this also incurs some costs for oneself; e.g., Horsten et al., 2021) and research on aversive traits showing that those with higher levels in such traits generally have more positive views towards punishment (e.g., Chung et al., 2022; Franklin-Luther & Volk, 2021). Concerning emotionality, the finding that individuals high in this dimension have a stronger preference for endorsing collective punishment aligns with research showing that such individuals are also very sensitive for the consequences of moral decisions (Kroneisen & Heck, 2020). In our study context, individuals high in emotionality might thus have estimated the consequences of not implementing collective punishment—which was introduced as a mean to curb the spread of a virus that might entail negative consequences for “weak” others in particular—as more severe and negative, as compared to the consequences of implementing it, which would have some costs on innocent others. Clearly, the results from Studies 4a and 4b also suggest that the dimension of emotionality deserves more consideration in research when moral issues and/or issues including the threat of some form of punishment are at stake.

Beyond personality dimensions, our results show that even though collective punishment may be considered an unfair and illegitimate form of punishment (Pereira et al., 2015), individuals are more likely to endorse its use if they themselves comply with the rules and believe that the societal consequences of too much noncompliance would be undesirable. Taken together, these results indicate that individuals are not universally opposed to the use of collective punishment and that there may be situations in which individuals would find the use of collective punishment legitimate—another avenue for future research.

Limitations and conclusion

To further advance the debate surrounding collective punishment and tackle some limitations of this investigation, future research should aim to critically examine the effectiveness of collective punishment in the field or in situations in which the criteria for its implementation are vague or uncertain. Future research could also aim to test the effectiveness of collective punishment for criteria other than dishonesty (while paying attention that respective study designs comply with the notion that collective punishment can, if at all, only be considered if it is impossible to detect or punish individual transgressors). Further, future research could aim to investigate under which circumstances individuals would (endogenously) self-select or agree to be part of a community that uses collective punishment, as well as the extent to which the perceived legitimacy of an authority introducing collective punishment influences its effectiveness. At this juncture, a particular focus might be given to the moral debate around the implementation of collective punishment, especially in (certain) applied contexts.

Lastly, the selection of WEIRD study populations in our studies (Denmark, UK, and US) might have limited the generalizability of our findings (Simons et al., 2017). Cultural variation in tightness-looseness, collectivism-individualism, and perceived legitimacy of authorities may shape both acceptance and effectiveness of collective punishment. What appears illegitimate in high-individualism contexts may be viewed as norm-consistent in tighter or more collectivist cultures. Thus, future research might aim to recruit other samples from other populations in this stream of research.

To conclude, we would like to emphasize that this research should, in line with ethical and legal debates throughout history (e.g., Heckathorn, 1988; Klocker, 2020; Levinson, 2003; White, 1994), not be taken as a call to increase the use of collective punishment. Rather, we believe that this work informs the evaluation of whether, and under which conditions, the use of collective punishment is effective and potentially morally defensible (from a consequentialist perspective), and how individuals with different characteristics might react to its implementation.

Supplemental Material

Supplemental material - Testing the effectiveness and endorsement of collective punishment

Supplemental material for Testing the effectiveness and endorsement of collective punishment by Christoph Schild, Lau Lilleholt, Robert Böhm, and Ingo Zettler in European Journal of Personality

Footnotes

Author contributions

Conceptualization: CS, LL, RB, IZ; Data curation: CS, LL; Formal Analysis: CS, LL; Funding acquisition: RB, IZ; Investigation: CS, LL; Methodology: CS, LL, RB, IZ; Project administration: CS, LL, IZ; Resources: CS, LL; Software: CS, LL; Supervision: RB, IZ; Validation: CS, LL; Visualization: CS, LL; Writing – original draft: CS, LL, RB, IZ; Writing – review & editing: CS, LL, RB, IZ.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by Carlsbergfondet, Grant Number: CF16-0444 (Ingo Zettler), Det Frie Forskningsråd, Grant Number: 7024-00057B (Ingo Zettler), Lundbeck Foundation, Grant Number: R349-2020-592 (Robert Böhm and Ingo Zettler), Faculty of Social Sciences, University of Copenhagen (Robert Böhm and Ingo Zettler).

ORCID iDs

Christoph Schild

Lau Lilleholt

Robert Böhm

Ingo Zettler

Supplemental Material

Supplemental material for this article is available online.

Notes

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