Wrong-doers may try to collaborate to achieve greater gains than would be possible alone. Yet potential collaborators face two issues: they need to accurately identify other cheaters and trust that their collaborators do not betray them when the opportunity arises. These concerns may be in tension, since the people who are genuine cheaters could also be the likeliest to be untrustworthy. We formalise this interaction in the ‘villain’s dilemma’ and use it in a laboratory experiment to study three questions: what kind of information helps people to overcome the villain’s dilemma? Does the villain’s dilemma promote or hamper cheating relative to individual settings? Who participates in the villain’s dilemma and who is a trustworthy collaborative cheater? We find that information has important consequences for behaviour in the villain’s dilemma. Public information about actions is important for supporting collaborative dishonesty, while more limited sources of information lead to back-stabbing and poor collaboration. We also find that the level of information, role of the decision maker, and round of the experiment affect whether dishonesty is higher or lower in the villain’s dilemma than in our individual honesty settings. Finally, individual factors are generally unrelated to collaborating but individual dishonesty predicts untrustworthiness as a collaborator.

In a $k$-replica Edgeworth box economy, we compare outcomes of laboratory markets in which human traders have different visualizations available on their screens. Novel visualizations include a heat map that shows at a glance the value of all feasible portfolios (i.e., final allocations); a geometric display of the order book; and order entry via point-and-click on the heat map. Efficiency metrics focus on allocations, prices and profitability. Compared to the traditional text-oriented trader screen for the continuous double auction, we find that the novel features generally increase all three efficiency metrics.

Information about the consequences of our consumption choices can be unwelcome, and people sometimes avoid it. Thus, when people possess information that is inconvenient for another person, they may face a dilemma about whether to inform them. We introduce a simple and portable experimental game to analyze the transmission of inconvenient information. In this game, a Sender can, at a small cost, inform a Receiver about a negative externality associated with a tempting and profitable action for the Receiver. The results from our online experiment (N = 1,512) show that Senders transmit more information when negative externalities are larger and that Senders’ decisions are largely driven by their own preferences towards the charity and their own use of information. We do not find evidence that Senders take the Receiver’s preferences into account, as they largely ignore explicit requests for information, or ignorance, even if Receivers have the option to punish the Sender.

Using data from a large-scale behavioral experiment in Beijing, we investigate how social efficiency orientation may relate to rice culture proxied by the rice farming ratio in the subject’s birth province. We find that the observed behavior in several behavioral games that enhances social efficiency is positively associated with the rice farming ratio. This is corroborated by a further analysis of data related to giving help from the China Family Panel Studies. The overall finding supports our hypothesis that rice culture fosters the individual’s intrinsic preference toward greater social efficiency.

In this paper, we present a flexible approach to estimating parametric cumulative Prospect Theory using Hierarchical Bayesian methods. Bayesian methods allow us to include prior knowledge in estimation and heterogeneity in individual responses. The model employs a generalised parametric specification of the value function allowing each individual to be risk-seeking in low-stakes mixed prospects. In addition, it includes parameters accounting for varying levels of model noise across domains (gain, loss, and mixed) and several aspects of lottery design that can influence respondent behaviour. Our results indicate that enhancing value function flexibility leads to improved model performance. Our analysis reveals that choices within the gain domain tend to be more predictable. This implies that respondents find tasks in the gain domain cognitively less challenging in comparison to making choices within the loss and mixed domains.

This paper analyzes individual behavior in multi-armed bandit problems. We use a between-subjects experiment to implement four bandit problems that vary based on the horizon (indefinite or finite) and the number of bandit arms (two or three). We analyze commonly suggested strategies and find that an overwhelming majority of subjects are best fit by either a probabilistic “win-stay lose-shift” strategy or reinforcement learning. However, we show that subjects violate the assumptions of the probabilistic win-stay lose-shift strategy as switching depends on more than the previous outcome. We design two new “biased” strategies that adapt either reinforcement learning or myopic quantal response by incorporating a bias toward choosing the previous arm. We find that a majority of subjects are best fit by one of these two strategies but also find heterogeneity in subjects’ best-fitting strategies. We show that the performance of our biased strategies is robust to adapting popular strategies from other literatures (e.g., EWA and I-SAW) and using different selection criteria. Additionally, we find that our biased strategies best fit a majority of subjects when analyzing a new treatment with a new set of subjects.

An abundance of statistics has shown gender disparity in hiring decisions. This paper shows that a previously unexplored factor, the decision-making process utilized by a hiring committee, plays a crucial role. Using a laboratory experiment, we find that gender disparity is eliminated when hiring decisions are made unanimously by a group. By comparison, we find that gender disparity is largest when decisions are made by a leader who volunteers. We do not find evidence of heterogeneity by gender as the results persist regardless of the number of women in the group or the leader’s gender. The experimental design allows us to rule out several possible mechanisms including differences in leadership characteristics and communication styles.

Amnon Rapoport made seminal contributions to research on investment decision-making and individual decision-making under risk. To build on his seminal work, this paper explores the impact of social influence on risk-taking. First, to build predictions for experimental testing, we modify a standard expected utility model by introducing a social norm variable. Using a standard 10-decision paired lottery choice task, we report the results from three experiments with different manipulations to test whether social influence information affects subjects’ own lottery choices. In Experiment 1, we find that participants are more likely to switch to choosing the risky option earlier if they are told that a large majority (>75%) of a large group (N = 100) of others have also chosen the risky option in the past. In Experiment 2, we find there is no effect if the social influence prompt is framed as a small group (N = 10) or the choice of one (N = 1) successful lottery participant, but there is an effect when participants are provided information about the consistently risky choices of one (N = 1) person in the past. In Experiment 3, using an in-person subject pool, we find some mixed effects on risk-taking when the social information is framed as a small group (N = 10) of peers (other students). Altogether, this paper demonstrates that social influence can impact risk-taking in line with a socially normed expected utility model.

In meritocratic societies, inequality is considered just if it reflects factors within but not outside individuals’ control. However, individuals often benefit differentially from other people’s efforts. Such passive inequality is simultaneously just and unjust by meritocratic standards, confronting meritocrats with a dilemma. We conducted an experiment with a representative US sample to investigate how people deal with this dilemma. In the experiment, impartial spectators redistribute payments between pairs of individuals. We vary whether initial payments result from luck or effort and whether spectators redistribute between individuals who worked themselves or individuals who benefited from the work of real-life friends. We find that spectators treat inequality based on the efforts of individuals’ friends as if individuals had worked themselves, and very different from inequality resulting from differential luck. This indicates that most people accept inequality if it is merited at some stage, which may explain opposition to redistributive policies.

Using a laboratory experiment, we investigate complexity in decision problems as a cause of failures in contingent reasoning. For this purpose, we introduce three dimensions of complexity to a decision problem: the number of contingencies, the dominance property of choices, and reducible states. Each decision problem is designed to reflect variations in complexity across the three dimensions. Experimental results show that the number of contingencies has the most significant effect on failures in contingent reasoning. The second dimension, the dominance property of choices, also has a statistically significant effect, though the effect size is smaller than in the existing literature. In contrast, the third complexity dimension has no impact; presenting the decision problem in a reduced or reducible form does not change subjects’ performance on contingent reasoning. Additionally, we examine the Power of Certainty and show its existence. This effect is particularly pronounced when the number of contingencies is large.

Many societies allocate wealth and status through competitions. These competitions may be seen as unfair if the playing field is uneven or if the competitors are of unequal strength. We run two experiments to document the extent to which people are willing to compete against others in situations with varying fairness concerns. In a between-subject experiment, we show that people’s willingness to compete is largely unaffected by the impact their choice has on the payoff of an opponent, no matter whether the opponent had a choice about whether to compete or not. In a within-subject experiment, we show that most people are willing to compete against opponents who have been exogenously disadvantaged or are known to be weaker. People who choose competition against weak or disadvantaged opponents are also more willing to give themselves an advantage by sabotaging the performance of their opponent.

We propose a two-sided market entry game and present experiments studying coordination behavior in the game. The two-sided market in the game is operated by an intermediary monopoly platform, serving two sides (i.e., customers and service providers) and featuring asymmetric agents, cross-side network effects, and endogenous market capacity. The game has multiple pure-strategy Nash equilibria if at least one side has a high willingness to enter the market and the other side’s willingness is not very low. We conduct a laboratory experiment involving three treatments corresponding to different combinations of willingness to enter the market among customers and service providers. The experimental results indicate that willingness to enter the market and cross-side network effects significantly influence coordination behavior in two-sided markets. When the multiple pure-strategy Nash equilibria are Pareto ranked on both sides, customers and service providers can coordinate their behavior to the payoff-dominant equilibrium via tacit coordination under strategic uncertainty. However, when the multiple pure-strategy Nash equilibria are Pareto ranked on one side but Pareto equivalent on the other side, coordination failure and disequilibrium occurred, and the equilibria cannot predict the aggregate behavior well. Our experimental results indicate that a thriving two-sided market should coordinate both sides on board.

We introduce a novel scenario that embeds the Downs-Thomson paradox in the context of departure-time choice during the morning commute. Commuters, departing from a common origin and traveling to a common destination, must choose between a congestible mode (car, road) and a non-congestible mode (train, railway). Those choosing the road must also select their departure times independently and anonymously. This decision involves a trade-off between the cost of queuing at the bottleneck and the cost of schedule delay (i.e., deviation from the desired arrival time). We numerically derive a symmetric mixed-strategy equilibrium that characterizes both mode and departure-time choices. We then examine how improvements to either the road or the railway affect mean travel costs. Our laboratory experiment shows that, consistent with the paradox, improving the railway lowers mean travel cost; however, contrary to the paradox, improving the road also reduces mean travel cost. These findings suggest that the Downs-Thomson paradox may fail to emerge fully when commuters must coordinate multiple strategic dimensions under intertemporal congestion externalities.

Research on individual decisions from experience reveals a robust tendency to behave as if rare events are underweighted. Experimental studies of strategic interactions often exclude probabilistic outcomes, thus neglecting the potential extension of this tendency to strategic games. Our study addresses this gap by examining how players in games adjust their strategies when confronted with low-probability, high-impact outcomes. We introduce two finitely repeated, asymmetric games with lottery-based payoffs. These games, when simplified by replacing lotteries with their expected values, yield straightforward equilibrium predictions based on dominant strategies. However, results from three experiments reveal players strongly deviate from these predictions, instead behaving consistently with underweighting of rare events. The results additionally indicate that social preferences also play a role in shaping behavior. To explain these observations, we propose the simplistic Reciprocal Altruistic Sampler (REALS) model. This model posits that players’ decisions are a result of the interplay between reliance on small samples of past experiences, altruistic tendencies, and strategic considerations. We experimentally compare behavior in variants of the games that disentangle the behavior to these three components, and show that the REALS model, despite its simplicity, effectively captures their complex interactions. Our results additionally demonstrate that players can often choose strictly dominated strategies in a sophisticated effort to react to underweighting of rare events by other players. Overall, this study enhances our understanding of strategic decision making by highlighting the crucial impact of rare events and the interplay of different uncertainties in influencing players’ choices.

We explore strategic betting in competitive environments with multiple participants and potential winners. We examine two scenarios: an ‘inclusive’ low-competition scenario with many winners and an ‘exclusive’ high-competition scenario with few winners. Using a simple model, we illustrate the strategic insights in these scenarios and present experimental results that align with our predictions. In the experiment, participants made repeated bets with feedback on past results and their payoffs. In the inclusive scenario, all but the worst guessers were rewarded, while in the exclusive scenario, only the top guessers received rewards. Our findings show that in the inclusive scenario, participants exhibit herding behavior by coordinating their bets, while in the exclusive scenario, they diversify their bets across multiple options. The main general insight of our findings is that in moderate competitions, one tends to join the majority to avoid standing out in case of failure, whereas in intense competitions, one tends to differentiate oneself from one’s peers to ensure that success stands out. This insight is relevant for a broad domain of strategic interactions.

People, across a wide range of personal and professional domains, need to accurately detect whether the state of the world has changed. Previous research has documented a systematic pattern of over- and under-reaction to signals of change due to system neglect, the tendency to overweight the signals and underweight the system producing the signals. We investigate whether experience, and hence the potential to learn, improves people’s ability to detect change. Participants in our study made probabilistic judgments across 20 trials, each consisting of 10 periods, all in a single system that crossed three levels of diagnosticity (a measure of the informativeness of the signal) with four levels of transition probability (a measure of the stability of the environment). We found that the system-neglect pattern was only modestly attenuated by experience. Although average performance did not increase with experience overall, the degree of learning varied substantially across the 12 systems we investigated, with participants showing significant improvement in some high diagnosticity conditions and none in others. We examine this variation in learning through the lens of a simple linear adjustment heuristic, which we term the “δ-ϵ” model. We show that some systems produce consistent feedback in the sense that the best δ and ϵ responses for one trial also do well on other trials. We show that learning is related to the consistency of feedback, as well as a participant’s “scope for learning” how close their initial judgments are to optimal behavior.

In a game with costly information acquisition, the ability of one player to acquire information directly affects her opponent’s incentives for gathering information. Rational inattention theory then posits the opponent’s information-acquisition strategy is a direct function of these incentives. This paper argues that people are cognitively limited in predicting their opponent’s level of information, and hence lack the strategic sophistication that the theory requires. In an experiment involving a real-effort attention task and a simple two-player trading game, I study the ability of subjects to (1) anticipate the information acquisition of opponents in this strategic game, and (2) best respond to this information acquisition when acquiring their own costly information. I study this by exogenously manipulating the difficulty of the attention task for both the player and their opponent. Predictions of behavior are generated by a novel theoretical model in which Level-K agents can acquire information à la rational inattention. I find an out-sized lack of strategic sophistication, driven largely by the cognitive difficulties of predicting opponent information. These results suggest a necessary integration of the theories of rational inattention and costly sophistication in strategic settings.

Awards are widely used as incentives. This paper situates awards in the broader incentives landscape and shows how the motivational value of awards can be understood through a framework that considers three sources of value: the tangible component of an award, the social signals it emits, and its self-signaling function. We identify and discuss several major characteristics of awards through the lenses of these three dimensions: the audience, scarcity, the giver’s status, and the selection process. Based on our framework, we integrate the awards literature published across economics, psychology, management, and sociology journals to elucidate what has been learned and offer a roadmap for future experimental research on awards and incentives.

We present and test a model of reciprocity in which people are more likely to repay good treatment to the extent they judge it as motivated by true caring rather than tactical self-interest. The model’s key contributions stem from how it handles ambiguously motivated behavior. It allows people to maintain divergent hypotheses: They can view behavior as driven by caring, self-interest, or a mix thereof. In contrast, previous analyses resolve rather than maintain ambiguity. They treat caring and self-interest as mutually exclusive hypotheses, and require that people commit to one and dismiss the other. By more realistically handling ambiguity, our model yields three benefits. First, it accommodates intuitive patterns of play that existing analyses do not and which we experimentally corroborate. These patterns reflect intermediate inclinations to reciprocate ambiguously motivated positive behavior. Second, it challenges conventional interpretations of long-studied phenomena, including unraveling in finitely iterated prisoners’ dilemmas, substantial offers in ultimatum games, and gift exchange. Third, it highlights how diversity in perceptions – the same action can appear generous to one person and miserly to another – is empirically consequential. Under conventional interpretations and without accounting for diverse perceptions, the aforementioned phenomena have been viewed as inconsistent with a taste for repaying good treatment. Our model shows that they are entirely consistent with a nuanced form of this taste: a desire to repay good treatment that seems to largely reflect genuine caring.

This paper considers a stationary model of inventory management in a rich setting in which unsold units carry over, in contrast with the full depreciation of unsold units that is implemented in laboratory studies of the news vendor problem. The model permits an array of costs associated with restocking, understocking, depreciation, financing, and holding inventories. The extra dimensions make it possible to hold the optimal inventory constant, while adjusting parameters that change the frequency of stockouts and the risks associated with storage and depreciation. This framework facilitates an investigation of factors that influence the nature and severity of behavioral biases observed in simpler news vendor settings. Optimal inventory decisions are derived and tested with a laboratory experiment. We consider four main questions in the inventory literature: the “pull-to-center” effect, the “recency” effect, the effect of increased up-front costs, and the effect of risk aversion.