This introduction presents the two-part Special Issue of honoring the life and work of Amnon Rapoport (1936–2022), a pioneering scholar whose six decades of research shaped experimental studies of interactive decision making. Rapoport’s hallmark was the interplay between formal game-theoretic modeling and rigorous laboratory testing, advancing understanding in coalition formation, social dilemmas, market entry, traffic networks, decision timing, resource dilemmas, behavioral operations, and methodological innovation. The 27 articles collected across the volumes revisit and extend these themes, offering fresh insights into how rationality assumptions succeed and fail in predicting human behavior. Together, the contributions reflect both continuity with Rapoport’s intellectual credo—“model first, test second, refine third”—and renewal through new methods and applications. Beyond scholarship, the issue pays tribute to Rapoport’s extraordinary role as a mentor and his enduring influence on the evolution of behavioral and experimental economics

While market design advocates for the importance of good design to achieve desirable properties, experiments on coalition formation theory have shown fragility in proposed mechanisms to do so. We experimentally investigate the effectiveness of “structured” mechanisms that implement the Shapley value as an ex ante equilibrium outcome with those of corresponding “semi-structured” bargaining procedures. We find a significantly higher frequency of grand coalition formation and higher efficiency in the semi-structured than in the structured procedures regardless of whether they are demand-based or offer-based. While significant differences in the resulting allocations are observed between the two structured procedures, little difference is observed between the two semi-structured procedures. Finally, the possibility of free-form chat induces an equal division more frequently than occurs without it. Our results suggest that when it comes to bargaining and coalition formation, not having various restrictions imposed by different mechanisms may lead to more desirable outcomes.

In two sets of novel laboratory experiments, we show that the mere presence of an existing alliance at the onset of coalition formation may lead managers to form economically suboptimal alliances. Study Set 1 considers alliance formation when a focal firm is already embedded in an existing coalition. These studies show evidence of a status quo bias: participants managing the focal firm tend to include the current partner in alliance offers and thus are less successful in forming optimal alliances compared to those in an unattached control condition. Study Set 2 examines the extent to which an unattached focal firm attempts to ‘poach’ away attractive coalition partners from their embedded alliances. Our results show evidence of poaching avoidance: participants make fewer offers to, and are less likely to partner with, an attractive firm already in an alliance. However, this tendency to avoid poaching may be attenuated when the existing coalition is perceived as a powerful threat and/or alternate partners are unavailable. These findings provide behavioral insights into how judgmental biases can constrain alliance formation. We conclude with a discussion of how selected environmental, firm, and decision-maker characteristics (e.g., turbulence, embedded relationships, and risk orientation) may moderate these results.

How do bribes and lobbying distort judgment? In our experiment, referees are tasked with judging a worker’s performance, and awarding a bonus to workers who score above a certain threshold. We find that bribes and lobbying are both distortionary, but in different ways. Whereas lobbying increases the number of workers receiving a bonus, bribes weaken the relationship between performance and success, with bonuses mostly being awarded to workers who bribe. We discuss implications for anti-corruption interventions.

Over the last four decades, a broad stream of experimental literature has been published using the Common Pool Resource (CPR) game to study how people react to congestible resources, and how to keep such resources from socially harmful overexploitation. With the goal of providing guidance to future work on this still-important paradigm, we provide a narrative review of the literature, summarizing the results for several key aspects of the experimental operationalization. We classify these aspects into two broad categories. The first describes ‘environmental’ assumptions on the modeled resource problem itself. This refers to aspects of the experimental environment reflecting factors such as group size, resource size and asymmetry of access, which generally constitute the nature of the dilemma. The second category involves ‘institutional’ issues related to how people might solve the problem, such as user communication between subjects, information about previous subjects’ choices, and regulatory measures.

Volunteering is a widespread allocation mechanism in the workplace. It emerges naturally in software development or the generation of online knowledge platforms. Using a field experiment with more than 2,000 workers, we study the effect of team size on volunteering in an online labor market. In contrast to our theoretical predictions and previous research, we find no effect of team size on volunteering, although workers react to free-riding incentives, and volunteering is perceived as costly. Eliciting workers’ beliefs about their co-workers’ volunteering reveals conditional volunteering as the primary driver of our results: Workers tend to volunteer more when they believe that others are volunteering, even when doing so is highly inefficient. Using additional experiments, we identify the importance of the task itself as an essential mitigating factor for those results.

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.

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.

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.

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.

Determining an individual’s strategic reasoning capability based solely on choice data is a complex task. This complexity arises because sophisticated players might have non-equilibrium beliefs about others, leading to non-equilibrium actions. In our study, we pair human participants with computer players known to be fully rational. This use of robot players allows us to disentangle limited reasoning capacity from belief formation and social biases. Our results show that, when paired with robots, subjects consistently demonstrate higher levels of rationality, compared to when paired with human players. Furthermore, players’ rationality levels are relatively stable across games when paired with robot players, even though those with intermediate rationality levels exhibit inconsistency across games. Leveraging our experimental design, we identify and document potential causes of this inconsistency.