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This paper studies a dynamic principal–agent setting in which the principal needs to dynamically schedule an agent to work or be suspended. When the agent is directed to work and exert effort, the arrival rate of a Poisson process is increased, which increases the principal's payoff. Suspension, on the other hand, serves as a threat to the agent by delaying future payments. A key feature of our setting is a switching cost whenever the suspension stops and the work starts again. We formulate the problem as an optimal control model with switching and fully characterize the optimal control policies/contract structures under different parameter settings. Our analysis shows that, when the switching cost is not too high, the optimal contract demonstrates a generalized control-band structure. The length of each suspension episode, on the other hand, is fixed. Overall, the optimal contract is easy to describe, compute, and implement. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis. Funding: The work of P. Cao is financially supported by the National Natural Science Foundation of China [Grants 72122019 and 71771202]. The work of F. Tian is financially supported by the Hong Kong Research Grants Council (RGC) funding (RGC Early Career Scheme 2022/23) [Grant 27500822]. Supplemental Material: The e-companion and data are available at https://doi.org/10.1287/mnsc.2023.4845. [ABSTRACT FROM AUTHOR]

People often need to plan how to allocate their attention across different tasks. In this paper, we run two experiments to study a stylized version of this attention-allocation problem between strategic tasks. More specifically, we present subjects with pairs of 2 × 2 games, and for each pair, we give them 10 seconds to decide how they would split a fixed time budget between the two games. Then, subjects play both games without time constraints, and we use eye-tracking to estimate the fraction of time they spend on each game. We find that subjects' planned and actual attention allocation differ and identify the determinants of this mismatch. Further, we argue that misallocations can be relevant in games in which a player's strategy choice is sensitive to the time taken to reach a decision. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Work on this project was provided by the National Science Foundation [Grant SES 1724550] "Collaborative Research: Attention in Games and Decisions," awarded to A. Schotter and E. R. Schotter. The work of M. Ribeiro and M. Zou was supported by the Center for Experimental Economics Social Science at New York University. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4834. [ABSTRACT FROM AUTHOR]

The rapid adoption of artificial intelligence (AI) technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks. In fact, when used in collaboration, machines can significantly enhance the complementary strengths of humans. Indeed, because of their immense computing power, machines can perform specific tasks with incredible accuracy. In contrast, human decision makers (DMs) are flexible and adaptive but constrained by their limited cognitive capacity. This paper investigates how machine-based predictions may affect the decision process and outcomes of a human DM. We study the impact of these predictions on decision accuracy, the propensity and nature of decision errors, and the DM's cognitive efforts. To account for both flexibility and limited cognitive capacity, we model the human decision-making process in a rational inattention framework. In this setup, the machine provides the DM with accurate but sometimes incomplete information at no cognitive cost. We fully characterize the impact of machine input on the human decision process in this framework. We show that machine input always improves the overall accuracy of human decisions but may nonetheless increase the propensity of certain types of errors (such as false positives). The machine can also induce the human to exert more cognitive efforts, although its input is highly accurate. Interestingly, this happens when the DM is most cognitively constrained, for instance, because of time pressure or multitasking. Synthesizing these results, we pinpoint the decision environments in which human-machine collaboration is likely to be most beneficial. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4744. [ABSTRACT FROM AUTHOR]

Exhibiting altruism toward and cooperativeness with others is a key ingredient for successful work relationships and managerial decision making. Rising political polarization creates a hazard because it ruptures this fabric and impedes the interaction of employees, especially across political isles. This paper's focus is to examine various behavioral-, belief-, and norm-based layers of (non)strategic decision making that are plausibly affected by polarization. I quantify this phenomenon via five preregistered studies in the context of Donald J. Trump, comprising 15 well-powered behavioral experiments and a diverse set of over 8,600 participants. To capture the pervasiveness of polarization, I contrast the findings with various political and nonpolitical identities. Overall, I consistently document strong heterogeneous effects: ingroup-love occurs in the perceptional domain (how close one feels toward others), whereas outgroup-hate occurs in the behavioral domain (how one helps/harms/cooperates with others). The rich setting also enables me to examine the mechanisms of observed intergroup conflict, which can be attributed to one's grim expectations regarding cooperativeness of the opposing faction, rather than one's actual unwillingness to cooperate. For the first time, the paper also tests whether popular behavioral interventions (defaults and norm-nudges) can reduce the detrimental impact of polarization in the contexts studied here. The tested interventions improve prosociality but are ineffective in closing the polarization gap. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by Deutsche Forschungsgemeinschaft [Grant EXC 2126/1– 390838866]. Supplemental Material: Data and the online appendix are available at https://doi.org/10.1287/mnsc.2023.4701. [ABSTRACT FROM AUTHOR]

We conducted a large-scale personalized field experiment to examine how match quality, recognition, and social impact influence domain experts' contributions to Wikipedia. Forty-five percent of the experts expressed willingness to contribute in the baseline condition, whereas 51% (a 13% increase over the baseline) expressed interest when they received a signal that an article matched their expertise. However, none of the treatments had a significant effect on actual contributions. Instead experts contributed longer and better comments when the actual match between a recommended Wikipedia article and an expert's expertise, measured by cosine similarity, was higher, when they had higher reputation, and when the original article was longer. These findings suggest that match quality between volunteers and tasks is critically important in encouraging contributions to digital public goods and likely to volunteering in general. This paper was accepted by David Simchi-Levi, behavioral economics and decision analysis. Funding: This work was supported by the National Science Foundation through [Grant SES-1620319] awarded to Carnegie Mellon University and the University of Michigan. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4852. [ABSTRACT FROM AUTHOR]

We measure the willingness to compete of entrepreneurs and salaried workers in an experiment. Participants can choose between a piece rate and a tournament scheme in either private or public. We find that in the private condition, entrepreneurs are less competitive than salaried workers, but in the public condition, this ordering is reversed. Survey data suggest that perceived norms of appropriate behavior, along with beliefs about the instrumental value of competitiveness for professional success, can explain why entrepreneurs are more competitive when decisions are publicly observable. We also find that the latter condition improves the quality of experimental decisions. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Financial support from the Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany´s Excellence Strategy [Grant EXC 2126/1–390838866], the University of Cologne through the Hans Kelsen Prize and the Austrian Science Fund through the Special Research Area [Grant SFB F63] is gratefully acknowledged. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4838. [ABSTRACT FROM AUTHOR]

Models of statistical discrimination typically assume that employers make rational inference from (education) signals. However, there is a large amount of evidence showing that most people do not update their beliefs rationally. We use a model and two experiments to show that employers who are conservative, in the sense of signal neglect, discriminate more against disadvantaged groups than Bayesian employers. We find that such non-Bayesian statistical discrimination deters high-ability workers from disadvantaged groups from pursuing education, further exacerbating initial group inequalities. Excess discrimination caused by employer conservatism is especially important when signals are very informative. Out of the overall hiring gap in our data, around 40% can be attributed to Bayesian statistical discrimination, a further 40% is due to non-Bayesian statistical discrimination, and the remaining 20% is unexplained or potentially taste-based. This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis. Funding: F. Mengel thanks the European Research Council for financial support [Starting Grant 805017]. P. Campos-Mercade acknowledges funding from the Danish National Research Foundation [Grant DNRF134 (CEBI)]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4824. [ABSTRACT FROM AUTHOR]

We exploit a unique data set from the Israeli Professional Football Leagues that provides high-frequency direct measures of players' effort to estimate effort peer effects in a high-skill collaborative team task. Using two complementary identification strategies, we find robust evidence of substantial positive peer effects. Our findings highlight that effort spillovers play an important role in team production and that even a change in just one worker's effort can substantially influence team effort and thus performance. Moreover, we present suggestive evidence that behavioral considerations are a relevant mechanism for creating peer effects even in highly skilled teams of workers. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4811. [ABSTRACT FROM AUTHOR]

This paper analyzes a dynamic relational contract for employees with reciprocal preferences. A model of a long-term employment relationship is developed that implies that generous upfront wages activate the norm of reciprocity and then are more important when an employee is close to retirement. In earlier stages, direct incentives promising a bonus in exchange for effort are more effective. Hence, direct and reciprocity-based incentives reinforce each other and should be used in combination. Moreover, a more competitive labor market may increase the utilization of reciprocity-based incentives. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Funding: This work was supported by Hardegg'sche Stiftung, the Deutsche Forschungsgemeinschaft [CRC TRR 190], and the Austrian Science Fund [Grant P 33307-G]. Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2022.4657. [ABSTRACT FROM AUTHOR]

In environments with impending regime shifts, previous research studies probability judgments of decision makers (DMs) regarding a regime shift and finds evidence for the system neglect hypothesis: In unstable environments with precise signals, DMs exhibit relatively more underreaction in their probability judgments, and in stable environments with noisy signals, they exhibit relatively more overreaction. In the present paper we focus on pricing decisions and study how risk attitudes, as well as probability judgments regarding a regime shift, affect these decisions. We develop a model that integrates prospect theory with the system neglect hypothesis and compare changes in empirical pricing decisions to those of a Bayesian risk-neutral agent. We find a pattern of under- and overreaction in pricing decisions that mimics the system neglect hypothesis in probability judgments only when the DM's prior probability of a regime shift is low; the system neglect pattern vanishes when the DM's prior probability of a regime shift is high. We argue that in the case of low priors, changes in risk attitude in reaction to signals indicative of a regime shift amplify system neglect in probability judgments. In the case of high priors, on the other hand, changes in risk attitude dampen the effect of system neglect. We test our model predictions in experimental insurance markets and offer various extensions to check for the robustness of our findings. Finally, we discuss implications for managerial practice in organizational contexts that are characterized by continuous change. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Funding: This work was funded by Fundação para a Ciência e a Tecnologia (UIDB/00124/2020, UIDP/00124/2020 and Social Sciences DataLab - PINFRA/22209/2016), POR Lisboa and POR Norte (Social Sciences DataLab, PINFRA/22209/2016). Furthermore, it was supported by the Ministerio de Ciencia e Innovación España [10.13039/501100011033, Grants ECO2014-52925-P, PID2019-111512RB-I00-HMDM, and HDL-HS-280218]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4661. [ABSTRACT FROM AUTHOR]

Decision making on the job is becoming increasingly important in the labor market, in which there is an unprecedented rise in demand for workers with problem-solving and critical-thinking skills. This paper investigates how indoor air quality affects the quality of strategic decision making based on data from official chess tournaments. Our main analysis relies on a unique data set linking the readings of air-quality monitors inside the tournament room to the quality of 30,000 moves, each of them objectively evaluated by a powerful artificial intelligence–based chess engine. The results show that poor indoor air quality hampers players' decision making. We find that an increase in the indoor concentration of fine particulate matter (PM 2.5 ) by 10 μ g / m 3 (corresponding to 75% of a standard deviation in our sample) increases a player's probability of making an erroneous move by 26.3%. The decomposition of the effects by different stages of the game shows that time pressure amplifies the damage of poor air quality to the players' decisions. We implement a number of robustness checks and conduct a replication exercise with analogous move-quality data from games in the top national league showing the strength of our results. The results highlight the costs of poor air quality for highly skilled professionals faced with strategic decisions under time pressure. This paper was accepted by Prof. Yan Chen, behavioral economics and decision analysis. Funding: The authors gratefully acknowledge the financial support from the Graduate School of Business and Economics at Maastricht University as well as the Institute of Labor Economics Bonn. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4643. [ABSTRACT FROM AUTHOR]

Do people have well-defined social preferences waiting to be applied when making decisions? Or do they have to construct social decisions on the spot? If the latter, how are those decisions influenced by the way in which information is acquired and evaluated? These temporal dynamics are fundamental to understanding how people trade off selfishness and prosociality in organizations and societies. Here, we investigate how the temporal dynamics of the choice process shape social decisions in three studies using response times and mouse tracking. In the first study, participants made binary decisions in mini-dictator games with and without time constraints. Using mouse trajectories and a starting time drift diffusion model, we find that, regardless of time constraints, selfish participants were delayed in processing others' payoffs, whereas the opposite was true for prosocial participants. The independent mouse trajectory and computational modeling analyses identified consistent measures of the delay between considering one's own and others' payoffs (self-onset delay, SOD). This measure correlated with individual differences in prosociality and predicted heterogeneous effects of time constraints on preferences. We confirmed these results in two additional studies, one a purely behavioral study in which participants made decisions by pressing computer keys, and the other a replication of the mouse-tracking study. Together, these results indicate that people preferentially process either self or others' payoffs early in the choice process. The intrachoice dynamics are crucial in shaping social preferences and might be manipulated via nudge policies (e.g., manipulating the display order or saliency of self and others' outcomes) for behavior in managerial or other contexts. This paper was accepted by Yan Chen, behavioral economics and decisions analysis. Funding: F. Chen acknowledges support from the National Natural Science Foundation of China [Grants 71803174 and 72173113]. Z. Zhu acknowledges support from the Ministry of Science and Technology [Grant STI 2030-Major Projects 2021ZD0200409]. Q. Shen acknowledges support from the National Natural Science Foundation of China [Grants 71971199 and 71942004]. I. Krajbich acknowledges support from the U.S. National Science Foundation [Grant 2148982]. This work was also supported by the James McKeen Cattell Fund. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4732. [ABSTRACT FROM AUTHOR]

Endogenous response time data are increasingly becoming available to applied researchers of economic choices. However, the usefulness of such data for preference estimation is unclear. Here, we adapt a sequential sampling model—previously validated to jointly explain subjects' choices and response times in laboratory experiments—to model users' responses to video advertisements on mobile devices in a field setting. Our estimates of utility correlate positively with out-of-sample measures of ad engagement, thus providing external validation of the value of incorporating endogenous response time information into a choice model. We then use the model estimates to assess the effectiveness of manipulating attention toward an advertisement at the beginning of a decision. Counterfactual simulations predict that making an ad "nonskippable" (requiring users to watch some portion of the ad)—as is the practice of some online platforms (e.g., YouTube)—generates only modest increases in click-through rates and revenue. This paper was accepted by David Simchi-Levi, behavioral economics and decision analysis. Funding: R. Webb work was supported by Social Sciences and Humanities Research Council [Grant 430-2019-00246]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4738. [ABSTRACT FROM AUTHOR]

In a large-scale natural field experiment, we partnered with a microlending company in Kyrgyzstan that asked over 180,000 of its clients for donations to social projects as a form of corporate philanthropy. In a 2 × 2 design, we explored two main (preregistered) hypotheses about giving by the poor. First, based on a conjecture that the poor are more price sensitive than the rich and in contrast to previous studies, we hypothesize that matching incentives induce crowding in of out-of-pocket donations. Second, we hypothesize that our population cares about their proximity to the charitable project. We find evidence in favor of the former hypothesis but not the latter. Previous studies of charitable giving focus on middle- or high-income earners in Western countries, neglecting the poor, although the lowest-income groups are often shown to contribute substantial shares of their income to charitable causes. Our results challenge the evidence in the extant literature but are in line with our theoretical model. The implications for fundraising managers are that the optimal design of fundraising campaigns crucially depends on the targeted groups and that donation matching is successful in stimulating participation in poorer populations. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Financial support was from the Deutsche Forschungsgemeinschaft [Grant 280092119] and the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [Grant 100018_189152]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4702. [ABSTRACT FROM AUTHOR]

Social reference points have been identified to be important determinants of individuals' welfare. We investigate the consequences of social reference points for risk taking in a laboratory experiment. In the main treatments, risk-taking subjects observe the predetermined earnings of peer subjects when making a risky choice. We exogenously manipulate peers' earnings and find a significant treatment effect: decision makers make less risk-averse choices in the case of larger peers' earnings. The treatment effect is consistent with an application of prospect theory to social reference points and cannot be explained by reference points based on counterfactual information, anchoring, and experimenter demand effects. In additional analyses, we show that diminishing sensitivity seems to play an important role in subjects' risky choices. We explore also whether inequity aversion and expectations-based reference points can account for our findings and conclude that they do not provide plausible alternative explanations for them. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This research was financially supported by the Bonn Graduate School of Economics and the Center for Economics and Neuroscience in Bonn. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4698. [ABSTRACT FROM AUTHOR]

Reputation feedback systems assign feedback scores to traders with the aim of separating them according to reliability. There is now a substantial amount of literature on what these mechanisms do well and not so well. Conspicuously absent is a theoretical framework to guide thinking on improving these systems. Here we construct a prototype market, stylized and conceptual in nature, but also suitable for laboratory testing. We use the prototype to examine competing approaches to eliciting feedback from traders. Using entropy to benchmark informativeness, we show that the informativeness of feedback elicitation approaches depends on the ability to solve a coordination problem such that traders use a common mapping to turn experiences into ratings. In theory, different approaches can be about equally informative although the map to coordinate on is more ambiguous in some cases. We then test the approaches in the laboratory. The resulting data find that the most informative feedback is associated with the elicitation methods where the solution to the coordination problem is least ambiguous. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Financial support from the Deutsche Forschungsgemeinschaft (German Research Foundation) through the Research Unit "Design & Behavior" [FOR 1371] is gratefully acknowledged. The authors thank the Dutch national e-infrastructure for support of the SURF Cooperative. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4694. [ABSTRACT FROM AUTHOR]

This study tests the hypothesis that competitive strategic interactions foster overconfidence. We experimentally compare a strategic environment in which players have an incentive to overstate their own ability to deter competitors and avoid competition with a nonstrategic environment in which these incentives are removed. Subsequently, we measure the participants' confidence. Overconfidence persists in the former environment but vanishes in the latter. We provide evidence for three mechanisms that contribute to the persistence of overconfidence. First, participants who win uncontested update their confidence as if they had won in an actual competition. Second, by contrast, participants who do not compete do not update their confidence, thus creating an asymmetry in updating. Third, inflated ability messages are "contagious" because they affect positively how their receivers update their confidence. We provide empirical evidence on the role of these mechanisms to explain the Dunning–Kruger effect and gender differences in confidence. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4688. [ABSTRACT FROM AUTHOR]

Trust is an important element of many financial transactions. Yet, the financial industry has been struggling with public mistrust. One explanation for this could be the selection of individuals who wish to work in and get job offers from the financial industry. In this paper, we examine the selection into the financial industry based on social preferences. We identify the social preferences of business and economics students, and, for more than six years, follow up on their early career choices and their job placement after graduation. Students eager to work in the financial industry behave in a substantially less trustworthy manner and show less willingness to cooperate than those with other career plans. The job market does not alleviate this selection. Those subjects who find their first permanent job in finance behave in significantly less trustworthy manner in a trust game than those working in other industries. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Financial support was provided from the Deutsche Forschungsgemeinschaft (German Research Foundation) under Germany's Excellence Strategy [Grant EXC 2126/1–390838866], the University of Cologne [Hans Kelsen Prize], and the Center for Financial Studies. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2022.4562. [ABSTRACT FROM AUTHOR]

Given the ranking of competitors, how should the prize endowment be allocated? This paper introduces and axiomatically studies the prize allocation problem. We focus on consistent prize allocation rules satisfying elementary solidarity and fairness principles. In particular, we derive several families of rules satisfying anonymity, order preservation, and endowment monotonicity, which all fall between the equal division rule and the winner-takes-all rule. Our results may help organizers to select the most suitable prize allocation rule for rank-order competitions. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: A. Y. Kondratev is supported by HSE University [Basic Research Program and "Priority 2030" Program]. [ABSTRACT FROM AUTHOR]

In nearly every betting market, gamblers overvalue the riskiest bets. This "longshot bias" is usually explained by a tendency to overweight low-probability events. We offer a novel explanation: contrast effects enhance the attractiveness of longshots because gambles presented in terms of their payoffs are easier to compare along the payoff dimension than along the probability dimension. Our analysis of historical betting odds suggests that contrasts between gamble payoffs can explain the longshot bias. Laboratory experiments confirm those contrast effects and show that the longshot bias disappears when gamblers consider bets in isolation or when winning probabilities are easier to compare. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: The authors thank the University of Chicago's Center for Decision Research and Richard Thaler for funding. Supplemental Material: The online supplement and data are available at https://doi.org/10.1287/mnsc.2023.4684. [ABSTRACT FROM AUTHOR]

Affirmative action policies are often implemented through reserve systems. In this study, we demonstrate that reserve systems face widespread misunderstanding by the public. This misunderstanding can lead individuals to support policies that ineffectively pursue their interests. To establish these claims, we present 1,013 participants in the Understanding America Study with choices between pairs of reserve systems. Participants are members of the group receiving affirmative action and are financially incentivized to choose the system that maximizes their chance of admission. Using this data, we apply a novel approach to identifying the rate of uptake of different decision rules used by participants. We find that participants rarely use a fully optimal decision rule. In contrast, we find that many choices—40% in our primary estimates—are rationalized by a nearly correct decision rule, with errors driven solely by failing to appreciate the importance of processing order. Failing to account for processing order causes individuals to fail to distinguish between two policies that achieve different degrees of affirmative action: policies that provide nonbinding minimum guarantees of the number of spaces allocated and policies that provide spaces over-and-above what would be allocated absent a reserve. Confusion about the importance of processing order helps to explain otherwise surprising decisions made in field applications of reserve systems. We discuss implications for managers and policy makers who are trying to implement reserve systems and who are accountable to the public. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Funding: The authors thank the National Science Foundation and the Wharton Behavioral Laboratory for financial support. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4669. [ABSTRACT FROM AUTHOR]

We study the joint implementation of reservation and de-reservation policies in India that has been enforcing comprehensive affirmative action since 1950. The landmark judgment of the Supreme Court of India in 2008 mandated that whenever the OBC category (with 27% reservation) has unfilled positions, they must be reverted to general category applicants in admissions to public schools without specifying how to implement it. We disclose the drawbacks of the recently reformed allocation procedure in admissions to technical colleges and offer a solution through "de-reservation via choice rules." We propose a novel priority design—Backward Transfers (BT) choice rule—for institutions and the deferred acceptance mechanism under these choice rules (DA-BT) for centralized clearinghouses. We show that DA-BT corrects the shortcomings of existing mechanisms. By formulating India's legal requirements and policy goals as formal axioms, we show that the DA-BT mechanism is unique for the concurrent implementation of reservation and de-reservation policies. This paper was accepted by Yan Chen, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

Many decision makers are thought to economize on attention by processing information at the simpler level of a category. We directly test whether such category focus reflects an adaptive response to attention constraints, in five preregistered experiments using an information sampling paradigm with mouse tracking. Consistent with rational principles, participants focus more on category-level information when individual differences are small, when the category contains more members, and when time constraints are more severe. Participants are sensitive to the statistical structure of the category even when it must be learned from experience, and they respond to a latent shift in this structure. Beliefs about category members tend to cluster together more when category focus is high—a key element of rational inattention. However, this is counteracted by greater weight placed on salient and idiosyncratic information when the category is large. Our results broadly substantiate influential theories of categorical thinking, giving us a clearer view on the drivers and consequences of inattention. This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis. Funding: This work was supported by the Office of Naval Research (N00014-21-1-2170), the Pershing Square Fund for Research on the Foundations of Human Behavior, and an NWO Vidi grant (VI.Vidi.201.059). Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4803. [ABSTRACT FROM AUTHOR]

A combination of point estimates from multiple judges often provides a more accurate aggregate estimate than a point estimate from a single judge, a phenomenon called "the wisdom of crowds." However, if the judges use shared information when forming their estimates, the simple average will end up overemphasizing this common component at the expense of the judges' private information. A decision maker could in theory obtain a more accurate estimate by appropriately combining all information behind the judges' opinions. Although this information underlies the judges' individual estimates, it is typically unobservable and thus cannot be directly aggregated by a decision maker. In this article, we propose a weighting of judges' individual estimates that appropriately combines their collective information within a single estimation problem. Judges are asked to provide both a point estimate of the quantity of interest and a prediction of the average estimate that will be given by all other judges. Predictions of others are then used as part of a criterion to determine weights that are applied to each judge's estimate to form an aggregate estimate. Our weighting procedure is robust to noise in the judges' responses and can be expressed in closed form. We use both simulation and data from a collection of experimental studies to illustrate that the weighting procedure outperforms existing methods. An R package called metaggR implements our method and is available on the Comprehensive R Archive Network. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: This work was supported by the Indiana University Kelley School of Business and INSEAD. Supplemental Material: The data files and e-companion are available at https://doi.org/10.1287/mnsc.2022.4648. [ABSTRACT FROM AUTHOR]

Achieving success often requires persistent effort. We study the effectiveness of two reward mechanisms, all-or-nothing and piece-rate, to incentivize full completion of repeated tasks over time. Our theoretical analysis shows that exogenously imposing the all-or-nothing mechanism can be ineffective due to the potential discouragement effect. In contrast, empowering individuals to choose between the two reward mechanisms can significantly improve the full completion rate. Data from a series of field experiments and follow-up replications provide robust evidence that the all-or-nothing mechanism is effective only when it is presented as an option. Our results highlight the importance of choice in incentivizing persistent effort. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by Monash University [Grant MUM-BTBL-2016-010], Australia-Malaysia 2021–2022 Research Collaboration Development Scheme (Monash Faculty of Business and Economic), and University of Technology Sydney Business School. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4649. [ABSTRACT FROM AUTHOR]

We experimentally study information transmission by experts motivated by their reputation for being well-informed. In our game of reputational cheap talk, a reporter privately observes information about a state of the world and sends a message to an evaluator; the evaluator uses the message and the realized state of the world to assess the reporter's informativeness. We manipulate the key driver of misreporting incentives: the uncertainty about the phenomenon to forecast. We highlight three findings. First, misreporting information is pervasive even when truthful information transmission can be an equilibrium strategy. Second, consistent with the theory, reporters are more likely to transmit information truthfully when there is more uncertainty on the state. Third, evaluators have difficulty learning reporters' strategies and, contrary to the theory, assessments react more strongly to message accuracy when reporters are more likely to misreport. In a simpler environment with computerized evaluators, reporters learn to best reply to evaluators' behavior and, when the state is highly uncertain and evaluators are credulous, to transmit information truthfully. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Financial support from the H2020 European Research Council [Grant 295835 (EVALIDEA)] is gratefully acknowledged. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4629. [ABSTRACT FROM AUTHOR]

We show that superstitions—beliefs without scientific grounding—impact the investment and risk-taking of Chinese firms. We focus on widely held beliefs in bad luck during one's "zodiac year," which occurs on a 12-year cycle around a person's birth year, to study superstitions and risk taking. We first show a direct correspondence between zodiac year and risk taking via survey data: respondents are two percentage points more likely to favor no-risk investments if queried during their zodiac year. Turning to corporate decision making, we find that return volatility declines in the chairman's zodiac year, suggesting a reduction in risk taking overall. Focusing on specific types of risk taking, investment in R&D and corporate acquisitions both decline during the chairman's zodiac year; returns around acquisition announcements are also lower, suggesting real allocative consequences of zodiac year beliefs. This paper was accepted by Gustavo Manso, finance. Funding: W. Huang thanks the Major Project of National Social Science Foundation of China [Grant 17ZDA090] and the "National Program for Special Support of Eminent Professions" for financial support. Y. Pan thanks the National Natural Science Foundation of China [Grant 71790601] for financial support. Y. Wang thanks the National Natural Science Foundation of China [Grant 72172090] for financial support. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4594. [ABSTRACT FROM AUTHOR]

Decision makers often ask experts to forecast a future state. Experts, however, can be biased. In the economics and psychology literature, one extensively studied behavioral bias is called herding. Under strong levels of herding, disclosure of public information may lower forecasting accuracy. This result, however, is derived only for point forecasts. In this paper, we consider experts' probabilistic forecasts under herding, find a closed-form expression for the first two moments of a unique equilibrium forecast, and show that the experts report too similar locations and inflate the variance of their forecasts because of herding. Furthermore, we show that the negative externality of public information no longer holds. In addition to reacting to new information as expected, probabilistic forecasts contain more information about the experts' full beliefs and interpersonal structure. This facilitates model estimation. To this end, we consider a one-shot setting with one forecast per expert and show that our model is identifiable up to an infinite number of solutions based on point forecasts but up to two solutions based on probabilistic forecasts. We then provide a Bayesian estimation procedure for these two solutions and apply it to economic forecasting data collected by the European Central Bank and the Federal Reserve Bank of Philadelphia. We find that, on average, the experts invest around 19% of their efforts into making similar forecasts. The level of herding shows an increasing trend from 1999 to 2007 but drops sharply during the financial crisis of 2007–2009 and then rises again until 2019. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Supplemental Material: The electronic companion and data are available at https://doi.org/10.1287/mnsc.2022.4487. [ABSTRACT FROM AUTHOR]

We initiate the study of incentive-compatible forecasting competitions in which multiple forecasters make predictions about one or more events and compete for a single prize. We have two objectives: (1) to incentivize forecasters to report truthfully and (2) to award the prize to the most accurate forecaster. Proper scoring rules incentivize truthful reporting if all forecasters are paid according to their scores. However, incentives become distorted if only the best-scoring forecaster wins a prize, since forecasters can often increase their probability of having the highest score by reporting more extreme beliefs. In this paper, we introduce two novel forecasting competition mechanisms. Our first mechanism is incentive compatible and guaranteed to select the most accurate forecaster with probability higher than any other forecaster. Moreover, we show that in the standard single-event, two-forecaster setting and under mild technical conditions, no other incentive-compatible mechanism selects the most accurate forecaster with higher probability. Our second mechanism is incentive compatible when forecasters' beliefs are such that information about one event does not lead to belief updates on other events, and it selects the best forecaster with probability approaching one as the number of events grows. Our notion of incentive compatibility is more general than previous definitions of dominant strategy incentive compatibility in that it allows for reports to be correlated with the event outcomes. Moreover, our mechanisms are easy to implement and can be generalized to the related problems of outputting a ranking over forecasters and hiring a forecaster with high accuracy on future events. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by the European Research Council [Grant ERC StG 307036] and the National Science Foundation [Grant CCF-1445755]. [ABSTRACT FROM AUTHOR]

Decision research often takes the variability of potential outcomes as a measure of risk. It thus characterizes sure things, which, by definition, guarantee a specific outcome, as safe. But is this characterization always empirically valid? We show that, when the prevailing reference point is an uncertain option or position, sure things can be perceived as risky rather than safe. Furthermore, preferences may hinge on such perceptions: when construed as risky, sure things can be less appealing. Our findings suggest a perception-based explanation for why the classic tendency to favor sure things over uncertain options is often attenuated given an uncertain reference point. More broadly, they tap an unresolved debate about the determinants of decisions. Much research focuses on taste-based determinants, such as attitudes toward perceived risks, and thereby underplays the critical role of the underlying perceptions. Appreciating the impact of perceptions on decision making leads to novel prescriptive recommendations. This paper was accepted by David Simchi-Levi, decision analysis. Supplemental Material: Data and the online supplement are available at https://doi.org/10.1287/mnsc.2022.4590. [ABSTRACT FROM AUTHOR]

A novel laboratory experiment is used to show that mismatching between task preferences and task assignment strongly undermines worker performance and leads to free riding in teams. Unlike prior experiments using real effort tasks, task preferences are elicited from all workers. Under team-based remuneration (revenue sharing), free riding is significant, but this effect is largely driven by those working on undesired tasks. Workers' endogenous sorting into tasks improves productivity as it mitigates task mismatching although workers' task selection per se has only small effects on work performance and effort provisions beyond the positive sorting effects. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by Independent Research Fund Denmark [Grant 4182-00163]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4556. [ABSTRACT FROM AUTHOR]

I develop a continuous-time model to examine how the interaction between competition and financial constraints affects firms' research and development (R&D) strategies. The model integrates two key characteristics of R&D investment: accelerability (i.e., higher R&D intensity leads to faster discovery) and scalability (i.e., higher R&D intensity leads to higher project payoff). I find that firms react strategically to their rivals' financial constraints when making investment decisions in a duopoly R&D race. In particular, firms respond positively to the R&D intensity of an unconstrained rival, while they respond in a hump-shaped fashion to the R&D intensity of a constrained rival. As a result, a constrained firm can pre-empt an unconstrained competitor in market equilibrium. Accelerability is necessary for such pre-emption to occur, and scalability generally reduces its likelihood. Comparison with a monopoly benchmark shows that the economic mechanism differs from over-investment induced by financial constraints alone. The model also generates new implications regarding how project characteristics and cash flow risks impact R&D decisions. This paper was accepted by Gustavo Manso, finance. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4503. [ABSTRACT FROM AUTHOR]

We document that women compete worse against men in field tournaments in over 150 countries and across all ages. Our field setting is the game of chess and we benefit from a large and rich data set to investigate the robustness and heterogeneity of our uncovered gender differences in competition. We find a macro gender gap in every country: there are fewer female than male players, especially at the top, and women have lower average rankings. Moreover, comparing millions of individual games, we find a small but robust micro gender gap: women's scores are about 2% lower than expected when playing a man rather than a woman with an identical rating, age and country. Using a simple theoretical model, we show how this small micro gap may affect women's long-run human-capital formation. By reducing effort and increasing the probability of quitting, both effects accumulate to explain a larger share of the macro gap. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Supplemental Material: The e-companion and data are available at https://doi.org/10.1287/mnsc.2022.4541. [ABSTRACT FROM AUTHOR]

We experimentally study how presentation formats for return distributions affect investors' diversification choices. We find that sampling returns alleviates correlation neglect and constitutes an effective way to improve financial decisions. When participants get a description of the probabilities for outcomes of the joint return distribution, we confirm the findings of others that investors neglect the correlation between assets in their diversification choices. However, when participants sample from the joint distribution, they change their allocation between two assets in response to a change in their correlation in the predicted direction. The results are robust across two experiments that have participants with varying experience (students versus private investors). This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: This work was supported by the Academy of Finland [Decision Item 322357] and the Deutsche Forschungsgemeinschaft [Grant We993/15-1]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4535. [ABSTRACT FROM AUTHOR]

In a finitely repeated game with asymmetric information, we experimentally study how individuals adapt the nature of their lies when settings allow for reputation building. Although some lies can be detected ex post by the uninformed party, others remain deniable. We find that traditional market mechanisms, such as reputation, generate strong changes in the way people lie and lead to strategies in which individuals can maintain plausible deniability; people simply hide their lies better by substituting deniable lies for detectable lies. Our results highlight the limitations of reputation to root out fraud when a deniable lie strategy is available. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Financial support from the Agence Nationale de la Recherche [Grant ANR-14-CE28-0010-01] and from IDEXLYON at Universite de Lyon (project INDEPTH) within the Programme Investissements d'Avenir of the Agence Nationale de la Recherche [Grant ANR-16-IDEX-0005] is acknowledged. This research also benefited from the support of the Laboratory of Excellence CORTEX of the Agence Nationale de la Recherche [Grant ANR-11-LABX-0042] of Universite de Lyon within the program Investissements Avenir operated by the Agence Nationale de la Recherche [Grant ANR-11-IDEX-007]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4526. [ABSTRACT FROM AUTHOR]

This paper studies how the presence of peers and different peer assignment rules—self-selection versus random assignment—affect individual performance. Using a framed field experiment, we find that the presence of a randomly assigned peer improves performance by 28% of a standard deviation (SD), whereas self-selecting peers induces an additional 15%–18% SD improvement in performance. Our results document peer effects in multiple characteristics and show that self-selection changes these characteristics. However, a decomposition reveals that variations in the peer composition contribute only little to the performance differences across peer assignment rules. Rather, we find that self-selection has a direct effect on performance. This paper was accepted by Yan Chen, decision analysis. Funding: Funding by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through CRC TR 224 (projects A01 and A02) is gratefully acknowledged. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2021.4267. [ABSTRACT FROM AUTHOR]

A key feature of online gaming, which serves as an important measure of consumer engagement with a game, is level progression, wherein players make play-or-quit decisions at each level of the game. Understanding users' level-progression behavior is, therefore, fundamental to game designers. In this paper, we propose a dynamic model of consumer level-progression decisions to shed light on the underlying motivational drivers. We cast the individual play-or-quit decisions in a dynamic framework with forward-looking players and consumer learning about the evolution patterns of their operation efficiencies (defined as the average score earned per operation for passing a level). We develop a boundedly rational approach to model how individuals form predictions of their own operation efficiency and playing utility. This new approach allows researchers to flexibly capture players' over/unbiased/underestimation tendencies and risk-averse/-neutral/-seeking preferences—two features that are particularly relevant when modeling game-playing behavior. We develop an algorithm for estimating such a dynamic model and apply our model to level-progression data from individual players with one online game. We find that players in the sample tend to overestimate their operation efficiency as their predicted values are significantly higher than the mean estimates inferred from their playing history with their completed levels. Furthermore, players are found to be risk-seeking with a moderate amount of uncertainty. We uncover two segments of players labeled as "experiencers" versus "achievers"—the former tend to derive a higher utility from the playing process, and the latter are more goal-oriented and derive a higher benefit from completing the entire game. Two counterfactual simulations demonstrate that the proposed model can help adjust the uncertainty level and configure a more effective level-progression point schedule to better engage players and improve the game developer's revenue. This paper was accepted by David Simchi-Levi, marketing. [ABSTRACT FROM AUTHOR]

This paper presents the results of two natural field experiments at a dental clinic. Guided by a simple theoretical model, we exogenously vary deadlines and associated rewards for arranging checkup appointments. Our data show strong and systematic effects of deadlines on patients' behavior. Imposing deadlines induces patients to act earlier and at a persistently higher frequency than without a deadline. We further document that individuals systematically respond to deadlines even if these are not tied to explicit rewards. Several of our findings suggest that individuals' responses to deadlines are shaped by limitations in memory and attention. Our results illustrate that deadlines can be a powerful management tool to encourage timely task completion and to increase the cost effectiveness of performance-contingent rewards. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

Subjects observe a private signal and make an initial guess; they then observe their neighbors' guesses, update their own guess, and so forth. We study learning dynamics in three large-scale networks capturing features of real-world social networks: Erdös–Rényi, Stochastic Block (reflecting network homophily), and Royal Family (that accommodates both highly connected celebrities and local interactions). We find that the Royal Family network is more likely to sustain incorrect consensus and that the Stochastic Block network is more likely to persist with diverse beliefs. These patterns are consistent with the predictions of DeGroot updating. It lends support to the notion that the use of simple heuristics in information aggregation is prevalent in large and complex networks. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: The authors thank the Keynes Fund (University of Cambridge), the Creative-Pioneering Researchers Program (Seoul National University), and C-BID (NYUAD) for financial support. Supplemental Material: The data files and e-companion are available at https://doi.org/10.1287/mnsc.2023.4680. [ABSTRACT FROM AUTHOR]

Fear of public speaking is very common, but we know little about its implications for individuals and organizations. We establish public speaking aversion as an economically relevant preference using three steps. First, we use laboratory and classroom experiments to show that preferences for speaking in public vary strongly across individuals with many participants willing to give up significant amounts of money to avoid giving a short presentation in front of an audience. Second, we introduce two self-reported items to elicit preferences for speaking in public through surveys. We show that these items are strongly related to choices in the incentivized laboratory experiment and that public speaking aversion is distinct from established traits and preferences, including extraversion. Third, we elicit these items in a survey of business and economics students and show that public speaking aversion predicts career expectations. Public speaking–averse individuals avoid careers in management consulting and are more attracted to data analyst and back office careers. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Funding: This project has received funding from the European Research Council under the European Union's Horizon 2020 research and innovation program [Grant 850590]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4500. [ABSTRACT FROM AUTHOR]

Despite the truthful dominant strategy, participants in strategy-proof mechanisms submit manipulated preferences. In our model, participants dislike rejections and enjoy the confirmation from getting what they declare desirable. Formally, the payoff from a match decreases in its position in the submitted ranking such that a strategic trade-off between preference intensity and match probability arises. This trade-off can trigger the commonly observed self-selection strategies. We show that misrepresentations can persist for arbitrarily small report-dependent components. However, honesty is guaranteed to be optimal if and only if there is no conflict between the quality and feasibility of a match. We substantiate the theory with already existing evidence and provide novel testable predictions. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by UniCredit and Universities Foundation [Modigliani Research Grant 2020/2021] and Deutsche Forschungsgemeinschaft [Grant 280092119]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4504. [ABSTRACT FROM AUTHOR]

Effective approaches to forecast model selection are crucial to improve forecast accuracy and to facilitate the use of forecasts for decision-making processes. Information criteria or cross-validation are common approaches of forecast model selection. Both methods compare forecasts with the respective actual realizations. However, no existing selection method assesses out-of-sample forecasts before the actual values become available—a technique used in human judgment in this context. Research in judgmental model selection emphasizes that human judgment can be superior to statistical selection procedures in evaluating the quality of forecasting models. We, therefore, propose a new way of statistical model selection based on these insights from human judgment. Our approach relies on an asynchronous comparison of forecasts and actual values, allowing for an ex ante evaluation of forecasts via representativeness. We test this criterion on numerous time series. Results from our analyses provide evidence that forecast performance can be improved when models are selected based on their representativeness. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2022.4485. [ABSTRACT FROM AUTHOR]

In this research we reexamine and update prior research on the association between decision conflict and choice deferral. Decision conflict has featured prominently in psychology literature, going back to the seminal work of Lewin (1933), Miller (1944), and Janis and Mann (1977). Building on this earlier work and the assumption of conflict as an inhibitor of choice, Tversky and Shafir (1992; see also Dhar 1997) argued that the tendency to defer a decision can increase when decision makers experience conflict because of the need to make trade-offs between options in a set. Tversky and Shafir (1992) showed that decision makers may defer choice more when faced with two options presenting trade-offs compared with when they are offered either a single option (see also Dhar 1997) or two options where one alternative dominates the other. Relatedly, Luce (1998) showed that decision makers may be more likely to defer choice when faced with multiple options presenting relatively difficult (versus easy) trade-offs. We reexamine published data and report the results of 40 well-powered direct and conceptual replications of these effects (total n = 26,703) that cast doubt on the replicability of prior research. Our data suggest that additional research is needed in order to reveal a robust association between experimental manipulations of decision conflict and choice deferral. We conclude our investigation by delineating a set of directions for future research on this topic. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Supplemental Material: The data and e-companion are available at https://doi.org/10.1287/mnsc.2022.4484. [ABSTRACT FROM AUTHOR]

Many important managerial outcomes hinge on the co-occurrence of multiple uncertain events, a situation termed conjunctive risk. Whereas past literature has addressed the psychology of choosing to enter situations with conjunctive risk, this article elucidates a novel way in which the psychology of managing conjunctive risk is importantly distinct. We examine a case in which there are two independent events, one is currently less likely than the other, both are required for overall success, and the decision maker must evaluate opportunities to increase the chance of the less-likely or more-likely requirement. We introduce the hypothesis of a worst-first heuristic. Decision makers intuitively evaluate improvements in conjunctive risk according to their impact on the biggest barrier to success, the least likely of the required events. We find evidence for such a worst-first heuristic across nine experiments (n = 3,653, including samples from the United States and United Kingdom in Studies 1–5 and Studies S1–S3 in the online supplement, as well as a sample of managers in Study 6). Participants invest more to improve chances of less-likely requirements than more-likely requirements, even when the latter improvements have at least as much impact on the aggregate chance of success. Moreover, we find that decision makers exhibit this behavior particularly when managing conjunctive risk, as doing so makes them attend to which threat is the worst. Conversely, they do not appear to exhibit the behavior when making formally equivalent decisions about choosing between conjunctive risks. This bias toward underinvesting in stronger-links holds important implications for decision making in contexts subject to conjunctive risk—both managerial and societal. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Supplemental Material: Data and the e-companion are available at https://doi.org/10.1287/mnsc.2022.4411. [ABSTRACT FROM AUTHOR]

In this article, the author discusses various topics related to publication of the journal. Topics include changes in research areas of management science such as analytics; criteria for submission of research papers to the journal, such as research relevant to the management science community; and different departments related to selection of papers, like departments of Behavioral Economics, and Judgment and Decision Making.

This paper introduces the index τ = ln β / ln δ as a measure of time inconsistency and vulnerability to self-control problems in the quasi-hyperbolic, beta-delta (β , δ) discounting model. We provide a preference foundation for τ and, consequently, a revealed preference definition of failed self-control. The τ index is independent of utility and has an intuitive interpretation as the maximum number of future selves who can disagree with the current self with respect to uniform deviations from an intertemporal plan. The index is also computable for continuous discount functions after an appropriate mapping of functions onto the (β , δ) family. The τ index thus provides a common yardstick for comparing temporal inconsistency across different functional forms. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

Practitioners and academics alike have argued that a firm's interest in its short-term capital market valuation (short-termism) is harmful to the firm's long-term profit. Their argument is intuitive—when a firm exhibits short-termism, its decision making will cater to the short term at the expense of the long term. Some practitioners claim that the adverse effects of increased short-termism become particularly acute in competitive markets. However, there is little academic research that examines the compound effect of short-termism and competition on a firm's operational choices and long-term profit. In this paper, we provide a rigorous analytical model to examine how short-termism and competition can interact to induce a firm to distort its capacity investment and affect its long-term profit. We model a firm that has private information about its market demand, which can be either high or low and is captured by the firm's type. Signaling this private information can influence both the investor's valuation and the competitor's entry decision. We find that operational distortion can emerge not only when short-termism is large, but also when it is small. In fact, when short-termism is sufficiently small, both firm types will distort their operational decision by underinvesting in a pooling outcome. We show, however, that the impact of short-termism on a firm's long-term profit is not monotonically negative, and a certain level of short-termism can be beneficial to a firm's long-term profit. The positive impact of incremental short-termism is robust to alternative modeling assumptions, including the form of competition and the investor's risk profile. This paper was accepted by Victor Martínez-de-Albéniz, operations management. [ABSTRACT FROM AUTHOR]

There is an ongoing debate regarding the degree to which a forecaster's ability to draw correct inferences from market signals is real or illusory. This paper attempts to shed light on the debate by examining how personal characteristics do or do not affect forecaster success. Specifically, we investigate the role of fluid intelligence, manipulativeness, and theory of mind on forecast accuracy in experimental asset markets. We find that intelligence improves forecaster performance when market mispricing is low, manipulativeness improves forecaster performance when mispricing is high, and the degree to which theory of mind skills matter depends on both the level of mispricing and how information is displayed. All three of these results are consistent with hypotheses derived from the previous literature. Additionally, we observe that male forecasters outperform female forecasters after controlling for intelligence, manipulativeness, and theory of mind skills as well as risk aversion. Interestingly, we do not find any evidence that forecaster performance improves with experience across markets or within markets. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

Ignorance enables individuals to act immorally. This is well known in policy circles, in which there is keen interest in lowering moral ignorance. In this paper, we study how the demand for moral ignorance responds to monetary incentives and how the demand curve for ignorance reacts to social norm messages. We propose a simple behavioral model in which individuals suffer moral costs when behaving selfishly in the face of moral information. In several experiments, we find that moral ignorance decreases by more than 30 percentage points with small monetary incentives, but we find no significant change with social norm messages, and we document strong persistence of ignorance across moral contexts. Our findings indicate that rather simple messaging interventions may have limited effects on ignorance. In contrast, changes in incentives could be highly effective. This paper was accepted by Yan Chen, behavioral economics and decision analysis. [ABSTRACT FROM AUTHOR]

This paper reports two experiments in which attitudes toward temporal risk resolution is elicited from choices between two-outcome lotteries that pay out at some future fixed date and can be resolved either now or later. We show that matching probabilities provides a simple method to measure attitudes toward temporal resolution—via the utility scale—under the recursive expected utility of Kreps and Porteus. We also analyze our data using a general recursive model that can reveal attitudes toward temporal risk resolution through the utility scale and/or the probability weighting scale. In terms of goodness of fit, as well as of prediction accuracy, our results point to a better performance of the probability weighting approach. More specifically, we show that individuals become less sensitive and more pessimistic with respect to winning probabilities when lotteries are resolved later rather than now. This paper was accepted by George Wu, decision analysis. [ABSTRACT FROM AUTHOR]