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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 discusses the selection and design of heuristic procedures for solving one-dimensional roll trim problems. These are well-defined combinatorial problems which are too large to optimize. Five different roll trim problems from the paper and film industries are described along with the heuristic procedures that have been used successfully to improve the quality of the solutions generated. The paper concludes with some general guidelines for developing "industrial-grade" heuristic problem solving procedures. [ABSTRACT FROM AUTHOR]

The article focuses on the editorial objectives of the journal. The Accounting Department publishes research on managerial decisions and accounting. The Decision Analysis Department publishes articles on scientific knowledge and decision making. The Finance Department publishes information pertaining to decision makers in management. The Business Strategy Department focuses on locating periodicals that publish research related to the field of management science. The Marketing Department strives to publish articles that pertain to various managerial decisions.

It is well documented that people have misperceptions about energy costs. However, there is mixed empirical evidence about the effectiveness of information provision and its persistence over time. Understanding the interplay between information regarding the private and social benefits of low-carbon technologies and identifying mechanisms through which information treatments affect people's long-term behaviors can help reconcile the mixed findings in the literature. In this paper, we measured the long-term effects of information provision through online experiments involving more than 3,000 households in China. We provided people with information on low-carbon light bulbs' monetary and climate benefits and observed their purchasing decisions over 10 months. We find that information on private or social benefits leads to a temporary effect on most households and a persistent one on the uninformed. This evidence suggests that information provision works through two different mechanisms: increasing saliency and filling the information gap. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Y. Gao received financial support from the National Natural Science Foundation of China [Grant 71903006]. M. Tavoni received financial support from the FP7 Ideas: European Research Council [Grant ERC-336155–COBHAM]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4910. [ABSTRACT FROM AUTHOR]

This study presents unique empirical evidence on the importance of moral support for performance. We take advantage of an unusual change in Argentinean football legislation. In August 2013, as a matter of national security, the Argentinean government forced all teams in the first division to play their games with only home team supporters. Supporters of visiting teams were not allowed to be in stadiums during league games. We estimate the effect of this exogenous variation of supporters on team performance and find that visiting teams are on average about 20% more likely to lose without the presence of their supporters. As a counterfactual experiment, we run the analysis using contemporaneous cup games, where the visiting team supporters were allowed to attend, and find no effect of the ban on those games. Moreover, the ban does not seem to bias the decisions of referees, the lineups, or the market value of the teams, suggesting that the effect on team performance is due to the loss of moral support rather than other factors. Finally, we find that moral support is more relevant when there is equal power between the two teams, suggesting that moral support compensates the power of monetary resources. This paper provides a proof of concept of moral support as an important nonmonetary resource, even in settings with high monetary incentives. 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.2021.02906. [ABSTRACT FROM AUTHOR]

Decisions with risky consequences at multiple points in time are driven not only by risk attitudes and time preferences but also by attitudes toward intertemporal correlation (i.e., the correlation between outcomes at different points in time). This paper proposes a model-free method to measure degrees of intertemporal correlation aversion. We disentangle attitudes toward positive and negative intertemporal correlation, which can differ if expected intertemporal utility is violated. In an experiment, subjects on average exhibited correlation aversion both for lotteries with positive correlation and for lotteries with negative correlation. That is, they disliked positive correlations and liked negative correlations. At the individual level, we found heterogeneity and remarkably, many subjects being insensitive to intertemporal correlations. Moreover, for most subjects, expected intertemporal utility was violated because attitudes toward positive and negative correlation differed. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis. Funding: Erasmus Research Institute of Management provided financial support. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4863. [ABSTRACT FROM AUTHOR]

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 article discusses editorial policy for management science research papers submitted to the journal, citing the aim of improving the understanding of how decisions are and should be made, and mentions research topics like individual and group decisions, and negotiations.

The paper by Huber [6] stimulates further comment. While his conclusions that cognitive styles research has not served and will not serve as a satisfactory basis for operational DSS design guidelines appear justified, some additional points need to be made. This paper looks at several of Huber's arguments more closely and suggests a potentially valuable role for cognitive style awareness in the DSS development process. [ABSTRACT FROM AUTHOR]

The normative solution concepts of game theory try to provide a clear mathematical characterization of what it means to act rationally in a game where all players expect each other to act rationally. Kadane and Larkey reject the use of these normative solution concepts. Yet, this amounts to throwing away an important piece of information to the effect that the players are rational and expect each other to be rational. Even in situations where the players do not expect each other to act with complete rationality, normative game theory can help them heuristically to formulate reasonable expectations about the other players' behavior. [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]

This paper addresses primarily two questions. First, when (and why) should a company's strategy be developed by its CEO versus by some outside analyst or other insider? Second, how does strategy interact with vision (in the sense of a strong belief about the right course of action)? The paper studies these questions using a functional definition of strategy as "the smallest set of choices to optimally guide other choices." Among other things, the paper shows that strategy formulation by the CEO leads to both better strategy and better execution, and that a strategist's vision may improve execution. In the process, the paper also identifies criteria that make a decision strategic and derives explanations why strategies often reflect the background of the strategist. This paper was accepted by Bruno Cassiman, business strategy. [ABSTRACT FROM AUTHOR]

Recent models assume that the anticipation of future consumption can have direct utility consequences. This gives rise to preferences over the timing and structure of information. Using a novel and purposefully simple setup, we study the determinants of preferences for sooner versus later information. Our main results are as follows. We find that the majority of subjects prefer receiving information sooner. This preference, however, is not uniform but depends on the context. When the environment allows subjects to not focus attention on (negative) consumption events, later information becomes more attractive. Finally, variations in prior beliefs do not seem to have strong effects on information preferences. This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis. Funding: This work was funded by the Deutsche Forschungsgemeinschaft [Germany's Excellence Strategy EXC 2126/1 Grant 390838866 and Grant CRC TR 224 Project A01]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.4975 [ABSTRACT FROM AUTHOR]

The growing prevalence of stock market chat rooms and social media suggests that communication between traders may affect market outcomes. Using data from a series of laboratory experiments, we study the causal effect of trader communication on market efficiency. We show that communication allows markets to convey private information more effectively. This effect is robust to a wide range of information settings. The presence of insiders limits the impact, whereas posted reputation scores in the communication platform magnify it. These findings illustrate the need to consider social interactions when designing market institutions to leverage the social motives that foster information aggregation. This paper was accepted by Axel Ockenfels, behavioral economics & decision analysis. Supplemental Material: The e-companion and data are available at https://doi.org/10.1287/mnsc.2023.4967. [ABSTRACT FROM AUTHOR]

We draw a surprising and direct mathematical equivalence between the class of fair division mechanisms, designed to allocate divisible goods without money, and the class of weakly budget-balanced wagering mechanisms, designed to elicit probabilities. Although this correspondence between fair division and wagering has applications in both settings, we focus on its implications for the design of incentive-compatible fair division mechanisms. In particular, we show that applying the correspondence to competitive scoring rules, a prominent class of wagering mechanisms based on proper scoring rules, yields the first incentive-compatible fair division mechanism that is both fair (proportional and envy-free) and responsive to agent preferences. Moreover, for two agents, we show that competitive scoring rules characterize the whole class of nonwasteful and incentive-compatible fair division mechanisms, subject to mild technical conditions. As one of several consequences, this allows us to resolve an open question about the best possible approximation to optimal utilitarian welfare that can be achieved by any incentive-compatible mechanism. Finally, because the equivalence greatly expands the set of known incentive-compatible fair division mechanisms, we conclude with an evaluation of this entire set, comparing the mechanisms' axiomatic properties and examining their welfare performance in simulation. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2022.02615. [ABSTRACT FROM AUTHOR]

Women are underrepresented in business, academic, and political decision-making bodies across the world. To investigate the causal effect of gender representation on multilateral negotiations, we experimentally manipulate the composition of triads in a majoritarian, divide-the-dollar game. We document a robust gender gap in earnings driven largely by the exclusion of women from alliances rather than differential shares within alliances. Experiments with different subject pools show that distinct bargaining dynamics can underlie the same inequitable outcomes; gender-biased outcomes can be caused by outright discrimination, but they can also be driven by more complex dynamics related to differences in bargaining strategies. Although replacing the male with a female majority all but eliminates the gap in one pool, it has minimal effect in the other. These findings show that there is no "one-size-fits-all" solution to the gender gap we uncovered and highlight the importance of studying bargaining dynamics in detail. This paper was accepted by Marie-Claire Villeval, behavioral economics and decision analysis. Funding: A. Baranski recognizes financial support from Tamkeen [under the New York University Abu Dhabi Research Institute; Grant CG005]. J. Tremewan acknowledges funding from the Agence Nationale de la Recherche [Grant ANR-21-CE03-0018 (Project ENDURA)]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01800. [ABSTRACT FROM AUTHOR]

Cognitive differences can catalyze social learning through the process of one-to-one social influence. Yet the learning benefits of exposure to the ideas of cognitively dissimilar others often fail to materialize. Why do cognitive differences produce learning from interpersonal influence in some contexts but not in others? To answer this question, we distinguish between cognition that is expressed—one's public stance on an issue and the way in which supporting arguments are framed—and cognition that is latent—the semantic associations that underpin these expressions. We theorize that, when latent cognition is obscured, one is more likely to be influenced to change one's mind on an issue when exposed to the opposing ideas of cognitively dissimilar, rather than similar, others. When latent cognition is instead observable, a subtle similarity-attraction response tends to counteract the potency of cognitive differences—even when social identity cues and other categorical distinctions are inaccessible. To evaluate these ideas, we introduce a novel experimental paradigm in which participants (a) respond to a polarizing scenario; (b) view an opposing argument by another whose latent cognition is either similar to or different from their own and is either observable or obscured; and (c) have an opportunity to respond again to the scenario. A preregistered study (n = 1,000) finds support for our theory. A supplemental study (n = 200) suggests that the social influence of latent cognitive differences operates through the mechanism of argument novelty. We discuss implications of these findings for research on social influence, collective intelligence, and cognitive diversity in groups. This paper was accepted by David Simchi-Levi, organizations. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.00895. [ABSTRACT FROM AUTHOR]

Heuristics and biases in probabilistic belief updating have typically been examined in simple two-state experimental settings. We argue that the two-state setting has probabilistic properties that do not extend to settings with more states. With three states, we find that individuals apply similar heuristics, such as representativeness and anchoring, when providing posterior probability distributions. However, because of the different normative benchmark, the use of these heuristics results in different biases for point estimates. In particular, we demonstrate that the well-known finding of stronger underinference for larger signal sets does not translate from the two-state to the three-state setting. Our findings caution against an indiscriminate transfer of updating biases observed in two-state settings to a broad set of real-world applications. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: This work was supported by the Fritz Thyssen Stiftung [Grant 20.21.0.023WW]. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2022.00513. [ABSTRACT FROM AUTHOR]

It is intuitive and theoretically sound to combine experts' forecasts based on their proven skills, while accounting for correlation among their forecast submissions. Simpler combination methods, however, which assume independence of forecasts or equal skill, have been found to be empirically robust, in particular, in settings in which there are few historical data available for assessing experts' skill. One explanation for the robust performance by simple methods is that empirical estimation of skill and of correlations introduces error, leading to worse aggregated forecasts than simpler alternatives. We offer a heuristic that accounts for skill and reduces estimation error by utilizing a common correlation factor. Our theoretical results present an optimal form for this common correlation, and we offer Bayesian estimators that can be used in practice. The common correlation heuristic is shown to outperform alternative combination methods on macroeconomic and experimental forecasting where there are limited historical data. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis. Supplemental Material: The data file is available at https://doi.org/10.1287/mnsc.2021.02009. [ABSTRACT FROM AUTHOR]

In many domains, it is necessary to combine opinions or forecasts from multiple individuals. However, the average or modal judgment is often incorrect, shared information across respondents can result in correlated errors, and weighting judgments by confidence does not guarantee accuracy. We develop a Bayesian hierarchical model of crowd wisdom that incorporates predictions about others to address these aggregation challenges. The proposed model can be applied to single questions, and it can also estimate respondent expertise given multiple questions. Unlike existing Bayesian hierarchical models for aggregation, the model does not link the correct answer to consensus or privilege majority opinion. The model extends the "surprisingly popular algorithm" to enable statistical inference and in doing so, overcomes several of its limitations. We assess performance on empirical data and compare the results with other aggregation methods, including leading Bayesian hierarchical models. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: This work was supported in part by the National Science Foundation [Grant MMS 2019982] and All Souls College Oxford [Visiting Fellowships in 2020 and 2022 to D. Prelec]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4955. [ABSTRACT FROM AUTHOR]

An applicant privately observes the value of an idea and files a patent application. After the examination, the patent examiner may not find conclusive evidence of the idea's value. In this case, granting a patent can be the right decision or a mistake. Moreover, it can prompt obfuscation—effort to disrupt communication—by the applicant, reducing allocative efficiency. We show there is more obfuscation when examiners are more lenient, and we provide an empirical exercise supporting this conclusion. We also show that more examination resources do not prevent and may lead to more obfuscation. This result continues to hold when applicants can invest in knowledge to increase their chances of having good ideas. We also show that there is less obfuscation when good ideas are harder to find. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis. Funding: N. Figueroa gratefully acknowledges financial support from ANID PIA/APOYO AFB220003. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.00140. [ABSTRACT FROM AUTHOR]

This article presents an update to an article entitled "Analysis of a Decision Making Investigation," by Kenneth D. MacKenzie, published in the December 1970 issue of the journal "Management Science."

Commentary is presented for the article "Remarks on the Analytic Hierarchy Process," by James S. Dyer, published in the March 1, 1990 issue of "Management Science." The author discusses the merits of various theories of decision making. He notes one in particular, the analytic hierarchy process (AHP), which is a theory of measurement designed to aid decision makers in deconstructing complex problems into multiple levels of subproblems that have a hierarchical structure. According to the author, as a theory, AHP exists independently of utility theory.

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]

About 400 publications, working papers and books are included in this bibliography on Stochastic Dominance. It contains an exhaustive listing of papers that are either basic contributions to this subject or primarily concerned with applications of the Stochastic Dominance concepts. It also contains selective listing of papers from finance, economics, mathematics, mathematical physics, mathematical psychology, operations research and statistics literature to illustrate the wide applicability of Stochastic Dominance concepts. [ABSTRACT FROM AUTHOR]

We introduce a new family of mechanisms for one-sided matching markets, denoted pick-an-object (PAO) mechanisms. When implementing an allocation rule via PAO, agents are asked to pick an object from individualized menus. These choices may be rejected later on, and these agents are presented with new menus. When the procedure ends, agents are assigned the last object they picked. We characterize the allocation rules that can be sequentialized by PAO mechanisms and the ones that can be implemented in a robust truthful equilibrium. We justify the use of PAO as opposed to direct mechanisms by showing that its equilibrium behavior is closely related to the one in obviously strategy-proof (OSP) mechanisms, but implements commonly used rules, such as Gale-Shapley DA and top trading cycles, which are not OSP implementable. We run laboratory experiments comparing truthful behavior when using PAO, OSP, and direct mechanisms to implement different rules. These indicate that agents are more likely to behave in line with the theoretical prediction under PAO and OSP implementations than their direct counterparts. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This research is funded by the National Natural Science Foundation of China [Grant 72033006]. R. Hakimov was supported by the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [Project 100018_189152]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4908. [ABSTRACT FROM AUTHOR]

Labor market outcomes depend, in part, upon an individual's willingness to put him- or herself forward for different opportunities. We use a series of experiments to explore gender differences in willingness to apply for higher-return, more challenging work. We find that, in male-typed domains, qualified women are significantly less likely to apply than similarly well-qualified men. We provide evidence both in a controlled setting and in the field that reducing ambiguity surrounding required qualifications increases the rate at which qualified women apply. The effects are mixed for men. Our results point to a way to increase the pool of qualified women applicants. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was funded by the National Science Foundation [Grant 1713752] and Harvard Business School. Supplemental Material: The e-companion and data are available at https://doi.org/10.1287/mnsc.2023.4907. [ABSTRACT FROM AUTHOR]

People tasked with replacing a departing group member are disproportionately likely to choose a replacement with the same demographic identity, leading to demographic "stickiness" in group composition. We examine this effect in 2,163 U.S. federal judge appointments over 75 years, in the selection of 5,616 S&P 1500 board directors from 2014 to 2019, and in four preregistered experiments (n = 2,900). The patterns we document are generally consistent with both impact aversion (desires to minimize changes to group composition and dynamics) and diversity loss aversion (outsized concerns about losing ground on demographic diversity relative to interests in gaining ground). Ultimately, our results suggest that replacement decisions are influenced by loss-averse preferences regarding the demographic identities of departing group members. The propensity to choose new group members based on whether they demographically resemble their predecessors suggests that once progress toward diversification has occurred, it should be "sticky," so backsliding is less likely than might otherwise be expected. An optimistic outlook is that one-time interventions to change group composition may have a lasting impact, and change agents committed to diversification may have enduring effects on equality beyond their tenure. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Supplemental Material: The data files and online supplement are available at https://doi.org/10.1287/mnsc.2023.4897. [ABSTRACT FROM AUTHOR]

We study belief updating about relative performance in an ego-relevant task. Manipulating the perceived ego relevance of the task, we show that subjects substantially overweight positive information relative to negative information because they derive direct utility from holding positive beliefs. This finding provides a behavioral explanation why and how overconfidence can evolve in the presence of objective information. Moreover, we document that subjects who receive more negative information downplay the ego relevance of the task. These findings suggest that subjects use two alternative strategies to protect their ego when presented with objective information. This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis. Funding: The authors gratefully acknowledge financial support from the ExperimenTUM. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.02537. [ABSTRACT FROM AUTHOR]

Emotional involvement is known to be necessary but not sufficient for good decision making in the face of uncertainty. It has been conjectured that emotional engagement in anticipation of risky outcomes constitutes "good" emotions. We introduce a new methodology to determine whether anticipatory emotional engagement is beneficial in the context of trading in financial markets. We focus on heart rate changes because they occur at a sufficiently high frequency to discern timing relative to events in the marketplace. After conservatively adjusting for multiple hypothesis testing, we find that participants whose heart rate changes anticipate their order submissions at inflated prices earn significantly more, whereas participants whose heart rate responds to their trades earn significantly less. By investigating cointegration between skin conductance response and the dynamics of individual portfolio values, we confirm the importance of emotional involvement in determining who makes or loses money. This paper was accepted by Bruno Biais, finance. Funding: This work was supported by the Australian Research Council [Grants DP180102284 and LE130100112]. The authors also thank the Monash Business School for funds associated with the Monash Business Behavioural Laboratory facility and equipment used in this study. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4883. [ABSTRACT FROM AUTHOR]

We deal with the problem of managing a project or a complex operational process by controlling the execution pace of the activities it comprises. We consider a setting in which these activities are clearly defined, are subject to precedence constraints, and progress randomly. We formulate a discrete-time, infinite-horizon Markov decision process in which the manager reviews progress in each period and decides which activities to expedite to balance expediting costs with delay costs. We derive structural properties for this dynamic project expediting problem. These enable us then to devise exact solution methods that we show to reduce computational burden significantly. We illustrate how our method generalizes and can be used to tackle a wide range of so-called stochastic shortest-path problems that are characterized by an intuitive property and can capture other applications, including medical decision-making and disease-modeling problems. Moreover, we also deal with the state identification issue for our problem, which is a challenging task in and of itself, owing to precedence constraints. We complement our analytical results with numerical experiments, demonstrating that both our solution and state identification methods significantly outperform extant methods for a supply chain example and for various randomly generated instances. This paper was accepted by Chung Piaw Teo, optimization. Funding: R. Mogre acknowledges support from the U.S.-UK Fulbright Commission and the Lloyd's Tercentenary Research Foundation through the Fulbright-Lloyd's Scholar Award, which allowed him to spend an extended period of time at Massachusetts Institute of Technology. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4876. [ABSTRACT FROM AUTHOR]

We explore the nature and robustness of the attraction effect. The attraction effect can be seen as a persistent bias or as the result of heuristics that may not persist upon reflection. We provide robust experimental evidence that the attraction effect first rises and then falls over time when participants are incentivized to make a quick choice they can later revise. Participants in two experiments under continuous time pressure make choices among options with the aim to maximize an objective, measurable value. We find that participants disproportionately favor the asymmetrically dominant option in the first seconds and then revise their choices until the effect disappears or is significantly reduced. The effect survives only in the special and often studied case of indifference among options. We develop a tractable extension to the multiattribute linear ballistic accumulator model to allow for choice revisions. That model explains how choice revisions reduce context effects. We estimate its parameters at the individual level and document differences between fast and slow participants that also play a role in explaining the rise-and-fall pattern in the attraction effect. We extend the analysis to similarity and compromise effects. We find a very small similarity effect, which does not exhibit any dynamics, and a significant reverse compromise effect displaying a rise-and-fall pattern. Our findings, although limited to objective-value tasks, are consistent with context effects being short-term heuristics that can be superseded by more reflective cognitive strategies when decision makers have time and incentive to do so. This paper was accepted by Manel Baucells, behavioral economics and decision analysis. Funding: This work was supported by the Institut National de la Recherche Agronomique [Grant SAE2 Jeune Chercheur 2017]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4874. [ABSTRACT FROM AUTHOR]

Despite mixed evidence for the relationship between demographic diversity and creativity, we propose that observers hold a lay belief that demographic diversity increases creativity and apply this lay belief in judgments about teams and their creative work. Across eight preregistered studies (n = 5,530), we find that observers judge teams diverse in terms of race and gender to be more creative than teams homogeneous in terms of race and gender, including in incentive-compatible predictions made about real teams competing in a creativity challenge. We also find that products attributed to demographically diverse teams are evaluated as more creative compared with identical products attributed to demographically homogenous teams. Mediation analyses provide evidence consistent with the notion that people perceive demographic diversity (i.e., social category differences) to be correlated with cognitive diversity (i.e., difference of perspectives), and this belief contributes to attributions of greater creativity to diverse teams and the ideas they generate. We can also turn off the perceived association between demographic diversity and creativity by directly manipulating people's perceptions of team cognitive diversity. Furthermore, we find evidence of a curvilinear relationship between the proportion of racial minorities or women in a group and judgments of the group's creativity. Together, our results suggest that the popular uptake of the belief that diversity boosts creativity may impact how creativity is identified in organizational contexts. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Funding: This research was supported by funds from the School of Industrial and Labor Relations, Cornell University, and Harvard Business School, Harvard University, including a grant from the Cornell Center for Advanced Human Resource Studies. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4862. [ABSTRACT FROM AUTHOR]

We examine whether the gender gap in competitiveness in stereotypically male tasks persists when the decision to compete is made by someone else. In a within-subject laboratory experiment, decision makers make competition entry decisions for both themselves and a randomly selected other. Although we replicate the standard gender gap in decisions for oneself, we do not find a gender gap when the decision to compete is made by someone else. This is driven by men being significantly more willing to enter themselves than others into competitions. Men's and women's willingness to enter others into competitions is statistically indistinguishable from women's willingness to enter themselves into competitions. Subgroup analyses reveal that competitive preferences are significantly greater for Asian than non-Asian subjects. Our results have implications for the effectiveness of nominations and mentorship to close gender gaps in labor market outcomes that are affected by competitive preferences. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by the Russell Sage Foundation [Grant G-5602]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4861. [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]

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]

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]

Many studies show that time preference data from experiments and surveys are related to field behavior. Time preference measures in these studies typically depend simultaneously on utility curvature, the level of impatience, and the change in the level of impatience. Thus, these studies do not allow one to establish which of these three components drive(s) the field behavior of interest. Of these components, the change in the level of impatience is theoretically thought to be the main driver of time inconsistencies and self-control problems. To test this theoretical presumption, one has to measure the change in the level of impatience independently from utilities and levels of impatience. This paper introduces a measure of the degree of decreasing impatience, the DI-index. It measures the change of impatience independently from the level of impatience and independently from utility. It can also be used to test various discounting models. An experiment finds no correlation between the degree of decreasing impatience and self-reported self-control problems in daily life, suggesting that changing impatience is not the sole driver of self-control problems. Data and the supplementary material are available at https://doi.org/10.1287/mnsc.2017.3015. This paper was accepted by Manel Baucells, decision analysis. [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]