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Although variable pricing enables sports teams to respond to changing demand across games, reports point to somewhat limited implementation. In this paper, we study the implications of a switch to variable pricing on the primary and resale ticket markets using quasi-experimental data from the National Football League. Applying a difference-in-differences technique with propensity score weighting, we first show that the adoption of variable pricing increases primary market ticket sales by 1.59% per game. We then explore the mechanism behind this positive impact. We find that lower prices for the less attractive games are well received by customers, and customers do not have an unfavorable response to higher prices for the more attractive games. Our analysis of the customers' activities in the resale market shows that the minimum resale market prices increase for the more attractive games following the switch to variable pricing. This analysis provides evidence for the increase in the option value created by the resale market and explains the positive response to higher prices for the more attractive games. Finally, we investigate when variable pricing is likely to be the most effective. We find that variable pricing has greater success in team hometowns with lower income levels and higher income diversity, and creating more game tiers in variable pricing leads to higher sales. This paper was accepted by Gabriel Weintraub, revenue management and market analytics. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4588. [ABSTRACT FROM AUTHOR]

Research in psychology shows that consumption goals can help consumers avoid excessive consumption of vice goods and the associated long-term harm. In this paper, we propose a model of self-control with consumption goals and examine how goals moderate the behavior of consumers and the firm's strategy. We find that consumers' personal goals lead to a lower price for a less unhealthy product but a higher price for a more unhealthy product. Furthermore, even though personal goals reduce the sales of a product, the firm can be better off if consumers have goals rather than no goals. The improvement in the firm's profits need not be at consumers' expense. In fact, consumer welfare increases with personal goals. In some contexts, consumption is not driven by personal goals but shaped by social norms, such as the advice of experts or social groups. We find that, unlike personal goals, normative goals make consumers less sensitive to price and do not always improve consumer welfare. Furthermore, normative goals can hurt the firm's profits in contexts in which personal goals could improve profits. Finally, we show that our framework with dynamically inconsistent preferences yields results that are consistent with alternative formulations of consumer self-control problems, such as the dual-self model of Thaler and Shefrin and the costly self-control model of Gul and Pesendorfer. This paper was accepted by Duncan Semester, marketing. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4567. [ABSTRACT FROM AUTHOR]

This paper examines the attention effect in the options market. We show that option investors (especially retail investors) buy more calls and puts on both daily winner and loser stocks, and this buying pressure leads to an overvaluation, as shown in subsequent lower hedged returns. The overvaluation is due to a combination of differences of opinion, risk aversion, and margin requirements. The economic magnitude is large. For instance, a zero-financing portfolio involving options on loser stocks renders an alpha of 2.90% per month. Aside from contributing to the broad literature of investor attention versus asset returns, our study also sheds light on an important yet largely neglected topic: the impact of margins on option trading and pricing. This paper was accepted by Lukas Schmid, finance. Funding: Financial support from King's College London, the University of Toronto, and the Social Sciences and Humanities Research Council of Canada [Grant 435-2018-0514] is gratefully acknowledged. Supplemental Material: Data and the internet appendices are available at https://doi.org/10.1287/mnsc.2022.4557. [ABSTRACT FROM AUTHOR]

One of the most prevalent demand models in the revenue management literature is based on dividing the selling horizon into a number of time periods such that there is at most one customer arrival at each time period. This demand model is equivalent to using a discrete-time approximation to a Poisson process, but it has an important shortcoming. If the mean number of customer arrivals is large, then the coefficient of variation of the number of customer arrivals has to be small. In other words, large demand volume and large demand variability cannot coexist in this demand model. In this paper, we start with a revenue management model that incorporates general mean and variance for the number of customer arrivals. This revenue management model has a random selling horizon length, capturing the distribution of the number of customer arrivals. The question we seek to answer is the form of the fluid approximation that corresponds to this revenue management model. It is tempting to construct the fluid approximation by computing the expected consumption of the resource capacities in the constraints and the total expected revenue in the objective function through the distribution of the number of customer arrivals. We demonstrate that this answer is wrong in the sense that it yields a fluid approximation that is not asymptotically tight as the resource capacities get large. We give an alternative fluid approximation where perhaps surprisingly, the distribution of the number of customer arrivals does not play any role in the constraints. We show that this fluid approximation is asymptotically tight as the resource capacities get large. A numerical study also demonstrates that the policies driven by the latter fluid approximation perform substantially better, so there is practical value in getting the fluid approximation right under high-variance demand. This paper was accepted by Omar Besbes, revenue management and market analytics. Funding: The work of the O. El Housni and H. Topaloglu was supported by a seed grant from Urban Tech research hub at Cornell Tech. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4769. [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]

With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by age-old social norms of not making the first move, are inhibited in their interactions in that they do not initiate contact with men. On the other side, men send an abundance of messages, the majority of which do not convert to matches. A key distinguishing feature of online dating versus its traditional counterpart is the ability to leave a range of digital signals not replicable in the offline world. These digital signals can impact the nature of online dating platform outcomes. In this paper, we study the impact of a feature that reveals "who likes you" (WLY) on engagement, the number of matches, match efficiency, and match sorting in online dating. This feature reveals the identity of the voters who have rated the focal user with a like. To causally identify the effect of this feature, we conduct a large-scale randomized control trial in collaboration with a major North American dating platform. The treatment causes women to be more proactive, sending 7.4% more messages, which is a highly desirable market improvement given that men send double the number of messages compared with women. Further, we find that the women endowed with this feature increase their matches by 14.4%, whereas men increase their matches by 11.5%. Analyzing the moderating impact of desirability—a key aspect of the WLY feature—provides us with nuanced findings. Depending on the levels of each of the two parties' desirability, we see evidence of sorting, encouragement, and discouragement. This paper was accepted by Anandhi Bharadwaj, information systems. Supplemental Material: The Online Appendix is available at https://doi.org/10.1287/mnsc.2022.4576. [ABSTRACT FROM AUTHOR]

The log realized volatility (RV) is often modeled as an autoregressive fractionally integrated moving average model ARFIMA(1 , d , 0). Two conflicting empirical results have been found in the literature. One stream shows that log RV has a long memory (i.e., the fractional parameter d > 0). The other stream suggests that the autoregressive coefficient α is near unity with antipersistent errors (i.e., d < 0). This paper explains how these conflicting empirical findings can coexist in the context of ARFIMA(1 , d , 0) model by examining the finite sample properties of popular estimation methods, including semiparametric methods and parametric maximum likelihood methods. The finite sample results suggest that it is challenging to distinguish Model 1 (ARFIMA(1 , d , 0) with α close to 0 and d close to 0.5) from Model 2 (ARFIMA(1 , d , 0) with α close to unity and d close to –0.5). An intuitive explanation is given. For the 10 financial assets considered, despite that no definitive conclusions can be drawn regarding the data-generating process, we find that the frequency domain maximum likelihood (or Whittle) method can generate the most accurate out-of-sample forecasts. This paper was accepted by Lukas Schmid, finance. Funding: S. Shi acknowledges research support from the Australian Research Council [Project DE190100840]. J. Yu acknowledges financial support from the Ministry of Education–Singapore Tier 2 Academic Research Fund [Project MOE-T2EP402A20-0002] and the Lee Foundation. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4552. [ABSTRACT FROM AUTHOR]

Buying display ad impressions via real-time auctions comes with significant allocation and price uncertainties. We design and analyze a contract that mitigates this uncertainty risk by providing guaranteed allocation and prices while maintaining the efficiency of buying in an auction. We study how risk aversion affects the desire for guarantees and how to price a guaranteed allocation. We propose to augment the traditional auction with a programmatic purchase option (which we call a Market-Maker contract) that removes allocation and price uncertainties. Instead of participating in the auction, advertisers can secure impressions in advance at a fixed premium price offered by the Market-Maker. It is then the responsibility of the Market-Maker to procure these impressions by bidding in the auction. We model buyers as risk-averse agents and analyze the equilibrium outcome when buyers face two purchase options (auction and Market-Maker contract). We derive analytical expressions for the Market-Maker price that reveal insightful relationships with uncertainties in the auction price and buyers' risk levels. We also show the existence of a Market-Maker price that simultaneously improves the seller's revenue and the sum of buyers' utilities. As a building block to our analysis, we establish the truthfulness of the multiunit auction when buyers have nonquasilinear utilities because of risk aversion. Recently, the Google's Display & Video 360 platform started offering a product akin to Market-Maker called "Guaranteed Packages," which was inspired by this paper. This paper was accepted by Gabriel Weintraub, revenue management and market analytics. Funding: The authors thank Google Research for its generous support. [ABSTRACT FROM AUTHOR]

Modern consumers are concerned about not only their material payoff, but also the fairness of the transaction when making purchasing decisions. In this paper, we investigate how consumers' inequity aversion affects a manufacturer who sources inputs from upstream suppliers. We find that, when the manufacturer sources from a single supplier or when consumers observe the manufacturer's cost, inequity aversion hurts both the supplier's and manufacturer's profits. However, when the manufacturer sources from multiple suppliers and consumers do not observe the manufacturer's cost, inequity aversion reduces both the suppliers' and manufacturer's margins, which significantly alleviates the double marginalization problem, increases consumer demand, and improves channel efficiency. As a result, inequity aversion benefits the suppliers, manufacturer, and consumers alike, leading to a "win–win–win" outcome. By comparing cases in which consumers observe and do not observe the manufacturer's cost, we also find that, when faced with inequity-averse consumers, a manufacturer may find it optimal to withhold its cost information to help secure lower procurement costs from upstream suppliers. This paper was accepted by Dmitri Kuksov, marketing. Funding: This work was supported by the Hong Kong Research Grants Council [Grant 21500920]. [ABSTRACT FROM AUTHOR]

This paper studies the role of shared analysts, who cover the target and the acquirer, in mergers and acquisitions outcomes. We find that deals where both firms are connected through shared analysts are less likely to be completed than deals without shared analysts. If completed, however, deals with shared analysts exhibit higher expected synergy gains, acquirer announcement returns, and acquirer post-completion performance. Shared analysts are also more likely to issue estimates about the acquirer in the proximity of the impending deal and their estimates are associated with a decrease in the uncertainty about acquirer's cash flows. Our results highlight how the position of analysts in a deal results in an informational edge that enhances the screening of deals and mitigation of the acquirer's informational disadvantage. Shared analysts who enhance the acquirer's ability to screen out deals also exhibit superior career outcomes post-completion. We find similar results in the pre- and post-Regulation Fair Disclosure period, using brokerage house closures as a quasi-natural experiment and after controlling for analysts' affiliations. This paper was accepted by Tomasz Piskorski, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4468. [ABSTRACT FROM AUTHOR]

Although the literature on network effects has focused on single-network firms, many industries feature multinetwork firms that play more complex dynamic pricing games. In this paper, we estimate the network effect at the smartphone operating system (OS) level and study multi-OS telecommunication carriers' dynamic pricing strategies in an oligopolistic setting, using data on the U.S. smartphone industry. We find a positive OS network effect. Counterfactual analysis indicates that if the carriers were single-OS sellers, they would increase the phone prices of large OSs and lower the prices of small OSs, which reduces the consumer surplus by $6.99 billion. Further analyses show that the multi-OS carriers choose lower prices for large OSs than for small OSs because of their preference for OS concentration. This paper was accepted by Eric Anderson, marketing. Funding: This work was supported by the National Natural Science Foundation of China [Grants 72203217, 71803205, and 72192803] and the fund for building world-class universities (disciplines) of Renmin University of China. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4530. [ABSTRACT FROM AUTHOR]

We consider the problem of a seller of data who sells information to a buyer regarding an unknown (to both parties) state of the world. Traditionally, the literature explores one-round strategies for selling information because of the seller's holdup problem: once a portion of the data set is released, the buyer's estimate improves, and as a result, the value of the remaining data set drops. In this paper, we show that this intuition is true when the buyer's objective is to improve the precision of the estimate. On the other hand, we establish that when the buyer's objective is to improve downstream operational decisions (e.g., better pricing decisions in a market with unknown elasticity) and when the buyer's initial estimate is misspecified, one-round strategies are outperformed by selling strategies that initially provide free samples. In particular, we provide conditions under which such free-sample strategies generate strictly higher revenues than static strategies and illustrate the benefit of providing data samples for free through a series of examples. Furthermore, we characterize the optimal dynamic pricing strategy within the class of strategies that provide samples over time (at a constant rate), charging a flow price until some time when the rest of the data set is released at a lump-sum amount. This paper was accepted by Itai Ashlagi, revenue management and market analytics. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4534. [ABSTRACT FROM AUTHOR]

Drawing on the notion of compensatory behavior, this paper studies how students compensate for learning loss during a pandemic and what role artificial intelligence (AI) plays in this regard. We further probe into a difference in compensatory behavior for learning loss in terms of quantity, pattern, and pace (i.e., tripartite aspect of learning behavior) of AI-powered learning app usage depending on the level of pandemic threat and the proximity of a goal to students. Results show that the pandemic threat affects student learning behavior differently. Immediately following the COVID-19 outbreak, students who live in the epicenter of the outbreak (versus those who do not) use the app less at first, but with time, they use it more (quantity), on a more regular basis (pattern), and rebound to a curriculum path (pace) comparable to students who do not live in the outbreak's epicenter. These findings collectively explain behavior that is consistent with compensation for learning loss. The results also partially corroborate the goal-proximity effect, revealing that proximity to a goal (e.g., the degree to which the national university admission exam is approaching) has a moderating role in explaining the tripartite perspective of student learning behavior. Overall, these findings have important theoretical and practical implications for understanding how innovative education technologies can not only facilitate student learning during adversity, but also support learning recovery after adversity. This paper was accepted by D. J. Wu, information systems. Supplemental Material: Data files available at https://doi.org/10.1287/mnsc.2022.4531. [ABSTRACT FROM AUTHOR]

Motivated by the agricultural industries, this paper studies the economic and environmental implications of biomass commercialization; that is, converting organic waste into a saleable product from the perspective of a processor that uses a commodity input to produce both a commodity output and biomass. We characterize the economic value of biomass commercialization and examine how input and output spot price uncertainties affect this value. Using a model calibration, we find that lower input spot price variability or higher output spot price variability or correlation between the two spot prices increases this value for a typical palm oil mill. To measure the environmental impact, we use total expected carbon emissions resulting from profit-maximizing decisions and characterize the change in total expected emissions after commercialization. Our analysis reveals that, although higher biomass demand or biomass price always increases the value of biomass commercialization, these changes are not necessarily environmentally beneficial as they may increase the emissions associated with biomass commercialization. We also characterize conditions under which biomass commercialization is environmentally beneficial or harmful; that is, it leads to a reduction or an increase in the total expected emissions, respectively. In comparison with the existing understanding which does not take into account optimization of operational decisions, our analysis highlights two types of misconceptions (and characterizes the specific conditions under which they appear): (i) we would mistakenly think that biomass commercialization is environmentally beneficial when it is not, and (ii) we would mistakenly think that biomass commercialization is environmentally harmful when it is not. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4518. [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]

We attempt to replicate a seminal paper that offered support for the rational expectations hypothesis and reported evidence that markets with certain features aggregate dispersed information. The original results are based on only a few observations, and our attempt to replicate the key findings with an appropriately powered experiment largely fails. The resulting poststudy probability that market performance is better described by rational expectations than the prior information (Walrasian) model under the conditions specified in the original paper is very low. As a result of our failure to replicate, we investigate an alternate set of market features that combines aspects of the original experimental design. For these markets, which include both contingent claims and homogeneous dividend payments (as in many prediction markets), we do find robust evidence of information aggregation in support of the rational expectations model. In total, our results indicate that information aggregation in asset markets is fragile and should only be expected in limited circumstances. This paper was accepted by Bruno Biais, finance. Supplemental Material: The data and online appendix are available at https://doi.org/10.1287/mnsc.2022.4463. [ABSTRACT FROM AUTHOR]

A firm's publicly available information reflects ex ante committed information releases and ex post discretionary disclosures. In a setting wherein a firm's CEO is concerned with stock market valuation and confrontations with the employee union, this paper endogenizes when the CEO retains ex post disclosure discretion and when the CEO curtails discretion, opting instead to ex ante commit to not gathering information or publicly disclosing information. The underlying economic forces entail a trade-off between the time-inconsistency problem (the CEO's ex post preferences can diverge from the CEO's ex ante goals) and how silence (absence of information) under the ex ante and ex post paths is valued differentially by the union. In effect, silence under different systems "speaks" differently, and this influences both the labor union's incentives to engage in bargaining with the firm and the stock market's pricing of the firm's equity. This paper was accepted by Ranjani Krishnan, accounting. [ABSTRACT FROM AUTHOR]

This paper examines whether "you get what you pay for" in firms that implement residual income (Rl)-based compensation. Specifically, this paper explores differences in investment patterns of firms that implement Rl-based compensation plans conditional on whether the firms switched from earnings or return on investment (ROI)-based compensation. I find that the pattern of investment for firms switching to RI from earnings-based compensation is opposite to that of firms switching from ROI-based compensation. Changes in investment within each individual subgroup yield weaker, mixed results. In addition, this paper documents that delivered RI increases in firms that implement RI. My paper contributes to the literature on the investment effects of RI by examining the relevance of a set of arguments that have been made in management accounting textbooks since 1965. These arguments are still found in current textbooks and are commonly taught to students in graduate level managerial accounting classes. The arguments help us to examine a natural experiment in which we can better specify the conditions under which RI use is expected to be associated with changes in investment. [ABSTRACT FROM AUTHOR]

The Optimization Department seeks contributions on all aspects of optimization and its applications, especially papers that bridge the gap between different fields and connect the dots to bring new tools [...]

This paper documents the increasing importance of software for successful innovation in manufacturing sectors well beyond the traditional definition of electronics and information technology. Using panel data for 229 publicly listed firms from 18 countries across four manufacturing industries over the period 1981–2005, we find significant variation across firms in the software intensity of their innovative activity. Firms that exhibit a higher level of software intensity generate more patents per R&D dollar, and their investment in R&D is more highly valued by equity markets. Data and the online appendix are available at https://doi.org/10.1287/mnsc.2017.2960. This paper was accepted by Anandhi Bharadwaj, information systems. [ABSTRACT FROM AUTHOR]

Under the assumption of multivariate normality of asset returns, this paper presents a geometric interpretation and the finite-sample distributions of the sample Hansen-Jagannathan bounds on the variance of admissible stochastic discount factors, with and without the nonnegativity constraint on the stochastic discount factors. In addition, since the sample Hansen-Jagannathan bounds can be very volatile, we propose a simple method to construct confidence intervals for the population Hansen-Jagannathan bounds. Finally, we show that the analytical results in the paper are robust to departures from the normality assumption. Data, as supplemental material, are available at . This paper was accepted by Jerome Detemple, operations management. [ABSTRACT FROM AUTHOR]

Personal data have become a key input in internet commerce, facilitating the matching between millions of customers and merchants. Recent data regulations in China, Europe, and the United States restrict internet platforms' ability to collect and use personal data for personalized recommendation and may fundamentally impact internet commerce. In collaboration with the largest e-commerce platform in China, we conduct a large-scale field experiment to measure the potential impact of data regulation policy and to understand the value of personal data in internet commerce. For a random subset of 555,800 customers on the Alibaba platform, we simulate the regulation by banning the use of personal data in the home page recommendation algorithm and record the matching process and outcomes between these customers and merchants. Compared with the control group with personal data, we observe a significantly higher concentration in the algorithmic recommendation of products in the treatment group and a very sharp decrease in the matching outcomes as measured by both customer engagement (click-through rate and product browsing) and market transaction (sales volume and amount). The negative effect is disproportionate and more pronounced for niche merchants and customers who would benefit more from e-commerce. We discuss the potential economic impact of data regulation on internet commerce as well as the role of personal data in generating value and fostering long-tail innovations. This paper was accepted by Chris Forman, information system. Funding: Z. Yuan wants to acknowledge financial support from NSFC [Grants 72203202, 72192803 and 72141305]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4828. [ABSTRACT FROM AUTHOR]

Because of many firms' lack of collateral, banks have imposed loan limits as a form of risk-control regulations of bank financing. In response, loan insurance has emerged as a useful instrument to lift loan limits. To study the joint value of bank loans and loan insurance, this article investigates a supply chain composed of one supplier and one capital-constrained buyer who takes out a bank loan and potentially purchases loan insurance. The analysis reveals that both the supplier and the buyer can benefit from the bank financing with loan insurance in an insurance-cooperation region wherein the supplier is willing to reduce the wholesale price to entice the buyer to purchase insurance. Further still, in the insurance-cooperation region, worse contract terms of the bank loan benefit the supplier, whereas worse policy terms of loan insurance help the buyer. Such benefits can lead to a higher order quantity than the capital-abundant one and partially coordinate the entire supply chain. However, when production cost is low, the supplier and the buyer can encounter a Stackelberg prisoner's dilemma, in which both firms no longer cooperate with each other, and both are worse off. Nevertheless, a government subsidy for the insurance premium can not only reduce the Stackelberg prisoner's dilemma, but also improve the social welfare although it is not always optimal for the government to provide that subsidy. The main qualitative results are robust in a variety of extensions. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: The first author acknowledges support from the National Natural Science Foundation of China (NSFC) [Grant 72171162] and the Humanity and Social Science Youth Foundation of Ministry of Education of China [Grant 20YJC630148], and the second author acknowledges support from the NSFC [Grant 72232001]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4827. [ABSTRACT FROM AUTHOR]

Simple and affordable testing tools are often not accurate enough to be operationally relevant. For coronavirus disease 2019 (COVID-19) detection, rapid point-of-care tests are cheap and provide results in minutes, but they largely fail policy makers' accuracy requirements. We propose an analytical methodology, based on robust optimization, that identifies optimal combinations of results from cheap tests for increased predictive accuracy. This methodological tool allows policy makers to credibly quantify the benefits from combination testing and thus, break the trade-off between cost and accuracy. Our methodology is robust to noisy and partially missing input data and incorporates operational constraints—relevant considerations in practice. We apply our methodology to two data sets containing individual-level results of multiple COVID-19 rapid antibody and antigen tests, respectively, to generate Pareto-dominating receiver operating characteristic curves. We find that combining only three rapid tests increases out-of-sample area under the curve by 4% (6%) compared with the best-performing individual test for antibody (antigen) detection. We also find that a policy maker who requires a specificity of at least 0.95 can improve sensitivity by 8% and 2% for antibody and antigen testing, respectively, relative to available combination testing heuristics. Our numerical analysis demonstrates that robust optimization is a powerful tool to avoid overfitting, accommodate missing data, and improve out-of-sample performance. Based on our analytical and empirical results, policy makers should consider approving and deploying a curated combination of cheap point-of-care tests in settings where "gold standard" tests are too expensive or too slow. This paper was accepted by Stefan Scholtes, healthcare management. Supplemental Material: The data files and electronic companion are available at https://doi.org/10.1287/mnsc.2023.4826. [ABSTRACT FROM AUTHOR]

Do gender diversity quotas enhance firm value? This broad question has sparked significant debate because, whereas diversity is generally thought to improve board functioning, prior research in international settings suggests mandating diversity may have adverse consequences if it moves firms away from market equilibrium. Exploiting the political events leading up to the passage of California Senate Bill (SB) 826 as an exogenous shock to assess the market implications of board gender composition, we document either significantly positive or insignificant two-day abnormal returns for California firms across a variety of model specifications. Importantly, this finding contradicts the strong claims of contemporary studies of SB 826 that the California mandate was value-destructive. We reconcile these findings by providing critical evidence that contemporaneous results lack robustness to alternative model specifications and provide an incomplete picture by failing to comprehensively examine a broader set of event dates or account for mixed messaging on the final event date. We also provide some evidence of significant negative abnormal returns to litigation milestones that threaten to overturn SB 826 with the magnitude increasing in the size of board gender deficits. Finally, we provide evidence that there is no observable decline in newly appointed female director quality following the implementation of SB 826 relative to either preregulation or male director appointments. Collectively, our results suggest nonnegative (if not positive) consequences to California firms arising from SB 826 and directly counter assertions that mandated gender diversity is detrimental to firm value. This paper was accepted by Brian Bushee, accounting. Funding: The authors gratefully acknowledge research funding from Brigham Young University and the University of Toronto. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4825. [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]

Using an hourly data set on retail investor individual security positions from Robinhood Markets, we find no evidence that environmental, social, and governance (ESG) disclosures inform retail investors' buy and sell decisions. The response on ESG press release days by retail investors is indistinguishable from nonevent days. In contrast, these same investors make economically meaningful changes to their portfolios in response to non-ESG press releases, especially those that pertain to earnings announcements. We use stock return tests to show that there is economic content in ESG press releases, and we conduct subsample analyses showing that retail investors do not respond to the most salient and economically transparent ESG disclosures. Collectively, these tests suggest that a lack of economic content, a lack of visibility, and difficulty with investment integration are unlikely to explain our findings. This paper was accepted by Suraj Srinivasan, accounting. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4822. [ABSTRACT FROM AUTHOR]

Quality disclosures regarding medical outcomes such as patient mortality are common healthcare policy instruments. Mixed evidence exists on whether quality disclosures improve outcomes for disclosed ailments. Moreover, disclosure policies can generate spillovers and impact ailments not targeted by the policy. We examine the effects of quality disclosure regulation on mortality improvements in disclosed and nondisclosed ailments. We use patient records for California hospitals for 1995–2014 and construct three groups of ailments: those that were the target of disclosure regulation, complementary ailments that were not the target of disclosure regulation but are medically related to the disclosed ailments, and medically unrelated ailments. Using a difference-in-differences design, we find that quality disclosure regulation is associated with declines in mortality risk of disclosed ailments ranging from 11.5% to 23%. Quality disclosure regulation is also associated with improvements for complementary ailments that are not the target of the disclosure policy. Such positive spillover effects yield an estimated 15.2% decline in mortality risk. Consistent with demand-side pressures driving improvements, market shares become sensitive to disclosed quality measures after disclosure regulation. Our findings of direct and spillover effects have implications for disclosure regulation. This paper was accepted by David Simchi-Levi, accounting. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4817. [ABSTRACT FROM AUTHOR]

We study the behavior of an individual avoiding peer information from a natural field experiment of charity crowdfunding. The unique experimental design enables us to employ an instrumental variable strategy to identify how the behavior influences individual giving to and promotion of charity campaigns. We find that, even with free access, 89% of individuals chose not to seek peer information. These individuals were less likely, whereas their peers were more likely to give and help promote in the past. The behavior would reduce the total distribution of campaigns by 8.5% and the total donation amount by 7.7%. A stylized model is used to illustrate how the pressure from peer comparison drives the individuals not to seek the information and how this behavior could influence giving and promoting behaviors of a group of marginal individuals. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: The project was supported by the National Natural Science Foundation of China [Grants 72103110]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4807. [ABSTRACT FROM AUTHOR]

I study the impact of financial stress on the incidence of harassment and discrimination using Equal Employment Opportunity (EEO) charges brought forward by U.S. Postal Service workers. An analysis of more than 800,000 EEO charges filed between 2004 and 2019 demonstrates that financial stress experienced in the second week of the pay cycle increases EEO incidents by about 5% compared with the first week. Further analyses suggest that the uncovered effects are driven by changes in the number of incidents rather than in their reporting. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by the Laboratory for Economic Analysis and Policy at Harvard University and a James M. and Cathleen D. Stone PhD Scholar fellowship from the Multidisciplinary Program in Inequality & Social Policy. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4815. [ABSTRACT FROM AUTHOR]

We study how social connectedness affected active mutual fund manager trading behavior in the first half of 2020. In the first quarter during which the coronavirus disease 2019 (COVID-19) outbreak occurred, fund managers located in or socially connected to COVID-19 hotspots sold more stock holdings compared with a control group of unconnected managers. The economic impact of social connectedness on stock holdings was comparable with that of COVID-19 hotspots and was elevated among "epicenter" stocks most susceptible to the pandemic shock. In the second quarter, social interaction had an overall negative effect on fund performance, but this effect depended on manager skill; unskilled managers who were connected to the hotspots underperformed, whereas skillful managers suffered no deleterious effect. Our evidence suggests that social connections can intensify salience bias for all but the most skilled institutional investors, and policy makers should be wary of the destabilizing role of social networks during market downturns. This paper was accepted by Gustavo Manso, finance. Funding: This work was supported by the Social Science and Humanities Research Council of Canada. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4814. [ABSTRACT FROM AUTHOR]

Does the arrival of culturally diverse workers affect the work style of incumbent workers? We examine how the large influx of Russian hockey players in the National Hockey League after 1989 affected North American–born players. The Soviet style of hockey was largely based on skilled skating, constant movement, circling, and passing. In contrast, the North American play was more individualistic and linear, with higher emphasis on physical strength and aggressive behavior. Using 50 years of data at the player-game level, we show that (i) the number of penalty minutes per game increases steadily from 1970 to 1989, but decreases thereafter; (ii) although Russian players get systematically fewer penalty minutes in and after 1989, the trend reversal is driven by North American–born players; and (iii) the number of penalty minutes per game of North American–born players decreases systematically with the number of Russian players on their team and on the opposing team. Evidence shows that the hockey style brought about by Russian players was adopted and diffused within and across North American teams and players. This paper was accepted by Lamar Pierce, organizations. Supplemental Material: Data and the online appendix are available at https://doi.org/10.1287/mnsc.2023.4808. [ABSTRACT FROM AUTHOR]

We explore the consequences of limiting executive pay on voluntary executive turnover by exploiting a Chinese government policy restricting executive pay at a subset of firms. Affected firms experience an increase in voluntary executive turnover, with executives increasingly moving to firms not bound by the pay policy. Executives that leave are of higher quality as suggested by their stronger stock and accounting performance in the year prior to the turnover. Affected firms suffer firm value losses, especially when talented executives leave. Our findings demonstrate the importance of compensation contracts in retaining executives and suggest a need for regulatory caution, since mandated constraints aimed at trying to "fix" executive pay can hurt firm value and ultimately, hurt shareholders. This paper was accepted by Suraj Srinivasan, accounting. Funding: S. Silveri acknowledges research support in the form of a summer research grant from the Fogelman College of Business and Economics at the University of Memphis. This research support does not imply endorsement of the research results by either Fogelman College or the University of Memphis. K. Wang is grateful for the financial support provided by the Tsinghua University Initiative Scientific Research Program and the research project of the Institute for State-Owned Enterprises, Tsinghua University. L. Zhao is grateful for the financial support provided by the Asia Research Center in Nankai University [Project AS2206]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4812. [ABSTRACT FROM AUTHOR]

We study the effects of grade nondisclosure (GND) policies implemented within master of business administration (MBA) programs at highly ranked business schools. GND precludes students from disclosing their grades and grade point averages (GPAs) to employers. In the labor market, we find that GND weakens the positive relation between GPA and employer desirability. During the MBA program, we find that GND reduces students' academic effort for a given course by approximately 4.9% relative to comparable students not subject to the policy. Consistent with our model, in which abilities are potentially correlated and students can substitute effort toward other activities in order to signal GPA-focused abilities, students participate in more extracurricular activities and enroll in more difficult courses under GND. Finally, we show that students' tenure with their first employers after graduation decreases under GND. This paper was accepted by Suraj Srinivasan, accounting. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4816. [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]

We study interdepartment knowledge sharing in an investment research setting where the benefits are potentially significant for the brokerage and the capital market, but so are the frictions impeding it. Using hand-collected data on equity analyst access to in-house debt research expertise, we find significant benefits to equity analysts in the form of improved ability to forecast cash flows and to anticipate credit rating downgrades. Moreover, we find evidence that access to management and research expertise underlie in-house debt analysts' capacity to generate information beneficial to equity analysts. Finally, these benefits exist only in the presence of a collaborative brokerage culture or debt-equity analyst collocation, consistent with these factors promoting knowledge sharing in the investment research industry. This paper was accepted by Brian Bushee, accounting. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4809. [ABSTRACT FROM AUTHOR]

Economic theory predicts that bond insurance lowers issuers' financing costs by resolving asymmetric information and mitigating credit risk. With comprehensive data over the last 36 years, we find increasingly diminished empirical support for these models. The value of insurance in resolving asymmetric information beyond that resolved by credit ratings and other observable bond characteristics is economically minimal. The average gross value of insurance ranges from 4 to 14 bps when bond insurers offer Aaa-rated coverage. However, this gross value becomes insignificant after 2008 when Aaa-rated insurance no longer exists. Evidence suggests that the lack of insurance benefit in the postcrisis period is attributable to the deteriorated creditworthiness of insurance companies. Examining noninterest saving explanations for the continued use of insurance in the no-Aaa insurance market, we find evidence that issuers purchase insurance out of habit (with insurance value most diminished for habitual purchasers with low governance quality) and for the convenience it affords in default, but no evidence that insurance improves secondary market liquidity. This paper was accepted by Gustavo Manso, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4813. [ABSTRACT FROM AUTHOR]

The overstatement of asset collateral values reduces bank capital requirements. We identify this novel form of regulatory arbitrage by studying housing overappraisals, the difference between housing collateral values computed by appraisers and actual transaction prices. We leverage granular loan-level data from Spain and a kink in the scheme of residential mortgage risk weights to show that tighter regulatory requirements cause larger overappraisals. This bias depends on the relationship between appraisers and banks; appraisers inflate mortgage collateral values only for their major customer banks. On average, overappraisals lower risk-weighted mortgages by 9%. Mortgage overappraisals allow banks to free up regulatory capital to support additional risk-taking in the corporate loan market. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4805. [ABSTRACT FROM AUTHOR]

We explore the statistical and economic importance of restrictions on the dynamics of risk compensation from the perspective of a real-time Bayesian learner who predicts bond excess returns using dynamic term structure models (DTSMs). The question on whether potential statistical predictability offered by such models can generate economically significant portfolio benefits out-of-sample is revisited while imposing restrictions on their risk premia parameters. To address this question, we propose a methodological framework that successfully handles sequential model search and parameter estimation over the restriction space in real time, allowing investors to revise their beliefs when new information arrives, thus informing their asset allocation and maximizing their expected utility. Empirical results reinforce the argument of sparsity in the market price of risk specification since we find strong evidence of out-of-sample predictability only for those models that allow for level risk to be priced and, additionally, only one or two of these risk premia parameters to be different than zero. Most importantly, such statistical evidence is turned into economically significant utility gains, across prediction horizons, different time periods and portfolio specifications. In addition to identifying successful DTSMs, the sequential version of the stochastic search variable selection scheme developed can be applied on its own and offer useful diagnostics monitoring key quantities over time. Connections with predictive regressions are also provided. This paper was accepted by Kay Giesecke, finance. Funding: T. Dubiel-Teleszynski acknowledges the support of the Economic and Social Research Council. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4801. [ABSTRACT FROM AUTHOR]

We study policy optimization for the feature-based newsvendor, which seeks an end-to-end policy that renders an explicit mapping from features to ordering decisions. Most existing works restrict the policies to some parametric class that may suffer from suboptimality (such as affine class) or lack of interpretability (such as neural networks). Differently, we aim to optimize over all functions of features. In this case, the classic empirical risk minimization yields a policy that is not well-defined on unseen feature values. To avoid such degeneracy, we consider a Wasserstein distributionally robust framework. This leads to an adjustable robust optimization, whose optimal solutions are notoriously difficult to obtain except for a few notable cases. Perhaps surprisingly, we identify a new class of policies that are proven to be exactly optimal and can be computed efficiently. The optimal robust policy is obtained by extending an optimal robust in-sample policy to unobserved feature values in a particular way and can be interpreted as a Lipschitz regularized critical fractile of the empirical conditional demand distribution. We compare our method with several benchmarks using synthetic and real data and demonstrate its superior empirical performance. This paper was accepted by J. George Shanthikumar, data science. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4810. [ABSTRACT FROM AUTHOR]

Does financial reform improve public good provision? We examine state-level adoption of municipal bankruptcy law. After reform, municipalities' borrowing costs decrease and bonds' issuance increase, particularly for bonds financing hospitals; hospitals' investments increase, particularly when using such bonds; local firms' investment and performance increase, particularly in the construction sector. Ex ante, reform occurs earlier in states with weaker unions, stronger bondholders' interests, and better courts. Similar factors explain congressional voting on municipal bankruptcy law. These results support the hypothesis that financial reform destroys labor union rents and expands investment, highlighting a novel spillover channel from public finance to the real economy. This paper was accepted by Victoria Ivashina, finance. Funding: This work was supported by the Baffi-CAREFIN Research Center at Bocconi. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4800. [ABSTRACT FROM AUTHOR]

We propose a mean field game model to study the question of how centralization of reward and computational power occur in Bitcoin-like cryptocurrencies. Miners compete against each other for mining rewards by increasing their computational power. This leads to a novel mean field game of jump intensity control, which we solve explicitly for miners maximizing exponential utility and handle numerically in the case of miners with power utilities. We show that the heterogeneity of their initial wealth distribution leads to greater imbalance of the reward distribution, and increased wealth heterogeneity over time, or a "rich get richer" effect. This concentration phenomenon is aggravated by a higher Bitcoin mining reward and reduced by competition. Additionally, an advantaged miner with cost advantages such as access to cheaper electricity, contributes a significant amount of computational power in equilibrium, unaffected by competition from less efficient miners. Hence, cost efficiency can also result in the type of centralization seen among miners of cryptocurrencies. This paper was accepted by Kay Giesecke, finance. Funding: A. M. Reppen is partly supported by the Swiss National Science Foundation [Grant SNF 181815]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4798. [ABSTRACT FROM AUTHOR]

Recent financialization in commodity markets makes it easier for institutional investors to trade a portfolio of commodities via various commodity-indexed products. We present several pieces of novel causal evidence that daily exposure to such index trading results in price overshoots and reversals, as reflected in negative daily return autocorrelations, only among commodities in that index. This is because index trading propagates nonfundamental noise to all indexed commodities. We present direct evidence for such noise propagation using commodity news sentiment data. This paper was accepted by Bruno Biais, finance. Funding: Z. Da acknowledges financial support from the Beijing Outstanding Young Scientist Program [Grant BJJWZYJH01201910034034] and the 111 Project [Grant B20094]. K. Tang acknowledges financial support from the National Natural Science Foundation of China [Grants 71973075 and 72192802]. Y. Tao acknowledges financial support from the Start-up Research Grant of University of Macau [Grant SRG2022-00016-FSS]. L. Yang acknowledges the Social Sciences and Humanities Research Council of Canada for financial support [Grants 430-2018-00173 and 435-2021-0040]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4797. [ABSTRACT FROM AUTHOR]

Using an administrative payroll data set for 2.6 million retail workers, we find that the staggered rollout of a major e-commerce firm's fulfillment centers reduces traditional retail workers' income in geographically proximate counties by 2.4%. Wages of hourly workers, especially part-time hourly workers, decrease significantly driven by a drop in the number of hours worked. We observe a U-shaped pattern in which both young and old workers experience a sharper decrease in wage income. Consequently, some workers experience an increase in credit card delinquency. Using data for 3.2 million stores, we find that sales (employment) at proximate stores decrease by 4% (2.1%). Exits, especially of young and small stores, increase, and entry decreases. Our results highlight how creative destruction led by e-commerce impacts local labor markets. This paper was accepted by Anindya Ghose, information systems. Funding: The authors gratefully acknowledge funding support from the Kauffman Foundation Junior Faculty Fellowship. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4795. [ABSTRACT FROM AUTHOR]

We consider a dynamic pricing problem in which a firm sells one item to a single buyer to maximize expected revenue. The firm commits to a price function over an infinite horizon. The buyer arrives at some random time with a private value for the item. He is more impatient than the seller and strategizes over the timing of the purchase in order to maximize his expected utility, which implies either buying immediately, waiting to benefit from a lower price, or not buying. We study the value of the seller's ability to observe the buyer's arrival time in terms of her expected revenue. When the seller can observe the buyer's arrival, she can make the price function contingent on the buyer's arrival time. On the contrary, when the seller can't, her price function is fixed at time zero for the whole horizon. The value of observability (VO) is defined as the worst-case ratio between the expected revenue of the seller when she observes the buyer's arrival and that when she does not. First, we show that, for the particular case in which the buyer's valuation follows a monotone hazard rate distribution, the upper bound of VO is exp(1). Next, we show our main result: in a setting very general on valuation and arrival time distributions: VO is at most 4.911. To obtain this bound, we fully characterize the solution to the observable arrival problem and use this solution to construct a random and periodic price function for the unobservable case. Finally, we show by solving a particular example to optimality that VO has a lower bound of 1.136. This paper was accepted by Itai Ashlagi, revenue management and market analytics. Funding: This work was partially supported by the Agencia Nacional de Investigación y Desarrollo Chile [Grants ACT210005 and FONDECYT 1220054], and by the Center for Mathematical Modeling at the University of Chile [Grant FB210005]. The work of D. Pizarro has benefited from the Artificial and Natural Intelligence Toulouse Institute, which is funded by the French "Investing for the Future – PIA3" program [Grant ANR-19-P3IA-0004]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4794. [ABSTRACT FROM AUTHOR]

This article studies the consumption of advertising when attention is costly. Our objective is to understand the advertiser's optimal decision for informational and noninformational content when facing consumers with heavy distractions common in the digital age. We take an equilibrium approach in which an ad is consumed if and only if the content of the ad is worth the viewer's attention. We classify many advertising decisions observed in practice. First, an advertiser can structure content to induce curiosity for continued viewing by showing the information that is relatively less likely to resonate with the broad audience. This tactic is evident in clickbait ads and "mystery ads." Second, we find that digital ads, which tend to be skippable, have lower amounts of noninformational content (e.g., entertainment) relative to nonskippable ads. This finding can explain the industry perception that ads on digital media are of lower copy quality than traditional ads. This paper was accepted by Dmitri Kuksov, marketing. Funding: This work was supported by the Marketing Science Institute [Grant 4000790]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4793. [ABSTRACT FROM AUTHOR]

In April 2020, the U.S. government sent economic impact payments (EIPs) directly to households as part of its measures to address the COVID-19 pandemic. We characterize these stimulus checks as a wealth shock for households and examine their effect on retail trading in Bitcoin. We find a significant increase in Bitcoin buy trades of size $1,200, which is the modal EIP amount. We find similar increases in trading for other countries that paid out stimulus checks. We estimate that the EIPs have a significant impact on the U.S. dollar–Bitcoin trading pair, increasing buy volume by 3.8% and the price by 0.6%. We also find that demand for Bitcoin is highly price inelastic compared with the demand for stocks. We suggest the demographic characteristics that make people more resilient to the COVID-19 economic shock—single, computer literate, and educated—are also characteristics of people who are more interested in Bitcoin. This paper was accepted by Bruno Biais, finance. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4790. [ABSTRACT FROM AUTHOR]

Retailers are increasingly selling returned products as open-box along with their new product offerings. Whereas some retailers position open-box products side-by-side with their new counterparts in the assortment (i.e., side-by-side strategy), other retailers position them separately in a different part of the retail space/website (i.e., separate strategy). We conduct multimethodology research to investigate the effectiveness of these two visual merchandising strategies. First, using a choice-based conjoint design in a controlled behavioral experiment, we identify how the two strategies affect the perceived value of new products. Next, using proprietary data from a retailer that has implemented both strategies across different stores, we empirically test the impact of each strategy on new product sales and returns under real market conditions. Finally, we extend our empirical analysis to prescribe how retailers can identify the right visual merchandising strategy for a given product profile. Overall, our results reveal a novel trade-off between the two visual merchandising strategies. With respect to retail revenue, the separate strategy outperforms the side-by-side strategy as we find that new product sales are higher with the separate strategy. However, with respect to retail cost, the side-by-side strategy outperforms the separate strategy as we find that new product returns are lower with the side-by-side strategy. Our extended analysis reveals that this tradeoff varies by product profile. Using counterfactual analysis, we further demonstrate that customizing the visual merchandising strategy by product mix could increase profit by 3.2% at the focal retailer. 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.2023.4786. [ABSTRACT FROM AUTHOR]

We provide new insights on how hedge funds use options and short-selling channels to trade on their negative information. Bearish information in hedge fund option positions is economically large, distinct from information in short interest, and it is the combination of option positions and short interest that provides the strongest information signal. A portfolio of stocks with high short interest and bearish hedge fund option positions predicts negative abnormal returns that are more than four times as large as the portfolio with high short interest and bullish options positions. The information in hedge fund option positions increases during periods of market stress, whereas that in short interest does not. This increase is concentrated in capital-constrained hedge funds, suggesting that options provide a channel for capital-constrained hedge funds to exploit their information advantage. This paper was accepted by Lukas Schmid, finance. Funding: J. Hua received support for this project from a PSC-CUNY Award, jointly funded by The Professional Staff Congress and The City University of New York. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4785. [ABSTRACT FROM AUTHOR]

A one-factor model based on long-run consumption growth explains the risk premiums on corporate bond portfolios sorted on credit rating, credit spreads, downside risk, idiosyncratic volatility, long-term reversals, maturity, and sensitivity to the financial intermediary capital factor. The estimated risk-aversion coefficient is lower when we use the consumption growth of wealthy households over a longer horizon as a risk factor, and a model with a 20-quarter horizon yields a risk-aversion coefficient of 15, a value similar to the one estimated from equity portfolios. This paper was accepted by Bruno Biais, finance. Funding: Y. Nozawa acknowledges funding from the Center for Investing at the Hong Kong University and Science and Technology. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4784. [ABSTRACT FROM AUTHOR]