Academic Publications

Business is personal: How CEO personality influences agency costs

2026-04-29T00:00:00+00:00

Strategic Management Journal
We examine whetherCEOpersonality traits influence the likelihood of engaging in behaviors that impose agency costs on the firm. We use an established open‐language machine learning program to measureCEOBig Five personality traits based onCEOremarks during earnings conference calls. We theorize and find that higher levels of agreeableness and conscientiousness inCEOsare associated with lower agency costs (operationalized here as unrelated diversification and the decoupling ofCEOpay from firm performance), while higher levels of neuroticism are associated with higher agency costs. By revealing howCEOpersonality traits affect agency costs, our study offers a new perspective on the sources of agency problems and broadens the application ofCEOBig Five personality traits to corporate governance.Managerial SummaryThis study explores how aCEO's personality can shape decisions that affect company performance. Using an advanced language analysis tool, we assessedCEOs' personality traits based on what they say during earnings calls. We find thatCEOswho are more agreeable and conscientious are less likely to make decisions that benefit themselves at the expense of the company—such as expanding into unrelated businesses or earning pay that does not reflect company performance. In contrast,CEOswith higher levels of neuroticism are more likely to engage in these costly behaviors. These findings suggest that understanding aCEO's personality can offer valuable insights into their leadership behavior and help boards and investors make better governance and hiring decisions.

The Cost of Regulatory Compliance in the United States*

2026-04-29T00:00:00+00:00

The Review of Financial Studies
A key question for studying business dynamism is whether the costs of regulatory compliance fall homogeneously on small and large businesses. Using comprehensive establishment-level occupational microdata and occupation task information, we quantify a firm’s compliance costs as the share of wage bill for performing regulatory compliance tasks (RegIndex). We reveal an inverted-U relationship between firms’ RegIndex and their size: On average, RegIndex for mid-sized firms with around 500 employees is about 47% greater than that of the smallest firms and 18% greater than that of the largest firms. We further develop a shift-share methodology to disentangle the influence of regulatory requirements and enforcement on driving firms’ compliance costs. (JEL G38, J01, K2, L43, L51)

A Booby Trap Game

2026-04-29T00:00:00+00:00

Operations Research
Strategic Defense Against a Resource Gathering AttackerIn many real-world security settings, defenders must monitor a space using limited resources while attackers try to exploit gaps in coverage without being detected. The space may be a shop, museum, or airport, where the defenders use hidden cameras to detect thieves or smugglers, who wish to steal items or conceal contraband. To capture this interaction, Lidbetter and Lin present an attacker-defender game in “A Booby Trap Game.” The defender places several hidden traps within a search space, while the attacker selects a subset of that space to exploit. The attacker’s reward is proportional to the size of the selected subset if the subset does not contain any trap; otherwise, the attacker gets nothing. The article presents optimal (max-min/min-max), or near optimal, randomized strategies for both players for various spaces—including circles, line segments, two-connected networks, trees, and arbitrary Lebesgue measurable, path-connected subsets of Euclidean space.

An Online Mirror Descent Learning Algorithm for Multiproduct Inventory Systems

2026-04-29T00:00:00+00:00

Operations Research
Learning to Manage Multiproduct Inventory from Incomplete Demand SignalsManaging inventory across different products within limited warehouse space is a central challenge in retail and supply chain operations, especially when demand is unknown and lost-sales data are missing. This problem becomes even harder as product assortments grow larger. In “An Online Mirror Descent Learning Algorithm for Multiproduct Inventory Systems,” Guo et al. develop the online mirror descent learning algorithm (OMELET), a scalable online learning algorithm that dynamically adjusts replenishment decisions using observed sales data. The method builds on mirror descent with cyclic updates to efficiently handle high-dimensional product menus. The authors show that the algorithm’s regret grows only logarithmically with the number of products, a significant theoretical improvement over existing approaches. Extensive numerical experiments using empirical data confirm that OMELET not only outperforms existing state-of-the-art methods but also, translates into practical, actionable insights for managers making real-time inventory decisions.

Decision Making with Side Information: A Causal Transport Robust Approach

2026-04-29T00:00:00+00:00

Operations Research
Making Robust Contextual Decisions with Causal TransportModern decision systems—from supply chains to financial planning—often rely on side information, such as customer attributes or environmental conditions, to guide better choices under uncertainty. Yet real-world data are imperfect, and naive models can fail when the underlying distribution changes. In the paper “Decision Making with Side Information: A Causal Transport Robust Approach,” the authors develop a new framework that integrates side information into distributionally robust optimization while preserving the causal structure between covariates and uncertain outcomes. The approach uses a causal transport distance to construct uncertainty sets that respect the conditional relationships learned from data. The authors show that the resulting worst-case distributions maintain this information structure and derive a tractable dual formulation for evaluating worst-case performance. For affine policies, the resulting optimization problem can be solved via convex programming, whereas more general settings reveal a new class of robust decision rules under convex costs.

Frontiers: The Demand for Counterfeits: A Descriptive Analysis

2026-04-29T00:00:00+00:00

Marketing Science
This paper documents descriptively new evidence about counterfeit demand using large-scale field data.

Talking Without Speaking: Paid Trolls on Social Media and Court Decision

2026-04-29T00:00:00+00:00

Marketing Science
This article aims to investigate how public opinions and paid trolls may affect the outcome of legal disputes between opposing parties.

A Sensemaking Model of Investor Reactions to CEO Achievement Expression

2026-04-29T00:00:00+00:00

Journal of Management
Prior research on investor reactions to CEO communication tends to focus on one linguistic cue at a time. Even when multiple cues are considered, they are often examined in an additive fashion as if they were independent from one another. Integrating sensemaking theory and research with terror management theory, we develop a sensemaking model that posits that investors do not react to routine cues from CEOs, such as achievement expression, in isolation. Instead, their reactions are moderated by nonroutine cues such as CEOs’ use of death-related words that trigger mortality salience. Under high mortality salience, CEO achievement expression indirectly enhances investors’ perceptions of firm investment attractiveness through agentic leader stereotypes and perceived leader competence. Two experiments with investors (Studies 1 and 2) and a panel study of U.S. S&P 500 firms (Study 3) support our model, showing that CEO achievement expression elicits stronger, more positive investor reactions under high mortality salience.

Flattening the Baby Bump: An Interdisciplinary Review of Gendered Return-to-Work Decisions After Childbirth

2026-04-29T00:00:00+00:00

Journal of Management
Compared to fathers, mothers take significantly more time off work after childbirth to care for infants and are more likely not to return to paid employment. To better understand these gendered outcomes, research on return-to-work after childbirth has grown exponentially. We conduct an interdisciplinary, systematic review of 303 articles to illuminate and compare the factors influencing mothers’ and fathers’ return-to-work decisions and their outcomes. This research reveals a complex web of factors that affect return-to-work and provides comprehensive evidence of the gendered dynamics that parents face. Based on this review, we synthesize existing research and explore alternative theoretical explanations for the persistent gender disparities in return-to-work. In this process, we identify and evaluate four key theoretical lenses, outlining the themes they address, their underlying assumptions, and their potential limitations: 1) the economic and human capital lens, 2) the resource and support lens, 3) the gender role and identity lens, and 4) the health and well-being lens. We conclude by highlighting the remaining gaps in understanding and propose a novel capability-based research agenda to guide future policy, organizational strategies, and support for families navigating return-to-work decisions after childbirth.

Micro‐Foundations of “ Doing Well by Doing Good ”: Multilevel Effects of Work‐Life Policies on Employee Well‐Being and Sales Growth

2026-04-29T00:00:00+00:00

Human Resource Management
This study unravels how the effects of work‐life policies (WLPs) on individual employees' perceived control over their work schedule have cumulative effects across employees, ultimately crossing levels to enhance organizational outcomes like sales. We tested a multilevel mediating model comprising two cross‐level mechanisms: a top‐down link between the organization's availability of WLPs and individual‐level variables like control over work schedule and job satisfaction, and a bottom‐up link between job satisfaction (aggregated within the organization) and sales growth. Analyses of multilevel, multisource data from 3262 employees in 70 organizations supported thetop–downhypotheses predicting that gains in employee control over their work schedule mediate the positive relationship between WLPs availability and job satisfaction. Furthermore, analyses of sales growth data using a matched subsample of 39 organizations and 1872 employees supported thebottom–uphypothesis that organization‐level job satisfaction is positively associated with sales growth over a three‐year span. Our results begin to shed light on the micro‐foundations of doing well (i.e., increasing sales) by doing good (i.e., increasing employees' control over their work schedules through WLP).

Measuring Socioemotional Wealth Using Content Analysis: A SEWi-Based Approach

2026-04-29T00:00:00+00:00

Entrepreneurship Theory and Practice
Socioemotional wealth (SEW) is a foundational construct in family business research; however, its empirical measurement remains limited by reliance on proxy variables and survey data. This study addresses these challenges by developing a computer-aided text analysis method to measure SEW using the SEWi framework. Our approach enables direct, scalable, and multidimensional assessment of SEW through organizational narratives. We detail the development and validation of the measure, demonstrating its reliability and construct validity. This method expands the methodological toolkit for family business scholars and enhances SEW measurement precision, offering a pragmatic solution for broader, comparative, and longitudinal research.

Identification and Estimation of Dynamic Random Coefficient Models

2026-04-30T00:00:00+00:00

Review of Economic Studies
I study linear panel data models with predetermined regressors (such as lagged dependent variables) where coefficients are individual-specific, allowing for heterogeneity in the effects of the regressors on the dependent variable. I show that the model is not point-identified in a short panel context but rather partially identified, and I characterize the identified sets for the mean, variance, and CDF of the coefficient distribution. This characterization is general, accommodating discrete, continuous, and unbounded data, and it leads to computationally tractable estimation and inference procedures. I apply the method to study lifecycle earnings dynamics among U.S. households using the Panel Study of Income Dynamics (PSID) dataset. The results suggest the presence of unobserved heterogeneity in earnings persistence, implying that households face varying levels of earnings risk which, in turn, contribute to heterogeneity in their consumption and savings behaviours.

Local Projection Based Inference under General Conditions

2026-04-30T00:00:00+00:00

Review of Economic Studies
This paper develops the uniform asymptotic theory for local projection (LP) regression when the true lag order of the model is unknown and potentially infinite. The theory allows for varying degrees of persistence in the data, growing response horizons, and general conditionally heteroskedastic martingale-difference shocks. Based on the theory, we make two main contributions. First, we show that LPs can achieve semiparametric efficiency at a given horizon under classical assumptions on the data, provided that the controlled lag order diverges. Thus the commonly perceived efficiency loss of LPs can become asymptotically negligible with many controls. Second, we propose LP-based inference procedures for (level and cumulated) impulse responses that possess robustness properties not shared by existing methods. Inference methods using two distinct standard errors are considered. The uniform validity for the first method depends on a zero fourth-order cumulant condition on shocks, while that of the second holds more generally for conditionally heteroskedastic martingale-difference shocks. We propose a bootstrap procedure that improves finite-sample performance and extend the standard error construction to structural responses.

EXPRESS: Tele-Follow-Up and Outpatient Care

2026-04-30T00:00:00+00:00

Production and Operations Management
Follow-up appointments are crucial for maintaining continuity of care, yet patients often encounter various barriers to accessing these services. In this study, we examine the potential of telemedicine applications for follow-up care (tele-follow-up), focusing on its impact on care access, service efficiency, and care quality. By collaborating with a large hospital that implemented tele-follow-up services across departments over time, we employ a staggered difference-in-differences design to identify the causal effects of tele-follow-up services. Our findings indicate that the adoption of tele-follow-up services increases total follow-up volume by 48.14%. Notably, we identify positive spillover effects on traditional onsite care, with onsite follow-up visits and initial visits increasing by 14.11% and 7.90%, respectively. We further investigate the mechanism underlying these results. On the demand side, patients with higher costs of accessing onsite follow-up care, such as those living in rural areas or with comorbidities, exhibit greater demand elasticity following the availability of the tele-follow-up channel. On the supply side, dedicating the telemedicine channel exclusively to follow-up care enhances physicians’ efficiency by enabling more focused practice across online and in-person work shifts. The increased access to follow-up services enabled by telemedicine further translates into better patient outcomes, as evidenced by a significant reduction in readmission rates. Our study demonstrates the value of tele-follow-up services and offers practical insights for healthcare decision-makers seeking to leverage digital health to enhance continuity of care.

The role of nearby suppliers after natural disasters

2026-04-30T00:00:00+00:00

Production and Operations Management
Natural disasters disrupt retail operations by simultaneously triggering demand surges and supply interruptions. Restricted access to affected areas raises transportation costs and complicates replenishment, while stores that remain open experience increased demand from displaced consumers and stockpiling behavior. Ensuring product availability becomes critical, forcing retailers to rely on suppliers who can deliver under constrained conditions. We examine whether supplier proximity mitigates these operational disruptions by comparing the sales evolution of products manufactured near each store (“nearby”) to those produced farther away (“distant”). We combine weekly retail scanner data, manufacturing location information, and FEMA disaster declarations for three North Atlantic hurricanes. Using a triple-difference design, we compare changes in sales of products from nearby versus distant suppliers before and after the event, across affected and unaffected stores. Across the three hurricanes, sales of products from nearby suppliers in operational stores located in affected areas increase by 7%–11% relative to products from distant suppliers. Moreover, we find that stockouts of products from nearby suppliers are less likely to occur in the aftermath of the disaster. Furthermore, we find that in two of the three events, products from nearby suppliers experience a price reduction compared to those from distant suppliers. These results show that supplier proximity is an actionable resilience lever: nearby suppliers could be more likely to deliver to affected areas when replenishment is challenging, enabling retailers to maintain product availability and continue serving customers. The findings offer guidance for preparedness planning, emphasizing the value of geographically diversified sourcing and coordination with nearby suppliers.

Space and Structure: The Interplay Between Proximity, Unit Boundaries, and Supervision in Shaping Workplace Interactions

2026-04-30T00:00:00+00:00

Organization Science
Organizations commonly colocate employees in the same office to foster collaboration, yet spatial interventions often fail to deliver their intended benefits. Conflicting evidence in the proximity and office design literatures highlights the need for a better understanding of when and how physical space shapes workplace interactions, particularly across organizational units. Drawing on theories of attention, we propose that spatial arrangements and organizational structures intersect to influence employees’ attentional processes. We argue that (1) proximity’s effects on work-related interactions should be stronger for same-unit dyads than cross-unit dyads because organizational relationships determine who is most likely to stand out in a busy office environment, and (2) proximity to supervisors should reduce cross-unit interactions as employees focus on demonstrating unit-focused productivity to nearby authority figures. We find evidence consistent with these hypotheses in a field study in which employees were quasi-randomly assigned to desks following a headquarters relocation, creating exogenous variation in proximity between employees from different units and between employees and their supervisors. This research contributes to the literatures on boundary spanning, physical space, and organizational attention by demonstrating that office design’s impact on collaboration depends critically on the organizational relationships among the employees within the space.Funding: This work was supported by Duke University, Fuqua School of Business.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2024.19786 .

You Can Have Your Cake and Redistrict It Too

2026-04-30T00:00:00+00:00

Operations Research
Mutually Fair Redistricting Even When Parties DisagreeCongressional redistricting is the process of partitioning a state into districts, each of which elects a representative to Congress. Several recent high-profile redistricting efforts aim to increase the political power of a party. This raises the question of whether “fair” redistricting plans exist. In “You Can Have Your Cake and Redistrict It Too,” Benadè, Procaccia, and Tucker-Foltz propose a new theoretical model for redistricting inspired by classical cake-cutting models. In this model, it shown that is always possible to find redistricting plans that satisfy a particular notion of fairness, called the geometric target, simultaneously for both parties, even when the parties disagree about voter preferences. On real-world data, they find that this fairness constraint can be satisfied in all instances evaluated; moreover, requiring fairness comes at little cost in terms of traditional redistricting objectives. This suggests it is possible and practical to guarantee mutual fairness even in a climate of extreme partisanship.

EXPRESS: Understanding Internal Linguistic Consistency of Person Brands on Social Media: An Empirical Investigation using the 2020 U.S. Presidential Election

2026-04-30T00:00:00+00:00

Journal of Marketing
Social media is essential to how brands are built and managed, especially for person brands. This research investigates how political person brands’ internal linguistic consistency shapes social media engagement. Specifically, the authors examine linguistic consistency relative to a candidate’s own prior social media posts (i.e., internal linguistic consistency). Using social media data from the 2020 U.S. presidential election and adopting an empirics-first approach, the authors find that three distinct constructs comprise internal linguistic consistency of person brands: topic (consistency in subject matter or themes), psychological (consistency in psychological states), and semantic (consistency in information and meaning), revealing that each dimension has its own best strategy: (1) topic inconsistency, (2) psychological consistency, (3) semantic inconsistency. The authors find that these effects are moderated by sudden changes in word of mouth, such as a sudden spike in online conversation about a political opponent, and by whether the election is a primary or a general election, such that moderate semantic consistency is most effective during the general election. The findings demonstrate the importance of simultaneously considering multiple dimensions of internal linguistic consistency in person brand strategies.

Prompt Adaptation as a Dynamic Complement in Generative AI Systems

2026-04-30T00:00:00+00:00

Information Systems Research
Do users automatically benefit when generative AI models improve, or does realizing those gains require changing how they interact with the technology? We ran two preregistered experiments with 3,750 participants submitting nearly 37,000 prompts across two versions of OpenAI’s DALL-E to find out. The answer depends critically on task structure. In a bounded task with a clear objective, replicating a specific target image, roughly half of the performance gain came from the model itself, and half came from users naturally adjusting their prompts. In an open-ended creative task, designing logos for hypothetical organizations, nearly all of the improvement was attributable to the model alone. We then asked whether automated prompt rewriting, a feature embedded in many commercial AI products, could substitute for this user adaptation. It could not: rewriting modestly helped in the creative task but substantially hurt performance in the replication task, where precise user control mattered most. For organizations deploying AI in precision-oriented workflows, our results point to an underappreciated priority: investing in how people learn to interact with a model may matter as much as the model itself.

Priming in Search: A Large-Scale Field Experiment on the Impact of Popular Search Genres in Mobile Shopping

2026-04-30T00:00:00+00:00

Information Systems Research
Mobile commerce platforms face persistent search frictions because of limited screen space and input constraints, making it difficult for consumers to initiate effective searches. This study evaluates a scalable, low-cost design intervention—the popular ranking search aid (PRSA)—that presents aggregated popular search categories at the entry point of the search interface. Using a large-scale randomized field experiment on a major mobile platform, we show that PRSA significantly reshapes consumer behavior and platform outcomes. From a practice perspective, PRSA reduces cognitive barriers in query formation by guiding users toward broader, category-level searches, leading to increased product views and higher purchase rates. However, this benefit comes with a trade-off; broader queries expand the choice set, increasing downstream decision complexity. For platform managers, this highlights the importance of balancing upstream guidance with downstream decision support. From a policy perspective, PRSA offers a privacy-compliant alternative to personalized recommendation systems as it relies on aggregated, nonpersonalized data. This makes it particularly relevant in regulatory environments with growing data protection constraints (e.g., General Data Protection Regulation-like regimes). Overall, the findings demonstrate that simple, nonpersonalized interface designs can meaningfully improve consumer engagement and market efficiency while aligning with emerging privacy standards.

How Costs Influence Preferences for Control in Generative Artificial Intelligence (GenAI): Human-Guided vs. GenAI-Based Delegated Search

2026-04-30T00:00:00+00:00

Information Systems Research
As generative artificial intelligence (GenAI) platforms transition to paid models, concerns grow that usage costs will diminish service value. However, our study of 1.8 million prompts shows that economic constraints actually change how users search solutions with AI. We distinguish between GenAI-based delegated search, which relies on probabilistic sampling, and human-guided delegated search, where users exert active control through refined prompting. We find that salient costs drive users to prioritize controllability over simple cost-minimization. Instead of settling for lower quality, users adapt by crafting precise, detailed prompts and actively “controlling” the AI. This strategic shift increases more purposeful exploration, leading to higher satisfaction and superior outcomes. Ultimately, our work shows that charging for AI usage transforms users into more purposeful, deliberate cocreators with AI, indirectly enhancing the service value of AI platforms.

The Value of Silence: The Effect of UMG’s Licensing Dispute with TikTok on Music Demand

2026-05-19T19:12:17+00:00

Marketing Science
This study examines how the dispute between TikTok and Universal Music Group (UMG) impacted music demand on streaming platforms.

A Bayesian Dual Clustering Approach for Selecting Data and Parameter Granularities

2026-05-19T19:12:17+00:00

Marketing Science
We propose a Bayesian dual clustering method that infers both data and parameter granularities.

Data and Algorithms: Strategic Disclosure of Competitiveness on Platforms Through Marketplace Analytics

2026-05-19T19:12:17+00:00

Marketing Science
This paper studies an e-commerce platform’s two intertwined decisions when offering marketplace analytics: the data access policy and the algorithm design.

Strategic Capacity Commitment: A Channel Competition Perspective

2026-05-19T19:12:17+00:00

Marketing Science
This paper examines how capacity commitment shapes strategic interactions between asymmetric channels—one centralized and one decentralized—and reveals that a centralized manufacturer’s capacity commitment can mitigate price competition and benefit both channels.

Leveraging Large-Scale Granular Single-Source Data for TV Advertising: An Identification Strategy

2026-05-19T19:12:17+00:00

Marketing Science
This paper introduces a new instrumental variable to estimate the causal effects of linear TV advertising, using granular household-level viewing and purchase panel data.

Is Competition Only One Click Away? The Digital Markets Act’s Impact on Google Maps

2026-05-19T19:12:17+00:00

Marketing Science
European Union-mandated changes to Google results increased map-related searches but produced little traffic gain for competitors, underscoring Google Maps’ dominance.

Automated Targeted Bidding for Sponsored Ads on E-Commerce Platforms

2026-05-19T19:12:17+00:00

Marketing Science
We examine how automated bidding for sponsored ads affects seller competition and consumer buying behaviors on e-commerce platforms.

Price Caps by Matching Platforms: The Case of Ticket Resales

2026-05-19T19:12:17+00:00

Marketing Science
This study examines ticket resale platforms’ voluntary price caps, analyzing their adoption incentives and effects on prices, sales, profitability, and welfare.

Communicating Attribute Importance Under Competition

2026-05-19T19:12:17+00:00

Marketing Science
The paper shows that competing firms with competitive advantages in distinct attributes can credibly coordinate their messaging about attribute importance, reducing consumer uncertainty and generating category demand. A truthful equilibrium arises in which each firm highlights the more important attribute—even when at a disadvantage—but such an equilibrium does not exist without competition.

Practice Paper—AI-Driven Behavioral Nudges for Organizations: An Integrative System for Sustainable Resource Management

2026-05-19T19:12:17+00:00

Marketing Science
This paper presents a novel integrative approach that combines artificial intelligence-driven forecasting with behavioral interventions to help businesses optimize energy consumption under critical peak pricing schemes.

Round Number Preferences and Left-Digit Bias: Evidence from Credit Card Repayments

2026-05-19T19:12:17+00:00

Management Science
We examine round number preferences and left-digit bias in credit card repayments. We show half of all manual credit card payments are at a small set of round-number values, although all values between the statement minimum and balance were permissible. We use minimum payments, which place a floor on the payment value, to measure the strength of rounding behavior in a natural experiment. We find that when the minimum payment level just rules out a round number from the bottom of the range of possible repayment (e.g., a minimum payment of £50.01 just rules out a payment of £50.00), payments at the next round number jump by 15%–20% (e.g., payments at £60.00). That is, in response to a smooth increase in minimum payments, the selected payments jump up a ladder of round numbers when each lower rung is removed. We also see a classic—although nuanced—left digit bias. When the balance increases such that the left digit changes (e.g., from £1,999 to £2,000), payments in full drop by 3%–8% as if an increase in the left digit makes the balance seem much larger. But average repayments increase by 10%–15%, as smaller partial repayments are all dragged up the ladder rungs. This preference for a small set of round numbers as payment values and this effect of left digit bias on the level of repayment have policy implications. Rounding could be used by policy makers to encourage faster paydown of credit card debt, using one-click “rounds-ups,” defaults, or shrouding. These policy options could deliver interest savings of up to 40%.This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis.Funding: This work was supported by the Economic and Social Research Council [Grants ES/K002201/1, ES/N018192/1, ES/P008976/1, and ES/V004867/1] and the Leverhulme [Grant RP2012-V-022]. H. Sakaguchi acknowledges PhD studentship funding from the Economic and Social Research Council [Award 1499648].Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2020.01995 .

Upfront Commitment in Online Resource Allocation with Patient Customers

2026-05-19T19:12:17+00:00

Management Science
In many online platforms like ride-sharing or grocery delivery, some demand agents can wait for a short period of time for a service if they are assured of its eventual provision within an acceptable delay. We study these “partially patient” agents in the context of an online resource allocation problem, contrasting them with impatient agents who require immediate service. We utilize a relaxed notion of competitive ratio, known as the resource/feature augmented competitive ratio, allowing online algorithms to benefit from additional features not available to the optimal offline algorithm. We introduce a class of polytope-based resource allocation (POLYRA) algorithms that achieve optimal or near-optimal competitive ratios by consulting specific polytopes and maintaining feasible algorithm states within these polytopes. For two or three types of agents, these algorithms can achieve the optimal competitive ratio. For more than three types, we present a near-optimal nested POLYRA algorithm that secures at least 80% of the optimal ratio. Our theoretical findings are supported by numerical analysis, highlighting the efficiency of our algorithms beyond adversarial arrivals and the modified competitive ratio framework.This paper was accepted by Chung Piaw Teo, optimization and decision analytics.Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03335 .

Owner Support for Green Shareholder Voting and Divestment

2026-05-19T19:12:17+00:00

Management Science
This paper examines the preferences of 10,000 capital owners worldwide, including nearly 3,000 from the world’s largest sovereign wealth fund, regarding green shareholder voting and divestment. Findings indicate substantial support (53%–72%) for shareholder engagement and green voting, which is more popular and less politically divisive than divestment. Preferences for green voting increase with the likelihood of green outcomes being implemented though 63% of the payoff is attributed to expressive benefits. These results suggest that shareholder engagement and green voting could play a central role in a broader climate strategy portfolio.This paper was accepted by Caroline Flammer, sustainability.Funding: This work was supported by The Norwegian Finance Market Fund (Finansmarkedsfondet).Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.08186 .

Does Trading Spur Specialization? Evidence from Patenting

2026-05-19T19:12:17+00:00

Management Science
We study how the market for technology (facilitated by the establishment of patent exchanges in China) affects innovation specialization. We find that the market for technology induces (i) specialization between patent buyers and sellers, (ii) specialization between patent licensors and licensees, and (iii) specialization based on a firm’s research and development efficiency. All these three specialization patterns indicate that the market for technology promotes comparative advantage–based innovation specialization. Firms with a comparative advantage in creating innovation redirect their resources toward producing patents, whereas firms with a comparative advantage in commercializing innovation switch their effort toward launching new products. A firm also shrinks its scope of innovation and invents in technological fields with greater proximity. Financial friction hampers innovation specialization and relieving trading friction in the market for technology mitigates such negative consequences.This paper was accepted by Lin William Cong, finance.Funding: P. Han acknowledges financial support from the China’s Natural Science Foundation [Grant 72103003]. C. Liu acknowledges financial support from the China’s Natural Science Foundation [Grant 72202034]. X. Tian acknowledges financial support from the China’s Natural Science Foundation [Grant 72425002].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03174 .

Wholesaler Execution Quality

2026-05-19T19:12:17+00:00

Management Science
We obtain a proprietary data set of all marketable orders routed to one or more wholesalers in May 2022 to study wholesaler execution quality. Contrary to conventional wisdom, external liquidity is used to fill 28.6% of the shares in our sample. We find that order size, both absolute and relative to book depth, and recent order imbalance are associated with the decision to source external liquidity. Using a new benchmark, we find the value of both price and size improvement provided to sample orders is 6.5 times greater than the value of price improvement as measured by mandatory monthly Rule 605 reports. Our results indicate that price improvement is not the only measure that should be used when evaluating the relative benefits of the current market structure to alternatives.This paper was accepted by Agostino Capponi, finance.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.04156 .

Does Personalized Pricing Increase Competition? Evidence from NIL in College Football

2026-05-19T19:12:17+00:00

Management Science
We investigate the impact of personalized pricing through Name, Image, and Likeness (NIL) rights within college athletics on the recruitment of high school football players by college programs. We focus on whether the new policy disrupts competitive balance by increasing the concentration of talent among top-ranked institutions. Using a data set that encompasses pre- and post-NIL recruitment patterns to examine the distribution of 3, 4, and 5* recruits at college football programs, we find a notable increase in the dispersion of talent. Contrary to the hypothesis that NIL would lead to a “rich get richer” dynamic, we observe a tendency for lower-ranked football programs to attract higher-quality recruits post-NIL, especially among 5- and lower ranked 4* athletes. Furthermore, we show that post-NIL 3* recruits are sacrificing schooling for NIL money and are attending colleges that are less selective and have lower SAT class averages and whose graduates earn a lower midcareer income. We also do not find evidence that schools that spend more money on football are attracting better talent post-NIL. Competitiveness improves post-NIL as sportsbooks set smaller point differentials even after controlling for talent, performance, and the transfer portal. Ultimately, this study offers a comprehensive examination of NIL’s short-term effects on competitive balance and sets the stage for ongoing research into the long-term consequences of this landmark policy change.This paper was accepted by Duncan Simester, marketing.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.06423 .

Active Liquidity Management, Strategic Complementarities, and Market Price of Liquidity

2026-05-19T19:12:17+00:00

Management Science
This paper examines how market uncertainty impacts the liquidity premium through a demand-side channel. I find that equity mutual funds actively increase the liquidity of their portfolios in response to increased redemptions during market stress. Liquidity preservation is more intense for funds more exposed to strategic complementarities. I show that a stock’s relative illiquidity within a fund’s portfolio is a key determinant in flow-induced rebalancing decisions, whereby funds follow a liquidation “pecking order.” This “flight-to-liquidity” is associated with increases in the liquidity premium and affects individual stocks’ reversal performance: Stocks held by more fragile funds and those with higher illiquidity ranks within funds’ portfolios experience greater returns to liquidity provision during market stress.This paper was accepted by Victoria Ivashina, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02095 .

Infrastructure Investment with Public and Private Product Development

2026-05-19T19:12:17+00:00

Management Science
Private firms often develop new products by utilizing substantial infrastructure investments made by government agencies. We construct a mixed oligopoly model to study the interactions between the government’s infrastructure quality decision and the subsequent public and private product development decisions. We have five main results: First, the government permits firm entry in the product market only when the firm is sufficiently more efficient at product development than the government. With firm entry, the government invests more in developing infrastructure because the firm’s presence increases the government’s return on investment in infrastructure. Second, the quality received by the consumer might improve or worsen in the presence of a private firm, depending on the relative product development efficiency as well as the cost of infrastructure development. Third, private presence can lead to a significant reduction in consumer surplus, especially at the lower end of the market. This happens when infrastructure investment cost is high, because the small increase in infrastructure quality with firm entry is not enough to compensate for the reduction in the government’s product quality. Fourth, depending on the relative product development efficiency of the private firm, the government might implement policies that prevent the private firm from entering the market. Finally, there exist circumstances under which private presence can be beneficial in that it leads to products that not only enhance social welfare but also improve overall consumer surplus.This paper was accepted by Raphael Thomadsen, marketing.Funding: S. Singh was partially funded by the Johns Hopkins Catalyst Award [2023-2025].Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.01609 .

Cost-Saving Synergy: Energy Stacking in Battery Energy Storage Systems

2026-05-19T19:12:17+00:00

Management Science
Despite the great potential benefits of battery energy storage systems (BESSs) to electrical grids, most standalone uses of BESS are not economical due to batteries’ high upfront costs and limited lifespans. Energy stacking, a strategy of providing two or more services with a single BESS, has been of great interest to improve profitability. However, some key questions, for example, the underlying mechanism by which stacking works or why and how much it may improve profitability, remain unanswered in the literature. Using two popular battery services, we analytically show that there often exists cost-saving synergy—the cost of performing both services at the same time (simultaneous stacking) is smaller than the sum of individual costs if we had performed each service alone—which allows for bigger profits. Furthermore, we perform comparative statics on the optimal mix of the services to systemically characterize grid/market conditions that maximize/minimize this synergy. We also derive a theoretical upper bound on simultaneous stacking’s benefits, showing that it can approximately double the profit of the best standalone service. Several generalizations of the base model not only show that the main lessons continue to hold but also that stacking’s benefits may become even stronger.This paper was accepted by Jayashankar Swaminathan, operations management.Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03477 .

A Theory of the Effects of Privacy

2026-05-19T19:12:17+00:00

Management Science
The growth of information technologies has intensified concerns about individual privacy and highlighted the importance of consumer privacy rights. At the same time, these technologies enable significant personalization of communications and offerings. We develop a theory of the effects of privacy based on the concavity of an individual’s derived payoff function with respect to market beliefs: When this function is concave, privacy is valuable. We identify market conditions that lead to concavity or convexity in the derived payoff function. The framework is applied to contexts such as product choice, price discrimination, data breaches, and health insurance.This paper was accepted by Raphael Thomadsen, marketing.Funding: A. Bonatti acknowledges financial support through the National Science Foundation [Grant SES-1948692].Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.05354 .

Fundamental Pricing of Utility Tokens

2026-05-19T19:12:17+00:00

Management Science
We propose a framework for the fundamental valuation of utility tokens. We introduce a requirement that is reminiscent of the cash-in-advance constraint, stipulating that services have to be accessed immediately. Our model endogenizes the velocity of token circulation, yielding a microfounded pricing formula that we calibrate using Ethereum’s adoption data. The equilibrium price path goes through two successive phases: initially, a portion of the tokens are held for purely speculative motives, and later on, all tokens are held with the intention of being used.This paper has been This paper was accepted by Will Cong for the Virtual Special Issue on Digital Finance.Funding: This project has benefited from the financial support of the academic chair Blockchain@Polytechnique. This research has been conducted as part of the project Labex MME-DII [ANR11-LBX-0023-01].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00566 .

How Do Taxes Affect the Trading Behavior of Private Investors? Evidence from Individual Portfolio Data

2026-05-19T19:12:17+00:00

Management Science
The removal of an intertemporal tax discontinuity in Germany provides us with a natural experiment to study the causal effect of taxes on individual stock-trading behavior and the disposition effect. Using individual investor transactions data combined with nonparametric regressions and bunching methods, we find that the presence of the tax discontinuity induces investors to adjust their holding periods, which reduces their effective tax rate by 11.3%. We also find that tax effects dominate the disposition effect in the days around the discontinuity and can inhibit it (by about 20%) during the six months preceding the discontinuity. We discuss the consequences of our results for the firms whose stocks are traded and policy implications.This paper was accepted by Camelia Kuhnen, finance.Funding: F. Buhlmann gratefully acknowledges financial support by MannheimTaxation ScienceCampus.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.04213 .

Natural Disasters, Financial Shocks, and Human Capital

2026-05-19T19:12:17+00:00

Management Science
We examine effects on productivity, employment, and debt outcomes among college students whose parents reside in areas that experience financial shocks caused by natural disasters. After shocks, treated students exhibit poorer academic performance. To boost the impaired grade point average, these students sacrifice educational content by withdrawing from more courses and enrolling in fewer STEM (Science, Technology, Engineering, Mathematics) courses. Effects are stronger for middle class students likely relying on family income to pay for college. Students mostly mitigate financial shocks with additional part-time employment. Ultimately, disrupted students are 10% more likely to default on student loans. Overall, these results shed light on the effects of financial stress on the intensive margin of human capital formation.This paper was accepted by Camelia Kuhnen, finance.Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.02977 .

The Adoption of Central Bank Digital Currency

2026-05-19T19:12:17+00:00

Management Science
We investigate the adoption of Central Bank digital currency (CBDC) in a partial equilibrium setting, focusing on four key features: remuneration, monetary incentives, interoperability, and architecture. Agents are interested in adopting CBDC because they have a preference for digital payments, and the Central Bank may incentivize adoption through subsidies and platform development, potentially in collaboration with the private sector. Our results demonstrate that both the remuneration scheme and monetary incentives significantly influence the adoption rate and transaction volume. Calibrating the model for the digital euro case study, we show that the target of 60% of the population using CBDC can be achieved, provided that platform productivity is substantially enhanced. Although this target is feasible within a one-layer architecture, it becomes significantly more challenging in a two-layer setting. CBDC is likely to win the adoption battle against stablecoins but is likely to lose it against debit cards.This paper has been This paper was accepted by Will Cong for the Virtual Special Issue on Digital Finance.Funding: This project has been partially funded by the European Union – Next Generation EU – PNRR project SERICS “Security and Rights in the CyberSpace” (PE00000014 – CUP B53C22003990006) – SPOKE 9.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.01504 .

Displaying and Discounting Perishables: Impact on Retail Profits and Waste

2026-05-19T19:12:17+00:00

Management Science
Empirical studies have shown that consumers’ purchasing behavior depends on product display, that is, how products are organized on store shelves. We explore how a retailer selling a perishable product with deteriorating quality over time can optimize product display and the discounting of soon-to-expire units to maximize profit and reduce waste. Specifically, we consider a product with a finite shelf life that is replenished periodically. The retailer optimizes the product display setting, the discount rate and timing, as well as the order quantity in each replenishment cycle. We assume that the length of the replenishment cycle is such that, at most, two different product ages can coexist on the store shelves, and we refer to these two groups of products as the fresh batch and the old batch. We show that, when the store traffic is deterministic, only the following two policies can be optimal: (i) discarding unsold units at each replenishment epoch, so that there is only one product batch on the shelves at all times, or (ii) keeping and discounting unsold old batch units but making the fresh batch units more accessible to consumers. In contrast, when the store traffic is stochastic, all possible strategies can be optimal, as waste becomes unavoidable. In particular, the optimal strategy depends on the characteristics of the product, store, and consumers. Our numerical results indicate that, compared with a benchmark where units from the fresh and old batch are equally accessible and no discount is offered, optimizing the display and the discount results in an average increase in profit of 6.01% and a decrease in (relative) waste of 21.24%.This paper was accepted by Victor Martínez-de-Albéniz, operations management.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00316 .

Enterprise Risk Management and Management Earnings Forecasts

2026-05-19T19:12:17+00:00

Management Science
Enterprise risk management (ERM) is an institutional agenda emphasizing holistic risk oversight and strategic planning. This study examines whether and how the adoption of ERM affects management earnings forecasts. We first document that ERM adoption increases the likelihood and accuracy of management earnings forecasts. We then provide evidence that ERM adoption improves forecast quality by reducing the volatility of fundamentals and enhancing managers’ ability to assess both internal and external information. Finally, we find that the positive effect of ERM in improving forecast accuracy is more pronounced for long-horizon forecasts, consistent with ERM’s long-term strategic focus. Collectively, our results shed light on how ERM adoption improves the quality of a key voluntary disclosure—management forecasts.This paper was accepted by Ranjani Krishnan, accounting.Funding: C. Li thanks the C.A. Scupin professorship at the University of Kansas, L. Sun thanks the Barney A. Coda professorship at the University of North Texas, and J. Xu gratefully acknowledges the G. Brint Ryan College of Business Summer Research Grant at the University of North Texas.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.01120 .

Tenant Riskiness, Contract Length, and the Term Structure of Commercial Leases

2026-05-19T19:12:17+00:00

Management Science
This paper explores the connection between tenant riskiness, commercial lease length, and the term structure of lease contracts. Theory shows that the possibility of default on a long-term lease generates a risk/lease-length connection. The empirical work uses a large CompStak lease data set combined with tenant characteristics (including risk) from Dun & Bradstreet (D&B). Regressions show that lease length is inversely related to the D&B risk measures, as predicted, and that risky tenants pay a higher rent premium for long-term contracts than low-risk tenants. The presence of such tenants thus raises the slope of the term structure of commercial rents.This paper was accepted by Tomasz Piskorski, finance.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.04959 .

Optimal Integration: Human, Machine, and Generative AI

2026-05-19T19:12:17+00:00

Management Science
I study the optimal integration of humans and technologies in multilayered decision-making processes. When each layer can correct existing errors but may also introduce new errors, who should have the final authority? I show that a decision maker’s correction capability normalized by its new errors is a one-dimensional quality metric that determines the optimal rule: deploying higher quality technologies in later stages. Intriguingly, despite its highest quality, the final layer may not generate the greatest error reduction; instead, its role hinges on minimizing new errors. Human effort varies asymmetrically across layers: early stages exert relatively lower effort and prioritize error correction, whereas later stages exert higher effort and focus on avoiding new errors. Applying the model to artificial intelligence (AI) reveals that AI’s generative capabilities make it more likely to serve as the final decision maker, reducing the need for costly human input at the risks of AI hallucination. The theoretical framework also extends to applications including repeated delegation, automation design, loan screening, tenure review, and other multilayer decision-making scenarios.This paper has been accepted by Will Cong for the Virtual Special Issue on AI for Business and Finance Decisions.

Product Ratings and Externalities

2026-05-19T19:12:17+00:00

Management Science
In this article, we investigate how information about production externalities, such as ecolabels, can be presented to create market pressure on firms to reduce these externalities. Specifically, we explore whether integrating information on externalities with consumer product ratings into a single combined rating can generate pressure to reduce externalities from all consumers, not just environmentally conscious ones. Theoretically, we demonstrate the existence of an equilibrium where producers invest in both high product quality and low production externalities. We show that under separate ratings, this equilibrium depends on a high proportion of “green” consumers, whereas a combined rating achieves similar results without such a requirement. More broadly, our model suggests that bundling ratings can compel producers to address niche concerns more effectively. We experimentally validate this prediction across two studies, confirming that bundling ratings significantly increases producer investment in additional attributes, such as reducing externalities, while maintaining the rating system’s ability to incentivize high product quality.This paper was accepted by Marie-Claire Villeval, behavioral economics and decision analysis.Funding: This research was financed by BI Norwegian Business School and the University of Bergen.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04684 .

Do Households React to Monetary Policy?

2026-05-19T19:12:17+00:00

Management Science
We study how households understand and respond to monetary policy by exploiting the open auctions of early-stage crowdfunding and inferring individuals’ expectations based on their maximum requested interest rates. Using loan listings from Prosper, we find that borrowers adjust their willingness-to-pay interest rates in response to unexpected Federal funds rate changes, whereas anticipated shifts have negligible effects. These responses are more pronounced among high-income, high-credit-score borrowers; large loan applicants; and when Federal Reserve communication is transparent. The responses are highly asymmetric—Borrowers sharply lower rates during unexpected easing but resist increasing them during unexpected tightening. The results are robust to alternative specifications, including regression-discontinuity-in-time designs and alternative measures of monetary policy shock. Lenders also respond to policy shocks and counteract borrowers’ adjustments. Analysis of Robinhood data shows that retail investors mirror this behavior by reducing equity holdings after surprise rate hikes.This paper was accepted by Kay Giesecke, finance.Funding: This work was supported by the general research fund from the Research Grant Council of Hong Kong [Grant 17504925], the Dean’s Research Fund of the Faculty of Liberal Arts and Social Sciences, The Education University of Hong Kong [Grant FLASS/DRF 04635], the Faculty Research Grants of Macau University of Science and Technology [Grant FRG-24-019-MSB], the Seed Funding Grant of EdUHK [Grant 02C11], and the Block Grant Blueprint of EdUHK [Grant 02A23].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04649 .

The Bright Side of Lower Quality: Evidence from Restaurant Exploration

2026-05-19T19:12:17+00:00

Management Science
The value derived from hedonic goods is affected by reference effects at the time of consumption, usually in the form of quality standards. Consumption typically involves two steps: First, the consumer chooses a given good, among a pool of available choices; then, the consumer experiences the good and derives a satisfaction from it. Between both steps, consumers might build expectations about the good that might affect the ultimate realized utility. We investigate the role of quality references in this two-stage (choice-outcome) process. We develop a flexible framework for estimating quality references and their effect in choice and outcome that can include consumers’ own past experiences, as well as that of others, and can give salience to more recent or more distant past experiences. Using novel longitudinal data from online restaurant reviews, we find evidence of quality loss aversion in the choice decision stage in accordance with prospect theory. However, in the outcome stage, we do find evidence of the opposite to loss aversion, that is, satisfaction is affected much less than one would expect when going to a lower quality restaurant. This is consistent with consumers adjusting their expectations downward and suggests that expectation adjustment protects consumers when they experience a good of lower-than-reference quality. Our results challenge the implicit assumption made by most recommendation systems that the expectation building process after making a choice does not change the outcome and imply that it may be better to patronize activities by alternating between high- and low-quality choices.This paper was accepted by David Simchi-Levi, operations management.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04141 .

An Economic Model of a Decentralized Exchange with Concentrated Liquidity

2026-05-19T19:12:17+00:00

Management Science
We develop an economic model of a decentralized exchange with concentrated liquidity (e.g., Uniswap v3 and v4), with a particular focus on the economics of liquidity provision. We demonstrate that providing liquidity for a risky/risk-free asset pool is comparable to investing in a covered call, except that the call option therein is sold at intrinsic rather than market value. Hence, when providing liquidity, liquidity providers forgo the time premium of the call option in exchange for fees, and thus equilibrium liquidity provision decreases in the time premium. Finally, we provide an expression for equilibrium liquidity provision that is useful for empirical work.This paper has been This paper was accepted by Lin William Cong for the Virtual Special Issue on Digital Finance.

Strategic Behavior by Equity Lenders

2026-05-19T19:12:17+00:00

Management Science
We document that stock lenders are informed about market conditions and pursue revenue maximization by setting premiums or offering discounts on stock loan fees. Using a model of supply and demand in the equity lending market, we illustrate the effect of stock borrowers’ private information on the elasticity of shorting demand. Strategic lenders respond to demand elasticity and increase their revenues through premiums or discounts on lending fees. Empirically, decomposing stock loan fees into intrinsic fee and premium or discount, we confirm lenders’ strategic behavior, showing that premiums and discounts among difficult-to-borrow stocks lead to increased lending revenues. This strategic lending behavior has new implications about informed shorting, short interest, and transaction costs in the equity lending market.This paper was accepted by Kay Giesecke, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03270 .

Does Q&A Boost Engagement? Health Messaging Experiments in the United States and Ghana

2026-05-19T19:12:17+00:00

Management Science
Effective information sharing is critical for the success of organizations and governments. Because information that is easy to access is more likely to be adopted, leaders often minimize friction in information delivery. However, one type of friction may increase engagement: piquing curiosity by posing relevant questions prior to sharing information. To test this, we shared identical information about COVID-19 in either question-and-answer format or via direct statements across two preregistered field experiments in Ghana and Michigan (total n = 49,395). Q&A-style communication increased information seeking about directly related topics (e.g., how to wear a mask properly) by 1.0 percentage point (216%) in Ghana and by 1.1 percentage points (19%) in Michigan (p’s < 0.001) and increased self-reported behavior change by 1.3 percentage points (4%) in Michigan (p = 0.002). However, sharing information in Q&A format did not increase interest in general COVID-19 information in either setting, suggesting that the impact of Q&A-style messaging on information seeking may be issue specific. In Michigan, both Q&A-style and direct statement messaging produced less information seeking than sending no informational messages, likely because of differential attrition: the more texts participants received, the more likely they were to opt out of receiving messages, which made it impossible for them to seek more information via text. In a follow-up implementation experiment with social media ads (a messaging strategy without attrition challenges), Q&A-style ads generated 9%–11% more unique clicks to the CDC website per dollar spent than ads that directly stated information about vaccines (p < 0.001). We speculate that Q&A-style information delivery may stimulate curiosity, driving its benefits.This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis.Funding: The authors thank the National Science Foundation [RAPID Grant 2033321], the Bill and Melinda Gates Foundation, Northwestern University’s Global Poverty Research Lab, Stanford University’s Golub Capital Social Impact Lab, Harvard Business School, the University of Pennsylvania, the AKO Foundation, John Alexander, Mark J. Leder, and Warren G. Lichtenstein for funding support. This work was also supported by Grand Challenges in Global Health.Supplemental Material: The supplementary materials and data files are available at https://doi.org/10.1287/mnsc.2024.04405 .

The Real Impact of FinTech: Evidence from Mobile Payment Technology

2026-05-19T19:12:17+00:00

Management Science
We utilize the introduction of mobile payment technology by the largest bank in Singapore in 2017 to study how mobile payment technology reshapes economic activities and stimulates business creation. After the introduction, business-to-consumer industries witnessed 18.3% more business creation relative to business-to-business industries, with the effect driven by small firms and more pronounced among industries with higher cash handling costs. Underlying this pattern is consumers’ strong adoption of mobile payment and a reduction in ATM cash withdrawals during the post-shock period. The reduced transaction cost also increases consumers’ spending capacity, which justifies the business growth. Interestingly, part of the increased consumer demand is credit card spending. The pattern of changes is consistent with the bank’s adjustment to the technological change: it reduces ATMs and allows more credit card openings and higher credit limits.This paper was accepted by Camelia Kuhnen, finance.Funding: Y. Ren received financial support from the National Natural Science Foundation of China [Grant 72303210], the Zhejiang Provincial Natural Science Foundation of China [Grant LQ24G010001], and the major project of the National Social Science Fund of China [Grant 24&ZD088]. S. Agarwal acknowledges the financial support from the National Natural Science Foundation of China [Grant 72495154].Supplemental Material: The internet appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03947 .

Individualism-Collectivism and Risk Perception Around the World

2026-05-19T19:12:17+00:00

Management Science
Understanding cultural differences in risk perception is critical in an increasingly uncertain world. Here we examine the relationship between the individualism-collectivism continuum and risk perception around the world using a data set from the Lloyd’s Register Foundation World Risk Poll. The data set contains rich information of a representative sample of 150,000 participants from 142 countries, and investigates risk perception in terms of perceived likelihood and personal experiences for a range of risks in daily life. We observe that participants from countries with a more individualistic culture perceive lower risk after controlling their personal experiences. We observe similar but weaker patterns when we adopt an epidemiological approach to investigate the individualistic cultural influence of first- and second-generation immigrants and use historical kinship tightness to proxy for individualism. Our study sheds light on the importance of culture in shaping risk perception and contributes to understanding global differences in behavioral traits.This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis.Funding: This research was supported by the Social Science Research Council (Singapore, grant number MOE2022-SSRTG-029), and National Natural Science Foundation of China (grant number 72425005).Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01612 .

It’s Not Who You Know—It’s Who Knows You: Employee Social Capital and Firm Performance

2026-05-19T19:12:17+00:00

Management Science
We show that the social capital embedded in employees’ networks contributes to firm performance. Using novel, individual-level network data, we measure a firm’s social capital derived from employees’ connections with external stakeholders. Our directed network data allow for differentiating those connections that know the employee and those that the employee knows. Results show that firms with more employee social capital perform better; the positive effect stems primarily from employees being known by others. We provide causal evidence exploiting the enactment of a government regulation that imparted a negative shock to networking with specific sectors and provide evidence on the mechanisms.This paper was accepted by Camelia Kuhnen, finance.Funding: D. Cho acknowledges the PHBS Dean’s Research Fund for financial support. L. Choi acknowledges the General Research Fund of the Research Grants Council of Hong Kong [Grant 21502018] for financial support.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.01179 .

Does the Locker Alliance Network Improve Last Mile Delivery Efficiency?

2026-05-19T19:12:17+00:00

Management Science
The Locker Alliance Network (LAN), a cutting-edge initiative under Singapore’s Smart Nation vision, aims to revolutionize parcel pickup processes. This government-led project seeks to implement two major changes in Singapore’s urban logistics: (i) establishing an open-access facility for all logistic service providers (LSPs) and (ii) enhancing the last mile delivery efficiency of each LSP, thereby reducing its operational footprint. This research investigates the impact of locker network design on the delivery efficiency of individual LSPs and explores strategies for the government to construct an inclusive network for all LSPs. Our study explores two operational modes: the two-trip mode, in which home and locker deliveries are managed separately, and the mixed-trip mode, which consolidates both into one route. We extend the Beardwood–Halton–Hammersley theorem to estimate the delivery trip length to remaining home locations, assuming consumers can choose between locker pickup or home delivery. This enables us to explicitly formulate the LAN design problem as a nonlinear optimization model. Furthermore, our models for both operational modes reveal that optimal locker network design tends to expand in a nested manner relative to the market share of an LSP. This finding suggests that governments could design locker networks based on the profiles of the largest LSP, ensuring that the expansion of these networks aligns with the existing logistics infrastructure. Leveraging data from LAN’s pilot program in Singapore, our research underscores the pivotal role of network design in last mile delivery efficiency. A poorly designed locker network can inadvertently reduce productivity by increasing the length of delivery trips, thus negating the potential benefits of the system. In contrast, an optimized network can mitigate this negative impact on delivery efficiency. Beyond network design, low customer adoption emerges as another critical bottleneck. Our findings show that, as more customers shift to locker pickup, especially in mixed-trip modes, delivery efficiency improves. Therefore, network design and a higher adoption rate of locker pickup are key to LAN’s success. The government’s role in driving deeper customer engagement, alongside efforts to optimize network design and delivery operations, is vital to unlocking the full potential of this smart nation initiative.This paper was accepted by David Simchi-Levi, operations management.Funding: This work was supported by the National Natural Science Foundation of China [Grant 72422006], the Hong Kong Research Grants Council [Grants 16210720, 16500423], the 2019 Academic Research Fund Tier 3, the Ministry of Education, Singapore [Award MOE-2019-T3-1-010], and the Natural Science Foundation of Chongqing, China [Grant CSTB2022NSCQ-MSX1667].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04567 .

The Usefulness and Limited Supply of Disclosure Accessibility

2026-05-19T19:12:17+00:00

Management Science
Firm disclosures are mostly unstructured and textual, imposing substantial processing costs on investors. We examine firms’ incentives to enhance the accessibility of these disclosures by expending resources to make them easier for investors to process. We show that an equilibrium with a positive supply of accessibility can be difficult to sustain—even though investors view accessibility as a favorable signal of firm productivity. We further explore how the supply of accessibility interacts with the quality of the numerical (easier-to-analyze) signals and textual (harder-to-analyze) disclosures. Our analysis generates predictions consistent with empirical evidence and offers a framework for evaluating policy initiatives and accounting standards aimed at improving accessibility.This paper was accepted by Ranjani Krishnan, accounting.

Forced to be Active: Evidence from a Regulation Intervention

2026-05-19T19:12:17+00:00

Management Science
Mutual funds known as closet indexers are marketed as active but actually operate as low-activity funds. Investors end up paying for full service but receiving only a part of it. Supervisory authorities around the world are considering ways to regulate these funds. In this context, we examine the impact of regulatory interventions by Scandinavian regulators. We compare the scrutinized Scandinavian funds with similar unaffected European funds. The findings suggest that the regulated Scandinavian funds preferred increased activity over fee reduction. Consequently, fund managers adopted more active management strategies, resulting in a significant 2% decrease in annual alpha. Therefore, the regulatory interventions resulted in unfavorable outcomes for investors.This paper was accepted by Bo Becker, finance.Funding: This research was supported by funding from the Varekrigsfond for forsikringsaktiviteter at NHH.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03124 .

Consequences of Resorting to Fines and Investments to Regulate Data Portability

2026-05-19T19:12:17+00:00

Management Science
Many jurisdictions have implemented data portability regulation (DPR) that requires that Data Controllers (DCs) enable users to download their personal data so that they can port their data to competing DCs. The intention of DPR is to return partial control of data to users, improve user choice of DCs, increase DC participation in the market, and reduce industry concentration. To achieve this, if nonmonetary corrective measures (e.g., warnings, orders to comply) to obtain portability compliance fail, then DPR allows policy-makers to impose fixed or variable (based on revenue) fines on DCs that do not comply. Additionally, policy-makers may invest to decrease compliance costs for DCs. We model this interaction as a two-stage game where in the first stage the policy-maker sets fines and makes investments. In the second stage DCs decide whether to participate in the market, and if so whether to comply with DPR. Contrary to the current regulatory objectives, we find that with partial compliance both fines and investments decrease DC participation and increase industry concentration. Comparing the use of fines and investment to achieve a predetermined level of compliance, the use of fixed fines has a smaller (larger) collateral effect on concentration (participation) than either variable fines or investment. Once all DCs that participate comply—full compliance—then additional investment increases participation. Moreover, full compliance and full participation can occur only if there is a DPR-induced demand expansion, such as from multihoming, and investment is the only instrument that can attain this outcome.This paper was accepted by Hemant Bhargava, information systems.Funding: This work was supported by Natural Sciences and Engineering Research Council of Canada [Grant RGPIN/06571-2015]; Social Sciences and Humanities Research Council of Canada [Grant 435-2022-0460].Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2024.08404 .

Using Social Recognition to Address the Gender Difference in Volunteering for Low-Promotability Tasks

2026-05-19T19:12:17+00:00

Management Science
Research shows that women volunteer significantly more for tasks that people prefer others to complete. Such tasks carry little monetary incentives because of their very nature. We use a modified version of the volunteer’s dilemma game to examine if nonmonetary interventions, particularly social recognition, can be used to reduce the gender gap associated with such tasks. We conduct a laboratory experiment with three treatments where (a) a volunteer receives positive social recognition, (b) a nonvolunteer receives negative social recognition, and (c) a volunteer receives positive social recognition but a nonvolunteer receives negative social recognition. Our results indicate that social recognition increases the overall probability that an individual volunteers. Positive social recognition reduces the gender gap observed in the baseline treatment, and so does the combination of positive and negative social recognition. These findings suggest that public recognition of volunteering for such tasks can change the default gender norms in organizations and increase efficiency simultaneously.This paper was accepted by Yan Chen, behavioral economics and decision analysis.Funding: This research was primarily funded by the Indian Institute of Management Bangalore [Seed Grant 7399FW].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04017 .

Vestigial Tails? Floor Brokers at the Close in Modern Electronic Markets

2026-05-19T19:12:17+00:00

Management Science
The closing auction is an increasingly important trade mechanism due to the rise of passive funds that require closing price execution. We study differences in auction mechanism design on NYSE and Nasdaq that may affect closing price efficiency. Unlike Nasdaq, NYSE allows late auction orders through its floor brokers, providing traders with more flexibility to mitigate or create large last-minute auction imbalances. Price changes in the closing auction are more likely to reverse on NYSE compared with Nasdaq, suggesting greater price inefficiency in NYSE closing auctions. Larger last-minute abnormal imbalances on NYSE, particularly in stocks where auction competition may be inhibited by relatively high floor broker auction fees, explain these stronger reversals. Evidence from the NYSE floor closure during the COVID-19 pandemic supports a causal interpretation. Our results highlight an important tradeoff between auction flexibility and price efficiency.This paper was accepted by Agostino Capponi, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00884 .

How Search Engine Impacts Market Structure: Empirical Evidence from a Multivendor Darknet Market

2026-05-19T19:12:17+00:00

Management Science
Despite the public’s familiarity with search engines, little existing research empirically investigates the impact of such a search-cost-reduction tool on online market structure. Knowledge scarcity of this question can mainly be attributed to the challenge of accessing detailed data from a cross-website search engine. Using data from the online illegal transaction platform, the Darknet markets, we manage to empirically evaluate the influence of a cross-website search engine (i.e., GRAMS) on the market structure at the vendor and product category levels. The results show that, although the search engine’s entry enhances the overall market performance, the benefit is more significant among leading vendors and popular products, contributing to a more concentrated market. Additional analyses provide empirical evidence that the trustworthiness and the scale-up ability of leading vendors can be the underlying mechanisms for the increased market concentration after the introduction of search engines into Darknet markets. Our study not only contributes to the literature on the dynamics of sales distribution in a multiple-vendor e-commerce market but also provides insights into understanding the operating dynamics of the Darknet markets, which can be helpful for law enforcement policymaking.This paper was accepted by D. J. Wu, information systems.Funding: D. Qiao acknowledges financial support from the Singapore Ministry of Education [Tier 1 Research Grant A-8001813-00-00]. S. He acknowledges financial support from the University of Florida, Warrington College of Business Summer 2022 Research Award.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04133 .

The Attention-Information Trade-Off

2026-05-01T00:00:00+00:00

American Economic Review
How does information transmission change when it requires attracting the attention of receivers? This paper combines an experiment that varies freelance professionals’ incentives to attract attention about scientific findings, with several online experiments that exogenously expose receivers to the content created. Attention incentives lead to significantly less information being transmitted, but not more factually inaccurate content. These incentives increase information demand and the knowledge of interested receivers. However, among the majority of receivers who do not demand more information, attention incentives lower knowledge and increase biases in beliefs, revealing a channel through which misperceptions can arise: missing information. (JEL C91, D83, D91)

Effects of Parental Death on Labor Market Outcomes

2026-05-01T00:00:00+00:00

American Economic Review
We use Danish administrative data to examine the effects of parental death on labor market outcomes. Leveraging the timing of sudden, first parental deaths and a matched-control difference-in-differences strategy, we find that men’s earnings decline by 2 percent, while women’s earnings decline by 3 percent following a parental death. Both women and men experience mental health deterioration, leading to increased use of psychological assistance and prescriptions for mental health conditions and opioids. Women with young children experience a comparatively larger earnings decline (around 4 percent) likely due to the loss of informal childcare. (JEL D91, I12, J13, J16, J31)

The Gender Pay Gap: Micro Sources and Macro Consequences

2026-05-01T00:00:00+00:00

American Economic Review
Using linked employer-employee data from Brazil, we document a significant gender pay gap, which is largely attributed to women working at lower-paying employers. To interpret this fact, we develop an equilibrium search model with endogenous firm pay, amenities, and hiring. We provide a constructive proof of identification of all model parameters. The estimated model suggests that amenities are important for both men and women, and that compensating differentials account for half of the gender pay gap. Equal treatment policies partly close gender gaps but are not output- or welfare-improving. (JEL E24, J16, J23, J31, J32, M51, O15)

Efficiency Criteria, Income Taxation, and Heterogeneous Elasticities

2026-05-01T00:00:00+00:00

American Economic Review
A common interpretation of Pareto-efficient policies is that, for some cardinal utility representations of preferences, they maximize utilitarian welfare. We show in the context of income taxation that such cardinalizations are often extreme, requiring unbounded curvature of utility with respect to consumption. Taxes can be justified as utilitarian without these extreme cardinalizations if and only if revenues are decreasing and concave in a class of narrowly targeted tax cuts. We reformulate this condition as a sufficient-statistics test. The test fails whenever elasticities of taxable income are too heterogeneous within some income level, as we argue is empirically likely. (JEL D81, H21, H23, H24, J22, J31)

Internal versus Institutional Barriers to Gender Equality: Evidence from British Politics

2026-05-01T00:00:00+00:00

American Economic Review
Weekly lotteries determine which politicians ask the UK prime minister a question in front of a male-dominated, noisy chamber. Lottery winners receive 4 percent higher vote margin in the next election, but women are 12 percent less likely to submit questions than same-cohort men. The gender gap does not close with lottery-induced experience asking a question, but it closes after a format change, with questions asked to a smaller, quieter audience. The switch differentially draws in women with quieter voices. Our findings support institutional change, rather than experience, as a response to gender gaps in adversarial settings like the UK Parliament. (JEL D44, D72, J16)

Social Preferences over Ordinal Outcomes

2026-05-01T00:00:00+00:00

American Economic Review
We study social preferences in settings where someone who chooses on behalf of others knows how those individuals rank the available options but may lack cardinal information concerning those comparisons. Contrary to majoritarian principles, most people place more weight on preventing least preferred outcomes for others than on enabling most preferred outcomes. Ranks matter both intrinsically and because they provide a basis for inferring cardinal utility. Ordinal aggregation principles are stable across domains and countries with divergent political traditions. Designing attractive social choice mechanisms is challenging in practice partly because aggregation principles that make manipulation difficult yield outcomes people consider normatively unappealing. (JEL C91, D71, D72)

Labor Market Competition and the Assimilation of Immigrants

2026-05-01T00:00:00+00:00

American Economic Review
This paper shows that the wage assimilation of immigrants is the result of the intricate interplay between individual skill accumulation and dynamic labor market equilibrium effects. When immigrants and natives are imperfect substitutes, rising immigrant inflows widen the wage gap between them. Using a production function framework in which workers supply both general and host-country-specific skills, we show that this labor market competition channel explains about one-fifth of the large increase in the average immigrant–native wage gap across arrival cohorts in the United States since the 1960s. The results further reveal substantial heterogeneity across different groups of immigrants. (JEL J22, J23, J24, J31, J61, K37, O33)

Production and Financial Networks in Interplay

2026-05-01T00:00:00+00:00

American Economic Review
We show that bank shocks to firms propagate along the production network with stronger upstream than downstream effects. Our identification relies on (i) administrative datasets from Spain covering supplier-customer transactions and bank loans, (ii) bank credit supply shocks from the global financial crisis, and (iii) a general equilibrium model of a production network with financial frictions, estimated structurally. We find network propagation amplifies the impact of bank shocks on GDP growth by nearly 50 percent. Moreover, bank shocks to firms’ distant suppliers and customers contribute similarly to this aggregate effect as bank shocks to firms’ direct customers and suppliers. (JEL D22, D85, E23, G01, G21, G32, L14)

The Effect of Field Training Officers on Police Use of Force

2026-05-01T00:00:00+00:00

American Economic Review
The influence of on-the-job training and supervisors, especially in high-stakes settings like policing, is poorly understood. Examining a central behavior in the debate surrounding police reform, we investigate the impact of a field training officer (FTO) on a recruit’s use of force. Leveraging a setting with conditional as-good-as-random assignment, we demonstrate a causal link between FTO and recruit use of force. A 1 standard deviation increase in FTO force propensity leads to a 14 to 18 percent rise in recruit force, persisting for at least two years. This underscores field training’s impact and reveals a promising avenue for reform. (JEL D91, J24, J45, K42, M53)

Conservation Priorities and Environmental Offsets: Markets for Florida Wetlands

2026-05-01T00:00:00+00:00

American Economic Review
We introduce an empirical framework for valuing markets in environmental offsets. Using newly collected data on wetland conservation and offsets, we apply this framework to evaluate a set of decentralized markets in Florida, where land developers purchase offsets from long-lived producers who restore wetlands over time. We find offsets led to substantial private gains from trade, creating $2.4 billion of net surplus from 1995 to 2020 relative to direct conservation. Offset trading also generated new hydrological externalities. A locally differentiated Pigouvian tax would have prevented $1.6 billion of new flood damage while preserving more than two-thirds of the private gains from trade. (JEL D47, D62, H23, Q24, Q54, Q57, R14)

Getting aggressive abroad through CEO and outside director stock options: An incentive‐based view of post‐entry internationalization pace of young entrepreneurial post‐IPO firms

2026-05-10T00:00:00+00:00

Strategic Entrepreneurship Journal
This study develops an incentive‐based view to examine the internationalization pace of young entrepreneurial firms after they have completed an IPO and expanded abroad for the first time. Using a sample of U.S. young entrepreneurial post‐IPO firms that internationalized from 2005 to 2020, we find that the pace of internationalization increases when CEOs are compensated with more stock options and that this relationship is weakened when the stock option compensation of independent outside directors increases. By showing that incentives of different agents shape how fast young entrepreneurial firms internationalize, this study extends international entrepreneurship research by relaxing the implicit assumption that young entrepreneurial post‐IPO firms that can internationalize fast will do so.Managerial SummaryWhat determines the internationalization pace of young entrepreneurial firms after they have already completed an IPO and expanded abroad for the first time? Our research finds that the internationalization pace of these firms increases when the CEO is compensated with more stock options. Absent CEO stock options, stock option compensation of independent outside directors provides a substitute through monitoring and advocacy for faster internationalization. Our research highlights that young post‐IPO firms that can internationalize fast will not necessarily do so, stressing the distinction between the firm resources needed for a strategic action and top management motivation to pursue that action.

Toward Faster Recalls of Dangerous Medical Devices: Does Ownership by Large Institutional Investors Matter?

2026-05-10T00:00:00+00:00

Journal of Operations Management
Recall delays expose consumers to prolonged risk and undermine a firm's long‐term performance and reputation. Building on agency theory's conceptualization of principal‐agent relationships, we theorize that large institutional investors play an important monitoring role wherein their ownership encourages faster recalls. We then build on agency theory's core dimension of information asymmetry to examine whether R&D intensity and device class moderate this influence. Using a matched sample of 2932 medical device recalls involving severe defects across 69 firms from 2002 to 2020, we find that greater ownership by large institutional investors is associated with faster recalls such that a 1% increase in ownership yields a 24‐day reduction in time‐to‐recall. This relationship is weakened by increases in R&D intensity and for high‐risk devices. Our study highlights the importance of considering how operations management phenomena are influenced by large institutional investors, and we identify both firm‐ and device‐level pathways that moderate this influence. While managers, policymakers, and regulators may be wary of the influence that large institutional investors have, our findings offer a previously unidentified benefit: faster recalls.

The Dynamics of Verification when Searching for Quality

2026-05-11T00:00:00+00:00

Review of Economic Studies
An agent samples projects over time, observing quality for each, while a principal can select at most one. The principal values quality, whereas the agent only wants a project chosen. Transfers are unavailable, but the principal can verify quality by paying a cost. We fully characterize the dynamics of verification by determining optimal mechanisms for this problem. With a low verification cost and a long horizon, the optimal mechanism involves a deterministic selection rule that initially discriminates on quality but chooses a project irrespective of its quality at a deadline. Verification occurs with an intermediate probability before the deadline, declining over time. We show how these conclusions change if the verification cost is high or the horizon is short, and under certain forms of imperfect commitment. Our analysis provides guidelines on how dynamics interact with the benefits of verification.

Counterfactual Analysis for Structural Dynamic Discrete Choice Models

2026-05-11T00:00:00+00:00

Review of Economic Studies
Discrete choice data allow researchers to recover differences in utilities, but these differences may not suffice to identify policy-relevant counterfactuals of interest. In fact, in the case of dynamic discrete choice models, only a narrow set of counterfactuals are point-identified. In this paper, we explore how much one can learn about counterfactual outcomes of interest within this framework. We focus on the partial identification of counterfactuals, while allowing for (mild) model restrictions that can gradually shrink the identified set. We derive bounds for low-dimensional objects (such as average welfare) as arguments of optimization programs, along with a uniformly valid inference procedure. Furthermore, we develop new and tractable computational tools and algorithms suitable for dealing with high-dimensional problems like this. Finally, we illustrate in Monte Carlos, as well as an empirical exercise of firms’ export decisions, the informativeness of the identified sets, and we assess the impact of (common) model restrictions on results.

Praying for Rain

2026-05-11T00:00:00+00:00

The Quarterly Journal of Economics
We study rainmaking as an instrumental religious belief. We present a model in which a religious leader tries to persuade people to believe. Praying for rain can persuade only where the hazard of rainfall during a dry spell is increasing over time, so that prayer is most likely to succeed when people most want rain. We present evidence from prayers for rain in Murcia, Spain, where the hazard rate is increasing, that the church’s prayers for rain predict rainfall over two centuries. To generalize this finding, we gather an original data set of whether ethnic groups around the world traditionally prayed for rain. We find that ethnic groups facing an increasing rainfall hazard are 47% more likely to pray for rain, consistent with our model’s prediction that societies are more likely to pray for rain where prayer is persuasive.

EXPRESS: Information Sharing and Manufacturer Rebate Competition

2026-05-11T00:00:00+00:00

Production and Operations Management
We investigate the incentive for a retailer to share private demand information with two rebate-offering manufacturers who sell substitutable products through the retailer. We show that the retailer's incentive to share information depends on the proportion of rebate-sensitive consumers, the competition intensity, and whether the retailer can charge a side payment for sharing the information. When the retailer cannot charge a side payment, we show that he will not voluntarily share information with a monopolistic manufacturer, but he may do so with none, one or both of the manufacturers when there is competition. Interestingly, we find that more intense competition or a smaller proportion of rebate-sensitive consumers may benefit a manufacturer if it induces the retailer to share information with her. When the retailer can charge a side payment, we consider the two cases when he either contracts concurrently or sequentially with the manufacturers for sharing the information. We show that the retailer always prefers concurrent contracting, which induces the system-optimal information sharing decision, over sequential contracting.

EXPRESS: Economics of Smart Products with Machine Learning

2026-05-11T00:00:00+00:00

Production and Operations Management
Driven by advances in machine learning (ML), smart products improve over time through data-driven insights as ongoing user interactions generate usage data that enable the training, evaluation, and refinement of underlying algorithms. However, when firms implement strategies to collect more data to enhance product quality and profits, they must also consider strategic consumer behavior that may lead to unintended negative consequences. Specifically, consumers may intentionally postpone purchases in the early stages of a product’s development, anticipating future quality improvements and price reductions, which in turn complicates data collection during this critical period. Considering advancements in disruptive technologies, this study examines the critical yet underexplored economic impact of ML on pricing strategies. Few studies have focused on how ML influences profit maximization in the presence of strategic consumers. To address this gap, we develop two-period game-theoretic models that employ two dynamic pricing strategies, responsive versus preannounced pricing, to investigate how firms developing smart products adapt to the disruptive impact of ML, considering the behavior of strategic consumers. Our study provides several significant implications. First, we find that ML impacts firms’ profits by impacting consumers’ strategic behaviors in opposite directions. Second, under both dynamic pricing strategies, prices may initially be low and may either rise or decline over time. Third, we demonstrate that, different from findings in the existing literature on strategic consumer behavior, preannounced pricing policies are generally not optimal for the firm when its ability to leverage ML is relatively limited, and consumers are less strategic. Overall, this study makes three contributions to the literature. First, we clarify the impact of ML on a smart product firm’s profit. We find two effects in the application of ML: 1) a positive effect associated with ML (the “ML+effect”) and 2) a negative effect (the “ML−effect”). Second, this study highlights a fundamental economic mechanism for smart products in the presence of strategic consumers. Finally, it provides a decision-making tool for smart product firms to select an optimal dynamic pricing strategy.

Assortment Optimization with Replacement Options for Retail Platforms with Stockout Risk

2026-05-11T00:00:00+00:00

Operations Research
A Smarter Way to Plan for StockoutsOnline retail platforms increasingly face a basic operational problem: a product that appears available when a customer places an order may be out of stock when the order is fulfilled. This paper shows how platforms can respond more effectively by optimizing not only the set of products shown to customers, but also the replacement options offered when stockouts occur. The authors study both non-adaptive and adaptive approaches, where the latter tailors replacement choices to the customer’s initially selected item. They show that both problems are computationally challenging, but develop approximation algorithms with strong performance guarantees. Using Instacart data, they find that explicitly modeling replacement options improves expected revenue, and that adaptive replacement assortments provide additional gains, especially in categories with higher stockout risk. This news story is based on the accepted paper by Mitrofanov, Topaloglu, and Wang, “Assortment Optimization with Replacement Options for Retail Platforms with Stockout Risk”.

Functional vs. Cross-Functional Teams and the Role of Productive Heterogeneity

2026-05-11T00:00:00+00:00

Management Science
An emerging body of research on teams highlights the importance of implicit incentives for cooperation and/or collusion that rely on mutual monitoring among team members. Whereas prior research on mutual monitoring in team production settings typically assumes that agents have identical abilities, this paper examines how such incentives operate when team members differ in their productive abilities. We show that the role of productive heterogeneity depends on the nature of team production. In cross-functional teams, collusion does not arise, and productive heterogeneity does not alter the qualitative nature of cooperative incentives. In functional teams, heterogeneity introduces additional (binding) constraints that ensure that both more and less productive agents are motivated to cooperate. However, when collusion among team members is a concern, productive heterogeneity can be advantageous. The optimal means of preventing collusion in functional teams is to employ asymmetric contracts, where the more productive agent receives higher-powered collusion-proof incentives. Asymmetric contracts shift effort away from the more productive agent under potential collusion, which reduces the agents’ joint gains from collusion. Productive heterogeneity is advantageous in functional teams when there is a high degree of productive substitutability and/or a high discount factor. These conditions lead to a severe collusion problem, which is mitigated by productive heterogeneity. When the productive substitutability and/or the discount factor are low, the optimal productive heterogeneity is either small or none. We also study optimal team design, allowing the principal to choose between a functional team and a cross-functional team and the optimal level of productive heterogeneity.This paper was accepted by Ranjani Krishnan, accounting.Funding: E. Kim acknowledges financial support from a PSC-CUNY Award [Cycle 56], jointly funded by the Professional Staff Congress and The City University of New York.

Regurgitative Training: The Value of Real Data in Training Large Language Models

2026-05-11T00:00:00+00:00

Management Science
What happens if we train a new large language model (LLM) using data at least partially generated by other LLMs? The explosive success of LLMs means that content online will increasingly be generated by LLMs rather than humans, which inevitably enters the training data sets of next-generation LLMs. In this paper, we study the implications of such “regurgitative training” on LLM performance. Starting with the machine translation task (a representative language task with well-established evaluation criteria), we fine-tune LLMs with data generated either by themselves or by other LLMs, and we find strong evidence that regurgitative training handicaps the performance of fine-tuned LLMs. A comparison between LLM-generated data and real data reveals suggestive evidence that higher error rates and lower lexical diversity in LLM-generated data may be at play. Accordingly, we propose and evaluate three strategies to mitigate the performance loss by (i) prioritizing high-quality LLM-generated data, (ii) mixing data generated by multiple LLMs, and (iii) prioritizing LLM-generated data that most resemble real data. All three strategies can improve the performance of regurgitative training to some extent but cannot fully close the gap from training with real data. This highlights that real, human-generated data cannot be easily substituted by LLM-generated data in training LLMs. Additionally, we investigate regurgitative training on a creative ideation task with human judgement-based evaluations. Interestingly, we find that preference-based fine-tuning with human feedback on LLM-generated ideas can actually improve ideation performance. This showcases that human preference data when combined with LLM-generated data can bring performance gains.This paper was accepted by Hemant Bhargava, information systems.Funding: This work was supported by the National Natural Science Foundation of China [Grants 72421001 and 72172070] and the Singapore Ministry of Education Academic Research Fund Tier 2 A-8003504 [Robert Brown Promising Researcher Award MOE-T2EP40].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07005 .

Combating Excessive Overtime in Global Supply Chains: The Workforce Perspective

2026-05-11T00:00:00+00:00

Management Science
Suppliers operating in developing economies may resort to compelling their workforce to engage in excessive overtime, resulting in severe physical and mental health issues for workers and the potential for significant damage to the brand image of multinational enterprises (MNEs) if these practices are exposed to the public. In this paper, we develop a game-theoretic model of a dyadic supply chain to analyze a manufacturer’s operational strategies to combat the use of excessive overtime by a supplier. These strategies encompass a stick strategy of auditing the supplier’s practice (i.e., the auditing strategy) and carrot supplier development strategies of subsidizing the supplier’s workforce retention initiative (i.e., the workforce retention subsidy strategy) and upskilling the supplier’s workers to increase their versatility (i.e., the cross-training strategy). When auditing stands as the sole viable strategy, it can effectively mitigate the supplier’s violation behavior only when the auditing accuracy is significant. In the scenario where both workforce retention subsidy and auditing are viable, interestingly, workforce retention subsidy may be a complement for auditing, contrary to the naive belief that the strategies are always substitutes in combating excessive overtime. Compared with the case when auditing is the sole viable strategy, we find that workforce retention subsidy may increase the manufacturer’s profit and reduce the supplier’s overtime simultaneously. However, the subsidy may also backfire, increasing the expected degree of excessive overtime and decreasing social welfare, when workforce retention subsidy and auditing are substitutes. Furthermore, the workforce retention subsidy could lead to a social welfare level that is even higher than that in a centralized supply chain benchmark without the workforce retention subsidy. In situations where both cross-training and auditing are viable, cross-training may also be a complement for auditing, driven by the enhanced flexibility of the workforce. However, similar to the workforce retention subsidy, cross-training may lead to a win-win outcome or backfire.This paper was accepted by Jayashankar Swaminathan, operations management.Funding: C. Jiao was partially supported by the National Natural Science Foundation of China [Grants 72301261, 72531009, 72188101, 72471218] and the China Scholarship Council.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03852 .

Portfolio Dynamics and the Supply of Safe Securities

2026-05-11T00:00:00+00:00

Management Science
I study dynamic portfolio rebalancing in Collateralized Loan Obligations (CLOs) by developing an industry equilibrium model of nonbank lending, in which CLOs and loan funds arise endogenously in response to a premium for safe securities. When loans deteriorate after issuance, CLOs rebalance their portfolios to maintain collateral quality, which protects senior tranches at the expense of equity investors. This “self-healing” mechanism lowers CLOs’ ex ante funding costs by enabling the issuance of larger safe tranches. As more lenders operate CLOs, their portfolio rebalancing generates greater nonfundamental price pressures, incentivizing other lenders to operate loan funds. Overall, portfolio dynamics facilitate risk sharing across nonbank lenders and increase both total lending and the supply of safe securities relative to static portfolios.This paper was accepted by Lukas Schmid, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07100 .

Personalized Pricing in the Presence of Privacy Concerns

2026-05-11T00:00:00+00:00

Management Science
We study firms’ incentives to adopt a tracking technology to collect personal data that enable personalized pricing in an online market where some consumers have innate desires for privacy. In a model where two differentiated goods are sold under two different market structures (monopoly and duopoly), we find that the presence of these privacy-sensitive consumers alters the firms’ incentive to adopt personalized pricing. In particular, no firm uses personalized pricing in equilibrium if the proportion of privacy-sensitive consumers in the market is high. Competition, however, leads to wider use of personalized pricing. Privacy regulation that gives consumers control over whether a firm can track their online activities has the intended impact of protecting consumer privacy only if the proportion of privacy-sensitive consumers is low. Otherwise, the regulation makes the use of tracking technology more widespread. A key force that drives these results is the inability of a monopolist to commit to personalized prices that will give privacy-sensitive consumers a nonnegative net surplus. This deters these consumers from purchasing from the firm. If the proportion of privacy-sensitive consumers is high, the risk of losing these consumers induces the monopolist to adopt uniform pricing. Under duopoly, competition between firms alleviates the impact of the commitment problem because the rivals undercut each other’s prices. Privacy regulation also mitigates this impact because a firm can credibly commit to offering a uniform price to those consumers who reject tracking. Consequently, both competition and privacy regulation lead to increased use of tracking technology.This paper was accepted by Raphael Thomadsen, marketing.Funding: Z. Chen acknowledges financial support from the Social Sciences and Humanities Research Council of Canada [Grant 435-2019-0866].Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2024.07170 .

EXPRESS: Ad Intensity Policies and Content Provision on Revenue-Sharing Content Platforms

2026-05-11T00:00:00+00:00

Journal of Marketing Research
Online content platforms monetize user engagement through advertising and share ad revenue with content creators to incentivize content provision. A central design decision for these platforms is the choice of ad intensity policy, which governs how advertising load is determined and shapes creator incentives, content quality, consumer consumption behaviors, and platform profitability. We analyze a model with one platform and two competing content creators to study three ad intensity policies:differentiated advertising(DA),uniform advertising(UA), andcreator-set advertising(CA). With symmetric creators and quality-independent marginal ad revenue, UA intensifies quality-based competition among creators and leads to higher revenue-sharing rate, content quality, advertising intensity, and platform profit than DA. Creators benefit more from UA than DA when creator substitutability is low, but may prefer DA when substitutability is high. Compared to DA, CA weakens incentives for content investment, resulting in lower content quality, lower ad intensity, and reduced platform profit; its effects on creators and consumers depend on the degree of creator substitutability. Extensions show that relaxing the benchmark assumptions—such as allowing for creator asymmetry or quality-dependent marginal ad revenue—can overturn UA’s advantage and make DA more profitable, highlighting that no single ad intensity policy is universally optimal.

EXPRESS: Global Ride-Hailing Platform Affordances and Developing Market Characteristics

2026-05-11T00:00:00+00:00

Journal of Marketing
Ride-hailing platforms are expanding globally, making inroads into developing markets. However, the technological affordances of many ride-hailing platforms were built in response to conditions in developed markets. Unlike developed markets, developing markets are characterized by infrastructural deficiencies, informality, and regulatory voids, which influence how consumers in these markets experience and use ride-hailing platforms. How do the affordances of ride-hailing platforms from developed markets shape the platform’s performance when utilized in developing markets? We explore this question using a qualitative ethnographic approach to examine Uber’s operation in Ghana, engaging with drivers, riders, investors, Uber executives, and government officials. We find that Uber’s platform performance in Ghana is shaped by three platform-market interaction outcomes: platform-infrastructural deficiencies, (in)formalization, and affordance-based regulation. These interaction outcomes affect the platform’s performance and manifest platform-market tensions. Market actors respond to the resulting platform performance with acceptance, avoidance, adaptation, substitution, resistance, brand responsibilization, and subversion. These insights contribute to research on the sharing economy, marketing in developing markets, and affordance theory. They also help ride-hailing managers understand how their platforms’ affordances work in other developing markets with similar characteristics, and how they can manage the resulting platform performance and tensions to succeed in these markets.

EXPRESS: Cushioning the Blow: Reducing Customer Attrition in Response to Price Increase Notifications

2026-05-11T00:00:00+00:00

Journal of Marketing
Price increases can elicit a range of negative customer responses, from dissatisfaction to complaints, exits, and even boycotts. Practicing managers and academics agree that firms must justify their price increases, and consider three justification types—cost, market, and quality—as the primary means to do so. Yet, the comparative effectiveness of these justifications in reducing customer attrition remains unknown. The authors collaborated with a multi-site Canadian storage provider to design and implement three experiments. Study 1 is a randomized field experiment involving 10 cohorts of 1,626 actual customers, demonstrating the effects of cost, market, and quality justifications on customer attrition, and variations in these effects across levels of justification concreteness, and price increase percentage and dollar amount. In marked contrast to prior practitioner recommendations and academic research, market justification is found to result in the lowest customer attrition. The authors use heterogeneity in the effects of the justifications to demonstrate that customers’ switching costs perceptions explain this finding. Studies 2 and 3 are online scenario experiments that further examine how these justifications affect customers’ switching costs and fairness perceptions. Together, these studies provide important insights to firms seeking to “cushion the blow” of price increases.

EXPRESS: The Impact of Legal Protection of Trade Secrets on Advertising Spending: Insights from the Recognition of the Inevitable Disclosure Doctrine

2026-05-11T00:00:00+00:00

Journal of Marketing
Protecting trade secrets is important for firms and policymakers because they are critical assets for firm performance and valuation. Extant research, however, seldom examines whether increases in trade secret protection have an impact on firms’ marketing actions to leverage their trade secrets, even though trade secret protection has limited value if firms cannot leverage them. Drawing on the attention-based view of the firm, this study proposes that stronger protection of trade secrets is likely to lead to higher managerial attention to leveraging trade secrets, resulting in higher advertising spending. The study tests this proposition by exploiting the staggered recognition of the inevitable disclosure doctrine (IDD) by U.S. state courts, a legal development that protects trade secrets by restricting employee movement to rival firms. The results show that firms headquartered in states that recognize IDD significantly increase their advertising spending. Consistent with the proposed contingency framework, the results also show that the positive effect of IDD recognition on advertising spending is weaker for firms with CEO duality but stronger for younger firms and firms in industries with higher peer advertising spending. Post hoc analyses show that increases in advertising spending following IDD recognition are associated with higher firm sales.

Historical Perspectives on Deglobalization's Drivers, Outcomes, and Managerial Responses

2026-05-11T00:00:00+00:00

Journal of Management Studies
The deglobalization process experienced in the early 2020s is not without precedent. This Special Issue leverages business history as a lens to generate new insights and to uncover previously hidden complexities and nuances. Studying previous periods of deglobalization and their varying drivers, outcomes, and responses, the papers in this Special Issue show how firms and individuals are more active in shaping deglobalization processes than commonly assumed, and that deglobalization is a periodical and uneven phenomenon. The Special Issue also points to exciting avenues for future research, not least to more fully understand the antecedents of deglobalization, and under what conditions possible drivers of deglobalization indeed translate into state action causing deglobalization.

The Equilibrium Effects of Eviction Policies

2026-05-11T00:00:00+00:00

The Journal of Finance
I propose a dynamic equilibrium model of rental markets that endogenously gives rise to defaults on rents and evictions. In the model, eviction protections make it harder to evict delinquent renters, but higher default costs to landlords increase equilibrium rents. I quantify the model using micro data on evictions, rents, and homelessness. I find that stronger eviction protections exacerbate housing insecurity and lower welfare. The key empirical driver of this result is the persistent nature of risk underlying rent delinquencies. Rental assistance reduces housing insecurity and improves welfare because it lowers the likelihood that renters default ex ante.

Risk‐Free Rates and Convenience Yields around the World

2026-05-11T00:00:00+00:00

The Journal of Finance
We infer risk‐free rates from index option prices to estimate safe asset convenience yields in 10 G11 currencies. Countries' convenience yields increase with the level of their interest rates, with U.S. convenience yields fifth largest. During financial crises, convenience yields grow, but the difference between United States and foreign convenience yields generally does not. Covered interest parity (CIP) deviations using our option‐implied rates are a similar size between the United States and each other country. A model in which convenience yields depend on domestic financial intermediaries, but CIP deviations reflect the funding costs of international arbitrageurs financed with dollar‐denominated debt, explains these results.

Effectively communicating uncertainty: The persuasive impact of different types of hedges

2026-05-11T00:00:00+00:00

Journal of Consumer Psychology
Communicators often hedge. Consumers say a restaurantmighthave good mimosas or that a product isprobablythe best while Amazon suggests moviesthey thinkyou'll like. But might these different hedges have different effects on persuasion? We suggest that (1) whether a hedge takes a personal (vs. general) perspective and (2) the likelihood suggested by a hedge both play important roles in determining hedging's persuasive impact. A multi‐method investigation combining experiments with machine learning of millions of online reviews supports these hypotheses. Together, they demonstrate that the effects of both hedge perspective and hedge likelihood are driven by a common mechanism: perceived confidence. Hedges that involve personal perspective or higher likelihood increase persuasion because they suggest communicators are more confident. Moreover, we demonstrate that hedging can protect communicators from backlash without sacrificing persuasive impact and highlight that brands can leverage hedging's persuasive impact when speaking through anthropomorphized agents. This work contributes to the literature on language in marketing, showcases how subtle linguistic features impact perceived confidence, and has clear implications for anyone trying to be more persuasive.

Incidence, Risk, and Disclosure of Corporate Litigation: Insights from Federal Court Filings

2026-05-11T00:00:00+00:00

Journal of Accounting Research
We assemble and describe a sample of 174,782 lawsuits filed against 218,437 public‐company lawsuit‐defendants in federal district court from 2006 to 2021. These lawsuits involve an array of allegations, including product liability, civil rights discrimination, contract breaches, improper compensation and labor practices, antitrust violations, corruption, securities violations, pollution, and intellectual property infringement. The sample exhibits rich variation across firms, industries, time, suit type, plaintiffs, and outcomes—reflecting not only firm activities but also social, political, and regulatory trends. Although many claims matter very little, some are important individually or in aggregate. We observe 23% of defendants experience a market value decline exceeding 10% of current assets around the lawsuit filing. Consistent with the notion that even low‐stakes claims, when numerous or persistent, can introduce frictions or reflect underlying issues, we find that aggregate legal exposure is associated with increased return volatility and decreased profitability. Subsequent tests indicate that materiality, public and private enforcement, and firms’ information environments (as well as other firm traits) are associated with managers’ decisions to disclose these claims. Collectively, our descriptive evidence establishes a foundation for further research into underexplored types of corporate litigation that represent a broad range of alleged wrongdoing and socially irresponsible behavior.

Generative AI and Asset Management

2026-05-12T00:00:00+00:00

The Review of Financial Studies
Using a novel measure of investment companies’ reliance on generative artificial intelligence (GenAI), we document a sharp increase in GenAI usage by hedge funds after ChatGPT’s 2022 launch. A difference-in-differences test shows that hedge funds adopting GenAI earn 2-4% higher annualized abnormal returns than nonadopters, while non-hedge funds do not benefit. The outperformance originates from funds’ AI talent and ChatGPT’s strength in analyzing firm-specific information. We conduct a new survey of fund managers’ GenAI usage to provide direct validation of our measure and offer additional new insights on how managers adopt GenAI tools in their practice. (JEL C81, G11, G14, G23)

Open Rule Legislative Bargaining

2026-05-12T00:00:00+00:00

Review of Economic Studies
The seminal paper by Baron and Ferejohn (1989) leaves significant gaps in our understanding of open rule bargaining. We aim to fill these gaps by providing a fresh analysis of open rule bargaining. Our approach relies on an appealing class of stationary equilibria. In this class, we show that delays tend to be longer and allocations tend to be less egalitarian than originally predicted by Baron and Ferejohn. Our results shed new light on the efficiency and fairness implications of using an open vs. closed rule in legislatures and of bargaining processes in general.

International Reserve Management Under Rollover Crises

2026-05-12T00:00:00+00:00

The Quarterly Journal of Economics
This paper investigates how a government should manage international reserves when it faces the risk of a rollover crisis. We ask, should the government accumulate reserves or reduce debt to make itself less vulnerable? We show that the optimal policy entails initially reducing debt, followed by a subsequent increase in both debt and reserves as the government approaches a safe zone. Furthermore, we find that issuing additional debt to accumulate reserves can lead to a reduction in sovereign spreads. Evidence from a panel of emerging economies is consistent with these predictions: increases in reserves financed by public external borrowing are associated with lower spreads, and reserve holdings are not systematically drawn down during crisis episodes.

The Power of Proximity to Coworkers

2026-05-12T00:00:00+00:00

The Quarterly Journal of Economics
How does proximity to coworkers affect training and productivity? We study software engineers at a Fortune 500 firm from 2019 to 2024, leveraging two shocks to proximity: (i) the office closures in 2020 and (ii) the subsequent return-to-office mandates in 2022 and 2023. In both cases, co-located teams experienced bigger changes in proximity than distributed ones, facilitating difference-in-differences designs. We find that sitting near teammates increases coding feedback by 18.3% and improves code quality. Gains are concentrated among less-tenured and younger employees, who are building human capital. However, there is a tradeoff: experienced engineers write less code when sitting near teammates. In national US data, we find evidence that the rise of remote work has had scarring effects on young college graduates. In remotable jobs, young graduates’ unemployment rate increased relative to older graduates’ post-pandemic (2022−2024) compared to pre-pandemic (2017−2019), a pattern we do not observe in non-remotable jobs.

Public Services Under Private Management

2026-05-12T00:00:00+00:00

The Quarterly Journal of Economics
Theory predicts that outsourcing public services to the private sector can reduce costs and improve efficiency, but can also induce cost-cutting and compromise quality. We assess the Brazilian “Organizações Sociais de Saude” model (OSS), which outsources management of public hospital services to the private sector while the state remains the residual claimant. We show that this enhances hospital production and operational efficiency without adverse effects on hospital quality and equity. Increased inpatient production addresses previously unmet demand, expanding local access to hospital care and reducing population mortality. Performance gains arise from improved operational efficiency achieved through increased hospital management capacity. This facilitates staffing adjustments, favoring higher-skilled personnel, dismissing lower-productivity staff, and adopting flexible, performance-tied employment contracts. Effects are larger among private organizations with more management experience, underscoring returns to managerial capacity. Our findings show that incentive-ownership structures can address the quantity-quality trade-off in public service delivery, even when contracts are incomplete and quality is hard to measure.

An Empirical Analysis of Optimal Nonlinear Pricing in Business-to-Business Markets

2026-05-12T00:00:00+00:00

Marketing Science
This paper provides a methodology for business-to-business firms to implement nonlinear pricing optimally.

Acquisition-Induced Kill Zones

2026-05-12T00:00:00+00:00

Management Science
We study how acquisitions by a dominant incumbent affect entry and R&D incentives in markets with multiple startups. We show that acquisitions can create a kill zone, which suppresses entry and distorts the innovation direction of nontargeted startups. The resulting reduced threat of entry may lead the incumbent to shelve the acquired technology. The kill zone effect strengthens targeted startups’ incentives to enter primarily to be bought out and makes acquisitions more attractive to the incumbent than in-house R&D. To balance kill zone distortions to innovation against the potential synergies from acquisitions, a consumer welfare–maximizing merger policy may involve blocking some, but not all, acquisitions.This paper was accepted by Anita McGahan, strategy.Funding: C. Wang thanks the Australian Research Council Discovery Project [Grant DP210102015] for the generous financial support. C. Teh thanks the European Research Council (ERC) [Grant 101088307] for the generous financial support.Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2024.07841 .

Why Do I Do What I Do? How Searching for Meaning at Work Can Facilitate the Spread of Unethical Conduct through Organizations

2026-05-12T00:00:00+00:00

Journal of Management Studies
Existing research explains the trickle‐down of unethical leader behaviour in organizations primarily in terms of social learning and social exchange processes. We highlight a key limitation of these explanations and propose a novel, meaning‐based mechanism. Drawing on Baumeister's account of meaning as a system of mental connections that enables people to interpret their experiences, we argue that organization members' search for meaning at work strengthens behavioural alignment with unethical leader conduct and thereby amplifies the trickle‐down of unethical leader behaviour from higher‐level managers through lower‐level managers to employees. Across a multi‐source survey of employees and their lower‐level managers (Study 1), an experiment with participants in the lower‐level manager role (Study 2), and two yoked experiments examining lower‐level managers (Study 3a) and employees (Study 3b), we find convergent support for this interaction pattern. Studies 3a and 3b further show that this amplification occurs only when behavioural alignment is perceived as organizationally validated. Our findings reveal a potential dark side of searching for meaning at work and identify a new mechanism through which unethical behaviour cascades through organizational hierarchies.

Long-Term Organizational Growth Following Disasters: The Role of Collective Empathy

2026-05-12T00:00:00+00:00

Journal of Management
This study examines how organizations exposed to disasters transform collective adversity into sustained growth. Drawing on organizational learning and collective emotion theories, we argue that disasters, while often disruptive in the short term, can also foster the emergence of collective empathy—an organizational-level sensitivity to others’ needs that motivates coordinated actions to support societal well-being—which, as organizations recover, contributes to long-term growth. Using difference-in-differences analyses on an 11-year panel of 575 Japanese companies affected by the 2011 Great East Japan Earthquake, combined with unique survey data, we find that organizations with moderate disaster exposure achieved, on average, higher long-term growth than those with low or high exposure. Further analyses suggest that this pattern is mediated by heightened collective empathy. The study identifies collective empathy as a key pathway to post-disaster organizational learning, underscoring the critical yet underexplored role of collective emotions in shaping organizational growth trajectories after disasters.

A Fish Rots from the Head Down: How Founders Lead Startup Fraud

2026-05-12T00:00:00+00:00

Journal of Management
Despite growing scholarly attention on entrepreneurial misconduct, little is known about how founders shape and sustain fraudulent practices through their influence over employees. Using an in-depth case study of Theranos—a fraudulent startup—we develop a grounded process model that explains how startup fraud is not simply the result of regulatory gaps or individual overreach but a multilevel embedded phenomenon. We provide insights into how founders shape employee responses to fraud in startups, eliciting both resistance and complicity. Employees, in turn, engage in a fluctuating moral evaluation process, oscillating between condoning and condemning fraud. We contribute to the literature on startup fraud by distinguishing it from fraud in established organizations, advancing a social process perspective on employee moral processes, and illuminating how founders enact multilevel influence mechanisms that embed fraud in startup contexts.

Revenue Recognition Comparability and Analysts’ Disclosure Processing Costs

2026-05-12T00:00:00+00:00

Journal of Accounting Research
I examine whether the FASB's revenue recognition guidance under ASC 606 influences revenue comparability across firms and industries and whether revenue comparability reduces analysts’ disclosure processing costs. I extract firms’ revenue policy disclosures from 10‐K filings to measure their textual similarity and compare revenue policies across firms and industries. I find an increase in revenue comparability for firms in different industries with similar revenue‐generating transactions upon adoption of ASC 606. In contrast, I find a decrease in revenue comparability for firms in the same industry with similar revenue‐generating transactions. Further, though I find that analysts are more likely to forecast revenues when firms have higher revenue comparability, this benefit of revenue comparability is less pronounced under ASC 606. This finding suggests the ASC 606‐related changes to revenue comparability impose disclosure processing costs on analysts.

Psychological Reactance to the Algorithmic Management of Online Expressions

2026-05-12T00:00:00+00:00

Information Systems Research
As digital platforms increasingly rely on automated tools to govern user expression, an important practical question is whether algorithmic moderation can improve content quality without undermining user cooperation. Drawing on Wikipedia’s bot-based enforcement of neutrality rules, we find an unintended consequence: Contributors whose prior edits are moderated often respond with more politically slanted subsequent expression, rather than moving closer to neutrality. This pattern is stronger when moderation targets a contributor’s focal area of attention, among contributors with stronger prior political bias, and after repeated bot intervention. It is weaker when moderation occurs outside the contributor’s focal area and among contributors with greater experience in politically sensitive topics. Together, these findings suggest that effective platform governance requires more than scalable automated enforcement. For platform leaders, the results underscore the value of pairing bots with transparent explanations, context-sensitive messaging, and human oversight. For policymakers, the study indicates that algorithmic content governance should be evaluated not only by its ability to remove problematic content, but also by its downstream effects on user behavior, participation, and polarization. Well-designed governance systems must balance rule enforcement with users’ sense of autonomy.

Living Up to Online Advice: How Health Platforms Influence Physicians’ Offline Practice

2026-05-12T00:00:00+00:00

Information Systems Research
Digital platforms are reshaping professional service delivery, yet how online engagement feeds back into offline clinical practice remains unclear. This study examines whether physicians’ information provision on healthcare question-and-answer platforms influences treatment decisions in hospital care. Drawing on cognitive consistency and professional identity theories, the study proposes a mechanism of identity-based digital commitment whereby publicly articulated medical advice functions as a “cognitive anchor,” creating pressure for physicians to align subsequent bedside decisions with the online standards, particularly in discretionary domains that are vulnerable to economic or institutional pressures. Using a physician-level matched data set that links a leading online health platform to hospital electronic health records, the analysis shows that physicians with higher levels of online advisory activity are associated with reduced overall medication costs, lower uncovered medication cost ratios, and lengths of stay that more closely adhere to guideline benchmarks. Mediation and stratified analyses mitigate concerns that these patterns are driven by patient selection or improved patient adherence alone, whereas moderation by dimensions of professional commitment and content relevance provides supportive evidence for a cognitive consistency mechanism. The results are robust to alternative model specifications and controls for peer spillovers, digital reputation, and local market conditions, indicating no deterioration in clinical quality as readmission and mortality rates remain unchanged. Overall, the findings position digital platforms as a form of “soft governance” that complements formal oversight by activating intrinsic professional motives for consistency between online identity and offline practice.History: Rajiv Kohli, Senior Editor; Wenjing Duan, Associate Editor.Funding: This work was supported by the Key Program of National Natural Science Foundation of China [Grant 72231009], the General Program of National Natural Science Foundation of China [Grant 72472128], the Science Fund for Creative Research Groups of the National Natural Science Foundation of China [Grant 71821002], the National University of Singapore, the Provost’s Chair Grant [Grant E-253-00-0021-01], and the Fundamental Research Funds for the Central Universities [Grant D5000240057].Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2022.0136 .

Proud to Not Own Stocks: How Identity Shapes Financial Decisions

2026-05-13T00:00:00+00:00

The Review of Financial Studies
This paper introduces a key factor influencing households’ decision to invest in the stock market: how people view stockholders. Using surveys we conducted with nearly 8,500 individuals from 11 countries, we document that a large majority hold negative views of stockholders based on identity-relevant characteristics. Linking survey and administrative data, we find that negative perceptions strongly predict households’ stock market participation. We show that negative perceptions causally influence household decision-making and provide evidence supporting identity concerns as the underlying mechanism. Our findings provide new perspectives on the malleability of financial decision-making and a novel explanation for low stock market participation. (JEL G41, G51, D14, D83)

Collective Moral Hazard, Risk Sharing, and Banking Unions*

2026-05-13T00:00:00+00:00

The Review of Financial Studies
We analyze optimal cross-country risk sharing and bank capital requirements amid collective moral hazard by governments and banks. Transfers provide insurance but weaken fiscal discipline. Since lenient fiscal policies amplify banks’ risk-shifting, optimal support must be contingent on banking system health. For fiscally weak countries, support is larger in sovereign crises with solvent banks. For fiscally strong countries, support is larger in joint sovereign and bank crises, requiring deposit insurance mutualization. Optimal contracts feature lower capital requirements than without cross-country transfers, raising the cost of joint sovereign and bank crises to strengthen fiscal discipline and enable greater risk sharing.

Firm–specific information processing and the delayed discovery of macroeconomic news: evidence from earnings announcement returns

2026-05-13T00:00:00+00:00

Review of Accounting Studies
Analyzing a panel of earnings announcers from 1998–2022, we document that the aggregate market return on quarterly earnings announcement dates is positively associated with the announcing firm’s subsequent three-day abnormal returns. This phenomenon is strongest for firms with extreme earnings surprises and dissipates by day seven, indicating a short-lived delay in incorporating the aggregate news. We also document a sluggish return response to same-day macro news disclosures, especially when earnings surprises are extreme. Effects strengthen when investors exert more effort in acquiring announcing firm information, measured by SEC EDGAR filing downloads, when macronews has a larger impact on a firm’s stock returns, when firms are smaller, and when investors’ attention and processing capacity are more constrained, proxied by retail trading. Overall, the findings support the notion that investors have finite information processing capacity and that intensive efforts to acquire firm earnings news delay the incorporation of macroeconomic news into prices.

Spreading the Style: Firm Leaders’ Early Life Experiences and Employees’ Behavior and Performance

2026-05-13T00:00:00+00:00

Management Science
Leaders shape firm strategy not only through the decisions they make directly, but also through influencing employees’ workplace behavior. We argue that leaders’ formative life experiences, which shape personal traits, can influence employee behavior and work performance. Using detailed data from Chinese securities firms, we examine the impact of chairpersons’ experiences as “sent-down youths” (SDYs) during China’s Cultural Revolution, which instilled in them a strong work ethic in the face of adversity. We argue that SDY chairpersons encourage security analysts to increase efforts to improve the accuracy of earnings forecasts for the publicly listed firms they follow. We show that when the same analyst experiences a change in chairperson within the same securities firm—from one without any SDY experience to one with SDY experience (both within the same cohort)—their forecast accuracy for the same listed firm increases. Specific actions, such as conducting site visits to gather company information firsthand, contribute to improving forecast accuracy. We find that analysts led by SDY chairpersons are more likely to conduct site visits, visit more companies for the first time, visit companies located in less-accessible areas, ask more targeted questions during site visits, and update forecasts promptly after major events. To strengthen causal inference, we employ fixed effects, examine various types of chairperson turnovers, and employ instrumental variable approaches and placebo tests. Our study suggests that, through influencing employee behavior, the “style” of a firm leader spreads far within an organization.This paper was accepted by Alfonso Gambardella, business strategy.Funding: Y. Wang received financial support from the National Natural Science Foundation of China [Grants 72172090 and 72572103]; N. Xu received financial support from the National Natural Science Foundation of China [Grants 72225005 and 72495154]; and R. Xie received financial support from the National Natural Science Foundation of China [Grant 72202249] and the Program for Innovation Research in Central University of Finance and Economics.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.09097 .

Financial Inclusion via Blockchain: Evidence from a Natural Experiment

2026-05-13T00:00:00+00:00

Management Science
The lack of formal and verifiable credit records among borrowers is a significant barrier to financial inclusion in developing countries. In this paper, we assess the effectiveness of blockchain technology in improving credit information authenticity and enhancing financial inclusion. Using a novel data set from the online prosocial lending platform Kiva, we exploit the implementation of a blockchain-based lending protocol change in Kiva Sierra Leone as an exogenous shock to conduct difference-in-differences analyses. Our results show that borrowers attract more guarantors and larger per-guarantor contributions under the blockchain protocol, thereby increasing their likelihood of being funded on the Kiva platform. Microfinance institutions (MFIs) adopting the blockchain protocol also experience lower portfolio risks and extend larger lending volume to borrowers. In addition, the implementation of the blockchain protocol allows MFIs to achieve both growth in financial revenue and reduction in operational expenses, thus enhancing the sustainability of their lending services in developing countries. We further explore the sensitivities of blockchain effects and find that the blockchain protocol has a greater propensity to benefit borrowers from rural areas, those with weaker financial credit records, and those seeking microloans in sectors such as agriculture, textiles, and the food industry. Our findings are robust against robustness checks and alternative explanations.This paper was accepted by Will Cong, finance and will be included in the Virtual Special Issue on Digital Finance.Funding: Financial support from the Research Grant Council of the Hong Kong Special Administrative Region, China [Grant T35-710/20-R] and the National Natural Science Foundation of China [Grant 71988101] is gratefully acknowledged.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02303 .

Invisible Primes: Fintech Lending with Alternative Data

2026-05-13T00:00:00+00:00

Management Science
We study the impact of alternative data on credit access and borrower outcomes using anonymized data from a major U.S. financial technology (fintech) platform that incorporates education, employment, and other nontraditional variables into its underwriting algorithm. The platform approves 15%–30% of low-credit-score applicants rejected by traditional models and offers them lower rates. It particularly benefits “invisible primes”—borrowers with thin credit files and low credit scores but low default risk. We show that gains for invisible primes are primarily driven by alternative data, while model sophistication yields additional improvements in segments where traditional credit report information is more extensive. Using exogenous variation, we find that expanded credit access improves borrowers’ subsequent financial outcomes.This paper has been accepted by Kay Giesecke for the Virtual Special Issue on Digital Finance.Supplemental Material: The internet appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07854 .

Crafting Interdisciplinary Research: Four Cornerstone Practices for Management Scholars

2026-05-13T00:00:00+00:00

Journal of Management Studies
Interdisciplinary research is widely promoted as essential for advancing understanding of complex managerial and organizational phenomena. Yet, while often celebrated rhetorically, authors keep facing significant challenges when they seek to integrate insights from other disciplines into management scholarship. To that effect, we outline four research‐informed cornerstone practices to help management scholars craft interdisciplinary research. Employing a narrative‐integrative review approach, we inductively develop anInterdisciplinarity Diffusion Frameworkthat maps interdisciplinary research according to the proximity of the source discipline to management (proximal–distal) and the primary mode of diffusion (theory, methods, or phenomena). Drawing on exemplary studies to illustrate our points, we show how different positions within this framework create distinct opportunities and barriers for authors. We draw on these findings, as well as on our own scholarly experience to detail four cornerstone practices, which serve as practical guidance for authors interested in advancing management theory with interdisciplinary research. Finally, we shift attention to the responsibilities of reviewers, editors, and institutions in shaping an environment where interdisciplinarity can flourish. We argue that supporting interdisciplinary research should be a rich and shared endeavour, central to the future intellectual vitality and societal relevance of management studies.

The impact of the global minimum tax on incentives for business location, investment, and profit shifting

2026-05-13T00:00:00+00:00

Journal of International Business Studies
In 2021, over 140 countries agreed to what is widely considered to be the most significant reform of international business taxes in a century: the introduction of a global minimum tax (GMT) at a rate of 15% on the profits of large MNEs. We study the reform’s impact on three interrelated MNE decisions: the location of investment, the size of investment conditional on location, and the extent to which profit is shifted to a low-tax country. We extend existing models of the impact of taxation on investment incentives to allow for profit shifting and the GMT. We also develop and quantify a measure of the economic cost of tax-induced distortions to location. We apply our model to taxes in 34 OECD countries. Raising the GMT rate reduces profit shifting as the benefits of profit shifting are reduced. This raises the MNE’s tax liability and its cost of capital, reducing its aggregate investment. The impact on location choice is more subtle, as the dispersion in effective tax rates across countries first rises, then falls, as the GMT rate rises. At a GMT rate of 15%, we estimate that there is a small rise in the dispersion, implying greater distortions to location decisions.

Discount now or later? The effect of payment framing on consumer preferences for discount timing in periodic payments

2026-05-13T00:00:00+00:00

Journal of Consumer Psychology
Consistent with the standard model of time discounting, subscription firms typically offer introductory discounts early in the subscription. However, we demonstrate that consumers are more likely to prefer a delayed discount when the discount is expressed in the same unit as the recurring price (e.g., “$10, $10, $5”). The identical framing leads consumers to perceive the payments as a coherent sequence, making it easier to identify an improving pattern and project it forward, thereby lowering expectations of the post‐promotion price. By contrast, when the discount is framed differently from the recurring price (e.g., “$10, $10, 50% off”), it is perceived as a segregated gain, and consumers revert to the standard preference for immediate benefits. Across four studies, we demonstrate this effect using actual online click‐through behavior (Study 1) and identify the underlying mechanism: the preference for delayed discounts arises from lower future price expectations driven by sequence‐continuation inferences (Study 2). Consistent with this account, the effect disappears when the basis for this inference is removed—either by disclosing the renewal price (Study 3) or by disrupting sequence coherence (Study 4). Four supplementary studies further generalize the findings across product categories and narrative pricing displays and rule out several alternative explanations.

Legal Shields, Hidden Costs: The Dual Effects of Patent Troll Laws on Information Technology Firm Innovation

2026-05-13T00:00:00+00:00

Information Systems Research
The information technology (IT) industry is especially vulnerable to patent trolls because digital products combine modular, interdependent, and software-intensive components, making patent claims difficult to isolate and easy to assert broadly. Many U.S. states responded by adopting patent troll laws aimed at abusive demand letters. These laws can affect firms through two channels; they may reduce litigation risk by discouraging coercive threats, but they may also increase compliance costs by requiring greater disclosure when asserting patents. We leverage staggered adoption across U.S. states and track 900 IT firms from 2012 to 2019. We find that these laws are associated with higher overall patenting, but the increase is concentrated in areas where firms already have experience; patenting in new areas does not increase on average. Consistent with the two-channel mechanism, firms with greater prior exposure to troll litigation show larger increases in patenting in familiar areas, whereas firms facing higher expected compliance burdens show lower patenting in new areas. These differences are more pronounced in laws with more stringent disclosure and enforcement provisions, highlighting the tension between deterrence and compliance costs. For policymakers, the findings show how to design these laws: deter abusive assertions without imposing compliance burdens that dampen longer-term technological search.

Women Lifting Up Women: The Transformative Potential of Parallel-Peer Connections

2026-05-13T00:00:00+00:00

Administrative Science Quarterly
Women in masculine-typed roles often experience their gender identity as a barrier to proving themselves by the ideal-worker norms of their male-dominated occupations. Yet, these women often internalize these experiences, blaming themselves for their struggles. They rarely identify as members of a disadvantaged identity group and often distance themselves from other women at work. How and when might such women externalize their struggles as gendered and collective? Drawing on data from a qualitative field study of staff working in many masculine-typed roles across various male-dominated occupations at a U.S. public-lands management organization, I develop grounded theory suggesting when and how some women might come to reappraise some of their struggles as rooted in the gendered cultures of their occupations rather than in their own deficiencies or idiosyncratic circumstances. I find that “parallel-peer connections” between similarly situated women outside their local tokenized work groups can spark transformative mindset shifts when these encounters occur under the right conditions: during a window of sensemaking about a career impasse and in a less competitive context that is conducive to sharing confidences. Some women credited these shifts with prompting them to shed years of self-doubt and to promote gender equality at work. This study contributes to our understanding of supportive workplace relations among tokenized women and mindset shifts at work.

Firm-Level Labor Shortage Exposure

2026-05-14T00:00:00+00:00

The Review of Financial Studies
We extract information from earnings call transcripts to develop a comprehensive and reliable measure of labor shortage exposure. After validating the measure at the state, industry, and firm levels, we show that firms with labor shortage exposures experience lower earnings call CARs, future stock returns and operating performance. Firms respond to labor shortages by substituting labor with capital and R&D investments, and by producing more production-process patents. Such responses help mitigate the negative effects on future performance. Our measure has broad applicability, and our findings provide new insight into labor-capital substitution in imperfectly competitive labor markets. JEL G12, G30, J2

Markov-Perfect Equilibria in Differential Games — with an Application to Climate Policy

2026-05-14T00:00:00+00:00

Review of Economic Studies
We analyse discontinuous Markovian strategies for differential games. The best response correspondence uniquely maps almost all profiles of opponents' strategies back to the strategy space. We thus make Markov-perfect equilibria in a wide class of differential games well-behaved, resolving a long-standing open problem. We provide a readily applicable necessary and sufficient condition for best responses and Markov-perfect Nash equilibria. We demonstrate our methods in a canonical model of non-cooperative mitigation of climate change. Our approach provides novel, economically important results: we obtain the entire set of symmetric Markov-perfect equilibria, and demonstrate that the best equilibria can yield a major welfare improvement over the equilibrium which previous literature has focused on. International climate negotiations can be seen as being about coordination on good equilibria, rather than about bargaining over the limited surplus available in a dynamic prisoner's dilemma.

Optimal Labor Income Taxation: A Flexible Moral Hazard Approach

2026-05-14T00:00:00+00:00

Review of Economic Studies
This paper reconsiders the question of optimal labor income taxes for the very rich in the context of a flexible moral hazard (FMH) model. In this setting, risk is not exogenous. Rather, each agent can affect the probabilities of all possible income outcomes by allocating a fixed time endowment across a variety of distinct tasks. I prove that the optimal income tax rates on high-end earners and the optimal Pareto tail index of the pre-tax labor income distribution are both endogenously determined by agent preferences. In particular, a society with less risk-averse agents will find it optimal to impose a lower tax rate on the rich, even though its members’ choices give rise to a smaller Pareto right tail index. In contrast, this kind of negative co-movement between inequality and optimal tax rates is a suboptimal response in the classical Mirrlees (1971)-Diamond (1998)-Saez (2001) setup to changes in the exogenous distribution of skills.

When is TSLS Actually LATE?

2026-05-14T00:00:00+00:00

Review of Economic Studies
Linear instrumental variable estimators, such as two-stage least squares (TSLS), are commonly interpreted as estimating non-negatively weighted averages of causal effects, referred to as local average treatment effects (LATEs). We examine whether the LATE interpretation actually applies to the types of TSLS specifications that are used in practice. We show that if the specification includes covariates—which most empirical work does—then the LATE interpretation does not apply in general. Instead, the TSLS estimator will, in general, reflect treatment effects for both compliers and always/never-takers, and some treatment effects for the always/never-takers will necessarily be negatively weighted. We show that the only specifications that have a LATE interpretation are “saturated” specifications that control for covariates nonparametrically, implying that such specifications are both sufficient and necessary for TSLS to have a LATE interpretation, at least without additional parametric assumptions. This result is concerning because, as we document, empirical researchers almost never control for covariates nonparametrically, and rarely discuss or justify parametric specifications of covariates. We apply our results to thirteen empirical studies and find strong evidence that the LATE interpretation of TSLS is far from accurate for the types of specifications actually used in practice. We offer concrete recommendations for practice motivated by our theoretical and empirical results.

Input Sourcing under Climate Risk: Evidence from U.S. Manufacturing Firms

2026-05-14T00:00:00+00:00

Review of Economic Studies
We study the effect of risk on how firms organize their supply chains. We use transaction-level data on U.S. manufacturing imports to construct a novel measure of input sourcing risk based on the historical volatility of ocean shipping times. Our measure isolates the unexpected component of shipping times that is induced by weather conditions along more than 331,000 maritime routes. We first document that unexpected shipping delays significantly reduce importers’ sales, profits, and employment. We then show that firms actively diversify weather risk by using more routes and foreign suppliers, although their import values decline. To rationalize these findings, we introduce shipping time risk into a general equilibrium model of importing with firm heterogeneity. Our quantitative analysis predicts substantial costs for the U.S. economy associated with supply chain risk.

A Model of Multiple Hypothesis Testing

2026-05-14T00:00:00+00:00

Review of Economic Studies
Multiple hypothesis testing (MHT) practices vary widely, without consensus on which are appropriate when. This article provides an economic foundation for these practices designed to capture leading examples, such as regulatory approval on the basis of clinical trials. MHT adjustments are appropriate in our framework to the extent that research costs are invariant to the number of hypotheses. Control of average size, as for example via a Bonferroni correction, emerges in the limit case where all costs are fixed; in the opposite limit, where costs vary in proportion to the hypothesis count, no correction is needed. We illustrate implications by calculating explicit critical values using data on actual costs in the drug approval process and in program evaluation research; these suggest that some MHT adjustment is warranted in these applications, but not as much as implied by standard practice.

Information Design of a Delegated Search

2026-05-14T00:00:00+00:00

Management Science
A principal delegates a sequential search with finite search opportunities to an agent, who bears the search cost and controls how far to search. The termination payoff is split between them according to a prespecified proportion. In our setting, only the principal can evaluate the search outcomes and design a policy to decide what information to provide to the agent after each search. Formulating the principal’s problem as a dynamic information design, we obtain a complete analytical characterization of the principal’s optimal information policy featuring a sequence of deterministic acceptance standards. The agent is simply recommended to and will voluntarily continue the search if and only if the current termination payoff falls below the corresponding standard prespecified at the beginning of the search. This policy offers an easy-to-implement prescriptive guideline for how information can be used as an incentive device in delegated search, especially absent pecuniary instruments. For nonrecallable search, the acceptance standards are informative, descending, and determined recursively as the optimal stopping thresholds that the principal would employ if the principal were to search directly at a shadow cost. In contrast, for recallable search, the optimal policy features a regime change: for the first cutoff number of search opportunities, the principal can set a constant, possibly uninformative acceptance standard that would be attainable in a costless search; after the cutoff opportunity, the principal sets a sequence of descending acceptance standards, each independently determined by equating the agent’s marginal perceived return from one additional search with the cost.This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis.Funding: This work was supported by the Ministry of Education, Singapore, under its 2019 Academic Research Fund Tier 3 [Grant MOE-2019-T3-1-010].Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2024.05925 .

Respecting Improvement in Markets with Indivisible Goods

2026-05-14T00:00:00+00:00

Management Science
A generalized matching problem consists of a set of agents, a set of objects, the agents’ endowments, a set of feasible matchings, and the agents’ preferences over feasible matchings. Respect for improvement means that when the ranking of an agent’s endowment improves in some other agent’s preference (while keeping other preferences unchanged), then this agent weakly benefits from it. Our main result shows across matching applications that on the strict domain, individual rationality, strategy-proofness, and nonbossiness imply respecting improvement. As a consequence for housing markets, we obtain that top trading with fixed tiebreaking and top trading with random tiebreaking satisfy respecting improvement on the weak domain. We further show that several application-based extensions of the top-trading-cycles mechanism (such as for kidney exchange and school choice) satisfy (a weak version of) respecting improvement.This paper was accepted by Martin Bichler, market design, platform, and demand analytics.Funding: The author acknowledges financial support from the Social Sciences and Humanities Research Council of Canada under Insight Grant 435-2023-0129 and the Fonds de recherche du Québec under Soutien aux équipes de recherche / Universitaire- nouvelle équipe 367853.

From Contextual Data to Newsvendor Decisions: On the Actual Performance of Data-Driven Algorithms

2026-05-14T00:00:00+00:00

Management Science
In this work, we study how the relevance/quality and quantity of past data influence performance by analyzing a contextual Newsvendor problem, in which a decision maker trades off between underage and overage costs under uncertain demand. We consider a setting in which past demands observed under “close-by” contexts come from close-by distributions and analyze the performance of data-driven algorithms through a notion of context-dependent worst-case expected regret. We analyze the broad class of Weighted Empirical Risk Minimization (WERM) policies which weigh past data according to their similarity in the contextual space. This class includes classical policies such as ERM, k-Nearest Neighbors, and kernel-based policies. Our main methodological contribution is to characterize exactly the worst-case regret of any WERM policy on any given configuration of contexts. To the best of our knowledge, this provides the first understanding of tight performance guarantees in any contextual decision-making problem, with past literature focusing on upper bounds via concentration inequalities. We instead take an optimization approach, and isolate a structure in the Newsvendor loss function that allows us to reduce the infinite-dimensional optimization problem over worst-case distributions to a simple line search. This in turn allows us to unveil fundamental insights that were obfuscated by previous general-purpose bounds. We characterize actual guaranteed performance as a function of the contexts, as well as granular insights on the learning curve of algorithms.This paper was accepted by Victor Martínez de Albéniz, operations management.Funding: This work was supported by the Deming Center for Operations Innovation and Excellence at Columbia Business School [Doctoral Fellowship (O. Mouchtaki)].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02068 .

Recruitment in Times of Crisis: The Impact of Negative Signals and CSR on Job Seekers' Attraction to Multinational Enterprises

2026-05-14T00:00:00+00:00

Journal of Management Studies
Recruitment research has traditionally focused on how positive signals about organizations influence job seekers' perceptions and attraction to them, despite the fact that job seekers often encounter a mix of positive and negative information about prospective employers. We conducted three experimental studies, with a follow‐up supplementary study, to explore the effects of negative signals on organizational attractiveness and whether positive signals can offset these effects. Drawing from signalling theory, we conceptualized two types of crises – national security threat accusations and product failure scandals – as negative signals and examined their effects on job seekers' perceptions of attractiveness to multinational enterprises (MNEs) and their job pursuit intentions in these enterprises. We further investigated if MNEs' corporate social responsibility (CSR) activities as positive signals could mitigate the negative effects of these crises on job seekers' perceptions of MNEs. Our results confirmed the anticipated negative signalling effects of organizational crises on MNEs' attractiveness. We also found that CSR efforts did not effectively counteract these negative effects. We offer a more nuanced understanding of signalling effects in recruitment and underscore the limitations of CSR as a positive signal in the face of organizational crises.

From Static Fit to Dynamic Alignment: The Emergence and Evolution of HR Ecosystems in Fragmented Workplaces

2026-05-14T00:00:00+00:00

Human Resource Management
Fragmented work arrangements increasingly challenge conventional firm‐centric approaches to human resource management (HRM), as HR activities become distributed across multiple actors. The concept of HR ecosystem offers a powerful lens for understanding this shift, yet we know little about how such ecosystems emerge and evolve over time. Drawing on 178 in‐depth qualitative interviews from China's online food delivery sector, we find that HR ecosystems evolve through four stages: pre‐emergence static alignment, misalignment, realignment, and dynamic alignment. A defining feature of this process is the emergence of functional shared governance, in which HR responsibilities are distributed out of operational necessity rather than consensual power sharing. As this diffusion disrupts previously established static alignment, organizations respond through maintenance and adaptation strategies, with digital technologies enabling coordination and responsiveness across dispersed participants. These efforts produce dynamic alignment—an ongoing process through which HRM is continually recalibrated to maintain coherence while accommodating variation and change. Our findings contribute to the literature by theorizing how HR ecosystems emerge, how functional shared governance develops, and how dynamic alignment is achieved over time.

Loose Monetary Policy and Financial Instability

2026-05-15T00:00:00+00:00

Review of Economic Studies
Do periods of persistently loose monetary policy increase financial fragility and the likelihood of a financial crisis? This is a central question for policymakers, yet the literature does not provide systematic empirical evidence about this link at the aggregate level. In this paper we fill this gap by analyzing long-run historical data. We find that when the stance of monetary policy is accommodative over an extended period, the likelihood of financial turmoil in the medium term increases considerably. We investigate the causal pathways that lead to this result and argue that credit creation and asset price overheating are important intermediating channels.

Monetary Policy and Endogenous Financial Crises

2026-05-15T00:00:00+00:00

Review of Economic Studies
What are the channels through which monetary policy affects financial stability? Can (and should) central banks prevent financial crises by deviating from price stability? To what extent may monetary policy itself unintentionally breed financial vulnerabilities? We answer these questions using a New Keynesian model with capital accumulation and endogenous financial crises due to adverse selection and moral hazard in credit markets. Our findings are threefold. First, monetary policy affects the probability of a crisis both in the short run (via aggregate demand) and in the medium run (via capital accumulation). Second, the central bank can reduce the incidence of crises in the medium run by tolerating higher inflation volatility in the short run. Third, prolonged periods of loose monetary policy followed by a sharp tightening can lead to financial crises.

Financial Intermediation and Aggregate Demand: A Sufficient Statistics Approach

2026-05-15T00:00:00+00:00

Review of Economic Studies
We show that the financial sector’s asset supply elasticities are sufficient statistics summarizing its macroeconomic effects for a large class of financial frictions. These elasticities are crucial for a wide range of policy questions, ranging from the size of fiscal multipliers to the relative effectiveness of asset purchases targeting the financial sector versus tax cuts targeting households. Workhorse macroeconomic models imply different values of these elasticities, generating output responses to policies that differ by orders of magnitude. We construct empirical measures of these elasticities and evaluate their policy implications in a quantitative model with household heterogeneity and illiquidity.

EXPRESS: Does Energy Efficiency Imply Cost Efficiency? Revisiting Design and Operations of Combined Heat and Power Systems

2026-05-15T00:00:00+00:00

Production and Operations Management
Combined heat and power (CHP) technology produces both heat and electricity from a single fuel input, achieving an efficiency (total useful energy output divided by fuel input) as high as 90%. However, using CHP exposes firms to a higher fuel price uncertainty, compared to purchasing electricity at a relatively stable price from the utility and generating heat separately. In this paper, we study the problem of optimizing the design (including capacity and power-to-heat ratio) and operations of a CHP system for an industrial firm facing variable fuel and electricity prices. A standard practice is to design a CHP system to match the thermal demand it serves and retire the legacy boiler, ensuring high energy efficiency. We revisit this standard practice by optimizing the firm’s energy supply system, including CHP design, the decision to retire or retain the legacy boiler, and the joint operation of the CHP system and boiler when the boiler is retained. We formulate the problem as a bilevel optimization, in which CHP design and boiler retirement-or-retention decisions are made at the beginning of a planning horizon, while system operations are optimized in each period. We identify two strategies for mitigating fuel price variability and improving cost efficiency: 1) Retaining the legacy boiler and operating it jointly with the CHP system, and 2) Designing the CHP system with excess capacity that may overproduce steam. Both strategies introduce operational flexibility, enabling the energy supply system to switch operating modes in response to fuel price fluctuations. We further identify the market conditions under which each strategy dominates.

EXPRESS: Proceed with Caution: How Broadband Access and Speed Help and Hinder Student Learning Outcomes

2026-05-15T00:00:00+00:00

Production and Operations Management
Background: Education, like other service operations, depends on the quality of its delivery channel. Broadband has become a critical delivery channel for learning in the current education system, but access and speed remain uneven across U.S. communities.Aim: Scholars disagree on how broadband access affects educational outcomes, and prior work often overlooks broadband speed. We extend prior work by assessing how both broadband access and speed together influence U.S. math proficiency.Methods: We analyze a national panel of U.S. school districts from 2017 to 2022 and link broadband measures to student proficiency with a dynamic panel model.Results: School districts with greater average access and smaller within-district gaps tend to have higher math proficiency. Nationally, a one percentage-point increase in broadband access corresponds to a 0.545 percentage-point increase in math proficiency, a 1.22% increase relative to the average baseline. We find speed also matters: gains rise with faster available connections, then reverse at very high speeds.Conclusion: Access alone is not enough. Our study shows that broadband policy should move beyond “more is better” and consider broadband speeds that maximize learning. As one headmaster noted: “The internet is essential, but proceed with caution!”

EXPRESS: Pay More, Use More: Consumer Bias and Demand Management for Digital Services

2026-05-15T00:00:00+00:00

Production and Operations Management
Consumers often purchase access to a digital service by paying an upfront fee, and then consume the service over a period of time. In this article, we examine the implications of such temporal separation of purchase and consumption on a user’s consumption choices, and on the firm’s optimal demand management strategy. Relying on behavioral economics and consumer behavior literature, we develop a formal micro-founded model of a user’s decision calculus, and use it to derive the implied demand function and thus analyze the firm’s optimal decisions. In contrast to the classical recommendation to pursueadmission controlthrough higher prices as a means to manage demand for the digital service, we find that when mental accounting bias is a key driver of consumer choices, it might be optimal for a firm to pursueconsumption controlthrough lower prices. These results are robust when quality is endogenized, capacity is constrained, subscription duration is finite, and in the presence of a two-part tariff. We translate our findings into a conceptual framework for digital service management that characterizes the optimal demand management strategy along two key dimensions: the strength of the consumer bias and the cost of servicing demand. When these factors are significant, firms need to employ a combination of admission control and consumption control so as to manage and maintain profitability.

Risk-Aware Linear Bandits: Theory and Applications in Smart Order Routing

2026-05-15T00:00:00+00:00

Operations Research
Learning to Route Orders with Risk in MindHow should a trader split an order across multiple venues when both returns and risk matter? In “Risk-Aware Linear Bandits: Theory and Applications in Smart Order Routing,” Jingwei Ji, Renyuan Xu, and Ruihao Zhu develop a new bandit framework for this problem by combining mean variance optimization with linear bandit structure. Their model is motivated by smart order routing, where traders must learn from partial feedback while facing a very large action space. The authors propose two algorithms, RISE and RISE++, and show that both achieve near-optimal regret guarantees while avoiding the strong dependence on the number of actions that limits existing risk-aware bandit methods. They also validate the linear approximation empirically using the NASDAQ ITCH data set and demonstrate strong numerical performance in both synthetic and market-based experiments. The paper opens a new path for risk-sensitive online learning in financial decision making.

Classical Lottery in Action: Quantifying Risk and Evaluating Uncertainty

2026-05-15T00:00:00+00:00

Management Science
The rarity of objectively known probabilities undermines the risk-ambiguity dichotomy, challenging the practical relevance of related theories. We return to classical lotteries—coins, dice, and similar devices—which inspired early probability theories through the idea of equiprobable outcomes and are widely considered strong candidates for objective probability. We adapt axioms of expected utility for risk to advocate average utility for classical lotteries, highlighting their conceptual affinity. Any general unknown event is conceived as a collection of possible classical-lottery frequencies, consistent with the ambiguity literature, and we suggest normative principles for their aggregation into an indifferent matching frequency. These principles identify a model in the spirit of the smooth model of ambiguity; the agent assigns subjective probabilities over the frequencies and aggregates them via a nonlinear mixture. The nonlinearity reflects the agent’s distinct attitudes toward classical-lottery frequencies versus subjective probabilities; a concave mixture, for example, captures ambiguity aversion. Our approach provides a concrete justification for the distinct attitudes and presents several advantages for model elicitation. We illustrate the theory’s applicability through examples and, especially, social policy evaluation where the veil of ignorance can be seen as a classical lottery.This paper was accepted by Manel Baucells, behavioral economics and decision analysis.Funding: J. Li was supported by the General Research Fund of the Hong Kong Research [Grant Council under research project LU13500322]. I. Tsetlin and F. Wang do not have fundings that need to be disclosed.

Rejecting Work Inequality: Women Say “No” to Unequal Workloads or Unequal Earnings?

2026-05-15T00:00:00+00:00

Management Science
Pay inequality can arise from unequal earnings for the same job or an unequal workload for the same earnings. Although existing research focuses on aversion to unequal earnings, little is known about aversion to unequal workloads, particularly gender differences. We show that female workers are more willing to accept unequal workload than unequal earnings allocations. By contrast, male workers exhibit similar responses to the workload and earnings inequality. The findings highlight that women’s lower aversion to unequal workloads can contribute to the gender earnings gap. Promoting equal workload allocation can be crucial in addressing the gender gap in the labor market.This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis.Funding: This research was supported by research grants from Bryant University and the Department of Economics at Monash University.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.07896 .

Is There a Macro-Announcement Premium?

2026-05-15T00:00:00+00:00

Management Science
The conditional return volatility barely drops at macro-announcements. This is at odds with the notion that high announcement returns are a manifestation of a large announcement premium. We show that models with an announcement premium cannot fully explain the joint patterns of returns and volatility over announcement days. Surprisingly, traditional models, which do not feature such a premium, can. Our estimation results based on a statistical setup indicate that the average announcement return is mostly attributable to the monetary policy surprise and pure small-sample components, which do not average out in-sample; the announcement premium is estimated to be small.This paper was accepted by Lukas Schmid, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06960 .

The Great Temporal Divide: How Top Management Team Temporal Faultlines and Dominant Subgroups Shape Firm Innovativeness in Iran

2026-05-15T00:00:00+00:00

Journal of Management Studies
While executives vary in attention to the past, present, and future, prior work has largely examined these temporal orientations in isolation or at the individual level, which limits insight into how they jointly configure within top management teams (TMTs) and translate into firm behaviours. In this study, we advance a configurational perspective by introducing TMTtemporal faultlines, defined as subgroup divisions based on the alignment of members' past, present, and future foci. We distinguish two key features of temporal faultlines: temporal faultline strength and the dominant subgroup temporal profile, and propose that these configurational properties shape the emergence of TMT time‐awareness norms through regulating how teams attend to and coordinate temporal demands. Based on multi‐wave survey data from 209 TMTs of small‐ and medium‐sized enterprises in Iran, our findings suggest that temporal faultlines, making temporal differences salient, foster the development of shared norms around time management. We further find that TMT time‐awareness norms exhibit an inverted U‐shaped relationship with firm innovativeness, with moderate levels enhancing innovativeness by balancing temporal discipline and flexibility. Together, these findings shift research on executive temporality from individual traits to team configurations and extend faultlines theory by showing that both subgroup differentiation and subgroup content matter.

The Drivers and Implications of Retail Margin Trading

2026-05-15T00:00:00+00:00

The Journal of Finance
Using granular data covering both regulated (brokerage‐financed) and unregulated (shadow‐financed) margin accounts in China, we provide novel evidence on retail investors' margin trading behavior and its price implications. We first show that retail investors' decisions to lever up in stock trading despite the hefty borrowing cost is related to their lottery preferences. We then show that margin borrowing affects investors' trading behavior—investors are more likely to liquidate their holdings as they approach margin calls. Finally, we show that margin‐induced trading aggregates to affect asset prices and contributes to shock spillovers across stocks (e.g., from lottery stocks to nonlottery stocks).

Consumption in Asset Returns

2026-05-15T00:00:00+00:00

The Journal of Finance
Using information in returns, we identify the stochastic process of consumption. We find that aggregate consumption reacts over multiple quarters to innovations spanned by financial markets. This persistent component accounts for over a quarter of consumption variation. These shocks command a large and significant risk premium, driving a large share of stocks' and a small yet significant fraction of bonds' time‐series variation. Nevertheless, we find no support for stochastic volatility of consumption driving time‐varying risk premia. Finally, an otherwise standard recursive utility model based on our estimated process explains equity premium and risk‐free rate puzzles with low‐risk aversion.

Fabricating Effectual Networks: How Hybrid Logics Collectivize Voice for Co-Creation in Makerspaces

2026-05-15T00:00:00+00:00

Entrepreneurship Theory and Practice
Effectuation research posits that effectual networks are composed of self-selecting stakeholders who purchase voice to gain influence in how the effectual process proceeds when they commit to co-create. However, entrepreneurship scholars wrestle with theorizing the social action underlying a theory originally based on the individual decision-making of experts and, specifically, explaining how voice emerges prior to commitment to influence effectual network formation. This study combines the literatures on effectuation and hybrid institutional logics to examine how intermediaries can shape the creation of effectual networks among their members. Through a multiple case study of six makerspaces, the findings reveal how voice emerges and becomes collectivized in the transition from informal collaboration to co-creation. Makerspaces with a high degree of hybrid logics support voice emergence through three social interaction mechanisms: project socializing, market logic embedding, and community logic extending. The study builds a model of effectual network formation via voice emergence moderated by logic hybridity, thereby sharpening the parameters of effectual networks pertaining to voice and co-creation.

Baby Boom or Baby Bust? Parental Leave of TMT Members and Innovation in SMEs

2026-05-15T00:00:00+00:00

Entrepreneurship Theory and Practice
We investigate the effect of parental leave taken by top management team (TMT) members on innovation outputs in small and medium-sized enterprises (SMEs). By analyzing a large sample of Swedish SMEs, we find that the length of parental leave taken by TMT members has a positive effect on SME innovation outputs. This effect is stronger for smaller and longer-tenured TMTs, as these TMTs likely exhibit greater behavioral integration. Such integration can support TMT members in mitigating role conflicts and leveraging the role enhancement benefits connected to performing multiple roles during and after leave. These results contribute to the literature and offer valuable practical insights.

EXPRESS: Integrating Operations and Finance for Sustainable Development: Theory, Practice, and Opportunities

2026-05-16T00:00:00+00:00

Production and Operations Management
Sustainable development demands addressing two core challenges: mobilizing financial resources and aligning stakeholder incentives. This paper surveys the operations-finance interface literature through the lens of “Mobilizing Resources” and “Aligning Incentives” framework. We highlight how the literature advances our knowledge of mitigating SME financing constraints and crafting operationally-informed financial contracts to internalize externalities. We identify a critical gap: while theoretical models for incentive alignment are well-established, empirical evidence remains limited due to the difficulty of analyzing unstructured data. To bridge this gap, we present Large Language Models (LLMs) as a rigorous methodological toolkit for empirical operations management research. We outline a four-step framework—Problem Definition, Model Selection, Prompt Engineering, and Validation—and illustrate its application via a case study that extracts novel data on supplier finance programs from corporate 10-K filings. We conclude by proposing a unified research agenda to advance future research at the intersection of operations, finance, and sustainability.

EXPRESS: Robustness of Online Proportional Response in Stochastic Online Fisher Markets: a Decentralized Approach

2026-05-16T00:00:00+00:00

Production and Operations Management
This study is focused on periodic Fisher markets where items with time-dependent and stochastic values are regularly replenished, and buyers aim to maximize their utilities by spending budgets on these items. Traditional approaches of finding a market equilibrium in the single-period Fisher market rely on complete information about buyers' utility functions and budgets. However, it is impractical to consistently enforce buyers to disclose this private information in a periodic setting. We introduce a distributed bidding algorithm,online proportional response, wherein buyers update bids solely based on the randomly fluctuating values of items in each period. The market then allocates items based on the bids provided by the buyers. We show connections between the online proportional response and the online mirror descent algorithm. Utilizing the known Shmyrev convex program, a variant of the Eisenberg-Gale convex program that establishes market equilibrium of a Fisher market, two performance metrics are proposed: the fairness regret is the cumulative difference in the objective value of a stochastic Shmyrev convex program between an online algorithm and an offline optimum, and the individual buyer's regret gauges the deviation in terms of utility for each buyer between the online algorithm and the offline optimum. Our algorithm attains a problem-dependent upper bound in fairness regret under stationary inputs. This bound is contingent on the number of items and buyers. Additionally, we conduct analysis of regret under various nonstationary stochastic input models to demonstrate the algorithm's efficiency across diverse scenarios. The online proportional response algorithm addresses privacy concerns by allowing buyers to update bids without revealing sensitive information and ensures decentralized decision-making, fostering autonomy and potential improvements in buyer satisfaction. Furthermore, our algorithm is universally applicable to many worlds and shows the robustness of performance guarantees.

EXPRESS: Operations Management under Paradox of Choice

2026-05-16T00:00:00+00:00

Production and Operations Management
This paper examines how assortment size influences consumer purchasing behavior and retailer profits, focusing on the paradox of choice (PoC), where overly limited or excessive options can diminish purchase intent. Although PoC effects are well-documented in behavioral research, their impact on assortment and pricing strategies in retail remains underexplored. To bridge this gap, we formalize PoC mathematically by modeling the utility of the no-purchase option as a U-shaped function of assortment size. We integrate this PoC framework into several discrete choice models, using the multinomial logit (MNL) model as the focal model. By decomposing the assortment problem into subproblems with fixed assortment sizes, we develop efficient solutions for the assortment optimization and the joint assortment and price optimization problems under the MNL with PoC model. Additionally, we compare the optimal solutions of the classical MNL model and the MNL model with the PoC effect through theoretical analysis and numerical experiments, offering managerial insights to guide firms in optimizing their assortments. We further extend our approach to derive optimal assortment and pricing solutions for the nested logit model employing a linear programming approach. Moreover, we devise a Fully Polynomial Time Approximation Scheme (FPTAS) for the assortment optimization under the mixture of multinomial logit model with the PoC effect. This study advances the integration of behavioral insights into discrete choice models, illustrating how retailers can optimize product assortments and prices by balancing variety with cognitive effects linked to assortment size.

Impact of disruption risk at different supplier tiers

2026-05-16T00:00:00+00:00

Production and Operations Management
This article aims to study the impacts of disruption risk at different supplier tiers on the performance of both centralized and decentralized supply chains. We consider a three-tier supply chain, containing a tier-0 firm (original equipment manufacturer [OEM]), two potential tier-1 suppliers, and two potential tier-2 suppliers. Either a tier-1 or a tier-2 supplier is susceptible to disruption risk. We solve and analyze the optimal/equilibrium sourcing strategy and production quantities and compare the resulting supply chain network structures and the profits. Our results show that without fixed sourcing cost (and so each firm adopts dual sourcing and the resulting supply chain network is complete), the centralized supply chain suffers a greater profit loss when facing disruption risk at tier-1 suppliers than at tier-2 suppliers. Interestingly, this result reverses in the decentralized supply chain if the disruption risk is high. When fixed sourcing costs are present, the centralized system is less inclined to source from an unreliable tier-1 firm than from an unreliable tier-2 firm. In the decentralized supply chain, with the increase of fixed sourcing cost, the OEM’s sourcing strategy changes from dual sourcing to single sourcing when a tier-1 supplier is unreliable; surprisingly, the OEM may switch from single sourcing back to dual sourcing when a tier-2 supplier is unreliable because of the change in tier-1 suppliers’ sourcing strategy. Our results offer some guidance for firms on their risk mitigation strategies in their supply chains and provide insights into the impact of disruption risk on the supply chain structure.

EXPRESS: The Value of Experience-Centric Stores in Omnichannel Retail: a Multi-Method Approach at the Category Level

2026-05-16T00:00:00+00:00

Production and Operations Management
For omnichannel multi-brand retailers, store openings are consequential strategic decisions. Beyond whether to open a store, firms must choose a format, select product categories, and decide how to support them in-store. To inform these decisions, we study the openings of two large experience-centric stores and one small convenience-centric store operated by an omnichannel consumer electronics retailer. Using a staggered difference-in-differences model, we estimate the impact of store openings on retailer performance while accounting for product-category heterogeneity. We find that all three openings reduce online net revenue (online purchases minus returns), contrary to halo-effect expectations. However, only the large experience-centric stores offset these losses, increasing total net revenue (online plus in-store purchases, net of returns) by 21%–23% in the short term, with effects that grow over time. The small convenience-centric store does not generate such gains. Total net revenue uplift also varies substantially across product categories within experience-centric stores. To explain this heterogeneity, we combine category-level sales data with survey-based measures of perceived in-store utility across three customer journey stages: information search, fulfillment, and returns. Using the retailer’s classification, we distinguish between destination categories‒higher-priced, complex products that motivate store visits (e.g., TVs)‒and accessory categories‒lower-priced complementary products (e.g., earbuds). For destination categories, variation in perceived in-store utility, especially at the information-search and fulfillment stages, explains differences in total net revenue uplift. For accessory categories, such variation is not statistically associated with revenue gains. These findings show that store format alone is not sufficient: the effectiveness of store openings depends on how well in-store capabilities align with category-specific customer needs across the customer journey, highlighting the importance of prioritizing destination categories while reconsidering the role of physical stores for accessory categories.

Bank Competition Amid Digital Disruption: Implications for Financial Inclusion

2026-05-17T00:00:00+00:00

The Journal of Finance
We examine how digital disruption affects bank competition using the staggered rollout of 3G mobile networks. 3G expansion increased mobile banking adoption among tech‐savvy households, reducing branch networks—especially in younger counties. Banks' strategies diverged: Less branch‐reliant banks closed branches and competed on price, while more branch‐reliant banks maintained branches but raised spreads. A structural model shows that perceived digital service improvements among younger consumers drove these shifts, reducing welfare for older savers. Counterfactuals demonstrate that subsidizing adoption for older savers can cost‐effectively reduce these disparities, facilitating a smoother digital transition.

Catastrophes, Delays, and Learning

2026-05-18T00:00:00+00:00

Review of Economic Studies
We propose a simple and general model of experimentation in which reaching untried levels of a stock variable may, after a stochastic delay, lead to a catastrophe. Hence, at any point in time a catastrophe might well be under way, due to past experiments. We show how to measure this legacy of the past from prior beliefs and the chronicle of stock levels. We characterize the optimal policy as a function of the legacy and show that it leads to a new protocol for planning that applies to a general class of problems, encompassing the study of pandemics or climate change. Several original policy predictions follow, e.g. experimentation can stop but resume later.

National security-related foreign investment screening laws and investment efficiency

2026-05-18T00:00:00+00:00

Review of Accounting Studies
This study investigates the effect of national security-related foreign investment screening laws on managers’ investment choices. These laws weaken takeover markets by granting regulators broad new powers to revise or reject foreign takeovers of firms in national security-related industries. I identify exogenous variation in national security-related foreign investment screening laws using the enactment of a U.S. national security-related foreign investment screening law known as the Foreign Investment and National Security Act (FINSA). Consistent with managerial entrenchment theory, I document that, following the enactment of FINSA, national security firms’ inefficient investment increases. Event-time tests corroborate and cross-sectional tests demonstrate that results strengthen with treatment strength. Results generalize to seven alternative investment efficiency measures. Stacked panel tests exploiting regulators’ staggered enforcement of FINSA across 66 industries over time between 2008 and 2021 further corroborate. Overall, this study documents the unintended consequences of national security-related foreign investment screening laws on managers’ investment choices.

EXPRESS: Should a Retailer Disclose Its Unit Variable Costs in Monopoly and Duopoly Markets

2026-05-18T00:00:00+00:00

Production and Operations Management
Should a retailer disclose its variable costs to consumers? While disclosing variable costs (e.g., material cost, production cost, and shipping cost) can build consumer trust through transparency, it may also lead to resentment if the actual gross profit margin, deduced from the disclosed costs, is perceived as excessively high. By incorporating key findings from behavioral experiments in the literature, we present an exploratory model to examineif and whena firm should disclose its variable costs in both monopoly and duopoly markets.Assuming that consumers use the concept ofrational expectation equilibriumto infer the firm’s actual variable costs when they are not disclosed, our equilibrium analysis yields the following results that provide insights when a retailer should adopt cost disclosure. Specifically, in the monopoly model, we find that consumers tend tooverestimatethe firm’s true variable costs when the firm does not disclose them. This occurs because consumers use the observed price as a “signal” about the undisclosed true cost, and believe that the firm would set its price closer to the true cost. Also, a monopoly should not disclose its true variable costs to prevent pressure to lower its gross profit margin, especially when consumers are highly concerned about the firm’s gross profit margin. This behavior persists in the duopoly model. In the duopoly model, we find two additional results: as competition intensifies, both firms are more likely to disclose their true variable costs in equilibrium to gain additional trust from consumers. However, when competition is moderate but the cost differential between firms is sufficiently high, only one firm would disclose its true costs in equilibrium.

EXPRESS: Assured Autonomy: How Operations Research Powers and Orchestrates Generative AI Systems

2026-05-18T00:00:00+00:00

Production and Operations Management
Generative artificial intelligence (GenAI) is shifting from conversational assistants toward agentic systems—autonomous decision-making systems that sense, decide, and act within operational workflows. This shift creates an autonomy paradox: as GenAI systems are granted greater operational autonomy, they should, by design, embody more formal structure, more explicit constraints, and stronger tail-risk discipline. We argue that stochastic generative models can be fragile in operational domains unless paired with mechanisms that provide verifiable feasibility, robustness to distribution shift, and stress testing under high-consequence scenarios. To address this challenge, we develop a conceptual framework for assured autonomy grounded in operations research (OR), built on two complementary approaches. First,flow-based generative modelsframe generation as deterministic transport characterized by an ordinary differential equation, enabling auditability, constraint-aware generation, and connections to optimal transport, robust optimization, and sequential decision control. Second,operational safetyis formulated through an adversarial robustness lens: decision rules are evaluated against worst-case perturbations within uncertainty or ambiguity sets, making unmodeled risks part of the design. This framework clarifies how increasing autonomy shifts OR’s role from solver to guardrail to system architect, with responsibility for control logic, incentive protocols, monitoring regimes, and safety boundaries. These elements define a research agenda forassured autonomyin safetycritical, reliability-sensitive operational domains.

EXPRESS: Rare Diseases Are Not Rare: Challenges and Opportunities for OM Research

2026-05-18T00:00:00+00:00

Production and Operations Management
There are more than 7,000 known rare diseases, yet around 95% of them lack effective treatments. This paper explores how Operations Management (OM) research can help improve patient access to rare disease treatments. We first examine key challenges and opportunities from the perspectives of governments, industry, insurers, and patients. We then outline future research directions, focusing on regulatory frameworks, subsidy and incentive schemes, pricing and coverage decisions, (bio)pharmaceutical manufacturing, and challenges in developing economies. The application of OM methodologies to the rare disease landscape is still limited, but offers significant potential to advance new drug development, increase patient access to correct diagnosis and treatment, and reduce healthcare inequalities for patients with rare diseases.

High-Dimensional Dynamic Pricing Under Nonstationarity: Learning and Earning with Change-Point Detection

2026-05-18T00:00:00+00:00

Management Science
We consider a high-dimensional dynamic pricing problem under nonstationarity, in which a firm sells products to T sequentially arriving consumers that behave according to an unknown demand model with potential changes at unknown times. The demand model is assumed to be a high-dimensional generalized linear model (GLM), allowing for a feature vector in [Formula: see text] that encodes products and consumer information. To achieve optimal revenue (i.e., least regret), the firm needs to learn and exploit the unknown GLMs, monitoring for potential change points. To tackle such a problem, we first design a novel penalized likelihood-based online change-point detection algorithm for high-dimensional GLMs, and this is the first algorithm in the change-point literature that achieves optimal minimax localization error rate for high-dimensional GLMs. A change-point detection assisted dynamic pricing (CPDP) policy is further proposed and achieves a near-optimal regret of order [Formula: see text], where s is the sparsity level and [Formula: see text] is the number of change points. This regret is accompanied with a minimax lower bound, demonstrating the optimality of CPDP (up to logarithmic factors). In particular, the optimality with respect to [Formula: see text] is seen for the first time in the dynamic pricing literature and is achieved via a novel accelerated exploration mechanism. Extensive simulation experiments and a real data application on online lending illustrate the efficiency of the proposed policy and the importance and practical value of handling nonstationarity in dynamic pricing.This paper was accepted by Vivek Farias, data science.Funding: F. Jiang is supported in part by the National Natural Science Foundation of China [Grants 72522009, 12201124, 12331009, 72271060, and 72432002] and National Key Research and Development Program of China [Grant 2024YFA1015700]. Y. Yu is supported by Engineering and Physical Sciences Research Council [Grant EP/Z531327/1] and the Leverhulme Trust.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00889 .

Designing Payment Models for the Poor

2026-05-18T00:00:00+00:00

Management Science
Millions of people in poverty lack access to basic services such as energy, clean water, and cooking gas. Private firms are increasingly delivering these services—for example, by offering solar home systems or clean cooking packages with remote lockout capabilities—through pay-as-you-go (PAYGo) contracts that give consumers flexibility over payment timing and amount to match their erratic cash flows. Because firms cannot observe consumer liquidity, however, consumers may misuse this flexibility and prioritize other needs over repayment. We study how to design contracts that preserve flexibility while creating incentives for timely repayment using an optimal contracting approach. The optimal contract summarizes each consumer’s payment history with a single score, controls flexibility by recommending payment amounts, and incentivizes payments by specifying how the score updates after each payment. The score determines both the level of technology access granted to the consumer and whether the contract is continued or terminated. Although effective in aligning incentives, this dynamic scheme can be difficult for consumers to comprehend. Therefore, we identify key structural features of the optimal contract and design a simpler, more practical version that preserves these features in which consumers access the technology using credit points that they gain or lose over time based on their payment histories. We also discuss how incorporating these key features could help PAYGo firms improve upon their current practices.This paper was accepted by Jay Swaminathan, operations management.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.02156 .

A Re-Examination of Firm Size and Taxes

2026-05-18T00:00:00+00:00

Management Science
We document that larger firms pay substantially lower cash effective tax rates (cash effective tax rates (ETRs)) over the long run than smaller firms. Over a 10-year period, firms in the largest decile pay 10.4 percentage points (p.p.) (25%) lower cash taxes than those in the smallest decile, and this gap balloons to 14.4 p.p. (35%) for the largest 1% of firms. This pattern is robust to various specifications but vanishes when cash ETRs are measured annually. The relation between firm size and taxes over the long run cannot be explained by foreign operations, depreciation, research and development spending, or stock compensation, characteristics commonly associated with aggressive tax practices. Meanwhile, the observed tax inequality is strongly associated with the incidence of losses. Because smaller firms are more likely to incur significant losses, which are often not deductible against profits, they consequently face higher effective tax rates. A key finding of our paper is that the size effect reflects differences in loss rates, and consequently utilization, rather than political costs or benefits. A cross-country analysis supports these findings.This paper was accepted by Ranjani Krishnan, accounting.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.05865 .

EXPRESS: Where Should Firms Implement Differential Privacy in Targeting? Implications for Profitability

2026-05-18T00:00:00+00:00

Journal of Marketing Research
Firms use privacy-sensitive data to make targeting decisions, which can inadvertently reveal the underlying information driving those decisions—a risk the authors termtargeting privacy risk. The authors use differential privacy to quantify and control this risk. Although firms increasingly adopt differential privacy, policymakers offer limited guidance on its implementation in a targeting framework. The crucial question, therefore, becomes: where should firms implement differential privacy? The authors find that profitability critically depends on where differential privacy is implemented within a typical targeting workflow. This insight stems from two novel targeting strategies: one implements differential privacy during model training, the other at the targeting-decision stage. Using a large-scale field experiment involving 747,975 customers and extensive simulations, the authors show that both strategies remain profitable under strong privacy protection. Notably, the decision-stage strategy yields, on average, fivefold higher profits than alternative implementations. To generalize this finding, the authors derive the expected profit for a given privacy risk level and a privacy elasticity of targeting profits. Collectively, the results offer guidelines for firms and policymakers to ensure privacy protection and profitability.

EXPRESS: First-Party Content Production in a Competitive Media Market

2026-05-18T00:00:00+00:00

Journal of Marketing
Major video streaming distributors are investing heavily in producing first-party (original) content, yet the economic viability of this high-cost strategy remains a subject of intense managerial debate. This paper develops an analytical model to investigate the optimal first-party content production strategy for asymmetric competing distributors. The analysis shows that two critical factors, existing content overlap and market price rigidity, affect their optimal strategies. In markets with high price rigidity, where subscription prices remain constant, increased existing content overlap may give distributors stronger incentives to invest in original content production. The equilibrium outcome can be both, only one, or neither producing first-party content. Conversely, in markets characterized by low price rigidity, where distributors can adjust subscription prices flexibly, high existing content overlap weakens their content production incentives. Importantly, compared to constant pricing, when prices are optimally adjusted, first-party and third-party content transition from substitutes to complements, and a win-win-win outcome can occur for distributors, third-party producer, and consumers. These findings challenge conventional wisdom regarding content competition and provide a strategic framework for managers to optimize content production investments based on their resource asymmetry and prevailing market pricing dynamics.

EXPRESS: Product Portfolio Choices with Product Life Cycles

2026-05-18T00:00:00+00:00

Journal of Marketing
How do multi-product firms adjust their product portfolios in response to increased competition, and what are the implications for policy evaluation? In high-tech markets, products with similar profits at launch may have predictably different future profit paths, shaping firms’ product introduction decisions. Using data from the Chinese smartphone market, the author shows that product life cycles (PLCs) vary systematically with product quality and market competition, and that firms act on these differences when introducing new products. The author embeds firms’ PLC expectations into a structural model of product portfolio competition and evaluates the effects of fringe entry induced by an industrial policy. Counterfactuals show that ignoring firms’ portfolio adjustments overstates consumer welfare gains from increased competition by 70%; conditional on portfolio adjustment, holding PLC expectations fixed understates firms’ portfolio response by 10% and overstates welfare gains by 9%. Increased low-end competition also shifts incumbent firms’ product introductions toward lower-quality “fighting brands.”

When Doing Good Feels Wrong: The Dual Influence of Perceived Organizational Opportunism on Employee CSR Behaviour

2026-05-18T00:00:00+00:00

Journal of Management Studies
Corporate social responsibility (CSR) initiatives are widely recognized for generating benefits such as enhanced reputation, stronger stakeholder trust, and improved employee engagement. These outcomes, however, often depend on the perception that organizations pursue CSR out of a sincere commitment to social and environmental values. Yet many employees question the sincerity of CSR efforts, especially when these initiatives are seen as opportunistic and self‐serving. Drawing on cognitive dissonance theory, we develop and empirically test a dual‐pathway model explaining employees' behavioural responses to perceived organizational opportunism (i.e., the strategic use of CSR to advance self‐interested motives rather than genuine social impact). Across two time‐lagged studies conducted in distinct organizational contexts, we demonstrate that such perceptions elicit divergent employee reactions: heightened moral disengagement and symbolic CSR behaviour alongside diminished moral ownership and substantive CSR engagement. We also show that psychological empowerment moderates these mechanisms by weakening the effect of perceived opportunism on moral disengagement and mitigating its adverse effect on moral ownership. Overall, our findings contribute to research on micro‐CSR and organizational behaviour by clarifying the moral processes through which employees interpret and respond to inconsistent organizational cues.

Conflict-Situated Cooperation: How Israeli and Palestinian IT Professionals Give Meaning to Cooperating Under Ethnonational Conflict

2026-05-18T00:00:00+00:00

Journal of Management
Despite persisting ethnonational conflict in Israel and Palestine, professionals in the information technology (IT) sector keep working together. They engage in professional cooperation by jointly developing software while embedded in societal narratives that cast the other as the enemy. We ask how individuals give meaning to their work when cooperating with their societal adversaries in such a context. Drawing on a qualitative case study that combines interviews, observations, and documents, we find that individuals use two main tactics to cope with the conflict context: depoliticizing and politicizing cooperation. We specify these individual-level tactics and show when they are used: depoliticizing in situations “at work” and politicizing in situations “about work.” We also show that these tactics are at times misplaced and hinder cooperation. Additionally, we find that physical and social interference can disrupt cooperation and thus set guardrails for it. Abstracting from our findings, we theorize a model that explains how individuals engage in what we term conflict-situated cooperation. We offer two main contributions to management research: We introduce the concept of conflict-situated cooperation to capture the distinct nature of professional cooperation in the context of ethnonational conflict, and we explain how individuals use and situate (de)politicizing coping tactics to give meaning to their professional cooperation.

Jackknife Standard Errors for Clustered Regression

2026-05-19T00:00:00+00:00

Review of Economic Studies
This paper presents a theoretical case for replacement of conventional heteroskedasticity-consistent and cluster-robust variance estimators with jackknife variance estimators, in the context of linear regression with heteroskedastic and/or cluster-dependent observations. We examine the bias of variance estimation and the coverage probabilities of confidence intervals. Concerning bias, we show that conventional variance estimators have full downward worst-case bias, while our jackknife variance estimator is never downward biased. Concerning confidence intervals, we show that intervals based on conventional standard errors have worst-case coverage equalling zero, while the jackknife-based confidence interval has coverage probability bounded by the Cauchy distribution, under the auxiliary assumption of normal errors. We also extend the Bell-McCaffrey (2002) student t approximation to our jackknife t-ratio, resulting in confidence intervals with improved coverage probabilities. Our theory holds under broad assumptions, allowing arbitrary cluster sizes, regressor leverage, within-cluster correlation, heteroskedasticity, regression with a single treated cluster, fixed effects, and delete-cluster invertibility failures. Our theoretical findings are consistent with the extensive simulation literature investigating heteroskedasticity-consistent and cluster-robust variance estimation.

The Dynamics of Internal Migration: A New Fact and its Implications

2026-05-19T00:00:00+00:00

Review of Economic Studies
We propose a new model of internal migration, based on persistent and spatially-correlated idiosyncratic utility. The model is motivated by a new fact in the data that simple moving cost models struggle to match: the t-year interstate migration rate is proportional to the square root of t. The new model maintains the tractability and flexibility of standard migration models, but better matches the dynamics of migration, including the new fact. It has substantially different welfare implications and makes different counterfactual predictions, especially in terms of dynamic adjustment and long-run responses.

Improving Upon the Generalized c μ Rule: A Whittle Approach

2026-05-19T00:00:00+00:00

Operations Research
Better Scheduling When the Cost of Delay Grows over TimeImagine a stream of jobs, in which each job costs us some money (a holding cost) for every hour that it is not complete. Furthermore, the holding cost of each job can increase over time and possibly even jump up at deadlines associated with the job. To minimize the rate at which we hemorrhage money, it is common to deploy well-known strategies such as the celebrated generalized c-mu rule, which prioritizes scheduling jobs based on their instantaneous holding cost. However, this approach is limited: it ignores how costs rise in the future; for example, a job with a deadline might be ignored until after the deadline is missed. Li, Gurushankar, Harchol-Balter, and Scheller-Wolf tackle this time-varying holding cost problem by translating it into a restless multiarmed bandit, which they use to derive a Whittle index. This leads to a new priority rule that accounts for how both holding costs and workloads evolve in the future. Their rule is simple to implement, yet it is remarkably robust, consistently outperforming all known heuristics across a wide range of settings.

Fifty Years of Anchoring Effects: A Theoretical Reintegration and Meta-Analysis

2026-05-19T00:00:00+00:00

Management Science
One of the most robust phenomena studied across the social behavioral sciences is numeric anchoring, in which a comparison against a presumed-to-be arbitrary number preceding a judgment can influence a myriad of real-world-relevant judgments. The authors meta-analyze the expansive literature containing 2,601 total effect sizes (1,280 comparing high anchors against low anchors), finding a large (Hedges’[Formula: see text] confidence interval [0.765, 0.884], [Formula: see text]) effect that remains large even after accounting for extensive publication bias. Evidence suggests reduced (or null) effects associated with incidental anchoring (i.e., numeric priming), anchors from different dimensions, or from random numbers, the presence of incentives or debiasing interventions, and whether the anchor provides directional information. The authors provide a comprehensive review of both the empirical and theoretical landscape and offer recommendations for consolidating the literature, improving theory testing, future development of theory and methods related to anchoring, and guidance for managers attempting to use anchoring effects in strategic and policy decisions.This paper was accepted by Jack Soll, behavioral economics and decision analysis.Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2023.03238 and at Open Science Foundation’s (OSF) repository page https://osf.io/d583s/overview .

Technology Adoption and Leapfrogging: Racing for Mobile Payments

2026-05-19T00:00:00+00:00

Management Science
Mobile payments are reshaping the global payment landscape with some developing economies leapfrogging advanced economies in adoption. We build and estimate a dynamic model of sequential payment innovations—progressing from cash to card to mobile—to explain this pattern. The model matches cross-country payment technology adoption patterns and shows how advanced economies’ early success in adopting card payments dampens subsequent mobile payment adoption. Extending the framework to a two-sided market with price coherence, we show that payment externalities justify policy intervention: Promoting mobile payment adoption and usage (e.g., via subsidies or price differentiation) enhances welfare, especially in developing economies.This paper was accepted by Lin William Cong, Virtual Special Issue on Digital Finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.00781 .

Learning Product Improvement from Consumer Evaluations

2026-05-19T00:00:00+00:00

Management Science
Product Improvement (PI) involves making minimal changes to an existing product to enhance its market performance. A key source of information for PI is Consumer Evaluation (CE), provided either in aggregate (e.g., sales volume) or descriptive (e.g., online reviews) form. Existing PI approaches analyze the descriptive CE of the focal product, which limits their applicability when descriptive CE is missing, abstract, or interdependent. More importantly, current methods are primarily descriptive and do not generate actionable PI recommendations, despite their considerable value to practitioners. We address these challenges with a new approach that leverages both aggregate and descriptive CE across the entire market to prescribe specific PI recommendations. We first develop Product Segmentation (PS) trees, a type of decision tree with a customized objective function designed to identify the features that best segment products by market performance. We then build a constrained shortest-path algorithm over the PS tree structure to prescribe minimal improvements for any underperforming product. To enhance robustness, we ensemble multiple PS trees, each trained with distinct objectives, into a novel PS forest. Using both real and synthetic data, our approach achieves 73% average precision in PI and improves upon the best benchmarks by 11%. Lastly, we conduct a conjoint analysis to behaviorally validate that consumers prefer the PI recommendations generated by our method over the original underperforming products. Our theoretical and empirical results show that the proposed approach addresses key challenges in using CE for PI and offers interpretable and actionable decision support for practitioners.This paper was accepted by D. J. Wu, information systems.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.00055 .

Know Your Users via Image Analytics Before Developing Posts: Data-Driven Optimization Framework to Enhance Social Media Engagement

2026-05-19T00:00:00+00:00

Management Science
Social media platforms are popular for advertisers to promote products to their audience via posts. Developing these posts with the appropriate number of image features is essential as these features enhance informativeness and visual complexity, impacting how users engage with posts. However, the existing literature offers a limited investigation into this topic, primarily examining low-level imagery information while overlooking high-level image features, cross-platform differences arising from different user expectations, and the tradeoffs firms must make in tailoring their strategies. To address this critical gap, we develop an optimization framework for analyzing and publishing social media image posts for different platforms within a firm’s limited budget. This optimization framework is grounded in empirical modeling of the association between image features and social media user engagement, with primary and secondary features identified using deep learning algorithms. We focus on secondary features because they add visual complexity and informativeness, are controllable by designers, and are costly to extract, underscoring the need to assess their value for engagement. We find a nonlinear association between secondary features and engagement that varies across the two platforms. The optimization framework, which models the nonlinear relationship and is tested on realistic scenarios, considers and compares our approach against commonly used strategies that allocate budgets solely based on the user bases of platforms, those that ignore secondary features, and those that do not use duplicate features that can enhance informational richness and context. We present key implications for firms seeking to maximize user engagement on social media platforms.This paper was accepted by George Shanthikumar, data science.Funding: S. Kumar was supported by the Temple Center for International Business Education and Research.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01838 .

From Platform Design to Attention Governance: Rethinking Social Media Externalities

2026-05-19T00:00:00+00:00

Journal of Management Studies
Social media platforms have become central infrastructures through which information is produced, distributed, and contested in contemporary societies, with growing consequences for organizations, social interactions, and democracy. Yet, management and organization scholars tend to treat social media platforms as contexts rather than focal organizational entities. Synthesizing aPoint Counterpointdebate, we argue that key disagreements across the debate articles can best be understood as a question of attention governance – who controls attention allocation, by what rules, and with what accountability. We show that despite divergent causal diagnoses (political capture, incentive distortion, or structural constraints), the contributions converge on attention considerations as a key factor through which social media externalities are produced. We synthesize the debate views through three unifying threads: an interest in how attention is valued and accumulated as currency and infrastructure, the recognition of a gradual shift of rule decision‐making from collectively negotiated to algorithmically determined, and the reliance on increasingly thinner decision rules. We conclude with a governance research agenda to advance theory on social media platform externalities.

Why Have CEO Pay Levels Become Less Diverse?

2026-05-19T00:00:00+00:00

The Journal of Finance
This paper documents a new stylized fact: the cross‐sectional variation in CEO pay levels has declined precipitously in recent years. We offer one explanation for this decline, namely, firms are increasingly benchmarking CEO compensation to industry peers closest in size, thereby creating pay clusters. Our empirical tests provide support for this explanation and suggest that the rise of industry‐size benchmarking is driven by three institutional factors: the mandatory disclosure of compensation peer groups, proxy advisory influence, and say‐on‐pay regulation. Our findings highlight a consequence of adopting a one‐size‐fits‐all standard in the pay‐setting process.

Games People Play: Strategies to Develop and Release Online Games

2026-05-19T00:00:00+00:00

Information Systems Research
When should a game studio continue building in beta and when should it go live? In an industry defined by continuous updates and diverse players, online game developers must decide what to build and when to release while balancing engagement, monetization, and development resources. Unlike traditional software, online games operate in a mass market environment where users differ widely in experience and tolerance for bugs, and where frequent updates are essential to maintain interest and competitiveness. We show that beta releases are not only testing tools but strategic instruments for managing user diversity, product complexity, and release timing. Beta phases allow firms to gather feedback and refine features before broader release. Full releases should be delayed when complexity is high or when experienced users represent a large share of the user base. Release decisions must balance development constraints with market pressures. Although delaying releases can improve quality, competition may require earlier launches. From a policy perspective, platform operators can support better outcomes by enabling structured beta programs, managing user expectations, and providing tools for staged rollouts. These practices help improve product quality, reduce negative user experiences, and enhance long-term user engagement in digital ecosystems.

When Do Employees Choose to Invest in Their Firms? An Empirical Examination of Factors Affecting Employees' Participation in Employee Stock Purchase Plans

2026-05-19T00:00:00+00:00

Human Resource Management
The present study examined factors predicting employee participation in employee stock purchase plans (ESPPs). Despite the plausible benefits of ESPPs for participating employees, many employees do not participate in ESPPs even when they are eligible. To shed light on this puzzle, we investigated key variables related to the plan (i.e., discount rates), the firm (i.e., stock price movements), and an external event (i.e., COVID‐19 pandemic) in relation to employees' participation in ESPPs. Using a unique proprietary dataset on employee stock purchases from 40 publicly traded companies with a total of 1,005,300 employees, we found that discount rates and past stock price increases, on their own, were not associated with higher participation. However, these relationships became significantly positive when past stock prices displayed stability rather than volatility during certain pre‐participation periods. In addition, we observed that the firms in our dataset had significantly higher ESPP participation rates during (vs. before) the pandemic. These findings offer various research and practical implications, extending the compensation and employee ownership literature that has paid little attention to the predictors of employees' ESPP participation.

Is the Venture Growth-Survival Relationship Inverted U-Shaped or Not? A Replication and Extension

2026-05-19T00:00:00+00:00

Entrepreneurship Theory and Practice
This study revisits the assumption that moderate growth offers the most reliable path to new venture survival. Adopting a lifetime growth perspective, we distinguish genuine failure from strategic or neutral exits to better understand the growth–survival relationship. Using 246,831 venture-year observations from 52,277 Dutch startups (2007–2019), we replicate and extend prior research. While moderate annualized growth enhances short-term survival, our extension reveals a contrasting long-term pattern: ventures with either low or high lifetime growth exhibit the greatest survival likelihood. These findings reconcile competing perspectives and highlight how ventures need to navigate short- and long-term pressures to survive.

Self-Employment Entry Across Family Transitions: Household Capability Reallocation Over the Life Course

2026-05-19T00:00:00+00:00

Entrepreneurship Theory and Practice
This study examines how major family transitions—marriage, childbirth, divorce, widowhood, and the co-occurrence of marriage and childbirth within the same observation interval—are associated with entry into self-employment as households reallocate risk, care, and income responsibilities. Using longitudinal Canadian data from the Longitudinal and International Study of Adults (2012–2020), it draws on life-course theory, household bargaining perspectives, and the capability approach to conceptualize self-employment entry as a process of contingent capability reallocation rather than simply a reflection of stable entrepreneurial preferences. The findings show that identical life events generate divergent entry responses across gendered breadwinner roles, caregiving demands, and life stage. Marriage and childbirth are positively associated with entry on average, but these associations are contingent: marriage is most strongly associated with entry among newly married secondary-earning women, while childbirth suppresses entry for primary-earning mothers and attenuates for new fathers as caregiving intensity rises. Divorce shows no uniform association: it is positively associated with childcare-expense responsibility but negatively associated with prior primary-earner status. Widowhood is associated with reduced entry, with no working-age moderation. Finally, the co-occurrence of marriage and childbirth within the same biennial interval is associated with higher entry than either transition alone.

The Promise–Risk Balance: Recalibrating Design Choices and Strategic Framing Following Catastrophic Innovation Failure

2026-05-19T00:00:00+00:00

Administrative Science Quarterly
Catastrophic innovation failure derails firms’ innovation process and threatens their legitimacy. Prior research has analyzed internal and external responses to failure separately, focusing either on intra-firm learning and failure remediation or on efforts to sustain stakeholder support. Research on these responses’ co-evolution has been notably absent. We examine how a firm jointly recalibrated internal design choices and external strategic framing following catastrophic innovation failure, through a study of Virgin Galactic’s 2014 test flight crash. We introduce and develop the concept of the “promise–risk balance”: a state in which the uncertainty inherent to innovation and the framing communicated to stakeholders stand in generative tension and jointly support the innovation process. Catastrophic innovation failure disrupts this balance. We map Virgin Galactic’s recalibration of risk via internal design choices and recalibration of promise via external framing as interdependent levers to restore balance. We show that design choices aimed at de-risking technology can have adverse effects on a firm’s capabilities, externally dampening promise. Following failure, strategic reframing must bring the firm’s external message in line with actual capabilities and inspire stakeholder support. Recognizing and managing interdependencies between design choices and strategic framing is crucial to the continuity of the innovation process and firm survival.

When more capacity creates more congestion: The role of risk aversion

2026-05-03T00:00:00+00:00

Production and Operations Management
A fundamental principle in operations management holds that increasing the number of servers reduces delays in service systems. To date, no mechanism has been identified that could reverse this effect. We propose, however, that risk aversion can cause increased service capacity to intensify congestion. We study an unobservableM/M/squeue where risk-averse customers choose whether to join based on their anticipated waiting time. We show that, in equilibrium, demand, expected waiting time, expected sojourn time, and the probability of waiting all increase with the number of servers, and that these effects are stronger for more risk-averse customers. We further uncover the mechanism behind this phenomenon: adding servers makes delays less risky (in the sense of second-order stochastic dominance), which increases the sensitivity of demand to capacity as customers become more risk-averse. These patterns are more prevalent in small systems and fade as the system grows. They can also persist when customers differ in their degree of risk aversion, when capacity is increased by raising service speed, and when the system is observable. Our findings reveal a novel trade-off created by customer risk aversion: expanding capacity attracts more customers, but also exacerbates congestion. A manager aiming to reduce waiting times may therefore prefer to de-pool service capacity instead of following the standard approach of pooling, while increasing capacity in the resulting smaller systems to preserve total throughput. When the objective is to maximize profitability, our results further suggest that the cost of additional servers may be offset by the associated increase in revenue when customers are sufficiently risk-averse.

Generative AI Use by Capital Market Information Intermediaries: Evidence from Seeking Alpha

2026-05-03T00:00:00+00:00

Journal of Accounting Research
We study the use of generative AI for firm‐specific financial analysis on the Seeking Alpha platform. After the initial launch of ChatGPT in November 2022, the share of AI‐generated articles rose sharply to 13.5% of all articles, then declined in late 2023 after Seeking Alpha equated the use of AI to plagiarism and announced a prohibition on its use. We organize our study around two questions: (1) Does AI use increase author productivity? and (2) does AI use have capital market consequences and ultimately affect the informational landscape? We find that authors who adopt AI become more productive, publishing more articles and covering more new firms than non‐adopters. Findings on AI article informativeness are more nuanced. On average, AI articles are less informative than human‐written articles, eliciting smaller trading volume and abnormal return responses. However, AI use leads to increased firm coverage and in turn to improved liquidity and faster price discovery. Our findings suggest that, while AI‐generated articles are currently perceived as less informative than human‐written articles, their comparatively low cost enables increased firm coverage and thereby improves the overall informational landscape.

A Tale of Two Market Disciplines: How Does Bank Financial Misconduct Affect Peer Banks in the Local Deposit Market

2026-05-03T00:00:00+00:00

Journal of Accounting Research
This study examines the spillover effect of bank financial misconduct on the uninsured deposits of peer banks within local markets. We first validate that misconduct banks experience an increase in deposit spreads and a corresponding outflow of deposits following the misconduct. We then show local peer banks exhibit divergent deposit responses, contingent on how misconduct is perceived by information recipients in different economic contexts. During normal periods, depositors receiving a negative signal about bank misconduct reallocate their funds from misconduct banks to local peers, alocal reallocation effectthat decreases deposit spreads and increases deposit inflows for peer banks. Cross‐sectional analysis further reveals that this local reallocation effect is more pronounced for financially sophisticated depositors, amplified when peer banks have strong fundamentals, but attenuated when misconduct banks are financially sound. During financial crisis periods, however, bank misconduct leads to withdrawals from both misconduct banks and their peer banks, alocal contagion effectwhereby local peer banks face increased deposit spreads and deposit outflows following the misconduct.

Asymptotic Product-Form Steady State for Generalized Jackson Networks in Multiscale Heavy Traffic

2026-05-04T00:00:00+00:00

Operations Research
Product-Form Steady-State Approximation of Generalized Jackson NetworksIn “Asymptotic Product-Form Steady State for Generalized Jackson Networks in Multiscale Heavy Traffic,” Dai, Glynn, and Xu revisit a long-standing question in queueing network theory. For open Jackson networks in which interarrival and service distributions are exponential, steady-state queue lengths are independent and admit a product-form distribution, making performance analysis tractable and scalable. For generalized Jackson networks with general primitive distributions, the product-form structure no longer holds. The authors show that under a multiscale heavy traffic condition—where different stations operate at widely separated levels of congestion—the stationary distribution of suitably scaled queue lengths admits an asymptotic product-form limit. In this limit, each component is exponentially distributed, with a rate that depends only on the first two moments of the primitive distributions. This result, along with its recent generalizations, creates the potential for a scalable performance analysis tool for generalized Jackson networks and beyond.

COPPAcalypse? The YouTube Settlement’s Impact on Kids’ Content

2026-05-04T00:00:00+00:00

Management Science
We examine how privacy restrictions affect online content creation and consumption by evaluating the impact of YouTube’s settlement with the Federal Trade Commission over violating the Children’s Online Privacy Protection Act. Under the settlement, YouTube limited personalization for made-for-kids (MFK) content starting in January 2020, and this included personalized ads and content engagement features such as subscriber notifications and playlists. We study the resulting impact on 5,066 top American YouTube channels by comparing the MFK content creators to their non-MFK counterparts using a difference-in-differences design. On the supply side, MFK content creators produce 18% less content and pivot toward non-MFK content production. MFK content creators also invest less in content quality: the proportion of original content falls by 9% and manual captioning drops by 28%, whereas viewer content ratings fall by 9%. On the demand side, views of MFK channels fall by 20%. The restrictions also affected market competition, increasing concentration of both content creation and viewership among top MFK channels.This paper was accepted by Jean-Pierre Dubé, marketing.Funding: This work was supported by the Questrom School of Business Digital Business Institute, the Program on Economics & Privacy at George Mason University, and the “Economics of Digital Services” initiative by the University of Pennsylvania’s Center of Technology, Innovation & Competition and Warren Center.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05295 .

Before the Storm: Firm Policies and Varying Recession Risk

2026-05-04T00:00:00+00:00

Management Science
Recession risk fluctuates substantially “before the storm,” yet little is known about how firms of different sizes adapt their policies accordingly. We embed time-varying recession risk into a model of liquidity management and investment, allowing firms to time their precautionary policies. Estimation reveals that small firms are less sensitive than large firms in their issuance, payout, and investment strategies to variations in recession risk. This is because small firms proactively build larger cash reserves relative to their current cash flow volatility during periods of low recession risk, anticipating that aggressive investment will gradually drain liquidity, grow cash flow volatility, and raise the risk of liquidation if a recession occurs. In contrast, large firms rely on robust cash flows to replenish liquidity during periods of low recession risk, deferring other precautionary actions until recession risk intensifies. These results have important implications for estimating the impact of recessions and macroprudential policy.This paper was accepted by Lukas Schmid, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.08861 .

Backfiring AI? AI Deployment in Workplace

2026-05-04T00:00:00+00:00

Management Science
Seeking value from artificial intelligence (AI) technologies, firms are rapidly deploying them to augment employees and improve business performance. The diffusion of AI into a firm’s business processes affords the tracking of task actions performed by high-performing employees and the codification of best practices into recommendation systems and training programs. The rising trend in AI deployment reveals managers’ expectations that AI-facilitated knowledge transfer would elevate overall firm performance. However, deploying AI in a workplace has the potential to change the competitive dynamics among employees. The AI system can learn from high-performing employees and make that knowledge available to others. In a competitive environment, this can disincentivize high-performing employees and ultimately backfire, leading to a decline in overall firm productivity. In this paper, we study this problem of employee incentive issues when deploying AI in a competitive workplace, using a game-theoretic model. Our results show that when employees compete using both tangible (“hard”) and intangible (“soft”) skills, firm policies that favor AI-facilitated knowledge transfer and task outcome-based compensation may lower firm performance. We illustrate that payoffs from AI deployments depend on workforce heterogeneity, reliance on tangible skills, the skill disparity between employees, and AI efficacy. Using our model, we develop policy recommendations for maximizing the return on organizational AI deployments. Our results suggest that some ostensibly simple solutions, like guaranteeing or increasing the wages of adversely affected employees, may not solve the problem effectively, and firms would have to judiciously choose optimal AI efficacy levels for achieving better outcomes.This paper was accepted by D. J. Wu, information systems.Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.03108 .

The Information Content of Commodity Futures Markets

2026-05-04T00:00:00+00:00

Management Science
Among commodity futures sectors, only industrial metals returns predict future industrial production growth and revisions in producers’ expectations about future economic conditions across a wide range of countries. This predictive power is stronger in countries more exposed to the global economy, is driven by demand shocks, persists after controlling for trade dependence, continues to hold after the financialization of commodity markets, and is reflected in international stock returns. In contrast, energy and agriculture futures also contain relevant information but mainly for countries that depend on these commodities through trade. Our findings provide global evidence in support of the informational role of commodity markets and identify industrial metals as a reliable barometer of future global economic activity.This paper was accepted by Lukas Schmid, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00899 .

Too Good to Be True – Individual and Collective Decision-Making with Misleading Signals

2026-05-04T00:00:00+00:00

Management Science
In many situations, an abundance of misleading evidence—such as fake customer reviews—can lead to false or deceptive conclusions. We experimentally investigate individual and collective decision-making in an information structure in which signals can be correlated, depending on the state of the world. In this setting, too much evidence pointing in one direction has the potential to mislead, necessitating a level of sophistication for rational decision-making. Overall, participants’ performance is poor with only small differences in collective and individual decision-making accuracy. Interestingly, the more complex environment tends to encourage greater honesty within heterogeneous groups than a benchmark setting with independent signals, thus corroborating a rather subtle game-theoretic prediction.This paper was accepted by Dorothea Kübler, behavioral economics and decision analysis.Funding: The authors received financial support from Tamkeen under NYU Abu Dhabi Research Institute Award CG005, from the Juniorprofessorenprogramm Baden-Württemberg, and from the Federal Ministry of Labour and Social Affairs (Germany) through the funding network Interdisciplinary Social Policy Research (BMAS-FIS).Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06504 .

An Information-Based Theory of Auditor Switching

2026-05-04T00:00:00+00:00

Management Science
We model auditor switching through a tender process involving an incumbent auditor, who has private information about the client firm’s audit cost (driven by audit complexity or audit risk), and an uninformed prospective auditor. When a firm’s audit cost is high, the auditor is more susceptible to audit failure by erroneously attesting to the firm’s favorable report. We show that, in equilibrium, the client facing a high audit cost is more likely to switch to a prospective auditor because of the winner’s curse. Clients who switch auditors experience a reduction in the overall expected audit fee and are more likely to receive favorable audited reports from the new auditor than clients who do not switch. Our analytical findings collectively present a new information-based perspective on auditor switching, extending beyond the conventional “opinion shopping” explanation. We caution researchers to consider the potential influence of information asymmetry among auditors when examining auditor switching.This paper was accepted by Suraj Srinivasan, accounting.Supplemental Material: The online appendices are available at https://doi.org/10.1287/mnsc.2024.05977 .

EXPRESS: Picture This: How Review Valence Shapes the Quality and Helpfulness of User-Generated Photos

2026-05-04T00:00:00+00:00

Journal of Marketing Research
User-generated photos play an increasingly important role in online reviews, yet little is known about the process by which they are initially created. This paper develops a theory of image creation arguing that reviewers invest more creative effort in photographing products/services they feel positively (vs. negatively) about. This greater effort results in higher-quality photos that observers find to be more helpful, both because they are easier to visually process and because they engender greater trust in the reviewer. Results across six studies—including controlled experiments and an observational laboratory study (N = 4,218) as well as field analyses of Amazon and Yelp reviews (N = 669,937)—lend support to these predictions. By identifying valence as a driver of creative effort in user-generated photography, the findings advance knowledge on how visual content is produced in online marketplaces and how such content is evaluated by consumers.

Navigating Temporal Plurality in Agile Software Development: A Process Explanation

2026-05-04T00:00:00+00:00

Information Systems Research
While agile software development (ASD) promises rapid, iterative delivery, agile teams often face temporal demands—such as organizational reporting schedules, quality requirements, and resource availability—that challenge their ability to meet this promise. These conflicting temporal demands create what we call temporal misfits.Based on an in-depth study of five software development projects, we found that a temporal misfit disturbs an agile team’s work by creating delays and undermining software quality every time it occurs. Because a given temporal misfit reoccurs at each sprint until resolved, work disturbance escalates over successive sprints. Teams respond in different ways. They may sacrifice the speed of delivery and comply with demands that jeopardize it. They may preserve the agile rhythm, sometimes shielding the team from external temporal requirements. Finally, they may mobilize people or tools—digital or not—to play the role of a differential gear, therefore allowing conflicting temporal demands to be met simultaneously.Our work invites ASD teams to consider both the immediate and the longer-term effects of temporal misfits and their responses, highlighting how decisions made within each agile sprint can impact the entire project.

Racial Disparities in Federal Sentencing: Evidence from Drug Mandatory Minimums

2026-05-05T00:00:00+00:00

Review of Economic Studies
I study racial disparities in the criminal justice system by analysing abnormal bunching in the distribution of crack-cocaine amounts used in federal sentencing. I compare cases sentenced before and after the Fair Sentencing Act, a 2010 law that changed the 10-year mandatory minimum threshold for crack-cocaine from 50 g to 280 g. First, I find that after 2010, there is a sharp increase in the fraction of cases sentenced at 280 g (the point that now triggers a 10-year mandatory minimum), and that this increase is disproportionately large for black and Hispanic offenders. I then explore several possible explanations for the observed racial disparities, including racial discrimination that occurs after entry into the criminal justice system. I analyse data from multiple stages in the criminal justice system and find that the increased bunching for minority offenders is driven by prosecutorial discretion, specifically as used by about 20–30% of prosecutors. Moreover, the fraction of cases at 280 g falls in 2013 when evidentiary standards become stricter. Finally, the racial disparity in the increase cannot be explained by differences in education, sex, age, criminal history, seized drug amount, or other elements of the crime, but it can be largely explained by a measure of state-level racial animus. These results shed light on the role of prosecutorial discretion and racial discrimination as causes of racial disparities in sentencing.

Why Doesn’t the United States Have National Health Insurance? The Political Role of the American Medical Association

2026-05-05T00:00:00+00:00

The Quarterly Journal of Economics
This study examines how the American Medical Association (AMA) helped shape the development of the U.S. health insurance system in the critical period after World War II. Working with the political public relations firm Campaigns, Inc., the AMA launched a nationwide campaign to weaken support for National Health Insurance by framing it as “socialized medicine,” while simultaneously enrolling people in private health insurance plans to shift demand away from a public alternative. Drawing on newly assembled archival data, we find that greater exposure to the campaign explains about 20% of the rise in private health insurance enrollment and a comparable decline in public support for a national program. The campaign also appears to have influenced policymaking through coordinated messaging, resolutions passed by civic organizations, congressional rhetoric, and political donations. These findings suggest that the rise of private health insurance in the United States was not solely due to macroeconomic forces or collective bargaining; rather it was also enabled by a strategic, interest group-financed effort to shape citizen views and influence policy.

Leveraging Generative Artificial Intelligence to Create Visual Content in Digital Advertising

2026-05-05T00:00:00+00:00

Marketing Science
Creating high-performing, brand-aligned advertising visuals is challenging; we develop a generative AI framework using Bayesian active learning to efficiently discover effective designs.

Soft Collateral, Bank Lending, and the Optimal Credit Registry

2026-05-05T00:00:00+00:00

Management Science
We study the design of an optimal credit registry in a general equilibrium steady-state setting where borrowers can default strategically and future access to credit markets serves as soft collateral to enforce loan repayment. We endogenize the probabilities for exclusion after default and subsequent reinstatement of clean credit records. When there are sufficient funds, optimal credit stringency is as loose as possible, subject to borrowers’ incentive constraints. When there are insufficient funds, credit stringency is driven by the need to equilibrate nonexcluded borrowers with available funds, and it increases as the imbalance grows. We examine how population growth, mortality, and persistence affect our results. Finally, we compare the simple two-tier scheme with the three-tier scheme and characterize solutions to a general N-tier registry. We show that a more graduated registry is not necessarily a better one.This paper was accepted by Will Cong, finance.

The Swaying Power of Business: Inconsistent Social Actions and Mitigating Mechanisms in Corporate Foundations

2026-05-05T00:00:00+00:00

Journal of Management
Corporate foundations (CFs) are increasingly prominent vehicles for channeling commercial resources toward social causes. However, their pursuit of social missions may be shaped by the strategic priorities of their corporate sponsors. Drawing on a longitudinal panel dataset of 214 Chinese corporate foundations from 2009 to 2022, we examine how changes in sponsor firms’ business portfolios are associated with inconsistency in CFs’ philanthropic engagement, and identify organizational conditions under which this association is attenuated. We find that as sponsor firms adjust their business portfolios, their CFs are more likely to alter their portfolios of philanthropic activities, indicating a destabilizing association. This association is weaker when CF executives have stronger nonprofit backgrounds and when foundations receive a greater proportion of funds from non-corporate donors. Furthermore, we document an asymmetric pattern consistent with activity compartmentalization: under these organizational conditions, changes in sponsor firms’ business portfolios are less strongly associated with changes in mission-related activities than with changes in mission-unrelated activities. These findings contribute to research on dependency management by identifying organizational conditions associated with reduced sensitivity to sponsor firms’ business changes, and by highlighting a form of buffering within prosocial activities under conditions of close oversight.

The Value of a Loss: The Impact of Restricting Tax Loss Transfers

2026-05-05T00:00:00+00:00

Journal of Accounting Research
We study the economic consequences of anti‐loss trafficking rules, which disallow the use of loss carryforwards as a tax shield after a substantial ownership change. We use staggered changes to these rules in the EU27 Member States, Norway, and the United Kingdom from 1998 to 2019 and find that limiting the transfer of tax losses is related to the number of mergers and acquisitions (M&A) declining by 18%, driven by loss‐making targets. Turning to broader industry dynamics, we find decreases in survival rates of young companies after tighter regulations. Loosening of regulation is associated with increased firm survival. Tightening (loosening) anti‐loss trafficking rules is related to decreased (increased) industry productivity, especially in R&D‐intensive industries that are more prone to loss‐making. Finally, tighter anti‐loss trafficking rules are associated with lower deal synergies and risk‐taking. All effects concentrate in strict regimes.

Artificial intelligence adoption and the demand for managerial expertise

2026-05-06T00:00:00+00:00

Strategic Management Journal
This paper examines how firms' adoption of artificial intelligence (AI) relates to the demand for managers and managerial skills. Using a skills‐based measure of AI adoption derived from Lightcast job postings, we show that firms with greater AI adoption post more managerial vacancies and a higher share of such vacancies than less intensive adopters. These relationships are strongest in manufacturing and among firms with higher research & development intensity. Greater AI adoption is also associated with shifts in managerial skill requirements toward interpersonal and growth‐oriented skills, including stakeholder management, creativity, and sales management, and away from routine administrative skills such as budgeting, planning, staff management, and customer service. Overall, the results suggest a reconfiguration of managerial roles toward capabilities facilitating scaling, coordination, and adaptation in AI‐enabled environments.Managerial SummaryAs artificial intelligence (AI) becomes more prevalent within firms, managers and executives face a practical question about how managerial roles may change. Using US job postings data from 2010 to 2022, we find that firms with higher AI adoption exhibit relatively greater demand for managerial roles, especially in manufacturing and among more innovative firms. We also find that more intensive AI adoption is associated with changes in what managers are expected to do. Demand shifts away from routine administrative skills such as budgeting and planning and toward growth‐related skills such as sales, creativity, and stakeholder management. Overall, the evidence suggests a growing emphasis on managerial roles that relate to scaling, coordination, and organizational adaptation.

Collaboration post‐acquisition: The role of acquirers' motives

2026-05-06T00:00:00+00:00

Strategic Management Journal
What role do collaborations with a target's partners play in an acquisition, and how do these collaborations evolve post‐acquisition? Research suggests that these collaborations are an important reason to acquire but often diminish post‐acquisition. But if they tend to diminish, why are they a reason to acquire? Our analysis of acquirers’ motives of 143 acquisitions of firms that collaborate with partners on 298 open‐source projects resolves the outlined puzzle and reveals two types of acquisition motives: protection‐motivated acquisitions—where acquirers focus on protecting the complementarity with the technology and the partners, and extraction‐motivated acquisitions—where acquirers focus on extracting technology and employees. We find that protection‐motivated acquisitions are associated with an intensification of collaborations, meanwhile extraction‐motivated acquisitions are associated with a diminishment of the collaboration. We contribute to research on acquisitions, collaboration, and OSS.Managerial SummaryAcquisitions don’t just change ownership—they reshape collaboration with the target's partners. We studied 143 acquisitions of firms that sponsor and collaborate with partners on 298 open‐source software projects. We track contributions before and after the acquisition. We find that the motives of the acquirers are associated with different outcomes. When acquirers aim to protect complementarities, contributions from the acquired target and its partners tend to rise. When they aim to extract resources—redeploying code or talent—contributions typically decline. Managerial takeaway: when you are a stakeholder in a particular OSS, examine how likely the acquisition of its sponsors is, and what the acquirers’ motives are.

A Dynamic Model of the Racial Wealth Gap

2026-05-06T00:00:00+00:00

The Review of Financial Studies
What explains wealth and portfolio differences between black and white Americans? We find that disparities in economic factors explain portfolios well, but only partly explain the wealth gap. In a dynamic setting, economic factors often change optimal saving rates in ways that offset their effects on income and returns. Consequently, their net wealth effect is often limited, making the wealth gap harder to explain. We estimate that differences in income levels, income risk, family structures, mortality, health expenditures, property taxes, mortgage rates, and asset returns explain half of the differential between the racial wealth gap and the racial income gap.

Optimizing Reserve Prices in Display Advertising Auctions

2026-05-06T00:00:00+00:00

Marketing Science
This paper examines how publishers should set reserve prices in display advertising auctions when advertisers face practical constraints such as campaign reach.

Crypto Carry

2026-05-06T00:00:00+00:00

Management Science
We analyze the dynamics of carry in crypto markets—the difference between futures and spot prices—and document that it can reach exceptionally high levels, sometimes exceeding 40% per annum, with significant variation over time. This phenomenon reflects a substantial and volatile inconvenience yield associated with holding spot cryptocurrencies relative to futures. We trace the large and volatile crypto carry to the interplay of two main forces: (i) demand from smaller, trend-chasing investors seeking leveraged exposure and (ii) the limited deployment of arbitrage capital because of regulatory and margin frictions. Our findings highlight how structural limits to arbitrage—especially severe in the case of crypto—can amplify price inefficiencies across financial markets, offering lessons for understanding asset pricing and market behavior more generally.This paper was accepted by Agostino Capponi, finance.Funding: M. Schmeling acknowledges financial support from the German Science Foundation [Grant SCHM 2623/2-1].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05069 .

Household Finance at the Origin: Home Ownership as a Cultural Heritage from Agriculture

2026-05-06T00:00:00+00:00

Journal of Financial and Quantitative Analysis
I show that home ownership decisions across countries and individuals are shaped by a cultural heritage from agriculture. For centuries, dominant assets in preindustrial economies were either land or cattle. Consequently, the type of farming prevailing locally shaped preferences and beliefs about the relative value of immovable and movable assets. This cultural heritage had long-lasting consequences. Today, individuals originating from societies with a history of crop agriculture—where the dominant asset was land—are more likely to be homeowners. For identification, I rely both on home ownership decisions of second-generation immigrants in the United States and on an instrument.

Inferences About Others’ Consumption Motives Influence What Consumers Expect from Similar Experiences

2026-05-06T00:00:00+00:00

Journal of Consumer Research
When consumers see someone else’s experience shared on social media, they often infer whether the sharer had relatively intrinsic or extrinsic motives for originally engaging in this experience. While prior research has documented how these inferred motives affect viewers’ social evaluations of the sharer, the present research demonstrates that these inferences can shift viewer beliefs about the experience itself. The findings from six studies show that when viewers infer a sharer originally had either relatively intrinsic or extrinsic motives for consuming an experience they shared about, it increases viewer beliefs that the experience is well suited to satisfy that same type of motive. This shift in the expected motive-based value of the experience, in turn, influences viewers’ behavior during and after their own engagement in a similar experience. However, when viewers are highly familiar with the experience that was shared, the expected motive-based value of the shared experience is not influenced by viewers’ inferences about the sharer’s original motives. Altogether, this research documents a new social influence phenomenon on social media and discusses managerial implications of these findings.

Caution Ahead: Numerical Reasoning and Look‐Ahead Bias in AI Models

2026-05-06T00:00:00+00:00

Journal of Accounting Research
Recent work within accounting and finance has highlighted that modern AI systems exhibit superhuman performance on a variety of foundational activities within these fields. However, the literature often does not provide economic rationale forwhyAI models seem to outperform, largely because these models are a black box. Through a series of experiments, I set out to open the black box and provide direct evidence onhowandwhyAI models appear to perform so well on accounting and finance‐related tasks. I show that much of the superior performance of AI models can be attributed to artifacts of the modeling itself, rather than to mechanisms grounded in economics. Focusing on two key components of AI models, which may bias inferences in papers that rely on them, I first show that Large Language Model (LLMs) exhibit extremely poor numerical reasoning and thus application in these settings should proceed with caution. Second, I highlight that commercial LLMs suffer from significant look‐ahead bias, which may explain a large portion of their predictive ability in various settings.

Macroeconomic Expectations and Credit Card Spending

2026-05-07T00:00:00+00:00

The Review of Financial Studies
We examine how macroeconomic expectations affect consumer decisions, using an experiment with 2,872 credit card customers at a large commercial bank. In the experiment, participants are randomized into receiving expert forecasts of inflation and the nominal exchange rate. We find that forecasts shift inflation and exchange rate expectations, but do not change spending or self-reported consumption plans as predicted by standard models of intertemporal choice. Results from a supplementary survey experiment suggest that consumers are sophisticated enough to anticipate nominal rigidities and reduce spending on durables for precautionary reasons, counteracting the effects predicted by standard models of intertemporal optimization.

The Pandora’s Box Problem with Sequential Inspections

2026-05-07T00:00:00+00:00

Operations Research
The Pandora’s Box Problem with Sequential InspectionsThis paper studies the fundamental problem of choosing among competing uncertain alternatives when the decision maker can invest resources to reduce uncertainty. The novelty of our work lies in examining settings in which uncertainty can be reduced either through a small investment or eliminated altogether through a more substantial one. The central question is how to navigate the selection process efficiently in order to achieve a good outcome. This type of problem arises, for example, in job search, when firms must choose among a large number of candidates whose fit for a position is uncertain and when uncertainty can be reduced through a small effort (e.g., an online or artificial intelligence–assisted interview) or a more substantial one (e.g., an in-person visit). We show that, whereas the problem is computationally challenging in general, there are two types of indices that can be computed efficiently for each alternative and that capture the attractiveness of a small or a large investment. These indices can guide the selection process, yielding optimal results in some cases and near-optimal results in all others.

Transfer Learning, Cross Learning and Co-Learning with Operational Data Analytics (ODA)

2026-05-07T00:00:00+00:00

Management Science
Making decisions with limited data and incomplete statistical characterization is challenging. The typical statistical-machine-learning approaches would call for migrating the experience of a related system with ample data through transfer learning or leveraging the similarity of multiple systems with limited data through data pooling. We, instead, develop new solution concepts to learn across related systems by adapting the parametric Operational Data Analytics (ODA) framework, which is known to produce uniformly optimal data-integrated decisions in the corresponding parametric settings, for nonparametric decision-making. We demonstrate, through the application of newsvendor systems, that transfer learning can, indeed, improve decision performance in the focal system by utilizing a model pretrained with ample data in a related system. However, through the lens of the ODA framework, the best transfer-learning decision falls in a subclass of operational statistics, limiting the ultimate optimality. In contrast, the ODA cross-learning approach utilizes the ample data from the related system to mimic the stochastic environment of the focal system. When the data from the old system are sufficiently large, the cross-learning solutions derived outperform any transfer-learning solution, and they are shown to asymptotically approach the parametric ODA solutions. When there are multiple related systems with limited data, we aggregate the data from different systems to create a generic stochastic environment for the decision-making problem, which facilitates the implementation of the parametric ODA solutions. We show that the derived co-learning solutions are asymptotically optimal for the aggregate system and for each subsystem. This approach outperforms the existing data-pooling techniques in the sense that the latter focuses only on the aggregated performance, and the chosen solution may be (asymptotically) suboptimal for individual subsystems. Our results underscore the roles of domain knowledge and the structural relationships between the data and the decision in designing efficient learning solutions with limited data. Though we demonstrate our development through the application of newsvendor systems, the solutions developed in this study apply to a much wider class of operational decision-making problems that exhibit certain homogeneous properties.This paper was accepted by David Simchi-Levi, operations management.Funding: L. Li’s research is partly supported by the Research Grants Council of Hong Kong [Grant 15515324] and The Hong Kong Polytechnic University under Grant 1-BEAT.Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.03688 .

Peer Evaluation and Team Performance: An Experiment on Complex Problem Solving

2026-05-07T00:00:00+00:00

Management Science
Today’s employees often work in teams on complex problems. Yet, we know very little about how to incentivize such work. We conduct two laboratory experiments where groups of three work on a complex task and are paid by the quality of their answer. We then study whether a peer evaluation which determines the individual pay share improves group performance. We do so both in an in-person as well as in an online setting. In both settings, overall group performance was not significantly affected by the peer evaluation. Yet, groups behaved differently under peer evaluation: Participants reported higher motivation and groups worked longer and communicated more. We find evidence consistent with two possible performance-reducing channels of peer evaluation tied to performance pay. First, behavior may shift toward impressing one’s team members, though this does not necessarily improve performance. Second, higher work effort because of the peer evaluation in the presence of time constraints may lead to more timeouts and incompletely worked-out solutions.This paper was accepted by Yan Chen, behavioral economics and decision analysis.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.00840 .

Practically Relevant: Reevaluating the “Relevance Problem” Through a Review of Practical Turnover Recommendations

2026-05-07T00:00:00+00:00

Journal of Management
Management research is frequently criticized for lacking practical relevance. Using voluntary turnover as a mature and managerially consequential research domain, we review 324 articles published between 2000 and 2023 and systematically extract 493 distinct practical recommendations. In advancing prior assessments of the relevance problem, we consider practical relevance at the recommendation-level of analysis, evaluating each recommendation along two core dimensions: data support (grounding in the study’s own empirical findings) and translatability (actionability for managers). We further situate recommendations within the turnover management process by coding for timing, level of action, and managerial goal of the recommendation. Our findings suggest that the relevance problem is less serious in the turnover research than commonly portrayed in the “relevance literature” regarding the management research in general. Although most studies included turnover management recommendations, only a small subset was both strongly grounded in the study’s evidence and readily actionable, with such high-quality guidance most concentrated on pre-hire interventions aimed at reducing overall turnover rates. In contrast, one of the gaps we detected was that such high-quality guidance is rarer for later-stage turnover management interventions focusing on reducing dysfunctional turnover. By contrasting high versus lower quality recommendations, we develop a five-step framework to help management scholars translate empirical findings into clear, context-sensitive, and actionable managerial guidance. Overall, we contribute to management scholarship by offering a more precise recommendation-level assessment of the relevance problem for use across areas, by identifying content-based gaps inhibiting improvement of practical relevance within the turnover research, and by improving the communication of practical recommendations in research articles.

Learning in the Limit: Income Inference from Credit Extensions

2026-05-07T00:00:00+00:00

The Journal of Finance
Combining a randomized controlled trial with administrative and survey data, this paper shows that credit limit extensions significantly increase total spending and income expectations. By controlling for changes in personal income expectations, the spending response to credit limit extensions weakens by approximately 30%. For financially unconstrained consumers, expectation changes account for around two‐thirds of the spending responses to limit extensions. These findings are consistent with consumers inferring future income from credit supply.

Made With AI: Consumer Engagement with Social Media Containing AI Disclosures

2026-05-07T00:00:00+00:00

Journal of Consumer Research
Social media shapes how people connect, communicate and consume information. As generative artificial intelligence (AI) becomes an increasingly common tool for content creation, many platforms have introduced disclosure requirements to inform consumers when content has been created or significantly edited by AI. Yet, little is known about how such AI-generated content (AIGC) disclosures influence consumer engagement, a key metric for creators, platforms, and brands. This research examines whether and why AIGC disclosures affect engagement on social media. Analysis of engagement behavior on TikTok following the introduction of their AIGC disclosure policy and eight preregistered experiments (including two in the Web Appendix) find that disclosures reduce consumer engagement. This reduction does not stem from concerns about content quality, wariness of artificial content, or general AI aversion. Instead, we identify a novel process: AIGC disclosures reduce parasocial connection—one-sided emotional bonds between consumers and creators. Reduced parasocial connection is driven in part by the perceived effort of the content creator. As such, disclosures that signal greater effort can mitigate reductions in engagement. We discuss the implications of these findings for platform policy, content creator strategy, and the future design of AI disclosure practices.

The Mutual Shaping of Boundaries and Boundary Organizations

2026-05-08T00:00:00+00:00

Organization Science
As firms increasingly host online communities, they need to mediate across the divergent interests of community members and the firm. One way of addressing this is to establish a formal governance structure referred to as a boundary organization (BO). Yet, how to design such an organization is a puzzle. If a BO is effective, it is likely to reshape firm-community relations and thus needs to be adjusted to respond to this change. Therefore, BOs must constantly adapt to the boundaries they span while also changing the very same boundaries. This research seeks to understand the mutual shaping of boundaries and BOs in firm-hosted online communities. To this end, we investigate the evolution of a BO set up by a firm hosting an online community engaged in a multiplayer game called “EVE Online.” We conducted an eight-year longitudinal qualitative case study of the BO, tracing change in its practices and attendant boundaries. We show how boundaries and the BO mutually shape each other through (1) surfacing of boundary tensions, (2) BO renegotiation practices, and (3) BO’s boundary spanning practices. Based on our findings we develop a theory that shows how mutual shaping unfolds through the varied enactment of these practices along the dimensions of where the voicing of discontent is channeled, how broad representation on the BO is, and the nature of information sharing. Our research contributes to research on boundary work by theorizing how the process of mutual shaping unfolds as an instable “chain reaction” with unintended consequences.

Planning a Community Approach to Diabetes Care in Low- and Middle-Income Countries Using Optimization

2026-05-08T00:00:00+00:00

Operations Research
Smarter Community Health Visits Improve Diabetes OutcomesDiabetes takes a severe toll in developing countries, where high blood glucose contributes more than half of premature deaths. Community health workers (CHWs) offer a culturally tailored lifeline, but deploying them efficiently requires balancing the screening of new patients against managing those already in treatment. In this issue, researchers introduce an innovative optimization framework that personalizes CHW visit plans to maximize community-wide glycemic control. Uniquely, the model explicitly factors in patients’ motivational states—predicting their likelihood of enrolling in or dropping out of care—to guide intervention strategies and reduce attrition. Applied to operational data from urban slums in India, the approach delivers remarkable results; optimized visit plans reduced fasting blood glucose levels by up to 25% compared with the best baseline methods using identical capacity. The model also proved to be robust under imperfect information, offering a powerful, practical tool for global health resource allocation.

Can Information Sharing Reduce Diagnostic Disparate Impact? Evidence from a Health Information Exchange

2026-05-08T00:00:00+00:00

Management Science
The literature has documented qualitative evidence of disparities in physician diagnoses, which can lead to disparities in healthcare delivery, patients’ perception of care, and health outcomes. In this research, we seek to understand whether (a) disparities in physician diagnoses can be attributed to disparate impact based on patient race, and (b) information technology–enabled health information sharing among healthcare providers can mitigate such disparate impact. Our empirical context focuses on racial disparities in diagnoses of heart disease between Hispanic patients and non-Hispanic, White patients. Utilizing patient-level, emergency room (ER) encounter data from 2015 to 2022, we find statistical evidence of diagnostic disparate impact where the likelihood of Hispanic patients being diagnosed with heart disease is around three percentage points lower than White patients after accounting for their underlying race-specific risk of heart disease. However, we find that health information sharing can reduce the level of diagnostic disparate impact against Hispanic patients by 18% and the likelihood of severe disparate impact by seven percentage points. We evaluate the robustness of our results using a range of specifications, such as instrumental variable estimation, falsification tests, and alternative measures of disparate impact. We also highlight the underlying mechanism that explains the role of health information sharing in mitigating diagnostic disparate impact. Specifically, we show that health information sharing between healthcare providers can reduce diagnostic uncertainty, especially for Hispanic patients, and low-skilled physicians benefit more from health information sharing compared with highly skilled physicians.This paper was accepted by D. J. Wu, information systems.Funding: The authors gratefully acknowledge the McCombs Dean’s Excellence Research Grant for this research.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05617 .

The Impact of Climate Change: An Empirical Analysis of Smart Thermostat Data

2026-05-08T00:00:00+00:00

Management Science
Extreme weather from climate change creates unprecedented fluctuations in residential heating and cooling demand. Understanding how households use thermostats and react to ambient weather is key to achieving demand reductions and avoiding power crises. To this end, we analyze high-frequency microlevel time-series data from smart thermostat users to examine how households adjust their thermostat operations in response to outdoor temperature. Comparing households within a city, we find that households that automate their HVAC mode decisions exhibit reduced responsiveness to temperature shocks. In particular, their heating energy consumption remains elevated, even in the face of a changing climate, compared with households that rely on less automation. With respect to temperature setpoints, households that frequently override preprogrammed schedules show inertia, remaining at the overridden setpoints for long periods, and only partially revert to their preprogrammed setpoints. This can lead to higher energy use compared with those who stay in their preprogrammed schedules. To quantify the impact of these results, we conduct a set of simulations under hypothetical climate scenarios. These simulations reveal that by 2050, total cooling energy usage could rise by at least 67% and as high as 300%, depending on the climate scenario and geographical location, with peak usage and demand variability increasing by over 50%. Whereas heating consumption is reduced, this decrease is dominated by the increase in cooling energy usage. As a case study of the operational implications, we project total hourly loads and generation costs for Texas’ electricity grid in 2050. The increased heating and cooling demand alone could raise annual grid operating costs by 20%–25% and require 21,700 megawatts of additional capacity to maintain grid reliability.This paper was accepted by Jayashankar Swaminathan, operations management.Supplemental Material: The e-companion and data files are available at https://doi.org/10.1287/mnsc.2024.06952 .

Dynamic Matching with Postallocation Service and Its Application to Refugee Resettlement

2026-05-08T00:00:00+00:00

Management Science
Motivated by our collaboration with a major refugee resettlement agency in the United States, we study a dynamic matching problem where each new arrival (a refugee case) must be matched immediately and irrevocably to one of the static resources (a location with a fixed annual quota). In addition to consuming the static resource, each case requires postallocation service from a server, such as a translator. Given the time-consuming nature of service, a server may not be available at a given time, thus we refer to it as a dynamic resource. Upon matching, the case will wait to avail service in a first-come-first-serve manner. Bursty matching to a location may result in undesirable congestion at its corresponding server. Consequently, the central planner (the agency) faces a dynamic matching problem with an objective that combines the matching reward (captured by pair-specific employment outcomes) with the cost for congestion for dynamic resources and overallocation for the static ones. Motivated by the observed fluctuations in the composition of refugee pools across the years, we design algorithms that do not rely on distributional knowledge constructed based on past years’ data. To that end, we develop learning-based algorithms that are asymptotically optimal in certain regimes, easy to interpret, and computationally fast. Our design is based on learning the dual variables of the underlying optimization problem; however, the main challenge lies in the time-varying nature of the dual variables associated with dynamic resources. To overcome this challenge, our theoretical development brings together techniques from Lyapunov analysis, adversarial online learning, and stochastic optimization. On the application side, when tested on real data from our partner agency and incorporating practical considerations, our method outperforms existing ones, making it a viable candidate for replacing the current practice upon experimentation.This paper was accepted by Martin Bichler, market design, platform, and demand analytics.Funding: This work was supported by the Stanford Impact Lab [Stage 2 Grant], Google.org [AI for Social Good Grant TF2111-103726], the Charles Koch Foundation, and the Stanford Institute for Human-Centered Artificial Intelligence [Hoffman-Yee Research Grant].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07817 .

Partisan Entrepreneurship

2026-05-08T00:00:00+00:00

The Journal of Finance
Republicans start more firms than Democrats. In a sample of 40 million party‐identified Americans between 2005 and 2017, we find that 5.5% of Republicans and 3.7% of Democrats become entrepreneurs. This partisan entrepreneurship gap is time‐varying—Republicans increase their relative entrepreneurship during Republican administrations and decrease it during Democratic administrations, amounting to a partisan reallocation of 170,000 new firms over our 13‐year sample. We find sharp changes in partisan entrepreneurship around the elections of President Obama and President Trump, with the strongest effects among the most politically active partisans: those that donate and vote.

How Physician Reviews Affect Online Consultation Demand: An Innovative Small Language Model with Fine-Tuning

2026-05-08T00:00:00+00:00

Information Systems Research
This study introduces an efficient specialized artificial intelligence (AI) tool and the SEPTE model—a comprehensive framework for evaluating healthcare service quality—to help healthcare platforms and hospitals better understand what drives patient demand for online consultations. By analyzing physician reviews from one of China’s largest telehealth platforms, our small language model (Doc-BERT) uses the SEPTE framework to accurately identify key aspects of service quality, such as medical effectiveness and empathy, that matter most to patients. Unlike traditional large language models, our approach is cost-effective and can be readily implemented in real-world healthcare settings. We find that higher service-quality scores, especially in effectiveness and patient-centeredness, lead to greater patient demand for online consultations. These insights offer actionable guidance for healthcare providers and administrators seeking to improve patient experiences, optimize physician performance, and inform platform design and policy. Our work demonstrates that targeted, domain-specific AI—guided by the SEPTE model—can deliver both efficiency and impact for digital health services.

When Influencers Delegate Replies: How Social AI Agents Shape User Engagement

2026-05-08T00:00:00+00:00

Information Systems Research
As social media platforms deploy large language model (LLM)-powered agents to help influencers manage social relationships with users, it remains unclear how this delegation impacts user engagement. Automating interactions provides scalability and efficiency for influencers, but it may weaken the influencer-user relationship if the agents fail to serve as effective social delegates. To explore this question, we empirically investigate the impact on user engagement when influencers delegate social interaction tasks, such as replying to comments, to a social artificial intelligence (AI) agent, an LLM-powered proxy that responds on behalf of an influencer. Leveraging the rollout of a social AI agent feature on a major social media platform, we use a staggered difference-in-differences design to compare engagement behaviors between users who received an AI reply (i.e., a reply from an influencer’s social AI agent) and those who did not. Our results show that receiving an AI reply significantly increases user commenting on subsequent influencer posts, particularly when AI replies amplify an influencer’s social presence, as reflected in content relevance, stylistic alignment, and reply timeliness. We also find heterogeneous effects based on influencer-user relationships: engagement gains are stronger among loyal followers but weaker for commercialized influencers and those in the technology domain. Additionally, reply scarcity amplifies the effect: engagement increases more when influencers rarely replied previously or when fewer AI replies appear under the focal post. The engagement boost extends to both sponsored and nonsponsored posts, as well as user reposting behavior, whereas influencers themselves also post more frequently after adopting AI agents. This study contributes to the literature on AI delegation and influencer engagement by highlighting when and how delegating social relationship management to social AI agents can enhance user engagement.History: Jeffrey Parsons, Senior Editor; Pallab Sanyal, Associate Editor.Supplemental Material: The online appendices are available at https://doi.org/10.1287/isre.2025.2270 .

The Divorce of Word and Deed—A Data-Mining Approach to Identify and Evaluate Customer Requirements

2026-05-08T00:00:00+00:00

Information Systems Research
Whereas online reviews have become a primary data source for understanding customer requirements in both research and practice, using such information alone to guide product design can be unreliable. Our research investigates whether and how consumers’ preferences expressed through online reviews (words) align with their actual purchase decisions (deeds). Our analysis shows that features praised in online reviews do not necessarily translate to market success. This inconsistency between what consumers say and what they do poses significant challenges for manufacturers in product development decisions. We empirically identify the existence of word–deed inconsistency in consumer preferences. Some features are silent in online reviews yet significantly drive purchase decisions, whereas others are frequently praised but have limited influence on actual purchases. Building on these insights, we propose an innovative dual-weights model that extends existing two-dimensional customer requirement analysis by integrating both prepurchase choice drivers and postpurchase satisfaction determinants. Using this model, we classify features based on their importance for satisfaction versus purchase decisions and offer actionable product improvement strategies for different types of features.

When Do Equity Appeals Increase Giving? Evidence from Educational Crowdfunding

2026-05-08T00:00:00+00:00

Information Systems Research
Equity appeals are increasingly used by digital fundraising platforms, nonprofits, and public institutions to direct attention and resources toward disadvantaged communities. However, it remains unclear whether and when equity appeals actually increase giving. We examine this question in the context of educational crowdfunding, where platforms explicitly focus on reducing funding disparities across schools, particularly for students from racial or ethnic minority and low-income backgrounds. Leveraging large-scale data from DonorsChoose, one of the largest educational crowdfunding platforms in the United States, and exploiting arbitrary cutoffs in the platform’s deployment of equity appeals based on the student composition of benefitting schools, we show that equity appeals increase fundraising when they highlight student disadvantage in terms of poverty while providing little to no measurable benefit when they highlight student disadvantage in terms of race. These differential effects reflect how donors interpret disadvantage. Many donors appear to view poverty as a legitimate and actionable barrier to learning, making poverty-based appeals effective. In contrast, perceptions of race as a structural barrier to educational opportunity are more heterogeneous and politically sensitive, limiting the impact of race-based appeals. For platform designers and policymakers seeking to reduce educational fundraising disparities, our findings highlight the importance of how equity appeals are framed. More broadly, our results contribute to understanding under what conditions behavioral nudges can meaningfully reduce inequality versus when alternative approaches may be necessary to achieve equitable outcomes.

Unraveling Generative AI from a Human Intelligence Perspective: A Battery of Experiments

2026-05-08T00:00:00+00:00

Information Systems Research
This study introduces a novel, human-centered framework for evaluating the holistic intelligence of large language models (LLMs), using behavioral theory and experimental benchmarks drawn from human intelligence. Through extensive online experiments, the framework reveals that GPT-4 outperforms humans in cognitive, emotional, and creative intelligence, but falls short in social intelligence, especially in social interest, self-efficacy, and understanding mental states. Beyond theoretical insight, the study validates this framework by assessing GPT-4’s impact across diverse job roles, finding results consistent with established labor market research. It also offers a reusable tool for firms and policymakers to evaluate LLM intelligence and forecast job-level impacts. This enables informed decisions about where and how to integrate LLMs, match models to specific job requirements, and identify risks in socially intensive roles. The framework provides a foundation for responsible LLM deployment, ensuring alignment with human-centered structures and supporting strategic workforce planning.

Into the Wild: Advancing Ecocentric Entrepreneurship Through Natural Non-Human Actors

2026-05-08T00:00:00+00:00

Entrepreneurship Theory and Practice
Mainstream entrepreneurship has traditionally focused on the human behaviors involved in the exploitation, innovation, and transformation of human-centric systems. However, this anthropocentric view is inadequate in addressing today’s grand challenges. Assuming human superiority in solving Earth’s problems can be misleading. We challenge this assumption by adopting an ecocentric perspective that incorporates natural non-human actors (NNHAs). Using actor-network theory, we take a relational approach to explore how entrepreneurial behaviors can be theoretically advanced from inclusive, distributed, mutualistic, and co-creative relationships between human and NNHAs. We advance ecocentric entrepreneurship by redefining entrepreneurial agency, interactions, places, and ecosystems.

Mutual Fund Flows and the Supply of Capital in Municipal Financing

2026-05-09T00:00:00+00:00

The Review of Financial Studies
This paper investigates how capital supply from mutual funds affects municipal bond financing, making three key contributions. First, we introduce an identification strategy using the rule-based update of Morningstar ratings for 5-year-old funds, isolating supply-side effects from fund and issuer fundamentals. The results indicate that exogenous fund flows increase bond issuance probability and decrease yields. Second, these fund flows lead to more issuances when funds and issuers are connected through underwriters, highlighting relationship lending in municipal bond financing. Third, municipal issuers leverage favorable financing conditions for new issuance of revenue bonds, which translates into higher local house prices. (JEL G23, G32, H74)