Academic Publications

It's a match! Similarity in personality traits in the business angel–founder dyad and follow‐on funding

2026-04-10T00:00:00+00:00

Strategic Entrepreneurship Journal
We assess how personality alignment in investor–founder dyads is associated with the likelihood of follow‐on funding, a vital outcome for early‐stage ventures. Using machine learning to infer the Big Five personality traits from Twitter data for 9497 business angel–founder dyads, we find that similarity in conscientiousness and agreeableness is associated with a higher likelihood of follow‐on funding, while similarity in neuroticism is associated with a lower likelihood. We attribute these patterns to the trait‐specific benefits of supplementary (conscientiousness and agreeableness) and complementary (neuroticism) fit. Robustness checks and additional analyses support and nuance the conclusion that personality fit matters for venture outcomes, highlighting the strategic role of personality fit in the investor–founder relationship.Managerial summaryWe show that personality similarity between business angels and founders is associated with whether a venture secures follow‐on funding. Similarity in conscientiousness (being organized and reliable) and agreeableness (being cooperative and trusting) is linked to a higher likelihood of securing follow‐on funding, while similarity in neuroticism (emotional instability) is linked to a lower likelihood. We interpret these patterns as collaboration dynamics: similarity can help through supplementary fit (e.g., shared work style and cooperation), but differences can help through complementary fit (e.g., one partner's emotional stability offsets the other's emotional instability). Practically, founders and business angels should develop self‐awareness and consider personality fit alongside other characteristics when forming partnerships. Policymakers and incubators can support better matches and strengthen collaboration by promoting awareness of interpersonal dynamics.

Codification, Technology Absorption, and The Globalization of the Industrial Revolution

2026-04-10T00:00:00+00:00

The Quarterly Journal of Economics
This paper examines the global adoption of technology in the late nineteenth century. We construct several novel datasets to test the idea that the codification of technical knowledge in the vernacular was necessary for countries to absorb the technologies of the First Industrial Revolution. We find that comparative advantage shifted to industries that could benefit from these technologies in countries and colonies with access to codified technical knowledge, but not in other regions. Using the rapid and unprecedented codification of technical knowledge in Meiji Japan as a natural experiment, we show that this pattern emerged only after the Japanese government codified vast amounts of technical knowledge. Our findings shed new light on the frictions associated with technological diffusion and offer a novel explanation for why Meiji Japan was unique among non-Western countries in successfully industrializing during the first wave of globalization.

Bridging Knowledge Capability Gaps: Digital Technology Offsetting in Interfirm Knowledge Transfer

2026-04-10T00:00:00+00:00

Journal of Management Studies
In this digital age, the adoption of digital technology (DT) is changing traditional business processes. Against this backdrop, we try to answer the question of whether DT could effectively bridge any interfirm knowledge capability gaps. Though effective knowledge transfer is dependent on the sender's and the receiver's knowledge capabilities, literature attributes very limited attention to their combined effects. Using signalling metaphor as the guiding framework, we forward disseminative capacity and absorptive capacity as the key capabilities of the sender and receiver, respectively, and study their combined effects on relational performance within vertical interfirm relationships. Additionally, with the belief that comprehending how DT could interplay with these capabilities holds crucial importance, we test the conjecture that DT can bridge knowledge capability gaps pertaining to the sender or the receiver. We position our hypotheses using the relational view and test them using the response surface methodology. The analysis is conducted based on a multi‐respondent dyadic survey dataset that is augmented with secondary data and longitudinal performance data. Our findings showcase that disseminative capacity and absorptive capacity are natural counterparts and that the channel effectiveness resulting from adopting DT could serve as an offsetting capability that can effectively bridge certain knowledge capability gaps.

Collusion with Optimal Information Disclosure

2026-04-11T00:00:00+00:00

The Quarterly Journal of Economics
Motivated by recent concerns surrounding the use of third-party pricing algorithms by competing firms, we study repeated Bertrand competition where market demand or the cost of serving the market is observed by an intermediary (or “algorithm”) that selectively discloses demand or cost information to maximize firms’ collusive profit. We show that an upper censorship disclosure policy is optimal, which leads to price rigidity and supra-monopoly prices in some states. Improving the algorithm’s accuracy reduces expected consumer surplus whenever it does so under monopoly pricing. When the state is positively correlated over time, the algorithm discloses more information when recent demand was lower or costs were higher. The analysis extends to a generalized model that accommodates product differentiation and capacity constraints. We relate our findings to recent antitrust cases.

When Goods Were Odds: Do People Prefer Uncertain Goods After Uncertainty Is Resolved?

2026-04-11T00:00:00+00:00

Journal of Consumer Research
Much of the uncertainty people face is eventually resolved (e.g., a person entered in a raffle eventually learns what prize they have received). How do people evaluate goods (e.g., a prize of a $50 gift card) resulting from uncertain promotions (e.g., raffles)? Seven experiments (total N = 12,128) provide evidence for an uncertainty spillover effect: People prefer goods originating from uncertain prospects compared to those that were always known. This effect appeared both with naturalistic scenarios (study 1) and with incentive-compatible decisions (study 2). The authors propose this effect arises because uncertainty induces a perception that the outcome is superior relative to salient downward counterfactuals (study 3). Supporting this idea, this effect: (a) weakened when downward counterfactuals were salient for certain goods (study 4), (b) weakened when the worst outcome from uncertainty was realized (study 5), and (c) reversed when uncertainty involved losses (study 6). Lastly, this effect carried over to products associated with previously uncertain goods (study 7). These findings demonstrate that the influence of uncertainty persists beyond its resolution, shaping the evaluation of goods derived from uncertain prospects.

A Curation Approach to Identity Management: The Costs of Combining Identity Expression and Suppression

2026-04-12T00:00:00+00:00

Administrative Science Quarterly
Many organizations want to increase diversity among their workforce, but employees from marginalized groups consistently face uncertainty about how to navigate their identities at work, which can lead to high turnover among these employees. To highlight the unexpected ways in which such risks can arise for employees and organizations, we investigate the intrapersonal consequences of a curation approach to navigating social identities in the workplace. Curation involves frequent identity expression (integrating an identity into the workplace, such as discussing identity-based traditions) and frequent identity suppression (concealing aspects of an identity at work, such as hiding concerns about discrimination). Given that expression and suppression both have benefits and risks, combining these behaviors into a curation approach could be seen as a socially adept and professionally beneficial solution. However, focusing on the intrapersonal experiences of employees of color, we argue that, compared to primarily expressing or primarily suppressing a minority identity, curation is more psychologically detrimental to these employees. Combining expression and suppression fosters ambivalence—conflicting thoughts about whether one’s identity is a resource or a liability—which is psychologically aversive. In two surveys and an internal meta-analysis (of the two studies in the manuscript and a supplemental study reported in supplementary online materials), curation was associated with greater ambivalence and psychological strain, which, in turn, were associated with greater turnover intentions. While our core findings emerge with employees of color, we also provide exploratory evidence that the costs of curation extend to women. Our findings regarding curation reveal a previously unrecognized well-being risk for employees from marginalized groups and a retention risk for organizations. We offer recommendations for future research and practice to address the conditions that lead employees to engage in curation.

Voting and Trading on Public Information

2026-04-13T00:00:00+00:00

The Review of Financial Studies
This paper studies how public information, such as proxy advice, affects shareholder voting and, thus, corporate decision-making. We find that while public information improves the voting decisions of uninformed shareholders, it also induces privately informed shareholders to exit rather than to exercise their voice (vote). As a result, public information impairs information aggregation by voting but improves information aggregation by trading. Overall, public information can undermine corporate decision-making. Furthermore, slightly more precise public information can lead to a discontinuous reduction in firm value. Our results give rise to new empirical predictions and have implications for regulation.

The Confederate Diaspora

2026-04-13T00:00:00+00:00

Review of Economic Studies
This paper develops a new framework for understanding when and how migrants shape culture, applying it to the Confederate diaspora—a small migrant group that left a large cultural imprint. Southern Whites that migrated after the Civil War played a pivotal role in spreading Confederate symbols and racial norms across the United States by the early 20th century. Their far-reaching influence stemmed from two key conditions: (i) an ideological intensity rooted in their experiences of slavery, secession, and military defeat, and (ii) access to malleable power structures during westward expansion and postwar reconciliation. These conditions enabled them to transmit Confederate culture to both kin and non-Southern neighbors and to expand their reach by mobilizing civil society organization and leveraging positions of authority. They shaped policies and institutions that helped entrench racial norms and inequalities in labor markets, housing, and the criminal justice system. Our findings provide empirical foundations for understanding how migrants can transform local culture, rather than merely assimilate.

EXPRESS: Production Planning with Markovian Production Relationships

2026-04-13T00:00:00+00:00

Production and Operations Management
We study a production planning problem with linear, nonlinear, deterministic, and/or stochastic production relationships between the production plans and actual production quantities. We start by introducing a stochastic dynamic programming formulation of the problem with a Markovian assumption on the production relationships. Under specific conditions, we establish the convexity of the optimal cost-to-go function and closed forms of optimal policies. To solve the original problem in the general case, we propose a solution framework based on sequential policy optimization and deep reinforcement learning. We discuss the theoretical properties of the framework and evaluate its numerical performance with linear and nonlinear production relationships. In the linear case, our framework performs in line with the state-of-the-art optimization-based methods with improved computational efficiency. In the nonlinear case, our framework achieves an optimality gap near 10–20%. We also illustrate that the proposed methodology can also be extended to the problem of joint production planning and scheduling.

EXPRESS: Improving Participation in Digital Feedback Applications: Social Norms Appeals in Technology Management

2026-04-13T00:00:00+00:00

Production and Operations Management
Real-time feedback applications are reshaping employee performance feedback in operations management. Their design and implementation significantly influence employee engagement, which is a key factor in the success of technology-driven business innovations. This study investigates an implementation strategy to optimize feedback app use by employing digital nudges to encourage regular engagement. Drawing on social norms theory and cognitive load theory, we examine how message framing and users’ cognitive states affect the quantity and content features of feedback, including ratings, review length, surprise, and recognition. We conducted two randomized experiments to evaluate the effectiveness of digital nudges. Experiment 1, a field study with over 250 users of the DevelapMe app in a financial firm, tested how message framing and timing influenced cognitive load. Experiment 2, an online randomized controlled trial, explored underlying mechanisms and validated cognitive load measures. The results show that while social norms-based nudges increase feedback volume, they are associated with shorter reviews and reduced recognition and surprise. Employees experiencing lower cognitive load provided more feedback but tended to give lower ratings. Importantly, the interaction between social norms and low cognitive load resulted in higher ratings and more detailed reviews. This suggests that reducing cognitive load can enhance the positive effects of social norms on feedback quality. This study underscores the moderating role of cognitive load in the effectiveness of digital nudges and offers insights into feedback design that promotes both participation and quality. Theoretically, it contributes to research on digital feedback systems by integrating social norms and cognitive load theories to explain employee feedback behavior. Practically, it provides guidance for managers in designing real-time feedback tools that strategically use digital nudges while minimizing cognitive load, fostering a culture of continuous feedback, strengthening engagement, and improving performance management systems.

EXPRESS: Apparel Retail and Rental Business Models and their Sustainability Implications

2026-04-13T00:00:00+00:00

Production and Operations Management
In this paper, we explore the question of whether an apparel manufacturer should incorporate a renting channel into its existing business model, which currently only includes a retailing channel. We also examine how such a change would affect product quality and sustainability. We develop several game-theoretical models where an apparel manufacturer, currently selling apparel products directly to consumers, may choose to rent them out either directly or indirectly through a third-party online platform. When both retailing and renting channels are available, the manufacturer will only sell the product if rental utility or brand quality is low. Otherwise, it will sell and rent out the product simultaneously. Our findings suggest that adding a renting option to a retailing-only business model could increase the manufacturer's profit and product quality, despite potential demand cannibalization. However, the environmental impact of rental versus pure retail depends on the level of rental utility. The increase in profit and quality from incorporating renting is more significant when brand quality is higher. Additionally, this change could enhance consumer surplus and social welfare. We also analyze the effects of three common public policies on sustainability when a renting channel is added, finding that two of the policies can promote product quality. We extend our model by considering consumer heterogeneity in preferences for green consumption or discounted utility from renting, and find that our results remain robust. When examining demand cannibalization over time, we observe that product quality decisions may be influenced by the extent of cannibalization over time, while the environmental impact could worsen.

Sustainable wildfire management meets social media: How virtual interaction affects wildfire response costs

2026-04-13T00:00:00+00:00

Production and Operations Management
This work addresses the operational conflicts between visibility-driven mobilization and cost efficiency in disaster management scenarios involving wildfires. Using official wildfire reporting on the social media platform Twitter (now X), we develop a temporal gravity model to extract a signal of public attention for California wildfires (2007–2021) without the “noise” of spurious content. Interpreting this signal through the lens of behavioral disaster management operations, our analysis finds a “Visibility-Efficiency Paradox.” This paradox shows that while social media visibility functions as a potent mobilization signal to the general public during wildfires and is associated with greater resource deployment, it simultaneously correlates with reduced cost efficiency under high resource use loads. We identify resource saturation as a boundary condition where heuristic signals appear to shift from valuable inputs to potential stressors. These findings challenge the assumption that high visibility of responders in a wildfire emergency is a direct proxy for operational urgency and effectiveness. We propose actionable strategies, including reverse audits and decoupling, in order to help counteract salience bias; thus, highlighting the potential for algorithmic governance to align public attention with sustainable resource management.

Is AI an Algorithm by Any Other Name? Behavioral Reactions to AI ‐ and Model‐Based Demand Planning Algorithms

2026-04-13T00:00:00+00:00

Journal of Operations Management
With the ongoing deployment of AI algorithms, managers do not know whether existing demand planning processes account for possible differences in human behavior when using AI‐based systems in comparison to legacy model‐based systems. This study examines how human behavior may differ when performing demand forecasting tasks due to the disclosure of algorithm type (AI or model) along with associated algorithm performance (low and improving). Using signaling theory, we hypothesize that algorithm type and performance influence user forecast adjustment behavior. We find support for these predictions across two laboratory experiments and a large quasi‐natural field experiment with approximately 575,000 observations from a multinational retailer. We find no significant direct effect of algorithm type independent of performance in the lab. In contrast, in the field, users implement significantly greater adjustments for AI‐based algorithms compared to model‐based algorithms. Across both contexts, algorithm performance, whether low or improving, has a significant direct effect on user adjustments, with users adapting their behavior to the algorithm's performance. Finally, we find that in the lab and the field, users' responses to low performance are amplified when the forecasts originate from AI‐based algorithms. Our findings underscore the nuance and complexity in which users interact with AI‐based algorithms compared to model‐based algorithms and demonstrate the value of signaling theory for understanding human–AI collaboration.

EXPRESS: Separating the Artist from the Art: Social Media Boycotts, Platform Sanctions, and Music Consumption

2026-04-13T00:00:00+00:00

Journal of Marketing Research
This paper investigates how demand for an artist’s creative work changes when social media mobilizes to “cancel” the artist in response to misconduct. Human brands are particularly vulnerable to reputational shocks, yet how misconduct translates into changes in demand remains poorly understood. Using R. Kelly’s case, we examine how consumption of his music changed following calls for boycott and platform sanctions, including the removal of his songs from major playlists on the largest streaming platform. A cursory examination of music consumption after these scandals would lead to the erroneous conclusion that consumers are intentionally boycotting the artist. We propose an identification strategy that leverages variation in song-removal status and geographic demand to assess the relative roles of platform visibility and intentional consumer responses. Our findings show that the decrease in music consumption is primarily driven by supply-side factors due to reduced platform visibility rather than demand-side factors. Media coverage and calls for boycott have promotional effects, suggesting that social media boycotts can inadvertently increase music demand. The analysis of other cancellation cases involving Morgan Wallen, Rammstein, and Diddy shows no adverse effects on music demand, reinforcing the potential promotional effects of scandals in the absence of supply-side sanctions.

EXPRESS: The ABCs of Marketing Principles: A Principles-Based Framework for Marketing Alignment and Adaptation

2026-04-13T00:00:00+00:00

Journal of Marketing
Prior research on marketing principles focuses mainly on the benefits of using a relatively small set of high-level principles. However, based on 38 in-depth interviews with marketing professionals across firms and industries, we find that principles are far more widespread and hierarchically layered. Informed by these insights, the present research complements prior research by introducing the “ABC” framework of marketing principles: a principles-based system of marketing alignment and adaptation based on Articulating, Bridging, and Calibrating principles throughout an organization.Articulatinghighlights the tradeoffs of varying a principle’s specificity. Less specific principles offer decision-making flexibility that fosters adaptation but increases misalignment costs (i.e., increased marketing resource misallocation, marketer mental burden, and marketing sprawl). More specific principles offer decision-making clarity that fosters alignment but increases maladaptation costs (i.e., increased marketing staleness, reduced marketer professional development, and increased opportunity costs). To address these tensions, this research identifies two key cost-mitigation processes:Bridging, which involves translating less specific principles into more contextualized guidance, andCalibrating,which involves evaluating and refining more specific principles to ensure they fit with changing conditions. Collectively, these insights underscore a new prescriptive framework for executing the ABC framework to achieve aligned and adaptive marketing strategy execution.

EXPRESS: Automated Versus Human-Operated: Impact of AI-Driven Autonomous Stores on Prosocial Behavior

2026-04-13T00:00:00+00:00

Journal of Marketing
Many leading retailers have introduced AI-driven autonomous stores, sparking a trend that others are eager to follow. Although prior research has emphasized consumer acceptance of these formats and their operational advantages (e.g., reduced costs, improved efficiency), their broader societal consequences remain underexplored. Across nine online and field experiments, this research demonstrates that consumers engage in less prosocial behavior after interacting with AI-driven autonomous (vs. human-operated) stores. This effect stems from a diminished sense of social connectedness caused by the absence of human interaction at key service touchpoints (e.g., reception, checkout) and persists across both non-embodied and embodied humanlike AI systems. Three boundary conditions specify when this adverse effect can be mitigated, spanning the consumer context (joint consumption), firm context (consumer-welfare AI framing), and charitable organization context (self-benefiting prosocial appeal). Together, these findings provide the first empirical evidence of the social costs associated with autonomous retail formats and offer actionable insights for marketers, charitable organizations, and policymakers seeking to balance technological efficiency with societal well-being in an increasingly automated world.

EXPRESS: Climate Communications in IPOs: Unpacking the Influence of Climate Disclosure Volume, Sender, and Message Characteristics

2026-04-13T00:00:00+00:00

Journal of Marketing
Climate disclosures have emerged as a prominent communication tool for firms facing growing pressure to address climate challenges, yet their impact on firm performance remains unclear. This study proposes a nonlinear (U-shaped) relationship between climate disclosure volume and IPO firm performance, grounded in a damage-limitation logic. At low to moderate levels, disclosures amplify risk salience and proprietary costs, damaging valuations. At higher levels, offsetting benefits related to information, stewardship, and climate-friendly reputation outweigh these costs. Using multi-sourced data from 1,586 IPO firms, a BERT-based large language model to identify climate-related text in prospectuses, and econometric methods that address endogeneity, the authors find support for the proposed U-shaped relationship. The research further demonstrates that sender characteristics (underwriter reputation, customer concentration, and market orientation) and message characteristics (discretionary disclosure and message clarity) moderate the nonlinear relationship. Post-hoc analyses decomposing disclosure content reveal that climate risk disclosures damage valuations. In contrast, climate risk-management disclosures (governance, strategy, and metrics/targets) generate positive effects, suggesting that disclosure effectiveness depends on both volume and content composition. These effects persist in the long-term performance of firms. The findings provide actionable insights for firms developing disclosure strategies and policymakers encouraging climate-related communication.

Repair Service Signals: How Brand Repair Services Signal Unused Utility and Increase Product Repair

2026-04-13T00:00:00+00:00

Journal of Consumer Research
Over the past several decades, there has been a shift toward disposable consumption resulting in a ‘throwaway society’, which includes replacing rather than repairing broken durable goods. Third-party repair services exist even as consumers choose to replace over repair, but more brands are offering repair services directly or supporting repair services through certifications. If consumers simply prefer newer products, brand repair services should not deter replacement through promoting repair. However, we propose that unlike third-party repair services, brand and brand-certified repair services signal unused utility in non-fully functioning products, increasing repair. We demonstrate this effect in two field studies and four lab experiments. Drawing upon the role of unused utility, we show the signal from brand repair services is not needed to drive repair when consumers have domain expertise or products hold sentimental value as repair occurs in such cases without an unused utility signal from the brand. However, when product upgrades are salient, consumers’ motivation to upgrade attenuates the effect of brand repair services on unused utility, decreasing repair likelihood. This research makes substantive contributions to sustainability efforts to mitigate overconsumption, offers implications for brand and third-party managers, and contributes to signaling theory and unused utility literature.

Where Do Transitioning Executives Go? Exploring Demand-Side and Supply-Side Drivers of Destination Rivalry

2026-04-14T00:00:00+00:00

Journal of Management
Executive movement to close rivals can have significant implications for firm competitiveness. While prior research has provided valuable insights into the antecedents of executive search and turnover in general, the theoretical understanding of where executives go when they move remains underdeveloped. We extend research in this area by introducing the concept of destination rivalry, defined as the degree of market commonality and resource similarity between an executive’s departure firm and destination firm. We then develop a theoretical model of key demand-side and supply-side factors associated with an executive’s position in the departure firm that explains movement to a closer versus more distant rivals. We theorize that among executives moving between firms, destination rivalry will be higher when the executive possesses competition-specific human capital (e.g., via core functional experience or corporate or divisional experience at the departure firm), has a larger pay gap to the CEO, and especially when both factors are present. Empirical tests of the theoretical model using a sample of executive movements from S&P 1500 firms to other public companies between 1993 and 2023 are largely consistent with these predictions. Our findings contribute to research on executive mobility and competitive strategy by providing novel insights into factors shaping the degree of rivalry in executive moves.

Earnings management around the Tax Cuts and Jobs Act of 2017

2026-04-15T00:00:00+00:00

Review of Accounting Studies
This paper examines earnings management in response to changes in tax planning and financial reporting incentives around the corporate income tax rate decrease from 35% to 21% enacted by Tax Cuts and Jobs Act (TCJA) of 2017. Given the higher level of book-tax conformity of real activities manipulation (RAM) relative to accrual-based earnings management (AEM), we hypothesize that firms concertedly use these techniques for different purposes. Specifically, we predict and find that firms use RAM to reduce taxable income prior to the TCJA with firms in our sample saving between $9.1 billion and $11.0 billion in taxes by shifting taxable income from the high-tax to the low-tax period. We also predict and find that firms use AEM, which has lower book-tax conformity than RAM, to simultaneously increase book income in the high-tax period. These results inform policymakers, regulators, and researchers on the economic effects of corporate tax reform.

Organizing across cognitive asymmetry in human–AI collaboration: A study of perfume creation

2026-04-16T00:00:00+00:00

Strategic Management Journal
As organizations increasingly adopt generative AI (GenAI), they face a strategic challenge: not only deciding which tasks AI should perform, but also how to organize the integration of human and AI efforts to produce viable solutions. We propose that a cognitive asymmetry between human's tacit, embodied knowledge and AI's codified knowledge creates a representational gap that complicates human–GenAI collaboration. Through a qualitative study of professional perfume creation, we identifyrepresentational integrationas an organizing process through which humans and GenAI coordinate to bridge this gap. This process unfolds across three practices: allocating tasks based on cognitive advantages, converting knowledge across tacit and codified forms, and steering GenAI outputs as problem solving evolves. This study advances a novel organizing perspective on human–GenAI collaboration under conditions of cognitive asymmetry.Managerial SummaryOrganizations increasingly deploy GenAI in knowledge‐intensive work, yet many struggle to convert human and AI contributions into strategic value. This study takes a cognitive lens, showing that humans and GenAI rely on different forms of cognition—and that value emerges when organizations can coordinate and combine them. Successful human–GenAI collaboration therefore requires more than adopting powerful models. It depends on organizing practices that help employees translate across representational formats, relate GenAI outputs to embodied expertise, and iteratively steer GenAI as their interpretations evolve. Investing in these practices and skills allows organizations to harness GenAI's generativity while recognizing that human sensemaking, tacit knowledge, and contextual understanding remain indispensable for producing coherent, high‐quality outcomes.

Persuasion in the political marketplace: How firms snitch on rivals to encourage regulatory enforcement

2026-04-16T00:00:00+00:00

Strategic Management Journal
We study an important, but largely overlooked, non‐market strategy used by firms in the enforcement stage of policy: “snitching,” that is, providing intelligence about potential violations of their rivals in an attempt to persuade regulators to fine them. Building on political marketplace theory, we develop and test a theoretical model of how firms use snitching during regulatory enforcement. We show that in equilibrium, firms snitch when the rival's violations are likely to cause significant harm to the population. We then derive several boundary conditions outlining when firms will engage in more or less snitching. We find support for our theory in panel data on enforcement actions by the U.S. Environmental Protection Agency for more than 8000 facilities over 12 years.Managerial SummaryFirms can use their corporate political activity (CPA) not only to help themselves, but also to snitch on their rivals. Using a formal model, we look at how CPA influences regulatory enforcement. We find firms are most likely to snitch on their rivals when their rivals' potential violations are likely to cause significant harm, since this is when regulators care the most. Our model also outlines when this is most and least likely to occur. We then test our theory using data from the U.S. Environmental Protection Agency (EPA) and find support for our claims. The EPA is more likely to fine facilities for infractions that process many toxic chemicals, but this effect is much greater when a firm's rivals are actively lobbying the EPA.

Mutual Fund Clienteles

2026-04-16T00:00:00+00:00

The Review of Financial Studies
Using a unique data set on the ownership composition of euro area equity funds, we find substantial differences in the flow-performance sensitivity across mutual fund clienteles. Households, followed by insurers, display the weakest sensitivity, whereas investment funds—as investors in mutual funds—exhibit the strongest sensitivity. Crucially, these behavioral differences hold within the same fund-quarter, ruling out heterogeneity across funds as a potential driver. We relate these clientele effects to monitoring incentives and balance sheet constraints. Lastly, we find that households respond more strongly to poor performance when surrounded by more performance-sensitive investors, indicating strategic interactions in investor flows.

New Frontiers in Household Finance

2026-04-16T00:00:00+00:00

The Review of Financial Studies
We present and discuss the papers in this special issue. We use the themes that these papers study to illustrate interesting new directions that are being pursued in the household finance literature and highlight open questions on which more work is needed.

How Do Firms Develop Safety Management Capabilities? The Impact of Institutional Forces and Digital Technology Resources

2026-04-16T00:00:00+00:00

Journal of Operations Management
In the digital age, industrial firms are facing significant challenges in achieving digitally‐enabled safety management (DSM, i.e., leveraging digital technologies to mitigate industrial accidents) due to rigid institutional structures and underutilized digital technology resources. To address this, we develop a research model integrating institutional theory and resource‐based view theory, and position safety management capabilities (i.e., the abilities of a firm to sense, seize, and reconfigure its safety operational routines and deploy new ones for DSM) as a pivotal process mechanism translating institutional forces (i.e., institutional isomorphism and top management support for DSM) and digital technology resources (i.e., digital technologies that are available and utilized for DSM) into improved safety performance. Using time‐lagged survey data in combination with secondary data from 216 industrial firms in China, our findings reveal that institutional isomorphism and top management support exert cascading influences on safety management capabilities. The alignment of digital technology resources with institutional forces significantly facilitates the development of safety management capabilities, emphasizing their synergistic role in fostering adaptive and strategic safety practices. Furthermore, safety management capabilities serve as the critical intermediary enabling institutional and resource factors to drive superior safety outcomes. Our results advance the theory of safety management and provide actionable insights for industrial firms to effectively operationalize DSM.

The Interactive Impact of Regulation, Entrepreneurship, and Cultural Values on Technology Adoption: Renewable Energy in the EU

2026-04-16T00:00:00+00:00

Journal of Management Studies
How can diverse sources legitimize new technology when it lacks economic parity? Government policies that endorse nascent technologies play a central role through regulatory legitimation. Yet, we know less about whether inducement policies that incentivize adoption or imposition policies that mandate it are more effective, and how that effectiveness depends on other sources of legitimation. We address this question by examining renewable energy adoption by incumbent electric utilities in the European Union from 1998 to 2009, a period when renewable energy had not yet achieved cost parity with fossil‐fuel alternatives. We find that inducement policies were generally more effective than imposition policies in fostering adoption. Further, entrepreneurial entry strengthened the impact of inducement policies through pragmatic legitimation, while pro‐environment cultural values strengthened the impact of imposition policies through normative legitimation. By showing how regulatory, pragmatic, and normative legitimation sources interact to shape technology adoption, we offer insights for accelerating technology transitions aimed at combating grand challenges such as climate change.

A Framework for Understanding Consumer Response to the Depiction of Historically Underrepresented Identities in Marketing Communications

2026-04-16T00:00:00+00:00

Journal of Consumer Research
In recent years, firms’ depictions of some historically underrepresented identities (HUIs) in marketing communications have elicited backlash, while depictions of other HUIs have been more broadly accepted. The present work develops a framework to explain when and why these divergent responses occur. We propose that, while liberals respond positively to the depiction of all HUIs due to their prioritization of the Fairness moral foundation, conservatives’ responses are more nuanced and depend on how a focal identity is perceived on two dimensions: agency and normativity with respect to descriptive norms related to bodily purity. These dimensions produce a four-quadrant typology whereby, due to their greater emphasis on the Purity/Sanctity moral foundation, conservatives respond negatively only to HUIs perceived as high on both dimensions (e.g., an obese model, a transgender model, or a model who wears a hijab). We validate this framework by showing that conservatives’ negative responses are attenuated when an identity is perceived as low on either dimension. We further identify a managerially relevant boundary condition, wherein conservatives’ negative reactions are also attenuated when the focal identity appears as a numerical minority within a broader campaign featuring primarily non-HUIs.

Human– AI partnerships: Living and working with AI Assistants, AI Agents, and AI Companions

2026-04-16T00:00:00+00:00

Journal of Consumer Psychology
As the use of interactive artificial intelligence (AI) expands exponentially, it will permeate into many aspects of consumers' lives, including decision‐making and consumption. As marketers, it is important to understand how consumers currently use interactive AI and how this usage will evolve. We propose that the increased functionality of interactive AI will encourage consumers to view many interactive AI products as long‐term partners, instead of as static tools for finite tasks. Consequently, the future uses of interactive AI will be determined not only by the advancement of the underlying technology but also by consumer responses to repeated interactions with AI technology. We propose a taxonomy of human–AI partnerships (i.e., AI Assistants, AI Agents, AI Companions), provide a profile for each type of AI partner, anticipate how AI partnerships will evolve over time, and discuss how this evolution will influence AI usage. Finally, we provide an extensive agenda for future research.

Quid Pro Quo? Private Information Flows in Shareholder Activism: Evidence from Mutual Fund Families

2026-04-16T00:00:00+00:00

Journal of Accounting Research
This paper hypothesizes that information flows from target firms to large shareholders during activist campaigns and that these flows have governance consequences. Focusing on actively managed mutual fund families, we find that informed trading by large‐holding fund families increases during activist campaigns relative to smaller‐holding fund families invested in the same firms. The effect is stronger for firms that attend more invitation‐only investor events, face greater threats from activist campaigns, and are harder to value. Consistent with information flowing from management to large‐holding fund families, the effect strengthens when Regulation Fair Disclosure enforcement is lax and when the information is favorable to the firm. Furthermore, the increased information advantage is associated with more management‐friendly voting behavior by these investors and a higher likelihood of target firms winning activist campaigns and retaining board seats. Overall, our findings are consistent with a potential quid pro quo in which investors’ access to information from management is associated with more pro‐management behavior.

Human + AI in Accounting: Early Evidence from the Field

2026-04-16T00:00:00+00:00

Journal of Accounting Research
This paper provides early evidence on the integration and impact of generative artificial intelligence (GenAI) in accounting at the accountant and task levels. Using survey data from 277 professional accountants, we document substantial heterogeneity in adoption patterns, perceived benefits, and concerns about GenAI. Using proprietary field data from an AI‐enabled accounting platform serving 79 small‐ and medium‐sized enterprises, we analyze over 200,000 transaction‐level records. We document that GenAI adoption is associated with significant productivity gains and systematic reallocation of effort away from routine data entry toward business communication and quality assurance tasks. GenAI use is also associated with improvements to financial reporting quality, evidenced by more granular ledgers and faster month‐end closing. Examining human–AI interaction, we find that accountants selectively intervene when AI confidence scores are low, consistent with complementarity between professional expertise and AI. A framed field experiment further shows that while AI assistance improves classification accuracy on average, reliance on non‐consensus AI recommendations can increase the risk of error. Overall, our findings highlight both the promise and the risks of GenAI in accounting and suggest that, in practice, AI is most effective as a tool that augments—rather than replaces—professional judgment.

Do Engagement Quality Reviewers’ Workplace Ties with Engagement Partners Influence Audit Quality?

2026-04-16T00:00:00+00:00

Journal of Accounting Research
The engagement quality review is a key component of an audit firm's quality control system. This study leverages unique data on individual engagement quality reviewers (EQRs) to examine how previous shared working experience between EQRs and engagement partners affects audit quality. While prior research suggests that within‐firm network ties between predecessor and successor partners facilitate knowledge transfer, we find that prior shared working experience between EQRs and engagement partners is associated withloweraudit quality. Mechanism tests indicate that such experience is associated with a higher likelihood of regulatory enforcement actions related to deficiencies in audit procedures, insufficient evidence, and a lack of professional skepticism. We also find that such experience corresponds with higher materiality thresholds, suggesting reduced scrutiny during audit planning and execution. Additional analyses reveal that these adverse effects primarily arise when previous shared working relationships did not produce adverse outcomes, when EQRs are not audit industry leaders, and when they face lower reputational risk. These findings are especially salient given that EQRs’ previous shared working experience with engagement partners appears to weigh heavily in EQR assignments. Overall, our study provides important insights into the implications of EQR independence and the determinants of engagement quality review effectiveness.

EXPRESS: When Does Skewness Matter in Robust Inventory Management?

2026-04-17T00:00:00+00:00

Production and Operations Management
We investigate the impact of skewed demand on robust inventory management. Including skewness in calculations leads to cubic constraints that prevent the standard two-stage method from deriving an explicit and tractable objective function. To overcome this roadblock, we propose a joint optimization method to directly derive the robust solution in closed form. The joint optimization method is widely applicable to various robust inventory models with different ambiguity sets. The notable advantage is that we can obtain the final solution without deriving the objective function, so many tedious intermediate steps are circumvented. We conduct numerical experiments on industry data to demonstrate that our moment-based policies deliver more consistent performance than divergence-based policies. After obtaining various closed-form solutions, we demonstrate that including skewness in the model improves the profit generated by the robust optimal order quantity if either demand is bounded or the cost-to-price ratio is low, even though the sample moments used may not equal the population moments. Furthermore, under these conditions in which skewness should be included in the calculations, the firm’s expected profit, under the most unfavorable distribution, increases with variance but decreases with skewness. This result stands in contrast to findings in the economics and finance literature, where distributional ambiguity is not considered.

EXPRESS: Competitive Markovian Pricing

2026-04-17T00:00:00+00:00

Production and Operations Management
Dynamic pricing is often complicated by strategic customer behavior. One tactic utilized by retailers to manage strategic customer behavior, known as Markovian pricing, is to offer price discounts at random intervals to prevent customers from predicting when the next discount will occur, thereby simplifying their strategic waiting behavior. In this paper, we study Markovian pricing in competitive settings. We show that retailers can effectively adopt Markovian pricing in competitive environments, establish the optimality of flash discounts under competitive Markovian pricing, and find surprisingly that increased levels of competition may benefit both retailers. We confirm the robustness of these insights and also establish their limits of applicability in two model extensions. Our findings suggest that retailers engaging in competitive Markovian pricing should refrain from naïvely applying common wisdom toward third-party price-monitoring and comparison services and reconsider the efforts in growing their loyal customer base, and more broadly highlight the unique properties of competitive Markovian pricing.

EXPRESS: Assortment Optimization for Online Video Games

2026-04-17T00:00:00+00:00

Production and Operations Management
We consider an assortment optimization problem for a class of online video games where the in-game virtual store has a unique structure with two sections: Featured and Just For You (JFY). All customers (players) are offered the same Featured section assortment, whereas the JFY section is used for personalized recommendations. We model customer choice under a constrained mixture-of-nested-logit model and propose different solution methods for the resulting assortment optimization problems. First, we introduce a novel mixed-integer nonlinear programming (MINLP) formulation. Numerical experiments show that the MINLP formulation generally obtains optimal solutions efficiently, using a variety of instances derived from conversations with our industry partner to mimic the environment found in their video game stores. In addition, we propose three approximate solution methods with theoretical performance guarantees: a fully polynomial time approximation scheme (FPTAS), a mixed-integer linear programming (MILP) formulation, and a heuristic algorithm. To understand the impact of a shared Featured section, we analyze the distribution of display capacity between the Featured and JFY sections. Our numerical experiments highlight that the Featured section plays a critical role in balancing revenue and customer utility. To validate our use of a mixture-of-nested-logit model, we further conduct a simulation study based on ground-truth instances that are independent of the underlying structure of the consumer choice models we consider. The results indicate that our nested structure yields superior performance in terms of both capturing customer behavior and simulation revenue, compared with the mixture-of-MNL model and the current practice of our industry partner. Overall, our paper is the first to study assortment optimization for the gaming industry under discrete choice models; it is also the first to devise both exact and approximate solution approaches for the constrained mixture-of-nested-logit model. Our results provide guidance for effective management of assortments in online video game stores and offer an “assortment” of solution approaches, allowing practitioners to choose one that best suits their environment.

Investment Performance of Private Pension Plans: Defined Benefit vs. Defined Contribution

2026-04-17T00:00:00+00:00

Management Science
Using data on over 160,000 U.S. private pension plans, we analyze the investment performance of defined benefit (DB) and defined contribution (DC) plans. We find a positive asset size effect in performance, stronger in DB plans partly because of greater economies of scale in administrative expenses. Small DB plans underperform small DC plans on various performance metrics and face the highest termination risk. After adjusting for investable passive benchmarks, DC plans outperform DB plans in all but the largest size decile. Our findings suggest that plan consolidation and converting small DB plans to the DC structure are likely to improve the efficiency of pension financing.This paper was accepted by Camelia Kuhnen, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05241 .

Analyzing Network Formation Using Big Data Analytics: A Study of Degree Distribution, Clustering Coefficient, Diameter, and Assortativity

2026-04-17T00:00:00+00:00

Management Science
This research presents an innovative approach to network development which goes beyond conventional models that use connection rules for individual agents. We show that agents can produce diverse network structures through uniform edge searches which involve random connection attempts without preference. This model offers a new viewpoint on network formation by emphasizing edges in contrast to nodes. Within this framework, edges are considerably more crucial than those in other network formation models as they represent tangible interactions such as question-and-answer exchanges, commercial transactions, and coauthorships, rather than abstract relationships. We prove that the model converges to a stationary equilibrium degree distribution, implying that in the long term, the probability of observing certain network characteristics stabilizes and becomes time-invariant. Furthermore, we derive closed‐form asymptotic expressions for key network statistics and validate them through both simulations and real‐world data sets. Our research shows that three core dimensions are inherently in competition with one another: (1) quantity (mean degree), reflecting agents’ overall connectivity; (2) quality (clustering coefficient), capturing local cohesion; and (3) equity (skewness of the in-degree distribution), indicating how strongly connections concentrate on a few nodes. Our results show that raising the search times boosts quantity but lowers quality by diluting clustering, whereas raising the secondary connection probability enhances clustering yet decreases equity by concentrating in-degree and intensifying the Matthew effect. These trade-offs reveal essential limits of network formation while providing a flexible framework which connects theoretical insight to practical decisions in network design and management.This paper was accepted by J. George Shanthikumar, data science.Funding: The research of J. Qi is funded by the National Natural Science Foundation of China [Grant 72422005] and the Hong Kong Research Grant Council [Grants GRF 16209923, 16213424, and TRS T32-615/24-R]. Y.-J. Chen acknowledges financial support from the Hong Kong Research Grant Council [Grants C6020-21GF, 16212821, and 16204521].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00475 .

EXPRESS: A More Creative World Is a More Sustainable One: How to Increase Length of Product Usage through Creativity and Emotional Attachment

2026-04-17T00:00:00+00:00

Journal of Marketing Research
Overproduction and overconsumption represent key issues in the fight against resource waste and environmental degradation. While the scientific debate has mainly focused on how to increase product durability by improving tangible aspects (e.g., technical characteristics, materials used, production processes), the present research focuses on a consumer-based view of durability, looking at how long consumers plan to use a product for, a construct labeled length of product usage (LPU). The core thesis is that LPU might depend not only on tangible, but also on intangible product characteristics, such as creativity, defined in terms of high novelty and adequate appropriateness. In advancing thiscreativity-based LPUaccount, the authors argue that higher product creativity leads to higher LPU by strengthening consumers’ emotional attachment to products. Seven pre-registered studies, employing different products, populations, and creativity manipulations, empirically support the proposed framework. Results also show that the effect of creativity on LPU, via emotional attachment, is especially pronounced for non-owners, vs. owners, and, for mass-market, vs. luxury, products. By emphasizing that creativity can be key to fostering sustainable consumption, this research advances the literature on the antecedents of LPU and product durability, offers implications for companies, and avenues for future research.

EXPRESS: Brand Performativity and Consumers’ Cultivation of Identity Value

2026-04-17T00:00:00+00:00

Journal of Marketing
How do brands provide identity value to consumers? The marketing literature provides three primary answers to this key managerial question: by building brand communities; by forging anthropomorphized relations whereby consumers regard brands as relationship partners; and by following cultural branding principles. This article argues that these three conceptual frameworks have often misdiagnosed the sources of the identity value that consumers derive from brands. Accordingly, it proposes that brand performativity is an unrecognized explanatory factor that underlies these extant theorizations. Drawing on sociological theories of performativity, it conceptualizes brand performativity as an arrangement of discourses, practices, material resources, normative standards, metrics, and goals that coalesce as a script that consumers can use to cultivate identity value through brand-mediated experiences. Through an analysis of CrossFit, it demonstrates that a theoretical sensitivity to brand performativity provides a fuller picture of how brands generate consumer identity value. It explains how this conceptualization revises strategic implications that follow from the aforementioned theorizations, especially for brands implementing more extensive modes of performativity. It closes with a discussion of the broader applicability of brand performativity framework and how it can help marketing managers transcend the conventional product versus service brand and functional versus expressive branding strategy distinctions.

Two Sides of the Same Coin: Sustaining Loan‐Use Ambiguity in Microfinance through Harmonizing Practices

2026-04-17T00:00:00+00:00

Journal of Management Studies
Despite its promise to alleviate poverty through entrepreneurship, microfinance is widely used for household purposes, challenging Western assumptions of microfinance as entrepreneurial finance and raising questions about the viability of microfinance organizations (MFOs). To understand how microfinance persists despite such use, we conducted an embedded case study of a South African MFO operating in a rural, resource‐constrained context shaped by Ubuntu – a communitarian ethic emphasizing relational interdependence and mutual care. Drawing on scarcity theory and a practice‐based view of financial resourcing, we show how scarcity is collectively navigated through culturally embedded practices that stabilize loan‐use ambiguity in everyday microfinance interactions. We find that loan officers and recipients jointly enact three harmonizing practices – reverence for repayment, empathic financial support, and entrepreneurial discretion – that sustain this ambiguity between the MFO's espoused entrepreneurial schema and enacted livelihood‐oriented practices. Through these practices, microfinance remains viable as a community‐embedded system of financial support, even as loan use departs from formal entrepreneurial prescriptions. By conceptualizing microfinance as a community‐embedded system of financial resourcing rather than a narrowly entrepreneurial intervention, this study contributes to research on microfinance, scarcity, and resourcing in communitarian settings.

Seeking, Shaping, Becoming: A Scoping Review of the Organizational Futures Literature

2026-04-17T00:00:00+00:00

Journal of Management
Across management disciplines, there is growing recognition that understanding organizational futures—that is, how organizations engage with futures—is integral to comprehending contemporary organizing and strategizing processes. In this paper, we conduct an in-depth scoping review aimed at organizing and synthesizing the rapidly expanding and fragmented literature on organizational futures across the strategy, entrepreneurship, innovation, and organization studies disciplines over the past several decades. Our survey identifies several research streams in these areas that we classify into three main categories: future seeking, shaping, and becoming. Furthermore, we identify three subcategories within each main group—anticipating, adapting, and non-adapting under future seeking; enacting, designing, and narrating within future shaping; and perpetuating, making/performing, and wayfinding/improvising inside future becoming—and review the key scholarship associated with each of these. In so doing, we provide a comprehensive and coherent map intended to enable this recently flourishing and perennially vital domain of research to move forward systematically. We also envision our review as a platform that facilitates the development of more prospectively-oriented (i.e., forward-looking) theorizing. Finally, we highlight many frontiers to explore in future work, that include more closely examining the role played by imagination, power and affect in the emergence of organizational futures.

Generative AI Models as Wicked Resources: A Dynamic Perspective on Resource Governance

2026-04-17T00:00:00+00:00

Journal of Management
The proliferation of generative AI models fundamentally alters organizational capabilities, enabling novel value creation while challenging incumbent governance frameworks. Employing a phenomenon-driven approach, this study integrates and extends property rights theory (PRT) and stakeholder resource-based theory (SRBT) to address governance challenges posed by generative AI. By leveraging system dynamics modeling, we conceptualize the dynamic interplay among stakeholder claims, institutional arrangements, and value appropriation outcomes, highlighting how feedback loops, delays, and accumulations shape these interactions. Our analysis reveals two insights: First, stable equilibrium states in stakeholder claims and property rights arrangements may not invariably lead to equitable outcomes, due to stakeholder power disparities and attribution ambiguity associated with generative AI. Second, framing the evolution of generative AI models as organizational resources from the complementary perspectives of PRT and SRBT reveals distinct resource features largely unexamined in the strategy literature. Hence, we introduce the concept of “wicked resources,” characterizing generative AI models by their inherent attribution ambiguity and emergent unpredictability. Building on prior research on resource complexity and uncertainty in the strategy literature, wicked resources are marked by the difficulty firms face in delineating and enforcing control within shifting sociopolitical contexts. This paper makes three key contributions: addressing the dynamic, multi-stakeholder nature of generative AI governance; introducing wicked resources as a novel resource category in strategy and management literatures; and identifying theoretical gaps, advocating for a dynamic, systemic approach to property rights and stakeholder bargaining.

Scaling high and wide: How firms leverage AI and organizational design to overcome the scale‐scope trade‐off

2026-04-20T00:00:00+00:00

Strategic Management Journal
The trade‐off between scale and scope has long posed a strategic dilemma, especially in digital settings, where specialization enables hyperscaling. Drawing on a longitudinal case study of ByteDance, we theorize how digital firms can overcome this constraint through the use of artificial intelligence (AI) combined with an adaptive organizational design. AI evolves and improves through self‐learning and cross‐fertilization across domains, becoming increasingly valuable as learning accumulates. This, however, is contingent on access to structurally related data that allow learning to transfer across domains. We show how AI reverses the conventional logic of the resource‐based view: rather than valuable resources enabling diversification, diversification amplifies the value of resources. AI thus transforms the scale‐scope nexus from being a trade‐off into a source of strategic advantage.Managerial SummaryThe growing centrality of AI and digital platforms is reshaping how firms pursue and sustain growth. This study examines how ByteDance leveraged AI and adaptive organizational design not only to scale rapidly but also to diversify across industries and markets. Rather than incurring rising costs or coordination complexity, the firm's AI capabilities improved with each deployment through cross‐fertilization across domains, enabling more efficient growth across multiple domains. For managers, the findings highlight how dynamic combinations of AI and organizational structure can help overcome traditional trade‐offs between scale and scope, opening new pathways for scalable, cross‐market expansion in increasingly competitive environments.

Throwing curveballs: A language‐based model of curveball questions in quarterly earnings calls uncovers their consequences and antecedents

2026-04-20T00:00:00+00:00

Strategic Management Journal
In evaluative contexts, evaluatees typically seek to present themselves in a favorable light, while evaluators ask penetrating questions to assess these claims. Here we develop a framework to identifycurveball questions: ones that areon‐topicyetperplexing(i.e., difficult to predict) relative to past discourse. We develop a language‐based measure of curveball questions and apply it to a corpus of quarterly earnings calls. After validating this question‐level measure, we next demonstrate that a call‐level curveball measure predicts absolute returns, absolute abnormal returns, and changes in a firm's average analyst rating. Finally, we identify the types of analysts who are most likely to pose curveball questions, the types of firms that are most likely to receive them, and the conditions under which they tend to arise.Managerial SummaryEven a carefully crafted presentation can be derailed by a challenging question. What makes a question challenging in ways that can be disruptive and how can such a question be measured? We propose that such questions, which we labelcurveballs, are on‐topic, and thus difficult to dismiss or deflect, yet difficult to predict based on prior knowledge. We harness the tools of computational linguistics to develop a measure of curveball questions and apply it to the context of quarterly earnings calls. We show that this measure predicts consequential economic outcomes and highlight the conditions under which curveball questions tend to arise. Our measurement strategy can be readily extended to other evaluative contexts such as job interviews and venture capital pitches.

Remeasuring Scale in Active Management

2026-04-20T00:00:00+00:00

The Review of Financial Studies
We show that scale in active equity portfolios is understated by at least 65% because the majority of mutual funds have “twin” institutional vehicles (IVs) managed under the same strategies. Omitting these IVs can severely skew crucial estimates in asset management research: by including IV assets, diminishing returns to scale of active investments is significantly reduced, and dollar value added of active strategies is more substantial and persistent than previously suggested. We further show that IV assets meaningfully influence managers’ portfolio decisions. In addition, these measurement issues apply to common flow measures and extend to passive funds and bond funds. (JEL G20, G23)

Political Pressure on the Fed

2026-04-20T00:00:00+00:00

Review of Economic Studies
This paper combines new data and a narrative approach to identify variation in political pressure on the Federal Reserve. From archival records, I build a data set of personal interactions between U.S. Presidents and Fed officials between 1933 and 2016. Since personal interactions do not necessarily reflect political pressure, I develop a narrative identification strategy based on President Nixon's pressure on Fed Chair Burns. I exploit this narrative through restrictions on a structural vector autoregression that includes the President-Fed interaction data. I find that political pressure to ease monetary policy (i) increases the price level strongly and persistently, (ii) does not lead to positive effects on real economic activity, (iii) contributed to inflationary episodes outside of the Nixon era, and (iv) transmits differently from a typical monetary policy easing, by having a stronger effect on inflation expectations. Quantitatively, increasing political pressure by half as much as Nixon, for six months, raises the price level by about 7% over the following decade.

Investing in Growth Stocks: Bimodal Payoff Distribution and Expected Returns

2026-04-20T00:00:00+00:00

Management Science
This paper documents that the payoffs from investing in growth stocks, as measured by the decile-rank distributions (DRD) of future revenues, earnings, investment, and stock returns, follow a bimodal U-shaped pattern. In contrast, the DRD of value stocks follows a traditional bell-shaped distribution. This divergence in payoff structures suggests growth stocks are more prone to structural shocks, such as disruptive technologies. Consequently, their pricing is heavily influenced by investors’ attitude toward exceptional outcomes, resulting in lower expected stock returns in equilibrium. We find that stocks with more pronounced bimodal payoffs are associated with significantly lower subsequent stock returns.This paper was accepted by Eric So, accounting.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.00980 .

The Trillion Dollar Bonus of Private Capital Fund Managers

2026-04-20T00:00:00+00:00

Management Science
Carried interest (carry) is the main performance-based component of compensation for private capital fund managers. Using fund-level cash flows and fee terms for more than 12,000 funds, we estimate which funds are in the carry and the total amount earned. Aggregate carry exceeds one trillion dollars and accounts for 18% of investor profits, about equal the contractual value-weighted rate of 19%. The difference reflects the role of hurdle rates and the relatively smooth distribution of fund outcomes. Carry is strongly related to both performance and fund size, and past carry is a stronger predictor of future performance than past returns.This paper was accepted by Lukas Schmid, finance.

The Market Cost of Business Cycle Fluctuations

2026-04-20T00:00:00+00:00

Management Science
We propose a novel approach to measure the cost of aggregate economic fluctuations that does not require complete specification of investors’ risk preferences or their beliefs. With data on consumption and asset prices, an information-theoretic method is used to recover an information kernel (I-SDF). The I-SDF prices asset returns much better than tightly parametrized structural models, thereby offering a reliable candidate for the measurement of the welfare cost of business cycles. Our method enables the estimation of both the unconditional (or, average) cost of fluctuations, as well as the cost conditional on the state of the economy. We find that the cost of fluctuations is strongly time varying and countercyclical and that the cost of business cycle fluctuations is substantial, accounting for a quarter to a third of the cost of all consumption uncertainty.This paper was accepted by Lukas Schmid, finance.Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.00484 .

Brief Commentary: Theory Testing for Differences in Process – Hypothesizing, Testing, and Reporting Comparisons Between Indirect Effects

2026-04-20T00:00:00+00:00

Journal of Consumer Research
Consumer researchers often compare a proposed process across contexts (i.e., moderated mediation) or across mediators (e.g., ruling out an alternative process in parallel mediation). This paper aims to help researchers in mapping process-related theoretical hypotheses onto statistical coefficients and in reporting their results. Researchers can formulate a variety of hypotheses about the conditional indirect effect (CIE) of a predictor X on an outcome Y through a mediator M, such as: (A) the CIE is greater for moderator condition W0 than W1, (B) the CIE is only positive for W0, (C) the CIE is positive for W0 and negative for W1. For example, if a researcher’s hypotheses align with case A, they must test and report the difference between the two conditional indirect effects (i.e., the index of moderated mediation). Reporting that the indirect effect is significant for W0 and non-significant for W1 would be insufficient for case A, but appropriate for case B. We generalize these examples in two tutorials–for moderated mediation and for parallel mediation–to help researchers 1) connect theory to testable predictions, 2) select the appropriate statistical model, and 3) report results transparently and consistently. We provide concrete examples of pre-registrations, data analyses, and manuscript reports.

The Impact of Financial Reporting Mandates on Labor Unions

2026-04-20T00:00:00+00:00

Journal of Accounting Research
Labor unions in the United States are subject to financial reporting mandates. This study examines how these mandates affect unions and their members. Using several regulation‐based empirical designs, we document that more granular reporting requirements adversely affect unions' election outcomes. Supplemental analyses suggest that these findings are consistent with the strategic use of unions' disclosed information by parties such as employers and their consultants. We find mixed evidence on whether the mandates materially improve oversight of unions. Lastly, we find that the mandate reduces employees' average pay without clear benefits for employers, aside from reallocating investment from labor to capital. Collectively, our results suggest that more fine‐grained financial reporting requirements impose costs on unions and weaken their ability to represent employees, resulting in worse employment outcomes.

Disclosure of Cybersecurity Investments and the Cost of Capital

2026-04-20T00:00:00+00:00

Information Systems Research
Executives often hesitate to disclose their company’s cybersecurity investments, fearing lawsuits or negative reactions from investors. Our research shows that transparency in this area actually pays off. Analyzing SEC filings from nearly 2,000 public firms, we find that companies that disclose cybersecurity investments enjoy a lower cost of capital—cheaper access to debt and equity financing. These benefits are strongest when disclosures are specific rather than boilerplate, when the firm is followed by more analysts and more institutional investors, and when disclosed investments in cybersecurity are substantial. The takeaway is clear: Meaningful disclosure builds trust with investors, who reward transparency by lowering financing costs. For leaders and regulators alike, this finding highlights that openness about cybersecurity readiness is not just good governance—It is smart business in a capital market that increasingly values risk management and resilience.

Align Generative Artificial Intelligence with Human Preferences: A Novel Large Language Model Fine-Tuning Method for Online Review Management

2026-04-20T00:00:00+00:00

Information Systems Research
Online reviews can shape where people stay, eat, and shop, but businesses often struggle to keep up with the flood of customer feedback. Although generative artificial intelligence (AI) offers a promising solution, general-purpose models are not designed for the specific judgment, tone, and accuracy required in customer review responses. This study introduces a new fine-tuning method that helps large language models generate review replies that better match human preferences in real business settings. The paper makes several technical advances. It identifies why review-response systems hallucinate and introduces a context-augmentation strategy to reduce factual errors. It also develops a theory-driven way to automatically construct preference data from existing review-response records, overcoming a major barrier in preference fine-tuning. In addition, the study proposes a curriculum learning design and a new support-constraint method that reduces the overconservatism of existing offline optimization approaches, with stronger theoretical guarantees. Tests on hotel reviews show that the method produces better responses than leading alternatives in both automated evaluations and human judgments. The findings point to a practical path for using AI to help firms respond faster and more consistently to customers while also underscoring the need for safeguards, human oversight, and domain-specific model alignment in customer-facing AI systems.

The True Colors of Money: Racial Representation and Asset Management

2026-04-21T00:00:00+00:00

The Review of Financial Studies
We examine the role of race and ethnicity in the mutual fund context at two distinct levels. At the fund manager level, we document a co-racial tilt—funds managed by minority-dominant (White-dominant) teams allocate larger portfolio weights to minority-led (White-led) firms. This tilt is not associated with superior performance. It diminishes as fund managers gain experience, suggesting the presence of inaccurate statistical discrimination. At the investor level, we find that minority-led funds are penalized similarly to White-dominant funds for poor performance but are not rewarded as much for superior performance. Overall, our results uncover race-related investment choices at both levels.

What Drives Variation in Investor Portfolios? Estimating the Roles of Beliefs and Risk Preferences†

2026-04-21T00:00:00+00:00

The Review of Financial Studies
We present a portfolio choice demand model that allows for the nonparametric estimation of investors’ (subjective) expectations and risk preferences. Using comprehensive 401(k)-plan-level data from 2009 through 2019, we explore heterogeneity in asset allocations using our empirical framework. We recover investors’ beliefs about each asset and examine the implications and potential sources of those beliefs. Heterogeneity in expectations across investors accounts for twice as much variation in portfolio holdings as heterogeneity in risk aversion. Belief heterogeneity is partly driven by investors’ characteristics and experiences, reflecting local sources of information such as county-level GDP and employers’ past performance. (JEL G11, G12, G40, G51, J32)

Machine Forecast Disagreement

2026-04-21T00:00:00+00:00

The Review of Financial Studies
We propose a statistical model of heterogeneous beliefs wherein investors are represented as different machine learning model specifications. Investors form return forecasts from their individual models using common data inputs. We measure disagreement as forecast dispersion across investor-models (MFD). Our measure aligns with analyst forecast disagreement but more powerfully predicts returns. We document a large and robust association between belief disagreement and future returns. A decile spread portfolio that sells stocks with high disagreement and buys stocks with low disagreement earns a value-weighted return of 13% per year. Further analyses suggest MFD-alpha is mispricing induced by short-sale costs and limits-to-arbitrage.

Dynamics of Asset Demands with Confidence Heterogeneity†

2026-04-21T00:00:00+00:00

The Review of Financial Studies
To understand the dynamics of investors’ asset demands, we develop a general-equilibrium model driven by a single latent variable: heterogeneity in investors’ confidence about mean endowment growth. The model predicts persistent heterogeneity in asset demands and concentrated portfolios. Consistent with the data, limited confidence reduces investors’ demand elasticities and makes stock prices excessively volatile—driven by latent demand rather than observable characteristics. The underlying economic mechanisms are driven primarily by investors’ desire to hedge changes in future beliefs instead of current disagreement. Finally, consistent with survey data, investors’ expectations correlate positively with past returns and negatively with future returns.

Testing Mechanisms

2026-04-21T00:00:00+00:00

Review of Economic Studies
Economists are often interested in the mechanisms by which a treatment affects an outcome. We develop tests for the “sharp null of full mediation” that a treatment D affects an outcome Y only through a particular mechanism (or set of mechanisms) M. Our approach exploits connections between mediation analysis and the econometric literature on testing instrument validity. We also provide tools for quantifying the magnitude of alternative mechanisms when the sharp null is rejected: we derive sharp lower bounds on the fraction of individuals whose outcome is affected by the treatment despite having the same value of M under both treatments (“always-takers”), as well as sharp bounds on the average effect of the treatment for such always-takers. An advantage of our approach relative to existing tools for mediation analysis is that it does not require stringent assumptions about how M is assigned. We illustrate our methodology in two empirical applications.

CEO Succession Under Anticipatory Awareness Misalignment

2026-04-21T00:00:00+00:00

Organization Science
We develop a dynamic model of chief executive officer (CEO) succession under anticipatory awareness misalignment: the divergence between the board’s and the CEO’s private beliefs about the firm’s strategic potential. The CEO chooses unobservable effort, may send costly noncontractible signals, and faces interim termination based on performance thresholds. We derive closed-form expressions for optimal CEO incentive intensity, effort, and fixed pay and show how they are influenced by belief misalignment, CEO capability, and market frictions. We present propositions that explain how belief alignment affects effort and pay, how misaligned types are separated through signaling, and how misalignment impacts firing thresholds and the matching of boards and CEO. We show that misalignment reduces incentive efficiency, increases fixed pay, and increases the probability of early dismissal. CEOs aligned with the board receive higher variable compensation; misaligned types must compensate with signals or accept weaker incentives. The model generates empirically testable predictions on compensation structure, retention, and succession outcomes.Funding: A. Camuffo and A. Gambardella acknowledge support from the H2020 European Research Council [Grant 101021061].Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2025.20384 .

What Is the Price of Spanning Domain Boundaries? Distant Recombination and the Market Valuations of Firm Inventions

2026-04-21T00:00:00+00:00

Organization Science
Do investors value firm inventions that recombine distant knowledge across domain boundaries? Analyzing more than 1.5 million firm patents, we find that, despite its strong association with long-term technological impact beyond the local domain, distant recombination of domain knowledge contributes less to a patent’s market valuation when compared to local recombination, thereby inducing a misalignment between valuation and impact. This valuation disadvantage is especially pronounced when distant recombination occurs in a domain primarily built on local knowledge, draws on knowledge from domains with broad applicability, and spans domains with limited connections. Mechanism tests suggest that the inherent evaluation and appropriation challenges for inventions built on distant recombination plausibly account for these findings. We thus establish domain distinctions in knowledge recombination as a key explanation of why innovations’ private returns may diverge from their technological impact despite the commonly assumed alignment between the two.Funding: The authors acknowledge financial support from Cornell University.Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2023.17475 .

A Platform Rating System and Vulnerable Workers: Evidence from Field Experiments in Singapore

2026-04-21T00:00:00+00:00

Organization Science
Rating systems are a common governance tool on two-sided platforms. Research suggests that, via indirect network effects, rating systems benefit participants on both the rating side and the rated side. However, participants on the rated side may not always recognize the benefits of the rating system and may respond negatively to its introduction. The rating side may anticipate the rated side’s negative reactions and react negatively as well, especially when the rated side holds more power over the rating side. To empirically examine participants’ reactions to a proposed platform rating system in the context of a substantial cross-side power differential, we conducted two field experiments in collaboration with a Singapore-based labor platform that connects foreign domestic workers with employers (families). We found that employers, on average, were indifferent to the proposed rating system, even when the benefits to them were highlighted, with the highest-income employers exhibiting negative responses. We also found that workers reacted negatively, with those informed of the proposed rating system completely disengaging from the platform. Post hoc interviews and analyses support our interpretation that power differential underlies workers’ negative responses to the rating system. This study contributes to the literature on platform rating systems by demonstrating that, in the presence of a substantial cross-side power imbalance, rating systems may not always be perceived positively, even by participants on the rating side, whom the system aims to empower. It also constitutes one of the first efforts in management research to study domestic workers, a highly vulnerable population of workers.Funding: This work was supported by Chazen Institute of Global Business (Columbia University) and INSEAD.Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2023.18153 .

Short-Lived High-Volume Bandits

2026-04-21T00:00:00+00:00

Operations Research
When Thousands of Items Arrive Every Hour: A New Approach to Online ExperimentationResearchers have reported a new approach to address a key challenge for online platforms. In a new paper in Operations Research, Jia et al. introduced the Short-lived High-volume Bandits (SLHVB) framework. This models modern platforms where thousands of items—such as ads, stories, or interface designs—arrive each hour but remain available only briefly.The study develops a near-optimal online learning policy that balances exploration and exploitation. Theoretical analysis shows the algorithm achieves nearly the minimal possible loss as the number of user impressions grows. The team tested the policy in a large-scale field experiment with Glance, a leading lock-screen content platform. The policy increased viewing duration by 4.32% and click-through rates by 7.48% compared to the platform’s existing deep-learning-based recommender system.

Frontiers: ChatGPT Referrals to E-Commerce Websites: How Do LLMs Compare Against Traditional Channels?

2026-04-21T00:00:00+00:00

Marketing Science
This is a descriptive study reporting financial and engagement metrics for 973 e-commerce websites, comparing organic large language model traffic (oLLM) with traditional digital channels.

Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach

2026-04-21T00:00:00+00:00

Marketing Science
This paper proposes a Bayesian deep-learning model that captures multifaceted, time-varying user activities on digital platforms, yielding interpretable and dynamic preference estimations at the platform and individual levels.

Government Debt Maturity and Term Structure of Credit Spreads

2026-04-21T00:00:00+00:00

Management Science
We investigate how government borrowing behaviors influence private sectors by exploring the relationship between government debt maturity and credit term structures. Using individual corporate bonds data between 1987 and 2015, we find that a longer government debt maturity is associated with a steeper credit term structure in both the primary and secondary corporate bond markets. An instrumental variable approach and an exogenous event study help us establish a causality. Our findings are more pronounced among riskier corporate bonds, and the influences of Treasury bond supply on credit term spreads are more pronounced near the maturity where this supply shock originates, suggesting that the credit risk and the maturity clientele channels together drive our findings.This paper was accepted by Victoria Ivashina, finance.Supplemental Material: The internet appendix and data files are available at https://doi.org/10.1287/mnsc.2020.01979 .

Unlocking Local Market Information Through Franchising

2026-04-21T00:00:00+00:00

Management Science
This paper examines the role of franchising in enabling firms to access valuable local market information. Using comprehensive data on U.S. franchised establishments, we show that franchisee-owned establishment openings robustly predict future local economic growth reflected by house price appreciation, whereas franchisor-owned outlets lack such predictive power. Franchisee investments are especially informative in markets with greater uncertainty and complexity and when facing higher investment hurdles. Franchisors appear sensitive to information frictions, avoiding direct investment in new markets that are geographically distant and lack direct flight connectivity. Our findings support the long-standing but untested assumption that franchisees possess superior private information.This paper was accepted by Maria Guadalupe, business strategy.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05903 .

From Black to Gray: Improving Access to Antimalarial Drugs in the Presence of Deceptive Counterfeits

2026-04-21T00:00:00+00:00

Management Science
In malaria-endemic countries, the limited availability of affordable antimalarial medication has contributed to the widespread distribution of counterfeit drugs. This paper examines such markets to determine how philanthropic donors can best allocate limited funds to subsidize the purchase or sales of antimalarial drugs via private-sector distribution channels. We develop a game-theoretic model of the antimalarial supply chain wherein the retailer strategically sources legitimate drugs from a donor-certified supplier, potentially counterfeit drugs from an uncertified supplier, or both. In contrast with the extant literature, we demonstrate that, in the presence of counterfeits, exclusive reliance on purchase subsidies may no longer be optimal. Specifically, under donor budget constraints, offering sales subsidies that incorporate both legitimate and counterfeit drugs may be preferable or, in some cases, abstaining from subsidy provision completely. Additionally, we evaluate the implications of three pertinent nonsubsidy strategies deployed to combat counterfeit drugs: imposing penalties for sourcing counterfeits, eliminating subsidies on counterfeit drugs with traceability technology, and implementing price controls. Our study concludes with extensive numerical analysis calibrated to malaria data from Mozambique. Overall, this paper offers strategic guidance for improving outcomes in the presence of counterfeit drugs. Our results highlight the need for governments and donors to carefully consider market-specific factors, such as retailers’ pricing power and donors’ budget constraints, when designing subsidy schemes and access policies for life-saving medicines. These insights could potentially be extrapolated to address similar challenges in other endemic disease contexts, offering a broader framework for enhancing public health in resource-constrained environments.This paper was accepted by Jeannette Song, operations management.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00885 .

Upward convergence: digital regulations and digital firms’ internationalization

2026-04-21T00:00:00+00:00

Journal of International Business Studies
Digital regulations are often portrayed as barriers to digital firms’ internationalization because they hinder digital firms’ market penetration and fragment their global operations. We argue, however, that regulations may play a different role for digital firms that internationalize through virtual presence. Leveraging the European Union’s (EU’s) General Data Protection Regulation (GDPR) as context, we examine how the GDPR affects digital products’ penetration in the EU and whether it drives operational fragmentation between EU and non-EU markets. We theorize that the GDPR does not uniformly reduce penetration opportunities; instead, it benefits low data-dependent products and explorative products that differ substantially from firms’ prior offerings. Moreover, building on digital firms’ reliance on network effects, we propose that digital firms may treat the EU as a global benchmark and release EU-penetrated products to non-EU markets, converging upward rather than separating their international operations, thus strengthening the positive association between EU penetration and subsequent non-EU entry. We found support for our hypotheses by analyzing international user-acquisition activities of the top 500 mobile game developers. Our findings contribute to international business research by showing that digital regulations can create new penetration opportunities and act as institutional catalysts that standardize digital firms’ cross-border expansion.

Are Auction-Based Promotions More Profitable for Short Video Platforms than Fixed Pricing?

2026-04-21T00:00:00+00:00

Information Systems Research
Short video platforms increasingly offer paid promotion tools that allow creators to boost the visibility of their content. These tools are typically priced through either fixed fees or auction-based bidding systems. We examine how these two promotion mechanisms affect platform revenue, creator incentives, and the engagement of promoted content. Our results show that auction-based promotion does not universally outperform fixed pricing. Auctions generate higher platform revenue only when competition for viewer attention is sufficiently intense—that is, when the number of creators relative to viewers is high. When competition among creators is limited, fixed pricing can produce greater revenue while maintaining stronger engagement. We also find that auctions attract more creators to promote their videos, but this broader participation can dilute engagement by allowing lower-appeal videos into the promotion queue. For creators, auctions tend to benefit those with very high-appeal or very low-appeal content, whereas those with moderately appealing content may be disadvantaged. These findings suggest that platforms should align their promotion policies with the maturity of their creator ecosystems, utilizing fixed pricing in early stages and shifting to auction mechanisms as competition intensifies. Ultimately, our framework empowers managers to dynamically adapt their pricing strategies as their user bases evolve.

Bargaining over Data and Analytics: Sellers, Buyers and Consultants

2026-04-21T00:00:00+00:00

Information Systems Research
Most firms routinely gather vast amounts of data as part of doing business. Monetizing this proprietary data is an increasingly attractive revenue stream for many of these firms. Two fundamental decisions need to be made when deciding to sell, the first involving a choice between selling exclusively to a single buyer or nonexclusively to many, and the second related to what exactly should be sold—just the data or a data product that bundles data with analytics services. As firms often resort to bargaining to arrive at sale agreements, we analyze these decisions through the lens of a bargaining framework. When the buyer needs help from a third-party consultant, she too needs to make a decision—between negotiating separately with the seller and the consultant, and with both of them simultaneously. We find that there are situations where sellers can benefit from bundling the data with analytics services even when their analytics capabilities are weak relative to those of external consultants. Simultaneous negotiations enable buyers to extract more of the consultant’s contribution, making them preferable to buyers when consultants add substantial value. Broadly, this study provides a road map for structuring contracts to firms considering the sale of their proprietary data.

The Market Consequences of Perceived Strategic Generosity: An Empirical Examination of NFT Charity Fundraisers

2026-04-21T00:00:00+00:00

Information Systems Research
NFT charity fundraisers have emerged as a powerful tool for rapid, scalable philanthropic mobilization, raising millions within minutes. However, the transparency of blockchain technology means that donors’ postpurchase behavior, particularly the decision to resell a charity NFT for profit, is visible to the entire marketplace. Our study reveals that this visibility carries significant economic consequences. Analyzing data from a major NFT charity fundraiser supporting Ukraine, combined with two controlled online experiments, we find that donors who quickly relist charity NFTs for resale experience an estimated 15.3% decline in the prices they can command for other NFTs in their portfolio. This penalty is driven by onlookers’ perception that the donor’s generosity was strategically motivated rather than genuine. Importantly, donors who hold their charity NFTs experience no such penalty and may even benefit. These findings carry direct implications for platform designers and fundraiser organizers: incorporating time-locked resale restrictions, reputation badges for sustained giving, or community governance features could discourage strategic flipping and protect the integrity of crypto-philanthropy. More broadly, our research highlights that in transparent digital environments, perceived motives matter as much as actions themselves, underscoring the need for donors and platforms alike to carefully manage the signals that charitable behavior sends.

The Effect of Primary Dealer Constraints on Intermediation in the Treasury Market

2026-04-22T00:00:00+00:00

The Review of Financial Studies
Using confidential microdata, we show that shocks to primary dealers’ constraints have significant effects on the U.S. Treasury securities market. We consider two types of constraints: the supplementary leverage ratio and trading desk value-at-risk constraints. In response to tighter constraints, dealers reduce their Treasury positions, triggering a reduction in aggregate turnover and an increase in dealer intermediation margin. Impaired intermediation also amplifies the yield response to net demand shifts and weakens Treasury auction outcomes. Our estimates suggest that the (shadow) cost of dealer constraints is as high as 9% of dealers’ profit margins. (JEL G10, G12, G18, G21)

Does the Financial Experience of SEC Regional Directors Impact SEC Investigations?

2026-04-22T00:00:00+00:00

Management Science
The U.S. Security and Exchange Commission’s (SEC’s) Division of Enforcement is frequently criticized for its ineffective oversight, and certain vocal critics attribute this to a lack of financial experience within the SEC. Using novel hand-collected data on SEC regional directors, I find that most of these senior SEC officials lack practical financial experience. I then use a staggered difference-in-differences research design and find that directors with financial experience open 62% more investigations (i.e., four to five additional investigations per office-year). This result is consistent with their financial experience impacting investigations. Additional analyses reveal that this effect is stronger when financial acumen likely matters more and that financial directors conduct more efficient and consequential investigations. Importantly, these results do not appear to be explained by the experience of other directors or by financial regional directors handling more cases. This study answers recent calls for more research on individual regulators and presents timely evidence as the SEC seeks to improve its investigation process. More generally, these findings provide new insights into the SEC’s oversight process and should be of interest to regulators and market participants concerned with the SEC’s policing of financial misreporting.This paper was accepted by Suraj Srinivasan, accounting.Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2024.05302 .

Revenue Management Under a Price Alert Mechanism

2026-04-22T00:00:00+00:00

Management Science
Many online platforms adopt a price alert mechanism to facilitate customers tracking price changes. This mechanism allows customers to register their valuation with the system if they find the price higher than their valuation. Once the price drops below the customers’ registered price, a message is sent to notify customers. This paper formulates the interaction between the seller and customers as a Markov decision process. We assume customers are patient and are willing to wait for K additional periods for the price to drop if the current price is high. We first analyze the model in which [Formula: see text] and find that the seller’s optimal policy has three properties: (i) the threshold property by which the seller uses a threshold to decide whether to accept or reject a registered price, (ii) the price-at-register property by which the seller sets the price at the customer’s registered level if the registered price exceeds the threshold, and (iii) the cyclic decreasing property by which the price trajectory under the optimal policy has a stochastic cyclic decreasing structure. Modified versions of these properties still hold for the general model in which K is large or when the waiting time is heterogeneous among customers. On the policy computation side, we propose a heuristic pricing policy based on the price-at-register property. Numerical results show that the policy achieves near-optimal performance on all cases tested. We also observe that the impact of the value of K on the optimal revenue is almost negligible in many cases, and this ensures that the policies derived under our model are robust to the misspecification of K. This policy can also be adapted to the model in which customer patience is different and achieves near-optimal performance. Lastly, we show the impact of the price alert mechanism on seller’s revenue, customer surplus, and social welfare.This paper was accepted by Omar Besbes, revenue management and market analytics.Funding: B. Jiang’s research is partially supported by the National Natural Science Foundation of China (NSFC) [Grants 72394364, 72171141, 72394363, and 72442013]. Z. Wang’s research is partially supported by the National Natural Science Foundation of China (NSFC) [Grants 72394361 and 72425013], the Guangdong Provincial Key Laboratory of Mathematical Foundations for Artificial Intelligence [2023B1212010001], and the 1+1+1 CUHK-CUHK(SZ)-GDSTC Joint Collaboration Fund [2025A0505000079].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05665 .

Investing in Lending Technology: IT Spending in Banking

2026-04-22T00:00:00+00:00

Management Science
Banks’ lending technology hinges on their handling of soft and hard information in dealing with different types of credit demand. Through assembling a novel data set on banks’ investment in information technologies (IT), this paper provides concrete empirical evidence on how banks adapt their lending technologies. We find investment in communication IT is associated with improving banks’ ability to produce and transmit soft information, whereas investment in software IT helps enhance banks’ hard information processing capacity. We exploit policies that affect geographic regions differentially to show causally that banks respond to an increased demand for small business credit (mortgage refinance) by increasing their spending on communication (software) IT spending. We also find that the entry of fintech induces commercial banks to increase their investment in IT—more so in the software IT category.This paper was accepted by Bo Becker, finance.Funding: Z. He acknowledges financial support from the John E. Jeuck Endowment at the University of Chicago Booth School of Business, as most of the work was done while he worked at the University of Chicago.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04608 .

Willful Ignorance and Moral Behavior

2026-04-22T00:00:00+00:00

Management Science
Consumers’ willful ignorance about the consequences of their actions may impede moral behavior. We test this concern in a real-world context based on a laboratory experiment and field data. We find that willful ignorance about farming practices increases consumption of meat from intensive farming, both in the laboratory and at university canteens. Individuals who prefer to avoid costless evidence are particularly responsive to it, yet their behavioral response vanishes within two weeks. Both findings demonstrate how difficult it is for organizations and governments to address willful ignorance through information interventions.This paper was accepted by Marie Claire Villeval, behavioral economics and decision analysis.Funding: This work was funded by the Austrian Science Fund [Grant 10.55776/F63] and the Deutsche Forschungsgemeinschaft [Grant CRC TR 224].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.01176 .

The Value of Logistic Flexibility in E-commerce

2026-04-22T00:00:00+00:00

Management Science
Shipping experience improvement has been an essential business strategy in e-commerce. Beyond investing directly in improving shipping speed, online retailers have recently expanded their focus on other shipping strategies, such as offering consumers the option to pick up orders at a local station. This paper uses the opening of hundreds of such pickup stations as a natural experiment to study the impact of these stations on consumers. We find that the introduction of pickup stations increased total sales by [Formula: see text]. In contrast with past literature, we show that shipping time reduction is not the driving factor in the impact of pickup stations. Yet, the logistic flexibility introduced by pickup stations explains the sales impact. To explicitly examine how logistic flexibility affects consumers’ decisions on purchases, we develop and estimate a structural model of consumer choice. In our model, consumers value two types of logistics flexibility—the flexibility to pick up their items at their preferred times, referred to as the value of preferred time flexibility, and the flexibility to delay pickup decisions to the last moment, referred to as the value of last-minute choice flexibility. We show that the value of preferred time flexibility accounts for [Formula: see text] of the impact on sales, whereas the value of last-minute choice flexibility accounts for the remaining [Formula: see text]. Using our estimated model, we develop a counterfactual strategy in building pickup stations that could achieve the sales lift with [Formula: see text]–[Formula: see text] fewer stations. Last but not least, using our estimated time flexibility, we also develop a novel shipping strategy without pickup stations that could improve sales by [Formula: see text]. Our estimates suggest that our counterfactual logistic strategies could increase consumer welfare by [Formula: see text]–[Formula: see text].This paper was accepted by Elena Katok, operations management.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00163 .

Distributionally Robust Group Testing with Correlation Information

2026-04-22T00:00:00+00:00

Management Science
Motivated by the need for more efficient and reliable methods of group testing during widespread infectious outbreaks, this paper introduces a novel operational improvement to the widely used Dorfman’s group testing procedure, where a single test is conducted on the pooled sample, followed by individual testing of positive pools. Our method minimizes a weighted sum of testing volume and misclassifications, taking prevalence rates and interindividual Pearson correlation coefficients as inputs, and employs a distributionally robust optimization (DRO) framework to address the ambiguity in the joint infection distribution induced by these correlations. We study two correlation structures within a population. In single-cluster cases, where all subject pairs share equal correlation, we connect our analysis to Nash equilibrium principles and show that higher correlation favors larger testing groups, whereas higher prevalence often calls for individual testing. In multicluster cases, where the population consists of several intracorrelated but interindependent clusters, we highlight the effectiveness of mixed-cluster testing strategies, particularly under low prevalence and correlation. This is a notable addition to the prevailing view that advocates pooling correlated individuals. We provide polynomial-time solutions for both correlation structures and demonstrate the trade-offs and benefits of our DRO approach through a thorough comparison with stochastic alternatives. Using a case study based on a real-world COVID-19 data set, we show that our proposed pooling strategy can save up to 0.1 tests per individual compared with an independence-based pooling scheme and up to 0.5 tests per individual compared with a heuristic pooling strategy implemented in the studied region.This paper was accepted by Jeannette Song, operations management.Funding: This research was supported by the National Natural Science Foundation of China [Grants 72293582 and 72422005], the Hong Kong Research Grants Council [Collaborative Research Fund C6103-20GF, General Research Fund 14210523, 16209923, and 16213424], and the Natural Sciences and Engineering Research Council of Canada [Grants RGPIN-2024-05910 and DGECR-2024-00094].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.04308 .

Generative AI in Capital Markets: Information Production, Dissemination, and Processing

2026-04-22T00:00:00+00:00

Journal of Accounting Research
We synthesize evidence from six papers presented at the 2025Journal of Accounting ResearchConference on how generative artificial intelligence (GenAI) is reshaping capital‐market information flows. Our discussion is organized around an economic framework with three layers: information production by firms and accounting professionals, information dissemination through intermediaries, and information processing by investors. Across these layers, the conference papers show that GenAI can lower preparation costs, improve intermediary productivity, and reduce investors’ processing costs. At the same time, they point to a common constraint: whether GenAI improves the information environment depends critically on information verification costs. We also highlight gaps in current evidence and outline future research opportunities within and across the three layers.

AI Democratization and Trading Inequality

2026-04-22T00:00:00+00:00

Journal of Accounting Research
We are among the first to investigate how Generative AI (GenAI) shapes investors' trading activities. Using an AI‐sentiment measure extracted from earnings‐call transcripts to proxy for textual signals, we find notable shifts in trading behaviors around earnings calls. Before the wide deployment of ChatGPT, short selling was aligned with AI‐sentiment, whereas retail trading was not. However, following ChatGPT's deployment, the alignment of retail traders with AI‐sentiment significantly increases, while the alignment of short sellers weakens, albeit insignificantly. Stocks with higher information processing costs exhibit a more pronounced increase in retail trading alignment, scenarios where retail investors are likely to benefit more from AI. Using retail‐AI alignment as a proxy for the extent to which retail investors trade based on AI signals, we show that information asymmetry declines and retail investors' trading profitability improves, whereas short sale profitability declines in high retail‐AI alignment stocks. Exogenous outages reduce the alignment between retail trading and AI‐sentiment, allowing us to draw causal inferences. Collectively, this study suggests that AI is a promising technology for narrowing the information gap in the trading of complex textual financial disclosures between investor classes with clear disparities in the ability to process public disclosures.

From Lexicons to Large Language Models: A Holistic Evaluation of Psychometric Text Analysis in Social Science Research

2026-04-22T00:00:00+00:00

Information Systems Research
Research Spotlight AbstractExtracting psychological insights from text is vital for modern analytics, yet organizations often rely on analysis tools that are either biased and simplistic or prohibitively expensive to build. Our research demonstrates that Large Language Models (LLMs) offer a superior alternative. They match the accuracy of specialized artificial intelligence (AI), while significantly reducing costs and technical barriers. Crucially for policy considerations, we find LLMs are statistically fairer than traditional methods. In our tests, they reduced racial and gender bias by up to 60%. Beyond assessing performance, we introduce a practical technique called “cognitive-affective prompting.” By instructing the AI to adopt specific human strengths, such as using “superior reasoning” for complex tasks or “emotional intelligence” for sentiment analysis, practitioners can boost accuracy by over 10%. To facilitate adoption, we provide a user-friendly “cookbook” to help nonexperts apply these findings immediately. For policymakers and business leaders, this research validates LLMs as a robust, consistent, and equitable standard for analyzing human behavior at scale.

Looking Back and Looking Forward: Thirty Years of Evidence on Strategic HRM Systems and Performance (1995–2025)

2026-04-22T00:00:00+00:00

Human Resource Management
Research on how to leverage high‐performance work systems (HPWS) and other strategic human resource management (HRM) systems to improve performance outcomes has long been a cornerstone of the HRM discipline. This study offers a comprehensive mapping of the field through bibliometric analysis and a thematic synthesis of 3503 peer‐reviewed articles published across 156 leading journals from 1995 to 2025. By revisiting the HRM‐performance relationship and tracing the evolving trajectories of scholarly inquiry, the review identifies four major thematic domains: (1) configurational HRM architectures, (2) multilevel HRM‐performance impacts, (3) “black box” mechanisms that mediate and moderate the HRM‐performance link, and (4) emerging topics in HRM systems in responding to crises and socio‐technological changes. The review finds evidence for complex transmitting patterns through which HRM systems improve performance, characterized by a horizontally interwoven and vertically multi‐level nature. The study addresses longstanding conceptual fragmentation by clarifying the structure and theorization of HRM systems and contributes a synthesized framework to guide future research. It also highlights promising but underexplored avenues, such as the role of algorithmic HRM, methodological pluralism, and configurational logics, in advancing the understanding of HRM‐performance dynamics. Practical implications are elaborated, translating theoretical findings into actionable guidance for practitioners.

ETP at 50: The Past, Present, and Future of Entrepreneurship Research

2026-04-22T00:00:00+00:00

Entrepreneurship Theory and Practice
Entrepreneurship scholars have over-invested in borrowed theories and under-invested in the evidence needed to test them—or to build something better. This editorial, written on the occasion ofETP’s 15th anniversary and my departure as Editor-in-Chief, argues for a rebalancing around the research question-design-data trio: important questions rooted in phenomena, designs matched to claims, and serious investment in data quality. The field’s greatest strength has always been its willingness to ask important questions, and its most enduring theoretical contributions come from developing home-grown theories addressing these questions rather than importing frameworks from outside. AI makes this rebalancing urgent. When the front end of a paper can be generated by a machine, the distinctive value of scholarship must reside in the question, the design, and the evidence. The field’s future depends on producing work that reveals how entrepreneurship actually works, and on exporting those insights rather than merely importing ideas from other disciplines.

Institutional Logics and Relational Inequality in UK Surgery: Demographic Dominance and the Uneven Governance of Careers

2026-04-23T00:00:00+00:00

Journal of Management Studies
Persistent gender and racial inequalities within elite professions remain inadequately explained by accounts focusing exclusively on either intra‐organizational processes or field‐level institutional dynamics. Relational inequality theory (RIT) provides a powerful account of closure within organizations but offers limited specification of how institutional environments shape variation in inequality outcomes. We bring RIT into dialogue with the institutional logics perspective (ILP), adopting a microfoundational lens to examine how demographic dominance and governance structures jointly shape career inequalities. Using longitudinal data on 3402 junior surgeons across 212 NHS trusts in England, we analyse promotion and exit outcomes across professional subspecialties and employing organizations. Intersectional inequalities are systematically associated with a dominant professional logic as captured by White male density (WMD). Higher WMD amplifies in‐group advantages and out‐group penalties. However, these effects vary across institutional contexts. Professional subspecialties exhibit stronger and more coherent dominance effects, whereas governance‐intensive trusts partially attenuate WMD‐associated advantages, particularly in formalized promotion processes, while exit patterns remain less responsive to governance constraints. In doing so, we clarify how the strength of relational inequality regimes varies systematically across institutional contexts and show that demographic dominance and governance centrality jointly shape when and where intersectional inequalities intensify or recede.

Think Before You Speak: Sensemaking and Sensegiving in New CEOs’ Strategic Communications with the Capital Market

2026-04-23T00:00:00+00:00

Journal of Management
We extend research on strategic communication by introducing a theoretical model of how newly appointed CEOs engage in sensemaking and sensegiving with the capital market through their first communication of strategic priorities. We conceptualize strategic topic novelty, the distinctiveness of the topics emphasized relative to the predecessors’, as an observable dimension of new CEOs’ priorities that reflects how they reconcile their desire to establish a unique vision with the need to legitimize their appointment. Our theory suggests that new CEOs draw on situational cues, particularly the nature of the succession (dismissal vs. routine) and the initial market reaction to their appointment, when determining how much novelty to introduce. Specifically, we propose that new CEOs communicate higher strategic topic novelty following dismissals and that this relationship may be strengthened by positive market reactions to their appointment and weakened by negative market responses. We further expect that the capital market responds more favorably to strategic topic novelty following dismissals. Applying textual analysis of new CEOs’ communication in earnings calls from 2004 to 2018, we find a positive relationship between dismissals and strategic topic novelty, which is weaker for more negative market reactions to the new CEO’s announcement. We also find more positive capital market reactions to strategic topic novelty following dismissals. Our findings advance understanding of how new CEOs approach their role by integrating sensemaking with sensegiving in research on CEO communication and highlight how new CEOs asymmetrically adjust novelty in response to positive versus negative market reactions.

Bias in, symbolic compliance out? GPT 's reliance on gender and race in strategic evaluations

2026-04-24T00:00:00+00:00

Strategic Management Journal
Organizations are increasingly using large language models (LLMs) to support strategic evaluations. We examine whether and how these systems rely on gender and race. We asked GPT to evaluate identical startup pitches varying only the founder's name, shaping gender and race perceptions. Across 26,000 evaluations, GPT did not systematically assign lower scores to underrepresented minorities but avoided ranking them last without increasing winning likelihoods. To explain these patterns, we conducted “Second Opinion” experiments where GPT evaluated pitches alongside inputs simulating human bias. GPT more readily corrected explicit, identity‐based bias than bias framed as neutral business critiques, with corrections limited in magnitude. We theorize these findings reflectsymbolic compliance: LLMs suppress overt discrimination without substantively altering evaluative logic, allowing inequality to persist in AI‐supported strategic evaluations.Managerial summaryLarge language models (LLMs), like OpenAI's ChatGPT, are increasingly used in strategic evaluations (e.g., hiring, pitches). We examine whether and how these models exhibit gender and racial biases in their evaluations of startup pitches, where we only varied founder names (shaping gender and race perceptions). Across multiple experiments, we find that GPT evaluators did not systematically assign lower scores to underrepresented minorities, primarily by reducing their likelihood of being ranked last. However, this behavior reflects a symbolic effort to avoid overt discrimination rather than a deeper fairness commitment. While LLMs may not reproduce historical and societal biases in overt form, their ability to correct them remains limited. These results highlight the need for implementing bias mitigation measures before integrating LLMs into high‐stakes strategic evaluation processes.

Abortion restriction laws and mobility of scientists

2026-04-24T00:00:00+00:00

Strategic Management Journal
We track the enactment of targeted regulation of abortion providers (TRAP) laws in the United States and analyze 4.98 million person‐year mobility records for 535,568 biomedical scientists from 1990 to 2018. Our estimations reveal a 0.8–1.6 percentage‐point increase in scientists' relocation probability after states enacted abortion‐restrictive laws, with substantially stronger effects among junior scientists (1.6–3.9 percentage points). Anti‐abortion states also became less likely to be chosen as relocation destinations, particularly by higher‐quality scientists. These responses appear driven by ideological misalignment and research‐related concerns in fields affected by abortion‐related regulation. We further find that states that have adopted TRAP laws experienced declines in scientific research quality, federal research funding, and patenting in relevant technological fields and among local firms.Managerial SummarySocial policies influence the location choices of creative talent, with further implications for organizational and regional innovations. Research scientists are an important part of the regional innovation ecosystem, whose work is intricately related to innovation activities in firms. In a large‐scale study of 4.98 million records of half a million biomedical scientists from 1990 to 2018, we reveal that restrictive policies, such as restrictions on abortion providers, deter high‐quality scientific talent from relocating to certain regions. Our analysis highlights that ideological (mis)alignment and research‐opportunity‐related concerns, rather than practical concerns like access to abortion services, heighten the effect of abortion‐restriction laws on the observed mobility patterns, underscoring the broader implications of policy choices in the sociopolitical environment on where scientific talent chooses to live and work.

Learning to innovate: How and when firms transform intellectual capital into exploratory and exploitative innovation

2026-04-24T00:00:00+00:00

Strategic Entrepreneurship Journal
Corporate entrepreneurship (CE) requires firms to pursue both exploratory and exploitative innovation, yet limited research explains how intellectual capital (IC) is translated into these distinct outcomes. We develop a contingency model that specifies how and when IC drives exploration and exploitation. We theorize that a firm's capacity for learning and transformation (CLT) functions as a firm‐level learning and transformation capability through which IC can be translated into either exploratory or exploitative innovation. Knowledge breadth strengthens the indirect effect of IC on exploratory innovation via CLT, whereas knowledge depth amplifies the indirect effect on exploitative innovation. We test the model in two complementary field studies. Study 1 employs a time‐lagged design with objective archival data, and Study 2 replicates the findings using survey data. Results consistently support the proposed theoretical model.Managerial SummaryFirms operating in fast‐changing and uncertain environments often struggle to balance developing new products with improving existing ones. Our study shows that simply having strong knowledge resources is not enough. What matters is how effectively firms learn from and use that knowledge. We find that firms perform better when they build strong learning capabilities that help them adapt, recombine, and apply knowledge over time. Importantly, the type of knowledge a firm holds shapes this process: broad knowledge supports new product development, while deep, specialized knowledge strengthens improvements to existing products. For managers, this means focusing not only on acquiring knowledge but also on building systems and practices that continuously translate knowledge into action and innovation.

Broken Relationships: Derisking by Correspondent Banks and International Trade

2026-04-24T00:00:00+00:00

The Review of Financial Studies
We study how terminated correspondent banking relationships affect international trade. Drawing on firm-level export data from emerging Europe, we show that when local banks lose access to correspondent services, their corporate clients, especially small- and medium-sized enterprises, experience significant export declines. Firms only partially offset lost exports with higher domestic sales, resulting in lower total revenues and employment. Other firms cease operations entirely. These firm-level impacts aggregate to lower product-level exports from countries more exposed to correspondent bank retrenchment. (JEL F14, F15, F36, G21, G28, L14)

The Effects of Mandatory Profit-Sharing on Workers and Firms: Evidence from France

2026-04-24T00:00:00+00:00

The Quarterly Journal of Economics
Since 1967, all French firms with more than 100 employees have been required to share a fraction of their excess profits with their employees. Through this scheme, firms with excess profits distribute, on average, 10.5% of their pre-tax income to workers. In 1990, the eligibility threshold was reduced to 50 employees. We exploit this regulatory change to identify the effects of mandated profit-sharing on firms and their employees. The cost of mandated profit-sharing for firms is evident in the significant bunching at the 100-employee threshold observed prior to the reform, which completely disappears post-reform. Using a difference-in-differences strategy, we find that, at the firm level, mandated profit-sharing (a) increases the labor share by 1.8 percentage points, (b) reduces the profit share by 1.4 percentage points, and (c) has small to non-existent effects on investment and productivity. At the employee level, mandated profit-sharing increases lower-skilled workers’ total compensation and leaves high-skilled workers’ total compensation unchanged. Overall, mandated profit-sharing redistributes excess profits to lower-skilled workers in the firm without generating significant distortions or productivity effects.

EXPRESS: Online Traffic Games: Should Firms Compete on Website Speed or Website Capacity?

2026-04-24T00:00:00+00:00

Production and Operations Management
In today’s fast-paced digital world, consumers demand instant access to online content and are intolerant of delays, making website speed a key competitive advantage in attracting web traffic. Google’s Speed Update and Core Web Vitals have further emphasized the significance of website speed in web traffic competition. This study examines how firms strategically compete for web traffic by managing website speed, focusing specifically on two distinct strategies: response-based and capacity-based. Under response-based competition, firms first set their desired website speed (or equivalently, website response time), subsequently determining the necessary website capacity. In contrast, in capacity-based competition, firms initially select the website capacity level, which in turn determines the website response time.We analyze a duopoly scenario in which two firms compete for web traffic. Although website speed and capacity are functionally related, surprisingly, firms sometimes compete more aggressively under response-based competition. Interestingly, the aggression of response-based competition can sometimes increase firms’ profits. We also show that when firms freely choose the decision process, firms sometimes engage in a mode of competition in equilibrium, which yields a lower profit for the capacity provider (e.g., computing capacity provider) than the alternative mode.We further show how the cloud provider can increase profit by strategically inducing firms to engage in a preferred mode of competition. This is achieved by lowering the unit price of renting capacity related to that mode of competition. This strategic price reduction can lead to faster websites for consumers, an increase in the provider’s revenue, and consequently an increase in the cloud provider’s profit under a cost-efficiency condition. The profit of firms can sometimes increase too, implying a win-win-win for all the parties, namely, firms, consumers, and the provider.

Crowding-Out or Crowding-In? The Effects of Idea Evaluation on Evaluators’ Idea Generation

2026-04-24T00:00:00+00:00

Management Science
Organizations rely on their employees to produce many high-quality ideas for the improvement of products, processes, and strategies. Evaluators such as managers and technical experts need to not only assess these ideas but also face expectations to contribute ideas of their own. We investigate this task duality by asking how idea evaluation activities affect evaluators’ ideation performance. Although much of the creativity and innovation literature points to a crowding-out effect, some theoretical arguments support idea crowding-in. Using data from a multinational firm’s idea management system and a difference-in-differences framework, we find robust evidence of substantial idea crowding-in: Evaluators’ likelihood of idea generation increases by 205% on the day that they evaluate ideas and remains elevated for the following two weeks. Extensive analyses support knowledge recombination as the key mechanism: By exposing evaluators to unfamiliar knowledge, idea evaluation creates new opportunities for recombination and idea generation. The ideas that evaluators generate postevaluation are 19% more valuable (but not more novel) than those they generate outside the postevaluation window. We contribute to innovation scholarship by identifying a hitherto overlooked effect of idea evaluation: triggering idea generation among evaluators.This paper was accepted by Karan Girotra, operations management.Funding: J. Schnier and C. Raasch acknowledge funding from the Deutsche Forschungsgemeinschaft [Grant RA 1798/4-1]. T. Schweisfurth acknowledges funding from the Tempowerk Technology Center Hamburg.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03335 .

Service-Oriented Considerate Routing: Data, Predictions, and Robust Decisions

2026-04-24T00:00:00+00:00

Management Science
In this research, we focus on improving service-oriented routing by addressing the nuanced challenge of punctuality through the consideration of couriers’ ability to ensure on-time deliveries. We utilize a comprehensive real-world data set from a cold chain logistics firm for analysis. Our empirical investigation indicates that relying solely on travel distance is inadequate for accurate delivery time prediction. We highlight critical elements, including couriers’ fixed effects and workload, as key covariates to improve prediction performance. Distinguishing our work from existing literature, we integrate couriers’ workload and location familiarity into our service-oriented routing model to enhance predictions of delivery times. We introduce the courier-assigned location mismatch (CALM) metric as a less intrusive approach to incorporating couriers’ location familiarity into their delivery efficiency. We propose the novel service-oriented considerate routing (SOCR) model; by minimizing the CALM metric, couriers are assigned routes within familiar territories to the extent possible within the total routing distance constraint. The considerate routing strategies could potentially reduce the stress couriers face when delivering in unfamiliar areas. Additionally, we develop the connection of the SOCR model with a robust satisficing approach. This strategy guarantees timely deliveries by effectively mitigating the effects of predictive inaccuracies and potential model misspecifications. To solve the SOCR model, we apply Benders decomposition for an exact solution and tabu search for a heuristic approach, demonstrating their effectiveness and superior out-of-sample performance. Notably, our heuristic solutions significantly outperform exact solutions of classical vehicle routing problems with deadlines, resulting in substantial improvements in timely delivery performance.This paper was accepted by Wolfram Wiesemann, data science.Funding: Y. Zhao and M. Sim were partially supported by the Ministry of Education, Singapore, under its 2019 Academic Research Fund Tier 3 [Grant MOE-2019-T3-1-010]. Z. Luo was supported by the National Natural Science Foundation of China [Grants 72222011, 72171112, and 72442006]. C. Chen was supported in part by the National Natural Science Foundation of China [Grants 72394363, 12431011, and 72394364].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05530 .

Forecasting and Managing Correlation Risks

2026-04-24T00:00:00+00:00

Management Science
We propose a novel and easy-to-implement framework for forecasting time-varying correlations based on a large set of salient realized correlation features and the sparsity-encouraging Least Absolute Shrinkage and Selection Operator technique. Considering the universe of S&P 500 stocks, we find that the new approach manifests in statistically superior out-of-sample forecasts compared with commonly used procedures. We further demonstrate how the forecasts translate into significant economic gains in the form of higher pairs trading profits, better equity premium predictions, more accurate portfolio risk targeting, and superior overall risk control and minimization.This paper was accepted by Kay Giesecke, finance.Funding: S. Z. Li received financial support from the Rutgers Business School Dean’s Research Seed Fund.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.08294 .

EXPRESS: Beyond Visibility: The Disability Inclusion Effect in Advertising

2026-04-24T00:00:00+00:00

Journal of Marketing
People with disabilities are among the most stigmatized groups in society, and the most underrepresented in advertising. We investigate advertising practices by which brands can include people with disabilities in ways that go beyond mere visibility. Across nine preregistered studies involving both hedonic and functional goods and services, we show a robust positive effect of featuring people with disabilities in advertisements on consumers’ attitudes toward the ad, brand, and product. Thisdisability inclusion effectgeneralizes broadly across products, endorsers (e.g., customers, models), disabilities (both visible and invisible), and consumer segments (people with and without disabilities). It arises because the brand demonstrates its support for the societal integration of people with disabilities. Accordingly, the effect arises whether the brand includes people with disabilities voluntarily or to comply with industry regulation, because both actions can produce the same perceived outcome—meaningful, concrete support of people with disabilities. On the contrary, the effect disappears when a brand’s portrayal emphasizes vulnerability or impairment rather than agency and social inclusion, or the brand conspicuously highlights the model’s disability in the ad itself in a tokenizing manner. Collectively, these studies reveal how managers can support people with disabilities and earn consumers’ patronage without risking their backlash.

Measuring Stakeholder Theory Mindsets: Development and Validation of a Measurement Scale

2026-04-24T00:00:00+00:00

Journal of Management
For four decades, stakeholder theory has played a key role in many research fields, from strategy to business ethics. More recent developments in the field of behavioral stakeholder theory highlight the importance of individual managers and their mindsets. The role of stakeholder theory mindsets of managers, however, has not been empirically investigated. Despite the prominence of stakeholder theory in management research, no measurement scale exists at the level of individuals that would allow scholars to assess the degree to which a manager agrees with the key assumptions of stakeholder theory. This research develops a scale to measure managers’ stakeholder theory mindsets. To do so, we followed scholarly best practices: First, we generated items based on existing stakeholder theory literature and then had expert stakeholder scholars evaluate them. This step was followed by two independent studies for exploratory and confirmatory factor analysis and a nomological network study. The actual scale development was complemented by an additional study, which tests the predictive power of the stakeholder theory mindset scale and demonstrates its incremental validity. As a result, we propose a validated measurement scale of stakeholder theory mindsets, consisting of 18 items that load on four factors corresponding to the four main assumptions in stakeholder theory: value creation, the integration thesis, jointness of stakeholder interests, and the responsibility principle. We draw out how future research can be inspired by using this scale, which inter alia allows testing antecedents of stakeholder theory mindsets, as well as consequences for managerial decision-making.

Identifying and Using Nonlinear and Interactive Control Variables

2026-04-24T00:00:00+00:00

Journal of Management
Nonlinear and interactive effects (NIEs) are central to management theory. Consequently, although researchers commonly include linear control variables, the omission of nonlinear and interactive control variables (NICs) can lead to incorrect conclusions because the omission can distort statistical tests and effect-size estimates. We reviewed 548 quantitative articles published between 2021 and 2023 in Academy of Management Journal, Journal of Management, and Strategic Management Journal. We discovered that about 73% tested for NIEs, but only 3% included NICs. Also, by reanalyzing a published study, we demonstrate that the exclusion of theoretically relevant NICs can reverse substantive conclusions, highlighting the threat such omissions pose to theory advancement. To address this methodological challenge, we introduce a five-step guide for systematically identifying, evaluating, and integrating NICs into research involving NIEs. The guide offers a structured, theory-driven approach that uses associations among model variables and their linear controls to determine which NICs are critical for unbiased estimation of NIEs. We also explain how to avoid over-control, maintain statistical efficiency, and transparently manage omitted NICs. Applying the five-step approach strengthens the validity of causal inference in studies of nonlinear and interactive effects and enhances the robustness of empirical results. In addition to improving estimation accuracy, the systematic and theory-based inclusion of NICs advances theory development by clarifying boundary conditions, distinguishing competing explanations, and enabling the cumulative integration of empirical results.

How Boards Use Competitor CEO Awards to Interpret Firm Performance in CEO Dismissal Decisions

2026-04-24T00:00:00+00:00

Journal of Management
To what extent do boards integrate external comparative signals when making CEO dismissal decisions? Drawing on the board information processing perspective, we propose that competitor CEO awards shape the weight boards assign to firm financial performance in dismissal evaluations. Specifically, when competitor CEOs receive prestigious recognition, boards are more likely to interpret firm underperformance as evidence of managerial inadequacy, thereby increasing the likelihood of CEO dismissal. In contrast, when firm performance exceeds that of industry peers, competitor awards amplify positive evaluations of the incumbent CEO’s managerial competence, reducing dismissal likelihood. We further identify three governance-related boundary conditions, i.e., CEO compensation structure, board busyness, and board–CEO demographic similarity, that condition these effects by shaping directors’ evaluative expectations, available attentional resources, and relational biases. Using a longitudinal sample of U.S. publicly traded firms from 2006 to 2020, we find consistent support for our theoretical predictions. Our study contributes to the corporate governance literature by demonstrating the extent to which boards embed firm performance evaluations within a broader comparative informational context. In doing so, we also uncover indirect competitive spillover effects of executive recognition, showing that CEO awards influence not only recipients’ outcomes but also governance decisions within rival firms.

What If We Took Entrepreneurship Practice Seriously? Prescriptive Theorizing From Explanatory Models for Practical Implications

2026-04-25T00:00:00+00:00

Entrepreneurship Theory and Practice
Just because we undertake value-neutral research to explain an entrepreneurial phenomenon does not mean we cannot extend our work through engaging values to prescribe what entrepreneurs (and/or other focal actors) should do. In this editorial, we illustrate how scholars can generate and offer prescriptive theorizing. Specifically, scholars can generate practical implications by (a) focusing on a phenomenon-based problem; (b) identifying focal actors and values; (c) defining desired outcomes; (d) developing an implementation roadmap; (e) thinking about reflexivity and boundaries; and (f) generating testable prescriptions. We offer additional considerations about when and for whom this prescriptive theorizing is most appropriate.

EXPRESS: Event ticket pricing with capacity constraints and price restrictions

2026-04-26T00:00:00+00:00

Production and Operations Management
Motivated by ticket pricing challenges facing live event managers, we study how to maximize the revenue when setting prices for multiple ticket categories with interdependent demand, realistic capacity constraints, and pricing restrictions. We define this decision problem as theEvent Ticket Pricing(ETP) problem and formulate it as a constrained nonlinear optimization model. To examine how the nature of product differentiation (i.e., differentiation across ticket categories) affects seat portfolio pricing and revenue outcomes, we analyze the ETP problem under two demand specifications: vertically and horizontally differentiated ticket categories. For each case, we isolate the role of different constraints by developing and solving a sequence of problems with progressively added restrictions. This approach enables us to identify structural properties that either fully characterize the optimal solution or guide the development of efficient algorithms. Under vertical differentiation, we prove that the optimal solution has asold-out threshold structure, with only highquality categories sold out. The treatment of partially sold products depends on the active constraints. Sales vanish under capacity constraints alone but become positive once pricing restrictions are introduced, producing solutions distinct from the unconstrained benchmark. Under horizontal differentiation, the threshold structure persists, but the addition of constraints breaks the well-known “equal markup” rule, yielding prices that are non-increasing in quality. Finally, we study how flexible adjustments in seat capacities reshape optimal outcomes. These results underscore the importance of incorporating realistic constraints and offer practical guidance for live event planners.

EXPRESS: Merchants of Vulnerabilities: How Bug Bounty Programs Benefit Software Vendors

2026-04-26T00:00:00+00:00

Production and Operations Management
We study how bug bounty programs shape software vendors’ security and release choices. Vendors invest in internal assurance before release to reduce residual vulnerabilities, and after launch they must manage vulnerability discovery, disclosure, and remediation. We develop a game-theoretic model in which a vendor chooses release timing and severity-contingent bounties, anticipating effort by ethical and malicious hackers in a winner-take-all discovery race. The model highlights two linked mechanisms: an incentive channel that shifts first discovery of severe vulnerabilities away from malicious exploitation and toward ethical reporting, and a governance channel in which coordinated disclosure changes how vulnerability information is managed while remediation is underway. We derive closed-form optimal bounties and characterize a feasibility region that sustains positive bounties and interior success probabilities. Within this region, a bug bounty program strictly increases the vendor’s expected profit by reallocating first-discovery probability on severe vulnerabilities from malicious to ethical hackers and by converting part of severe-loss exposure into bounded, pay-for-results expenditures. For private programs, we also solve for the optimal invited set of ethical hackers and show that this optimal set is strictly smaller than the expected number of malicious attackers. Higher bounties raise ethical hackers’ effort and first-discovery probabilities but also increase program cost, and they interact with reputational (non-monetary) incentives. Finally, in the baseline model, BBP adoption conditionally reduces the marginal value of additional pre-release delay and therefore conditionally implies earlier release relative to the no-BBP benchmark. This timing result is a within-model conditional implication; its practical relevance depends on operational readiness, triage throughput, and the vendor’s ability to validate and safely deploy fixes once a valid report arrives. Managerially, BBPs should be viewed as a post-release governance layer that complements strong internal assurance rather than as a substitute for it. Policymakers can support responsible use of BBPs by encouraging timely remediation, transparent post-patch disclosure, and reporting standards that reduce information asymmetry and triage frictions.

EXPRESS: Research Opportunities in Disaster Warning Signals from an Operations Management Perspective

2026-04-26T00:00:00+00:00

Production and Operations Management
Effectively utilization of disaster warning signals is crucial for mitigating impacts and enhancing operational resilience in disaster management. Although an emerging area of scholarly interest, the literature remains fragmented and lacking a unifying framework to guide research and practice. To consolidate knowledge and direct future research, this study conducts a systematic review of the literature on disaster warning signal research published in leading journals in operations management, management science, operations research, and related supply chain and logistics. Building upon the classic communication model proposed by Shannon, this study develops a conceptual framework for systematically classifying the relevant literature according to three dimensions of a warning signal: (1) signal type (natural, engineering, behavioral, informational, composite), (2) signal transmission (source, channel, receiver) and (3) signal purpose (directing the response of the authority, guiding the protection of the public). We then cross-tabulate this framework with the disaster management domain (e.g., disaster phase, type, and function) and the data domain (e.g., data type, analytics techniques). By synthesizing academic contributions with practical challenges, we articulate the specific value that operations management research on warning signals offers to disaster management practice. Finally, we propose a structured agenda for future research focused on the intersections of signal, disaster, and data domains.

EXPRESS: Whether, When, How, and Why Sales Managers Should Be Involved in Sales Teams

2026-04-26T00:00:00+00:00

Journal of Marketing
This manuscript examineswhether,when,how, andwhysales managers should get involved in customer exchanges as members of sales teams. It does so by drawing on the literature on status and deference in teams to advance novel hypotheses and testing them across seven main studies. Results of Study 1—based on a multisource dataset involving over 5.5 million business-to-consumer (B2C) exchanges—indicate that a sales manager’s involvement as a member of a sales team enhances the team’s performance (whether). These performance-enhancing effects are stronger for new customers relative to returning customers (when). To addresshowmanagers should engage when involved in sales teams, the manuscript introduces the concept ofselling position primacyand demonstrates that performance is enhanced when sales managers take on a secondary, rather than a primary, selling position within the team. Experimental results across several settings (e.g., automotive services, retail clothing, and kitchen showroom) reinforce these findings and further identify customer-perceived team status and customer orientation as the mechanisms explainingwhysales manager involvement and selling position primacy impact sales performance.

Hypothesis-testing research in international business: progress, pitfalls, and a way forward

2026-04-26T00:00:00+00:00

Journal of International Business Studies
Building on Meyer, van Witteloostuijn, and Beugelsdijk’s (2017) editorial on best practices for conducting and reporting hypothesis-testing research in IB, we examine the extent to which their guidelines—and related recommendations by Hahn and Ang (2017)—have been adopted in leading IB journals. We analyze all null-hypothesis significance testing-based articles published in theJournal of International Business Studiesand theJournal of World Businessbetween 2012 and 2024, using fine-grained inferential trend analyses of methodological and reporting standards alongside state-of-the-art tests for p-hacking and publication bias. Our results indicate meaningful progress in several areas, including greater methodological rigor and transparency. However, adoption remains uneven and has plateaued for several practices. Persistent shortcomings include limited reporting of standard errors, confidence intervals, and effect sizes, incomplete disclosure of robustness analyses and outlier treatment, and the continued predominance of confirmed hypotheses. Moreover, we find no evidence that p-hacking or publication bias have declined over time. Drawing on these results, we outline actionable recommendations for advancing methodological and reporting standards in IB by (1) enhancing transparent reporting, (2) providing convincing evidence, and (3) reporting and probing null and negative results. Overall, our study offers a roadmap for strengthening research credibility in IB.

Stakeholder synergies in acquisitions

2026-04-27T00:00:00+00:00

Strategic Management Journal
Acquisitions can create synergies by combining an acquirer's and a target's pre‐existing relationships with nonmarket stakeholders. We introduce the “reset effect” as a novel mechanism that occurs when a firm with cooperative stakeholder relationships combines with a firm that has conflictual relationships, prompting the affected stakeholders to re‐evaluate their pre‐acquisition strategies. We argue that post‐acquisition conflict with nonmarket stakeholders will decline when the cooperative and conflictual stakeholders brought together by an acquisition are aligned on one or more of the three elements that characterize stakeholder fields: (1) issues stakeholders care about, (2) relationships between stakeholders, and (3) preferences for how issues should be addressed. We find support for these arguments by studying changes in Fortune 500 firms' conflict with environmental movement organizations after acquisitions.Managerial SummaryAcquisitions can create synergies by resetting a firm's relationships with external stakeholders. Studying 25 years of Fortune 500 acquisitions and environmental stakeholder interactions, we find that acquisitions can reduce stakeholder conflict when one firm's cooperative stakeholder relationships complement the other firm's conflictual ones. Complementary relationships exist when cooperative and conflictual stakeholders are aligned on issues or have pre‐existing relationships with one another. Simply combining conflictual‐cooperative stakeholder relationships is not enough, however, and post‐acquisition conflict can increase when stakeholder groups are divided over how issues should be addressed. These findings can help managers understand when an acquisition will ease or exacerbate external conflict with stakeholders.

Local regulatory anticipation and GHG emissions

2026-04-27T00:00:00+00:00

Strategic Management Journal
Regulatory anticipation is a nonmarket response whereby firms, foreseeing future penalties, adjust their behavior when peers are targeted by regulators. Prior research defines peers using broad jurisdictional boundaries. Instead, I argue that regulatory anticipation may emerge locally, driven by two channels: proximity to peer scrutiny and firms' perceived sanction risks. Examining U.S. facilities' GHG emissions, I exploit variation in local‐peer scrutiny arising from a change in the EPA's High‐Priority‐Violation policy. Difference‐in‐differences estimates show that heightened scrutiny of county peers is associated with 7% lower emissions among non‐targeted firms, driven by those facing higher sanction risks. Distance‐decay analyses indicate that these anticipation patterns weaken with geographic separation. The findings encourage managerial attention to local regulatory conditions and suggest that avoiding regulatory deserts could improve policy effectiveness.Managerial SummaryThis paper examines how stricter regulatory scrutiny of one firm can prompt nearby, non‐targeted firms to reduce their emissions. Using U.S. data on facilities' greenhouse gas (GHG) emissions, I find that when a county peer faces heightened oversight, non‐targeted firms are associated with about 7% lower GHG emissions on average. These patterns are stronger for firms already at higher risk of environmental penalties, declining as geographic distance from scrutinized peers increases. For managers, the findings highlight the importance of monitoring local regulatory activity and the behavior of nearby peers, as local comparisons can shape stakeholder expectations. For policymakers, the results suggest that avoiding regulatory ‘deserts’ may enhance the effectiveness of climate‐related and environmental regulation.

Fast learning and sustained exploration: The role of timely performance feedback

2026-04-27T00:00:00+00:00

Strategic Management Journal
How should organizations manage learning dynamics? Strategy theories suggest “more‐is‐better”—fast, frictionless sharing enhances performance—while organizational learning theory warns that “less‐is‐more,” as fast learning causes premature convergence. We reconcile this tension by showing that the “less‐is‐more” prediction depends critically on a key assumption in classic computational models: that information about agents' performance is not continuously updated. When performance information is timely, fast learning enhances exploration. The mechanism is Target Diversity: fast learning allows many individuals to rapidly reach the performance frontier, increasing the set of imitation targets. Organizations thus learn from a diverse, shifting set of targets. The implication is that organizations achieve superior performance not by restricting information or slowing learning, but by making data on choices and performance available more quickly.Managerial SummaryInnovation relies on recombining diverse knowledge, yet facilitating this is challenging. Organizations often encourage copying stars with established track records or reputations, but this can lead to suboptimal results. We demonstrate a superior approach: provide up‐to‐date performance data and spotlight emergent top performers, regardless of their history. When feedback is timely, rapid learning allows “underdogs”—employees starting from lower positions—to quickly catch up to the frontier via unique knowledge combinations. Spotlighting these emergent successes creates “Target Diversity,” providing the organization with a continually renewed and diverse set of imitation targets. Such a design enhances the exploitation of diverse knowledge and improves long‐run performance.

Smokestacks and the Swamp

2026-04-27T00:00:00+00:00

The Review of Financial Studies
We examine whether politicians affect local firms’ industrial pollution, and whether such effects are transmitted through plant-level networks to affect pollution in other regions. We first document that close Democrat wins in U.S. congressional races are associated with lower emissions and higher abatement at the plant level, especially when politicians have strong pro-environmental preferences. We also find evidence of reallocation: firms shift emissions away from areas represented by Democrats. However, reallocation is imperfect: firm-level costs are higher and market-to-book ratios lower if firms’ representation is more Democratic. Lower pollution-related illnesses around plants in Democratic districts suggest pass-through effects on local communities.

Corporate response to the Black Lives Matter movement: determinants of speaking out in support of social causes

2026-04-27T00:00:00+00:00

Review of Accounting Studies
We document that firms vary in their timeliness of support for the Black Lives Matter (BLM) movement following the death of George Floyd in May 2020, and that timeliness is an indicator of authenticity. We predict that firms that speak outquicklyin support of BLM (via Twitter or their websites) have made more investments in diversity and inclusion, relative to firms that speak outslowly(via conference calls or annual reports) or that remain silent. Consistent with this prediction,quick-disclosing firms have greater workforce diversity, have boards with greater ethnic diversity, and are more likely to tie executive compensation to diversity and inclusivity. Furthermore,quick-disclosing firms increase their hiring of both Black American employees and Black directors relative to firms that stay silent. We also document that quick-disclosing firms are part of more supportive stakeholder networks. We develop aninclusivity indexand show that firms with higher index levels are more likely to speak out on the Capitol Riots, the Asian Spa Shootings, and voting rights.

When Certification Backfires: Negative Spillovers on Noncertified Offerings in Airbnb Plus

2026-04-27T00:00:00+00:00

Organization Science
Research on certification has largely emphasized its positive effects, showing that certification can enhance trust and legitimacy for certified actors and in some cases, generate positive spillovers that benefit uncertified counterparts. Yet, certification programs are frequently scaled back or discontinued, suggesting that their broader consequences may be more complex than commonly assumed. In particular, certification can produce negative spillovers by sharpening distinctions between certified and noncertified actors; through a contrast mechanism, juxtaposition with certified offerings heightens the salience of uncertainty and leads audiences to evaluate noncertified actors less favorably, even when underlying quality is unchanged. We test this argument using data from the launch of Airbnb Plus, a program in which Airbnb certified a subset of listings based on verified quality standards. Employing a difference-in-differences design comparing Los Angeles (where the program was launched) and San Diego (where it was not), we find a negative treatment effect on the revenues of noncertified listings in Los Angeles. This negative spillover is attenuated when alternative quality signals are available, when noncertified listings are less directly comparable with certified ones, and when listings are more difficult to substitute outside the platform. Our findings suggest how certification systems intended to enhance trust and legitimacy can under certain market conditions inadvertently disadvantage noncertified actors.Funding: We benefited from the Cornell Management and Organizations Ph.D. Student Research Grant for this project.

More Versus Better: Artificial Intelligence, Incentives, and the Emerging Crisis in Peer Review

2026-04-27T00:00:00+00:00

Organization Science
As the AI Task Force for Organization Science, we provide an early account of artificial intelligence’s (AI) impact on both submissions and reviews at a major academic journal. Submission volume has risen 42% since the late 2022 release of ChatGPT, while writing quality has declined. The rise in AI-generated writing accounts for nearly all of these trends. AI-generated writing in reviews has also increased, and is characterized by lower writing quality and less topical diversity than human-generated writing. We are, to our knowledge, the first journal to report these early impacts of AI in the review process. Conversations with editors across scientific disciplines, however, suggest that what we observe is not limited to our journal or to the social sciences. At this early stage of AI adoption, we cannot make a normative assessment about appropriate or ideal levels of AI usage. We can, however, conclude that the current state of AI tools, amplified by existing publish-or-perish incentives, appears to be pushing the system toward an equilibrium of more rather than better research. Reaching an equilibrium in which AI serves as a critical engine of innovation will require that our institutions and the incentive structures they create adapt.Funding: S. Hasan used research funding from Duke University’s Fuqua School of Business. C. Gartenberg used research funding from University of Pennsylvania’s Wharton School.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2026.ed.v37.n3 .

The Ripple Effect of Platform Quality Controls in a Submarket: Evidence from a Secondhand Marketplace

2026-04-27T00:00:00+00:00

Marketing Science
Platform quality controls within a submarket have a positive carryover effect on adopters and a U-shaped spillover effect on nonadopters.

Consumer Reviews and Regulation: Evidence from New York City Restaurants

2026-04-27T00:00:00+00:00

Marketing Science
This paper examines whether consumer reviews predict restaurant health violations and how online signals influence hygiene compliance and consumer demand.

Does AI Cheapen Talk? Theory and Evidence from Global Entrepreneurship and Hiring

2026-04-27T00:00:00+00:00

Management Science
Screening human capital based on signals such as job applications or entrepreneurial pitches is crucial for organizations. Signals are often informative insofar as they require differential knowledge and effort to produce. Generative AI (GAI) complicates screening by lowering the cost of producing impressive signals. We model the informational effects of GAI, showing that applicants’ access to GAI can increase—and also decrease—an evaluator’s screening mistakes. This result depends on how GAI affects experts’ signals compared with nonexperts’. Using experiments in hiring and start-up investing, we estimate that senders’ access to GAI (ChatGPT) lowers screening accuracy by 4%–9% for employers and start-up investors. Consistent with our model, senders’ access to GAI also improves screening accuracy in some settings, in our case, among senders from non–English-speaking countries. These results show that GAI can profoundly shape screening accuracy.This paper was accepted by Anindya Ghose, information systems.Funding: We are grateful for the Columbia Business School Digital Future Initiative Grant for helping fund this project. B. Cowgill thanks the Kauffman Foundation Emerging Scholars Program, the Columbia Center for Political Economy, the NET Institute, and the Stellar Development Foundation. P. Hernandez-Lagos thanks the Yeshiva University Sy Syms Dean’s Research Fund.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07027 .

Shared or Solo? Platform Pricing and Rider Choices in Ride-Hailing

2026-04-27T00:00:00+00:00

Management Science
As ride-sharing becomes an integral part of ride-hailing platforms, understanding its operational and economic implications is crucial. Although shared rides can improve system efficiency and reduce congestion, they also introduce trade-offs, such as longer wait times and rider discomfort. In this paper, we develop a game-theoretic queueing model to examine how a platform operating with one of three objectives, i.e., volume, revenue, or social welfare maximization, sets prices for solo and shared rides, while self-interested riders decide whether to request a ride and, if so, whether to share. Our analysis uncovers a counterintuitive pricing pattern in stark contrast to the standard pricing theory: a platform that aims to maximize volume or social welfare may charge higher prices for both solo and shared rides than when it pursues revenue maximization. Because ride-sharing expands service capacity and improves society-wide service access (particularly for riders not so sensitive to the discomfort of sharing), a volume-maximizing platform and a social planner tend to induce more ride-sharing than a revenue-centric platform. Increased ride-sharing, in turn, further relieves platform congestion, decreases riders’ average wait times, and boosts their willingness to pay for both shared and solo services. That said, a platform may shut down shared services in small markets with low arrival rates of riders, as the extended rider-pairing process can make the entire system less efficient than one with only solo services. Finally, although ride-sharing always (weakly) enhances a specific targeted performance metric desired by the platform, its effect on rider welfare is more nuanced. Under volume or revenue maximization, ride-sharing expands service access and benefits riders overall. However, under social welfare maximization, it may reduce total rider surplus, as the platform restricts service access to prevent excessive discomfort borne by sharing riders from outweighing the overall gains in the platform’s operational efficiency. We calibrate the model and illustrate our insights using the Chicago ride-hailing data.This paper was accepted by Karan Girotra, operations management.Funding: This research was supported by the Natural Sciences and Engineering Research Council of Canada [Grant RGPIN-2021-04295].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04324 .

Privacy Regulation and Fintech Lending

2026-04-27T00:00:00+00:00

Management Science
Consumers dislike sharing data with fintechs, but greater access to data can improve loan market outcomes through better screening. We study how the California Consumer Privacy Act (CCPA), which grants users control over and mitigates concerns about sharing their data, affects fintech lending. After the CCPA’s introduction, fintechs’ loan rates decline relative to those of other lenders. In addition, rate dispersion across fintech loans increases, fintechs deny more applications, and they make greater use of nontraditional credit scoring models, whereas their default rates decline by more than those of other lenders. These results are consistent with an improved screening process enabled by additional data. Mortgage originations by fintechs also increase, suggesting that well-designed privacy regulation may enhance financial inclusion.This paper was accepted by Bo Becker, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.02874 .

Techno-nationalism’s paradox in international standard setting

2026-04-27T00:00:00+00:00

Journal of International Business Studies
Grounded in realism, geopolitical techno-nationalism advocates restricting technology outflows to targeted entities from rival countries to safeguard national security and technological superiority. We examine this logic in international standard-setting organizations (ISSOs), which exemplify decentralized innovation ecosystems that shape future-generation technologies. We identify a paradox: techno-nationalist restrictions would unintentionally undermine, rather than strengthen home-country firms’ influence over international standards relative to targeted foreign firms. This paradox emerges because techno-nationalist logic clashes with two defining features of decentralized innovation ecosystems: (1) multilateral complementarity, where complementary knowledge needed to co-create value is widely distributed among firms, and (2) emergent technological evolution, where multiple potential trajectories exist and the eventual technological path is socially constructed. Both features make interaction and coordination between firms in ISSOs essential for influencing standards, yet technology disclosure restrictions directly disrupt these processes. The backfiring effect intensifies when home firms exhibit deep technological complementarity with targeted foreign companies, engage in early-stage standardization, or pioneer frontier innovations requiring ecosystem-wide validation. Evidence from the recent U.S. sanctions on Huawei in an influential ISSO supports our hypotheses. Our findings caution policymakers that techno-nationalist controls may backfire in decentralized innovation ecosystems and alert firms to factors that can increase their vulnerability to geopolitical tensions.

The Effect of Advisors' Incentives on Clients' Investments

2026-04-27T00:00:00+00:00

The Journal of Finance
We use granular data from an investment firm and a credible identification strategy to estimate the effect of financial advisors' incentives on client investments. Exploiting a natural experiment triggered by the 2018 implementation of Markets in Financial Instruments Directive II (MiFID II), we find that clients' investments respond strongly to changes in advisor incentives. Advisors react through multiple mechanisms: (i) inducing existing clients to bring in new money, (ii) channeling it to high‐incentive funds, and (iii) attracting more new clients. We also find that the MiFID II reform generated more balanced incentives, which translated into higher portfolio efficiency through lower average fees and stronger portfolio diversification.

Using Unconscious Thought to Improve Evaluations of Complex Accounting Estimates

2026-04-27T00:00:00+00:00

Journal of Accounting Research
Complex accounting estimates are becoming increasingly important to financial statements. Yet, such estimates create ample opportunities for bias. Although both management and independent auditors are tasked with ensuring these estimates are free from error and bias, evaluating the appropriateness of these measures can be quite difficult. Drawing on unconscious thought theory, we predict and find across three experiments that engaging in unconscious thought can improve accounting practitioners’ evaluations of accounting estimates. In Experiment 1, we use practicing auditors as participants and find that unconscious thought improves less‐experienced auditors’ ability to recognize income‐decreasing patterns of bias. In contrast, more‐experienced auditors respond similarly to both incoming‐increasing and income‐decreasing bias, regardless of whether they use conscious or unconscious processing. In Experiments 2 and 3, we provide evidence that prompting managers to engage in unconscious thought also improves their recognition of patterns of bias within estimates. Overall, our findings demonstrate how unconscious processing can be intentionally prompted to improve accounting professionals’ ability to recognize subtle patterns of bias that they might otherwise overlook.

Do Investors Value Auditor Involvement in Non‐GAAP Reporting?

2026-04-27T00:00:00+00:00

Journal of Accounting Research
This paper examines investors’ perceptions of auditor involvement in non‐GAAP reporting as captured by non‐GAAP disclosures in 10‐K filings. We find that firm‐years with auditor involvement in non‐GAAP reporting have higher CARs, lower bid–ask spreads, lower stock volatility, and lower abnormal trading volume on 10‐K filing dates. To sharpen identification of auditor involvement, we hand‐collect non‐GAAP measures and reconciliations for S&P 500 firms and identify which exclusions reconcile directly to the audited financial statements. As the percentage of exclusions that reconcile directly to the audited financial statements increases, bid–ask spreads and stock volatility on 10‐K filing dates decrease. We find that the results are not driven by strategic reporting or managers’ responses to perceived litigation risk. This study provides new insights into non‐GAAP disclosures outside of earnings announcements, which have been largely ignored in prior literature. Collectively, our results suggest investors value auditor involvement in non‐GAAP reporting and inform policymakers and standard setters considering the usefulness of assurance over non‐GAAP measures.

Acquisitive and Organic Growth in Penrose’s Theory: A Replication and Extension of Lockett, Wiklund, Davidsson, Girma (2011)

2026-04-27T00:00:00+00:00

Entrepreneurship Theory and Practice
We replicate Lockett, Wiklund, Davidsson, and Girma’s (LWDG) (2011) study, which draws on Penrose’s theory to explicate how organic and acquisitive growth interact, using data from 128,368 Dutch firms (2011–2016). Our results confirm LWDG’s finding that past organic growth negatively affects subsequent organic growth. However, unlike LWDG, reporting a positive association, we find that past acquisitive growth reduces subsequent organic growth. Extending LWDG’s framework reveals that this effect turns positive over time, particularly for complementary acquisitions. While our findings align with Penrose’s theory, they also provide a more nuanced understanding of the conditions under which acquisitive growth enhances organic growth.

What do public company audit clients want from their auditor?

2026-04-28T00:00:00+00:00

Review of Accounting Studies
We survey public company executives and directors to understand what audit clients want from their auditor in today’s regulated environment. Our results provide at least three important takeaways. First, executives and directors view elements of auditors’ service quality (e.g., timeliness of communications) as at least as important as auditors’ technical competence. Second, we find no evidence that stakeholders’ preferences for service quality replaces their expectation for technical competence. Third, we find that 57% of executives and 67% of directors feel they can very accurately assess audit quality after an audit’s completion, but we are unable to identify clear determinants of participants’ self-reported ability to assess quality. Our results highlight the challenges facing auditors as they attempt to please clients, protect shareholders, and comply with regulations, all while offering a product whose quality is inherently challenging for others to assess. Our findings motivate future research and inform regulatory efforts.

Knowledge Will Always Get through: Inventors, International Networks, and Flows of Technological Knowledge between Britain and the United States in the Interwar Deglobalization Period

2026-04-28T00:00:00+00:00

Journal of Management Studies
Researchers have highlighted that institutional contexts affect the transnational diffusion of knowledge. However, the influence of institutions on the flow of knowledge through cross‐national networks remains under‐theorized, limiting our understanding of the dynamics of knowledge creation and the factors that may hinder it. Drawing on data from over 8000 US patents granted to British inventions, alongside a case study of a network of inventors and scientists, this research examines how the interwar phase of deglobalization affected the international diffusion of technological knowledge. The analysis shows that interwar nationalistic states' efforts constrained, rather than fully halted, the cross‐border flow of knowledge within networks. Deglobalization particularly hindered the diffusion of tacit knowledge, which depends on personal interaction, whereas codified knowledge in patents and scientific publications continued to circulate more easily. These findings have contemporary relevance and suggest that, despite policymakers' efforts to reverse globalization through protectionist policies, tacit and codified knowledge is likely to continue crossing national borders through the networks of inventors and scientists.

From armed roots to airline routes in South America: A dual imprinting perspective

2026-04-09T00:00:00+00:00

Strategic Management Journal
Reserch SummaryWe propose that founding partner relationships can leave distinct imprints on organizations that differ in durability and in how they respond to subsequent changes involving the founding partner. Examining South American airlines founded between 1919 and 1984, we argue and find that such relationships simultaneously create an internal capability imprint, enhancing operational performance and facilitating international expansion, and an external identity imprint, constraining expansion by triggering national security concerns among foreign regulators. Internal capabilities persist longer because they are embedded in organizational structures and tacit knowledge, while external identity resides in more malleable stakeholder perceptions. Post‐founding changes to the imprinter reshape these effects asymmetrically: the transition to civilian air traffic control erodes the competitive advantage of military‐derived capabilities by diffusing previously scarce expertise, while military coups intensify the negative consequences of a military‐associated identity. These findings advance a dual imprinting perspective and contribute to strategy research by explaining persistent organizational heterogeneity through founding‐era capabilities and identities.Managerial SummaryWhen launching a venture, founders instinctively seek to collaborate with powerful partners such as celebrated investors and high‐profile board members. Those relationships leave two distinct legacies. The first is operational: the knowledge and systems a powerful partner brings embed themselves deeply, sharpening capabilities that sustain competitive advantage for years. The second is reputational: the outside world immediately begins to categorize your organization through that association, and that categorization can be hard to escape. Our research on South American airlines shows how military‐era founding partners produced operational excellence that fueled international growth, while simultaneously creating a security‐sensitive identity that blocked market access in politically sensitive contexts. The lesson for founders: think several moves ahead. The question is not solely what this partner can give us today, but how will we be seen if his or her reputation shifts tomorrow.

Where Sentence Is Served: Entrepreneurship and Socioeconomic Mobility Among Ex-Offenders

2026-04-09T00:00:00+00:00

Organization Science
Entrepreneurship is often promoted as a pathway to upward mobility, especially for those who face barriers in traditional labor markets. However, whether and when entrepreneurship truly improves the long-term prospects of individuals with criminal records remains poorly understood. This study examines how the type of sentences—community service versus short incarceration—shapes ex-offenders’ employment routes and socioeconomic outcomes. Using three decades of Danish registry data, we compare individuals convicted of similar offenses but given different sentences and follow their trajectories over time. We find that incarceration substantially increases the likelihood that ex-offenders enter entrepreneurship as an alternative to wage work. However, this career path proves costly: compared with those who secure regular employment, individuals who pursue entrepreneurship after release earn persistently lower income and are more likely to reoffend. Mechanism analyses show that transitions into entrepreneurship concentrate among groups facing the steepest hiring barriers—foreign-born individuals, those without vocational training, residents of high-unemployment areas, and offenders convicted of property crimes or serving longer sentences—suggesting that entrepreneurship often reflects “push” rather than “pull” dynamics. Relative to unemployment, entrepreneurship is associated with modestly lower recidivism but similar income penalties. Our findings add nuance to the narrative of entrepreneurship as an emancipatory route for marginalized populations. They highlight the risks of relying on entrepreneurship as a re-integration strategy and underscore the need for organizational and policy interventions that expand access to stable jobs and provide targeted support for people with criminal records.Funding: Financial support from the Carlsberg Foundation (Carlsbergfondet) [Grant CF21-0156] is gratefully acknowledged.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2024.19965 .

Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives

2026-04-09T00:00:00+00:00

Operations Research
GraphL0: Sparse Gaussian Graphical Models with Discrete OptimizationRecovering sparse dependency graphs in undirected Gaussian graphical models is a well-known problem in statistical machine learning. Given samples from a [Formula: see text]-dimensional Gaussian distribution, the task amounts to estimating the [Formula: see text] precision (inverse covariance) matrix under the assumption that only a small fraction of its entries are nonzero. In “Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives,” the authors introduce GraphL0. GraphL0 is an estimator based on an [Formula: see text]-penalized pseudo-likelihood, departing from the more common [Formula: see text] relaxation. The resulting formulation is a convex mixed-integer program, which becomes challenging for standard commercial solvers at moderate-to-large [Formula: see text]. To make the approach practical, the authors develop a custom nonlinear branch-and-bound algorithm, alongside scalable approximate solvers. The paper also provides new statistical guarantees for estimation accuracy and support recovery, and experiments on synthetic and real data sets show substantial computational gains over off-the-shelf solvers and competitive runtime and accuracy versus leading alternatives.

Search Games with Predictions

2026-04-09T00:00:00+00:00

Operations Research
Searching with Advice You Cannot Fully TrustSearching for a hidden target is a classic problem in operations research, arising in contexts such as search-and-rescue missions, exploration for natural resources, and robotic navigation.In many real-world scenarios, the searcher is not completely in the dark: it may have some prior information suggesting where the hider might be located. Such predictions can be helpful—but they may also be wrong. In “Search Games with Predictions,” Angelopoulos, Lidbetter, and Panagiotou present the first study of search games in a fully randomized setting where both the Searcher and the Hider employ mixed strategies, and the prediction may be erroneous. The paper identifies strategies that optimally balance two competing objectives: the search performance when the prediction is correct, and the performance when there are no assumptions on the quality of the prediction. The paper demonstrates this approach on several classic search problems such as box search with or without overlook, line search, and star search. The results quantify both the benefits and limitations of predictive information and provide a framework that does not apply only to search games, but to two-player zero-sum games more broadly.

Dual Sourcing Made Easy: Distributionally Robust Optimization of Inventory Systems Under Independent Demand

2026-04-09T00:00:00+00:00

Operations Research
A Distribution-Free Playbook for Dual SourcingIn the paper “Dual Sourcing Made Easy: Distributionally Robust Optimization of an Inventory System Under Independent Demand,” the authors study a common dual-sourcing dilemma: a low-cost supplier with a long lead time versus a faster, more expensive backup. Rather than committing to a parametric demand model, they propose a distributionally robust formulation that relies only on the demand mean and variance, while leveraging independence across periods. This yields a simple, closed-form way to set a tailored base–surge (TBS) policy: regular orders cover the predictable component of demand, and emergency orders buffer the remaining uncertainty, with inventory targets reflecting lead-time differences. The resulting policy is lightweight to calibrate, easy to deploy, and straightforward to stress test. In a field application using data from a multinational food manufacturer, the robust TBS settings improve service performance and reduce stockouts relative to the firm’s current rule and standard benchmarks, without sacrificing cost efficiency under volatility.

“Glossy Green” Banks: The Disconnect Between Environmental Disclosures and Lending Activities

2026-04-09T00:00:00+00:00

Management Science
Using confidential information on banks’ portfolios, we show that banks that emphasize the sustainability of their lending policies in their disclosures do not exhibit a reduced environmental impact and, if anything, they extend a higher volume of credit to brown borrowers, without charging higher interest rates, shortening debt maturity, or requiring more collateral. These results cannot be attributed to the financing of borrowers’ transition toward greener technologies. Examining the mechanisms behind the strategic disclosure choices reveals that banks extend credit to existing brown borrowers, especially those who are financially underperforming.This paper was accepted by Caroline Flammer, sustainability.Funding: M. Giannetti acknowledges financial support from the Swedish House of Finance, the Nasdaq Nordic Foundation, the Karl-Adam Bonnier Foundation, and the Jan Wallander and Tom Hedelius Foundation. M. Jasova acknowledges financial support from the Barnard College Presidential Research Award. M. Loumioti acknowledges financial support from the University of Texas at Dallas. The opinions expressed herein are those of the authors and do not necessarily reflect those of the ECB or the Eurosystem. All errors are the authors’ own.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07420 .

Labor Market Outcomes of Restatements for Corporate Accountants

2026-04-09T00:00:00+00:00

Management Science
Our study examines the impact of nonfraud financial restatements on the careers of corporate accountants. Using LinkedIn data, we identify a sample of accountants working at 201 firms that restated their financial statements between 2004 and 2014. We find that compared with human resource employees within the same company or corporate accountants in matched control firms, accountants in restatement firms, particularly senior staff, have a higher rate of departure and a lower probability of moving to a higher-ranked position outside the company after a restatement is announced. Using a longer job search period as a measure of being forced to leave, we find that the higher departure rate for senior accountants is because of being forced out rather than leaving voluntarily. The higher departure rates occur only for accountants working at firms with more severe restatements. In a separate sample of firms that restate financial statements because of clerical errors, we do not find higher departure rates for accountants after the restatement is revealed. Our results suggest that senior accountants in restatement firms experience negative outcomes in the labor market.This paper was accepted by Suraj Srinivasan, accounting.Funding: J. (X.) Jiang acknowledges research support from the Eli Broad College of Business. M. Shen acknowledges financial support from the NUS Start-up Grant [Grant A-0003914-00-00] and the Singapore MOE Tier-1 Grant [Grant A-8000098-00-00].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.00430 .

Estimating Effects of Long-Term Treatments

2026-04-09T00:00:00+00:00

Management Science
Estimating the effects of long-term treatments through A/B testing is challenging. Treatments, such as updates to product functionalities, user interface designs, and recommendation algorithms, are intended to persist within the system for a long duration of time after their initial launches. However, because of the constraints of conducting long-term experiments, practitioners often rely on short-term experimental results to make product launch decisions. It remains open how to accurately estimate the effects of long-term treatments using short-term experimental data. To address this question, we introduce a longitudinal surrogate framework that decomposes the long-term effects into functions based on user attributes, short-term metrics, and treatment assignments. We outline identification assumptions, estimation strategies, inferential techniques, and validation methods under this framework. Empirically, we demonstrate that our approach outperforms existing solutions by using data from two real-world experiments, each involving more than a million users on WeChat, one of the world’s largest social networking platforms.This paper was accepted by Omar Besbes, revenue management and market analytics.Funding: S. Huang and C. Wang were supported by the Innovation and Technology Support Programme, Hong Kong [Grant ITS/311/22FP].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02575 .

Tax avoidance and ESG disclosure mandates: international evidence

2026-04-09T00:00:00+00:00

Journal of International Business Studies
This paper examines how regulations mandating environmental, social, and governance (ESG) disclosure affect corporate tax behavior. Using a difference-in-differences analysis on a sample of firms from 48 countries, we find that ESG disclosure mandates lead to significant reductions in tax avoidance, with stronger effects for mandates that include tax-relevant provisions. We identify increases in ESG information transparency and improvements in firms’ ESG performance as channels through which ESG disclosure mandates reduce tax avoidance. We further find that the decrease in tax avoidance following ESG disclosure mandates is more pronounced in countries with weaker financial disclosure requirements, legal and tax enforcement, and environmental and social institutions. Collectively, the evidence suggests that non-financial disclosure regulations can curb aggressive tax behavior, supporting broader goals of corporate accountability and sustainable development.

Funding Black High‐Growth Startups

2026-04-09T00:00:00+00:00

The Journal of Finance
We classify the race of over 160,000 U.S. founders and investors and study the venture capital (VC) funding gap for Black entrepreneurs. Only 3.1% of VC‐funded startups are Black‐owned, and they raise half as much VC funding as others. We attribute much of this gap to Black founders having fewer traditional success markers, like patents or entrepreneurial experience. This disparity also affects matching: Black VC partners invest more in Black founders, and these investments have higher successful exit rates. We attribute this outperformance to lower information asymmetries due to network overlap and “screening discrimination,” whereby Black VCs better differentiate among Black founders.