Academic Publications

Passive Investing and the Rise of Mega-Firms

2025-10-10T00:00:00+00:00

The Review of Financial Studies
We study how passive investing affects asset prices. Flows into passive funds disproportionately raise the stock prices of the economy’s largest firms, especially those large firms in high demand by noise traders. Because of this effect, the aggregate market can rise even when flows are entirely due to investors switching from active to passive funds. Intuitively, passive flows increase the idiosyncratic risk of large firms in high demand, which discourages investors from correcting the flows’ effects on prices. Consistent with our theory, prices and idiosyncratic volatilities of the largest S&P500 firms rise the most following flows into that index. (JEL G12, G23, E44)

Climate-related disclosure commitment of the lenders, credit rationing, and borrower environmental performance

2025-10-10T00:00:00+00:00

Review of Accounting Studies
U sing lenders who become members of the Task Force on Climate-Related Financial Disclosures (TCFD) as an exogenous shock, we examine whether and how lenders’ commitment to transparent climate-related disclosures affects borrowers’ environmental performance. We find that borrowers of TCFD-member lenders, relative to control firms, significantly improve their environmental performance after the TCFD launch. Lenders’ disclosure commitments influence borrowers through credit rationing and monitoring. Specifically, polluting borrowers face higher borrowing costs, reduced access to credit, and greater incorporation of environmental action covenants in loan agreements. Additionally, polluting borrowers of TCFD-member lenders experience heightened financial constraints. Finally, borrowers of TCFD-member lenders are more likely to adopt the TCFD framework for climate-related disclosure after the TCFD establishment. Together, these findings illuminate the role of lenders in driving corporate environmental performance improvement through their commitment to transparent climate-related disclosures.

The Price of Housing in the United States, 1890–2006

2025-10-10T00:00:00+00:00

The Quarterly Journal of Economics
We construct the first annual market rent and home sales price series for American cities over the 20th century using 2.7 million newspaper real estate listings. Our findings revise several stylized facts about U.S. housing markets. Real market rents did not fall during the postwar period in most cities and rose nationally by 60% from 1890 to 2006. We also document higher sales price growth between 1953 and 1987 relative to previous series. Real prices reached almost 4 times their 1890 level by 2006. Prices grew most in metros with high demand and low levels of construction. We find that the rent-to-price ratio fell from about 8% in the early 20th century to 3% by 2006, consistent with declines in the cost of owning housing relative to renting. For the typical year in our period, the annual return to owning housing was 9%, driven mostly by rental returns of 7.7%, with capital gains contributing only 1.3%. While capital gains were close to zero from 1890 to 1940, they grew to nearly a third of total returns from 1970 to 2006.

Dynamic Pricing for a Multiproduct Consumer Electronics Trade-in Program

2025-10-10T00:00:00+00:00

Operations Research
Boosting Profits of Trade-in Programs Through Smarter PricingAs electronics trade-in programs expand worldwide, firms face complex pricing challenges: quoting offers instantly while managing vast product varieties and uncertain demand. In the article “Dynamic pricing for a multiproduct consumer electronics trade-in program” in Operations Research, the authors address this challenge and present effective solutions. The study develops pricing policies that determine both trade-in offers and resale prices over time to maximize profits. It first introduces a static pricing approach and proves that it performs nearly optimally; then, it further proposes a dynamic “batched-adjustment” policy that adapts to demand uncertainty and delivers an improved profit performance. Numerical experiments confirm the advantages of these methods. By demonstrating simple yet powerful strategies with provable effectiveness, the research offers firms actionable tools to increase profitability in trade-in operations.

Correlation Improves Group Testing: Modeling Concentration-Dependent Test Errors

2025-10-10T00:00:00+00:00

Management Science
Population-wide screening is a powerful tool for controlling infectious diseases. Group testing can enable such screening despite limited resources. Viral concentration of pooled samples are often positively correlated, either because prevalence and sample collection are influenced by location, or through intentional enhancement via pooling samples according to risk or household. Such correlation is known to improve efficiency when test sensitivity is fixed. However, in reality, a test’s sensitivity depends on the concentration of the analyte (e.g., viral RNA), as in the so-called dilution effect, where sensitivity decreases for larger pools. We show that concentration-dependent test error alters correlation’s effect under the most widely used group testing procedure, the two-stage Dorfman procedure. We prove that when test sensitivity increases with concentration: pooling correlated samples together (correlated pooling) achieves asymptotically higher sensitivity than independently pooling the samples (naive pooling). In contrast, in the concentration-independent case, correlation does not affect sensitivity. Moreover, with concentration-dependent errors, correlation can degrade test efficiency compared with naive pooling, whereas under concentration-independent errors, correlation always improves efficiency. We propose an alternative measure of test resource usage, the number of positives found per test consumed, which we argue is better aligned with infection control, and show that correlated pooling outperforms naive pooling on this measure. In simulation, we show that the effect of correlation under realistic concentration-dependent test error is meaningfully different from correlation’s effect assuming fixed sensitivity. Our findings underscore the importance for policy makers of using models that incorporate naturally occurring correlation and of considering ways of strengthening this correlation.This paper was accepted by Carri Chan, healthcare management.Funding: This work was supported by the Provost’s Office of Cornell University, the Air Force Office of Scientific Research [Grant FA9550-19-1-0283], and the National Science Foundation Division of Mathematical Sciences [Grant DMS2230023].Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2021.04217 .

No Gifts Returned: Surprise Bonuses Reduce Productivity in a Natural Field Experiment

2025-10-10T00:00:00+00:00

Management Science
The gift exchange hypothesis posits that workers reciprocate above-market wages with increased productivity. This paper tests this hypothesis in a natural field experiment where one or both workers in a pair received a discretionary bonus after an initial round of data entry tasks. Bonuses were assigned based on one of three criteria: (i) relative productivity in the initial round, (ii) economic need, or (iii) an arbitrary decision. Two conditions where neither or both workers received a bonus served as the baseline. Contrary to the gift exchange hypothesis, we found a significant decline in postbonus productivity, especially when both workers received the bonus. This result suggests that workers interpreted the bonus as a signal of employer contentment, allowing them to reduce their effort. We conjectured that the postbonus productivity decline may result from either (a) a lower perceived risk of repercussions from slacking, such as early dismissal, or (b) a reduced sense of obligation to reciprocate the employer’s kindness. A follow-up experiment replicated the primary result, providing moderate evidence for the explanation based on reduced fear of dismissal. The main effect of bonuses on productivity was substantial, with effort reductions of 15.1% in the first experiment and 8.4% in the follow-up relative to baseline. In cases where only one worker received a bonus, nonrecipients’ inequality aversion appeared to decrease productivity markedly in the economic need treatment, whereas status-seeking behavior slightly increased productivity by bonus recipients in the productivity treatment.This paper was accepted by Dorothea Kübler, behavioral economics and decision analysis.Funding: F. Bogliacino acknowledges funding from the Fundación Universitaria Konrad Lorenz [Internal Grant 7INV1141], Open Evidence [Research Grant 009], and the Universidad Nacional [Internal Grant 26007]. G. Grimalda and D. Pipke gratefully acknowledge funding for the follow-up experiment from the Kiel Institute for the World Economy.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.04085 .

Anomalies as New Hedge Fund Factors

2025-10-10T00:00:00+00:00

Journal of Financial and Quantitative Analysis
We identify a parsimonious set of factors from a large pool of candidates for explaining hedge fund returns, ranging from equity market, anomaly, and trend-following factors to macroeconomic factors. The resulting 9-factor model, including five anomaly factors, outperforms existing hedge fund models both in sample and out of sample, with a significant reduction in alphas while showing substantial cross sectional performance heterogeneity. Further analysis based on fund holdings confirms the model’s ability to capture returns from arbitrage trading. Overall, the anomaly factors help quantify hedge fund strategies and risk exposures and improve fund performance evaluation.

Common Factors in Equity Option Returns

2025-10-11T00:00:00+00:00

The Review of Financial Studies
We explore the factor structure in delta-hedged equity option returns. A sparse latent factor model generates a correlation of 0.90 or higher between average and predicted option returns. A comparable performance is achieved with a characteristic-based model containing four factors: the equally weighted option portfolio, a factor based on the difference between historical and implied volatilities, a factor based on the ratio of corporate cash holdings to the total value of the firm’s assets, and a factor based on volatility of volatility. Traditional stock return factors cannot explain these option factors.

Non‐Market Strategy and Deglobalization: Firm–State Relations and the Historical Microfoundations of Corporate Political Activity

2025-10-11T00:00:00+00:00

Journal of Management Studies
This study examines deglobalization through the lens of non‐market strategy (NMS), focusing on the antecedents and microfoundations of corporate political activity (CPA) in the global aluminium industry. Drawing on archival research and historical analysis, we challenge the prevailing view of deglobalization as a state‐driven reversal of globalization. Instead, we reconceptualize it as a co‐evolving process of firm–state relations, where multinational enterprises (MNEs) and governments jointly construct institutional arrangements. Our analysis demonstrates how MNEs leverage ideological alignments, elite networks, and long‐term political capabilities to influence protectionist policies, trade governance, and national development agendas. We identify the microfoundations of CPA – ideological affinity, embedded agency, and networked trust – as critical to shaping institutional and policy outcomes with macroeconomic and geopolitical consequences. By tracing firm–state interactions across a century of global change, we demonstrate how CPA functions as a historically constituted practice through which firms exercise both ideological and political agency. In reframing deglobalization as not merely an external constraint but a strategic outcome co‐produced by business and state actors, this study extends non‐market strategy theory. We highlight how deglobalization and globalization are not sequential opposites but intertwined processes, co‐constructed through the persistent deployment of NMS and CPA.

Design-Mediated Morality: The Transformative Potential of Aesthetic Objects

2025-10-11T00:00:00+00:00

Journal of Consumer Research
Art and artisanal objects carry the potential for moral transformations. Although consumer research suggests a relationship between aesthetic taste and morality, scholars have not deeply considered the role of material design in shaping consumers’ moral self. We address this missing link by theorizing the formative process of design-mediated morality: defined as the transmission of moral values into design objects through manifestos and design scripts, which allow consumers to experience morality in direct material engagements. We draw on a longitudinal ethnography of the New Nordic Food movement and its iconic flagship restaurant, noma, to demonstrate the influence of manifestos in streamlining moral virtues with aesthetic expressions. We identify three distinct scripting strategies (simulation, estrangement and sensitization) that steer consumers’ sensory and affective engagement with design objects. Our findings also explain that consumers’ moral awakening is tied to direct material engagement (or 'thinging’) with said objects. By highlighting the embodied dimensions of moralization, our work connects and advances research streams on market-mediated moralization, taste formation and experiential marketing. We conclude with critical reflections on the role of artisanal movements and design in affecting moral transformations, as well as outline avenues for future research on design-mediated morality in everyday consumption contexts.

Don't calm down! How affective climate emerges in start‐ups

2025-10-13T00:00:00+00:00

Strategic Entrepreneurship Journal
Different types of affective climates—norms related to the experience, expression, use, and regulation of emotions—have been shown to impact organizational outcomes. However, we know less about how these climates emerge. This study investigates the emergence of affective climates through a 22‐month longitudinal multiple‐case study of five early‐stage start‐ups. Our analysis revealed that an affective climate of high authenticity emerged in start‐ups through three key mechanisms: the interaction between positive and negative emotions, constructive meta‐emotions, and interpersonal emotion regulation characterized by emotional validation and problem‐solving. Our findings contribute to the understanding of affective climate emergence and offer nuanced insights into how founders, managers, and teams can cultivate constructive emotional dynamics in highly uncertain, fast‐paced environments.Managerial SummaryWe explore how affective climate emerges through a longitudinal case study of five start‐ups. Affective climate describes norms and assumptions concerning the experience, expression, use, and regulation of emotions. Research suggests that an affective climate of high authenticity—meaning that members feel free to express their actual emotions—contributes to creativity and performance while reducing burnout. However, prior research offers few insights into how and why different affective climates emerge in start‐ups. We find that managers and founders may shape their organization's affective climate toward high authenticity by fostering positive emotions, through an accepting attitude toward their own negative emotions, and by validating employees' emotions. By doing so, managers and founders can foster healthy emotional dynamics in their start‐ups.

Data-Driven Investors

2025-10-13T00:00:00+00:00

The Review of Financial Studies
How does the increased use of data technologies, like machine learning, by financial intermediaries affect the allocation of capital towards innovation? I study this question in the context of startup financing by venture capitalists (VCs). While VCs adopting data technologies become better at screening startups similar to those in historical data, they tilt their investments towards this pool and become concurrently less likely to finance innovative startups that achieve rare major success. Plausibly exogenous variations in VCs’ screening automation suggest that these effects are causal. These findings highlight how investors’ adoption of data technologies can have real effects through innovation financing. (JEL G24, L26, O30)

Teams in Crisis: The Effect of Team Familiarity on Performance Under Conditions of Crisis and Uncertainty

2025-10-13T00:00:00+00:00

Organization Science
Research on fluid teams has consistently found a positive relationship between team familiarity and performance, but little empirical research has investigated whether these benefits of familiarity extend to times of crisis and uncertainty. This study examines how team familiarity influences provider decision times in the emergency department, focusing on how its effects vary across different crisis and uncertainty contexts. Using patient and provider assignment data from a large, multisite emergency department, we construct care team familiarity networks and analyze familiarity’s impact on decision-making speed during both low-uncertainty crises (high-acuity patient surges) and high-uncertainty crises (early COVID-19 pandemic), as well as under conditions of patient-level task uncertainty. We find that team familiarity consistently reduces provider decision times; familiarity is particularly beneficial during crises. However, across both crisis and noncrisis situations, we find that the positive effects of familiarity are significantly weakened under conditions of high uncertainty. These findings underscore the conditional nature of familiarity’s benefits, suggesting that in highly uncertain or novel situations, teams cannot rely solely on past shared experience to maintain performance. Implications for staffing strategies in healthcare and other high-stakes environments highlight the need for organizations to balance the benefits of familiarity with adaptability in the face of uncertainty.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2025.20912 .

Investor Valuation for Socially Responsible Assets: A Willingness to Pay Experiment

2025-10-13T00:00:00+00:00

Management Science
We present an experimental study of investors’ willingness to pay for socially responsible assets. In our initial public offering experiment, various assets share identical financial risk-return profiles but differ in the intensity and timing of societal benefits, represented by charitable donations. We find that subjects value societal benefits positively and prefer a positive correlation between financial returns and these societal benefits. We offer implications for the design of corporate social responsibility policies and for the pricing of responsible assets.This paper was accepted by David Sraer, finance.Funding: This work was supported by the Research Chair on Sustainable Finance at Toulouse School of Economics. S. Pouget gratefully acknowledges the Agence Nationale de la Recherche [Grant ANR-17-EURE-0010], the Research Initiative Finance Durable et Investissement Responsable, and Netspar for financial support.Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.01349 .

Motivator or Depletor? Unraveling the Double‐Edged Effects of Peer Monitoring on Employee Job Performance

2025-10-13T00:00:00+00:00

Human Resource Management
Peer monitoring, as a type of organizational control, is increasingly important in managing employee performance. However, extant research primarily focuses on the benefits of peer monitoring on job performance, while largely ignoring its potential negative consequences. We advance the literature to theorize and test the double‐edged effects of peer monitoring on job performance by examining its self‐regulatory consequences. Specifically, we propose that peer monitoring can simultaneously increase both work engagement and ego depletion, which in turn exert positive and negative impacts on job performance, respectively. Furthermore, we theorize that trait self‐control is a critical contingent factor that moderates both the positive and negative pathways from peer monitoring to job performance. We test our model through a two‐wave, multisource field survey study involving 203 employees and their 49 direct supervisors in China, as well as through an experimental study with 149 full‐time working employees in the United States. We find consistent evidence for the negative consequences of peer monitoring on job performance via ego depletion, while the positive pathway through work engagement is only supported by the field survey study. Furthermore, both studies show that there is a positive indirect effect of peer monitoring on job performance via work engagement when employees have lower trait self‐control and a negative indirect effect via ego depletion when employees have higher trait self‐control. Such examination helps elucidate the positive and negative effects of peer monitoring on job performance and has important theoretical and practical implications.

The Pace of Change: Socially Responsible Investing in Private Markets

2025-10-14T00:00:00+00:00

The Review of Financial Studies
We show that socially responsible investors can have a negative impact by slowing the pace of firm reform. Investors with broad prosocial preferences value acquiring dirty firms with high negative production externalities because they can reform these firms. The anticipation of trading gains for dirty firms decreases the incentive of current firm owners to reduce externalities proactively, potentially causing delay in reform. The presence of financial investors—alongside socially responsible investors—can exacerbate delay. Investment mandates through which socially responsible investors commit to paying a premium for green firms can incentivize reform in a timely manner. (JEL G11, G23, G24, G34, H41, M14)

Auctions with Frictions: Recruitment, Entry, and Limited Commitment

2025-10-14T00:00:00+00:00

Review of Economic Studies
Auction models are convenient abstractions of informal price-formation processes that arise in markets for assets or services. These processes involve frictions like bidder recruitment costs for sellers, participation costs for bidders, and limitations on sellers’ commitment abilities. This paper develops an auction model that captures such frictions. We derive novel insights, notably that outcomes are often inefficient, that markets sometimes unravel, and that the observability of competition may have a large effect.

Scandal, Associative Stigma, and Sorting in Labor Markets: Archival and Experimental Evidence

2025-10-14T00:00:00+00:00

Management Science
Stigma stemming from managerial scandals often spreads beyond the implicated transgressor and contaminates other actors via stigma by association. We study how associative stigma resulting from scandals involving managerial misconduct affects subordinate worker careers. We extend prior work by distinguishing between managerial misconduct in the professional domain from managerial misconduct in the personal domain and theorize that this distinction will affect the severity of associative stigma, audience evaluations, and associated workers’ labor market outcomes. Our multimethod empirical approach combines archival analysis of administrative employment records with a series of preregistered, randomized vignette experiments. Our archival analysis demonstrates that workers associated with managers who engage in misconduct sort into organizations with a history of managerial misconduct. The magnitude of this effect is amplified when associative stigma arises from managerial misconduct in the personal domain, a pattern driven by the fact that associative stigma arising from managerial misconduct in the professional domain tends to carry a relatively stronger labor market penalty and increased likelihood of worker exit from the industry. Our experimental studies, which measure employment intentions of workers and hiring intentions of employers, suggest that the psychological mechanism of stigma apprehension plays a role in facilitating the sorting that we observe, a result consistent with the interpretation that sorting emerges from greater tolerance of actors stigmatized by association rather than a taste for misconduct and thus, affirmative assortative matching. These findings contribute to the stigma literature by showing how stigma by association effects vary across audiences and linking this variation to sorting outcomes.This paper was accepted by Isabel Fernandez-Mateo, organizations.Funded: The authors thank the Blake Family Fund for Ethics, Leadership, and Governance at Purdue University for supporting this research.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.00075 .

Textual Factors: A Scalable, Interpretable, and Data-Driven Approach to Analyzing Unstructured Information

2025-10-14T00:00:00+00:00

Management Science
We introduce a general approach for analyzing large-scale text-based data, combining the strengths of neural network language processing and generative statistical modeling to create a factor structure of unstructured data for downstream regressions typically used in social sciences. We generate textual factors by (i) representing texts using vector word embedding, (ii) clustering the vectors using locality-sensitive hashing to generate supports of topics, and (iii) identifying relatively interpretable spanning clusters (i.e., textual factors) through topic modeling. Our data-driven approach captures complex linguistic structures while ensuring computational scalability and economic interpretability, plausibly attaining certain advantages over and complementing other unstructured data analytics used by researchers, including emergent large language models. We conduct initial validation tests of the framework and discuss three types of its applications: (i) enhancing prediction and inference with texts, (ii) interpreting (non–text-based) models, and (iii) constructing new text-based metrics and explanatory variables. We illustrate each of these applications using examples in finance and economics such as macroeconomic forecasting from news articles, interpreting multifactor asset pricing models from corporate filings, and measuring theme-based technology breakthroughs from patents. Finally, we provide a flexible statistical package of textual factors for online distribution to facilitate future research and applications.This paper was accepted by David Simchi-Levi, finance.Funding: The authors gratefully acknowledge the financial support from the Ewing Marion Kauffman Foundation, the Becker Friedman Institute of Economics, the Fama-Miller Center for Research in Finance, INQUIRE Europe, the Kenan Institute of Private Enterprise, and the Risk Institute at OSU Fisher College of Business (while L. W. Cong was a fellow at the institute). W. Zhu acknowledges financial support from the Tsinghua University Initiative Scientific Research Program [Grant 2022Z04W02016], the Tsinghua University School of Economics and Management [Research Grant 2022051002], and the National Natural Science Foundation of China [Grant 72442014].Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2020.01180 .

How Do Mergers Affect the Mental Health of Employees?

2025-10-14T00:00:00+00:00

Management Science
We study employee mental health to assess the long-term nonmonetary consequences of mergers. Using employer-employee level data linked to individual health records, we document that the incidences of stress, anxiety, depression, and psychiatric medication usage increase following mergers. These effects are prevalent among employees from both targets and acquirers, in weak and in growing profitable firms. Employees who experience negative career developments within the merging firms, ‘blue-collar’ workers, and employees with lower skills are most affected. Mergers that generate more mental illness among employees perform worse after the transaction. A variety of tests address endogeneity concerns.This paper was accepted by Camelia Kuhnen, finance.Funding: Funding from the Mistra Center for Sustainable Markets (Misum) and the Nasdaq Nordic Foundation is gratefully acknowledged.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.04277 .

The Imperfect Intermediation of Money‐Like Assets

2025-10-14T00:00:00+00:00

The Journal of Finance
We study supply‐and‐demand effects in the U.S. Treasury bill market by comparing the returns on T‐bills to the policy rate on the Federal Reserve's reverse repurchase (RRP) facility. We develop and test a simple model where the RRP‐bill spread is policed both by heterogeneously elastic money funds and by corporate treasurers who derive collateral benefits from holding T‐bills. In response to shifts in T‐bill supply, money funds act as front‐line arbitrageurs. However, when T‐bills become extremely scarce, less elastic corporate treasurers become the marginal investors and supply shifts have a larger effect on T‐bill rates.

Post-Succession Innovation in Family Businesses: Exploring the Tension Between Incumbent Imprinting and Successor Self-Determination

2025-10-14T00:00:00+00:00

Entrepreneurship Theory and Practice
This study advances the understanding of innovation across generations in family businesses by revealing how imprinting and self-determination shape innovation trajectories following succession. Through a case study of 16 Dutch family Small and Medium-sized Enterprises (SMEs) in the food industry, we identified four innovation trajectories—Inherited, Ancillary, Synergistic, and Detached Innovation. We disentangle the effect of structural imprinting and behavioral imprinting on the successor and examine how successor self-determination mediates imprinting forces. We rebalance the emphasis on incumbent-centric family business studies and explain the heterogeneity of post-succession innovation outcomes. These insights offer new theoretical tools for understanding and managing innovation during critical transition periods.

Revisiting the Role of Gender and Beauty in Entrepreneurship: A Large-Scale Conceptual Replication

2025-10-14T00:00:00+00:00

Entrepreneurship Theory and Practice
Some research has suggested that investors prefer pitches made by men rather than women entrepreneurs, and physically attractive men entrepreneurs are even more successful than their physically unattractive counterparts. However, empirical evidence remains limited. We re-examine these findings using a large archival dataset with 9,285 entrepreneurs across 13 industries and 105 countries between the years of 2014 to 2018. Our results replicate the female penalty effect—women raised 12.9% less funds compared to men. However, we found that the physical attractiveness of the entrepreneurs has a negative main effect on startups’ success, and that this effect is only significant for men entrepreneurs.

What Problem Do Intermediaries Solve? Evidence From Real Estate Markets

2025-10-15T00:00:00+00:00

The Review of Financial Studies
We study intermediation in the housing market. Using data from an online platform utilized by real estate agents to generate leads, we identify exogenous intermediary attention arising from the quasi-randomized ordering of potential listings. Greater intermediary attention leads to an increased probability of listing with an agent and selling quickly, and a higher transaction price. The listing and transaction probabilities of neighboring properties decrease in intermediary attention. These results contrast sharply with endogenous correlations and provide causal evidence that intermediaries resolve property-level frictions deriving from search, information, or behavioral considerations but do not mitigate neighborhood-level information asymmetries.

Slum Upgrading and Long-run Urban Development: Evidence from Indonesia

2025-10-15T00:00:00+00:00

Review of Economic Studies
Developing countries face massive urbanization and slum upgrading is a popular policy to improve shelter for many. Yet, preserving slums at the expense of formal developments can raise concerns of misallocation of land. We estimate causal, long-term impacts of the 1969-1984 KIP program, which provided basic upgrades to 5 million residents covering 25% of land in Jakarta, Indonesia. We assemble high-resolution data on program boundaries and 2015 outcomes and address program selection bias through localized comparisons. On average, KIP areas today have lower land values, shorter buildings, and are more informal, per a photographs-based slum index. The negative effects are concentrated within 5km of the CBD. We develop a spatial equilibrium model to characterize the welfare implications of KIP. Counterfactuals suggest that 79% of the welfare effects stem from removing KIP in the center and highlight how to mitigate losses to displaced residents.

EXPRESS: The Effect of Competitive Collection in Closed-Loop Supply Chain

2025-10-15T00:00:00+00:00

Production and Operations Management
Recycling and remanufacturing have gained significance and popularity in response to growing environmental concerns and economic pressures. Although previous studies have extensively examined the competitive collection in a closed-loop supply chain, they ignored the pricing decisions in both the forward and reverse channels. In this paper, we develop a two-period analytical framework that considers pricing decisions in both the forward and reverse channels to explore the impacts of competitive collection on optimal prices and profits within a closed-loop supply chain. This study focuses on three distinct used-product collection models: (1) the manufacturer collects used products directly from consumers; (2) the manufacturer outsources the collection activity to a third-party collector (TPC); and (3) the manufacturer and TPC engage in a competitive collection. Our analysis uncovers several intriguing insights. First, competitive collection does not necessarily increase the collecting price for consumers as the TPC prefers to increase its collecting price while the manufacturer prefers to reduce its collecting price. Second, the TPC’s increased collecting price does not force the manufacturer to increase his transfer price for the TPC. Third, competitive collection will benefit those consumers who buy the remanufactured product as the price of this product decreases. Fourth, the manufacturer and retailer may be better off directly or through revenue-sharing mechanisms in competitive collection. In addition, the competitive collection could also achieve a win–win situation in terms of financial performance and environmental sustainability. Lastly, when the competitive collection is between the manufacturer and retailer, the manufacturer benefits from the competition but the retailer does not. This paper also discusses the intuition behind these findings and their managerial implications.

EXPRESS: Dynamic Relief Provision Planning for En Route Refugees: Modeling Probabilistic Movements Using Migration Pull Drivers

2025-10-15T00:00:00+00:00

Production and Operations Management
Forced displacement crises have become a pressing humanitarian concern. Refugee movements expose individuals to dire living conditions with severe inaccessibility to essential resources. Humanitarian organizations play a vital role in alleviating these hardships through relief aid interventions. This study aims to optimize the fulfillment of recurring needs for geographically dispersed refugee groups en route to safe destinations. Here, capacitated mobile facilities are tasked with delivering relief aid to refugee groups periodically to ensure equitable service frequency. We formulate the problem as a Markov decision process with multinomial state-transition distributions, shaped by external migration pull factors such as safety conditions, road accessibility, and spatial proximity. The objective is to minimize the relocation and replenishment costs of mobile facilities, along with the deprivation costs faced by underserved refugees. We develop an approximate dynamic programming algorithm featuring a novel policy replication routine. To complement this offline method, we introduce a state-dependent variable threshold policy that enables high-quality, real-time relief provision. Using instances inspired by the Syrian refugee crisis, our results demonstrate the substantial value of stochastic modeling, yielding a 25% reduction in expected total costs compared to deterministic baselines and up to 12% savings through coordinated planning among humanitarian actors. The proposed methods remain effective under dispersed and cohesive refugee group dynamics and multi-destination migration scenarios. Furthermore, we uncover high-frequency traversal and service hotspots along migration paths to provide tactical insights for parameter calibration and resource prepositioning. Collectively, our findings offer practical insights for managing ongoing and future refugee migration crises.

EXPRESS: Refining Data-driven Upfront Reservation Discount Pricing via Inverse Inferring Newsvendor Transactions

2025-10-15T00:00:00+00:00

Production and Operations Management
This paper investigates the supplier’s pricing problem under upfront reservation discount (URD) contracts where the buyer reserves products in advance and then adjusts the purchase quantity based on realized end-market demand. A key challenge is that the supplier typically has limited data to estimate the demand distribution and possesses inferior information compared to the buyer. To address the challenges of distributional ambiguity and information asymmetry, we develop a Refined Distributionally Robust Optimization (RDRO) model for the supplier’s URD pricing to maximize her worst-case profit. To better infer true demand patterns, beyond the conventional reliance on historical demand data, our approach leverages past transaction records involving supplier-buyer interactions through the inverse optimization underlying the first-order conditions of the buyer’s newsvendor behavior. Then, a general Wassersteinp-distance minimization problem forp≥1 is developed to generate a Refined Empirical Distribution (RED) in the enhanced set. We prove that the RED provides a superior estimation of the true demand distribution compared to the classical empirical distribution when the buyer holds an informational advantage. Although identifying the RED leads to an intractable semi-infinite program, we show that the RED admits a closed-form solution. To obtain the supplier’s worst-case profit involving a non-convex distributionally optimistic optimization problem with a decision-dependent uncertainty set, we exploit the monotone transport structure between univariate distributions to truncate the distributions and convert the decision-dependent quantile constraints, which results in a finite-dimensional convex model that can be efficiently solved. Moreover, we extend the model to accommodate data noise, volatile market prices, evolving market conditions, and multi-item settings. Numerical experiments based on a virtual machine reservation problem in the cloud service market demonstrate the effectiveness and robustness of the proposed approach.

EXPRESS: Individual versus Institutional Philanthropy: Crowdfunding During Crises

2025-10-15T00:00:00+00:00

Production and Operations Management
Crises are accompanied by resource shortages, operational challenges, and shifts in demand for resources. During crises, non-profit organizations have historically played a crucial role in mitigating these challenges, with crowdfunding platforms emerging as a new solution for resource mobilization. In this study, we examine how individual and institutional donors respond to the sudden shifts in demand that accompany a global crisis. We analyze rich, granular data from multiple sources, including donation data from a leading education crowdfunding platform, before and after the onset of the COVID-19 pandemic, and find notable contrasts between individual and institutional responses. While there was a significant increase in institutional donations during the pandemic, individual donations remained relatively stable overall. Adopting a motivation-opportunity-ability (MOA) framework, we center donor heterogeneity in our approach, deriving nuanced insights. Donations from individuals in economically disadvantaged communities, which were the worst impacted by the crisis, decreased; however, these communities prioritized immediate and time-sensitive needs. Small and local institutions played a pivotal role in supporting high-need schools during the crisis. These findings make meaningful contributions to the operations literature on crowdfunding and have practical implications for platform designers. By distinguishing between individual and institutional donors and identifying the factors that drive their behavior, our study offers important implications for platform designers to improve crisis-time resource mobilization through more targeted engagement strategies.

Good Lessons Despite Bad Feelings: How Boundary-Spanning Teams Learn from Collaboration Failure

2025-10-15T00:00:00+00:00

Organization Science
To stay competitive, organizations set up boundary-spanning teams (BSTs) to learn from external partners. However, collaborating across boundaries is challenging and BSTs often face collaboration failure, defined as divergence from desired or expected collaboration goals. Given the costs associated with such failures, they usually evoke negative emotions which often lead to blaming the external partner and a collaboration breakdown, undermining joint learning from failure. This raises the question of how BSTs can learn from collaboration failure despite negative emotions. Our inductive study on drug discovery teams provides a silver lining: certain emotive-cognitive conditions can give rise to learning interactions that allow BSTs to either neutralize or transform their negative emotions into positive ones. Averting collaboration breakdown, these interactions allow BSTs to both create and integrate explicit knowledge after collaboration failure and change their collaboration dynamics in order to prevent failure in the future and improve their way of collaborating. Our study brings forward an emotive perspective on learning from collaboration failure and expands the literature on BSTs and emotions in groups. It further informs management practices on how to overcome negative emotions and beliefs so that BSTs sustain fruitful collaborations, enabling critical innovations such as treatments for diseases to be further developed.

Culture as a Toolkit for Robust Action: Tackling Grand Challenges with Cultural Entrepreneurship

2025-10-15T00:00:00+00:00

Organization Science
A new grand challenges paradigm has emerged in organization theory that has reoriented scholarly attention toward how society can effectively tackle a broad array of complex, uncertain, and evaluative matters of concern including climate change, forcible displacement, poverty, authoritarianism, child malnutrition, commercial sex exploitation, and many more. In this paper, I argue that the literature has tended toward a view of culture as a constraining force that inhibits tackling grand challenges and renders them remarkably intractable. Yet, alternative views of culture also purport that it can serve not merely as a constraining force that prevents action but also as a toolkit or repertoire of resources that actors use to solve problems and thus an enabling force for progress. The substantial literature on cultural entrepreneurship provides several powerful theoretical affordances that are uniquely useful in overcoming known obstacles to addressing grand challenges. I draw on the intellectual resources of this literature to augment the robust action model—one of the premiere theoretical frameworks for tackling grand challenges—by expanding each of the three robust action strategies through an integration with cultural entrepreneurship. This theoretical elaboration advances our understanding of the early moments of initiation of robust action strategies when they are merely uncertain future possibilities, as well as the culturally informed ensuing dynamics by which robust action continues in perpetuity. I conclude by discussing a new generative dialogue at the interstice of these two domains which has substantial synergies for future scholarship.

Unsettling Settled Knowing: Reconciling Differences in Expert Practice

2025-10-15T00:00:00+00:00

Organization Science
Occupational subgroups with similar training often develop differing work practices within their local settings. These differences may create inconsistencies when organizational change brings subgroups together to work alongside each other. Based on a two-year qualitative study of a hospital merger combining two neonatal intensive care units, we consider how differing expert practices may be challenged, preserved, or reconciled when subgroups are brought together. We find that reconciliation processes are unexpectedly triggered by novice newcomers who struggle to socialize into a consistent way of working. Comparing five expert practices over time, we also find that when groups are able to converge around the type of knowledge that should apply to expert practices (abstract versus experiential knowledge), a form of reconciliation is possible, but when there is divergence around the type of knowledge that is relevant to the situation, reconciliation fails. Converging on experiential knowledge implies a simplified process of reconciliation that preserves expert autonomy while masking residual differences. Converging on abstract knowledge involves a complex, multilayered process in which expert subgroups need to revert in part to mechanisms resembling those that underpinned their initial socialization into the discipline. These mechanisms include mobilizing evidence to update abstract knowledge, situated mentoring with respected experts, and authoritative reinforcing via interventions from high-status professionals. Our study highlights the challenges of changing expert practices that are rooted in ingrained experiential knowledge. It reveals that abstract knowledge alone is insufficient and that reconciliation invariably involves settlements and agreements on what form of knowledge matters.Funding: This work was supported by the Social Sciences and Humanities Research Council of Canada.

Sinkhorn Distributionally Robust Optimization

2025-10-15T00:00:00+00:00

Operations Research
Entropy-Regularized Wasserstein Distributionally Robust OptimizationUncertainty in data poses a central challenge in operations research. Distributionally robust optimization (DRO) offers a principled framework for addressing this challenge by producing solutions resilient to distributional variations. Among various DRO approaches, the Wasserstein DRO has received significant attention though its computational efficiency relies on stringent assumptions, and its worst case distributions are typically discrete. In “Sinkhorn Distributionally Robust Optimization,” Wang, Gao, and Xie leverage the Sinkhorn distance—an entropy-regularized variant of the Wasserstein distance—to more realistically model uncertainty, enhancing computational efficiency. The authors establish a strong duality reformulation and propose a first order stochastic mirror descent algorithm with provable complexity guarantees for general loss functions. Unlike Wasserstein DRO, Sinkhorn DRO yields continuous worst case distributions, offering a more flexible representation of practical uncertainties. Extensive experiments in the newsvendor problem, portfolio optimization, and adversarial classification demonstrate its superior performance in both out-of-sample performance and efficiency.

Near-Optimal Pricing and Resource Allocation in a Large-Scale Service System

2025-10-15T00:00:00+00:00

Operations Research
Pricing and Resource Allocation Made Simple for Service SystemsLarge-scale service systems—from drone delivery to cloud computing—face the dual challenge of balancing customer delays with revenue maximization. In “Near-Optimal Pricing and Resource Allocation in a Large-Scale Service System,” Wu, Liu, and Sun propose a dual-based pricing and resource allocation policy that is both simple and theoretically powerful. This greedy, one-step heuristic delivers performance guarantees matching the theoretical lower bound.Beyond the stylized model that illustrates its core idea, the study shows the value of dynamic pricing through an insensitivity result: any work-conserving rule can stabilize the system. The policy also proves robust under realistic conditions, including heterogeneous server pools and nonexponential service environments.Perhaps most striking, the authors uncover a “compensation effect”: near-optimal pricing curves need not rise monotonically with congestion. Instead, they may offset customers’ delay disutility to sustain revenue. These insights offer a practical, theory-backed framework for modern service operations.

Deep Learning-Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence

2025-10-15T00:00:00+00:00

Management Science
Large-scale online platforms launch hundreds of randomized experiments (also known as A/B tests) every day to iterate their operations and marketing strategies. The combinations of these treatments are typically not exhaustively tested, which triggers an important question of both academic and practical interest. Without observing the outcomes of all treatment combinations, how does one estimate the causal effect of any treatment combination and identify the optimal treatment combination? We develop a novel framework combining deep learning and doubly robust estimation to estimate the causal effect of any treatment combination for each user on the platform when observing only a small subset of treatment combinations. Our proposed framework (called debiased deep learning ( DeDL )) exploits Neyman orthogonality and combines interpretable and flexible structural layers in deep learning. We show theoretically that this framework yields efficient, consistent, and asymptotically normal estimators under mild assumptions, thus allowing for identifying the best treatment combination when observing only a few combinations. To empirically validate our method, we collaborated with a large-scale video-sharing platform and implemented our framework for three experiments involving three treatments, where each combination of treatments is tested. When observing only a subset of treatment combinations, our DeDL approach significantly outperforms other benchmarks to accurately estimate and infer the average treatment effect of any treatment combination and to identify the optimal treatment combination.This paper was accepted by Vivek Farias, data science.Funding: R. Zhang is grateful for financial support from the Hong Kong Research Grants Council General Research Fund [Grants 14502722, 14503224, and 14504123].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.04625 .

Roles of Artificial Intelligence in Collaboration with Humans: Automation, Augmentation, and the Future of Work

2025-10-15T00:00:00+00:00

Management Science
Humans will see significant changes in the future of work as collaboration with artificial intelligence (AI) will become commonplace. This work explores the benefits of AI in the setting of judgment tasks when it replaces humans (automation) and when it works with humans (augmentation). Through an analytical modeling framework, we show that the optimal use of AI for automation or augmentation depends on different types of human-AI complementarity. Our analysis demonstrates that the use of automation increases with higher levels of between-task complementarity. In contrast, the use of augmentation increases with higher levels of within-task complementarity. We integrate both automation and augmentation roles into our task allocation framework, where an AI and humans work on a set of judgment tasks to optimize performance with a given level of available human resources. We validate our framework with an empirical study based on experimental data in which humans classify images with and without AI support. When between-task complementarity and within-task complementarity exist, we see a consistent distribution of work pattern for optimal work configurations; AI automates relatively easy tasks, AI augments humans on tasks with similar human and AI performance, and humans work without AI on relatively difficult tasks. Our work provides several contributions to theory and practice. The findings on the effects of complementarity provide a nuanced view regarding the benefits of automation and augmentation. Our task allocation framework highlights potential job designs for the future of work, especially by considering the often-ignored, critical role of human resource reallocation in improving organizational performance.This paper has been accepted by D. J. Wu for the Special Issue on the Human-Algorithm Connection.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.05684 .

EXPRESS: The Weekend Effect in Online Reviews

2025-10-15T00:00:00+00:00

Journal of Marketing Research
This paper finds that online reviews submitted during the weekend tend to have lower rating scores than reviews submitted during the week. Analyzing 400 million reviews across 33 e-commerce, hospitality, entertainment, and employer platforms, the authors find that weekend reviews have a 3% lower relative share of 5-star ratings and a 6% higher relative share of 1-, 2-, or 3-star ratings compared to weekday reviews. The pattern emerges even when controlling for quality of reviewed items. This weekend effect is surprising given that studies usually report higher happiness levels and a better mood on weekends. The authors discuss several explanations related towherethe review is submitted (platform characteristics),whatthe review is about (listing characteristics), andwhosubmits the review (reviewer characteristics). They present evidence that temporal self-selection of reviewers is a dominant driver of the weekend effect. During the weekend, a different set of users—those more prone to write negative reviews—is more likely to select to leave a review. These findings complement extant research on review self-selection by adding a temporal layer to the self-selection processes inherent in online reviews. This paper also highlights managerial implications by demonstrating that solicitations sent during the weekend (versus weekday solicitation) lead to collecting more negative reviews.

Privacy and Team Incentives

2025-10-15T00:00:00+00:00

The Journal of Finance
Real‐world contracts are typically private, observed only by their direct signatories, so agents working together are vulnerable to the principal opportunistically reducing other agents' incentives. The principal can mitigate this commitment problem by giving the most skilled agent a budget and delegating authority to write other agents' contracts. This endogenous hierarchy, never optimal with public contracts, raises effort, output, and compensation but allows rent extraction. The principal prefers it when contracts are opaque enough, skill is sufficiently heterogeneous across agents, and joint output is sensitive enough to effort. Our model provides novel predictions for the structure of banking syndicates.

Attention or Sentiment: How Social Media React to ESG?

2025-10-15T00:00:00+00:00

Information Systems Research
Despite the increasing attention associated with ESG investing, a natural yet overlooked question is how investors would react to the ESG performance of firms, given that investors’ activities can ultimately impact firm performance. Utilizing data from multiple sources, we empirically find that ESG performance positively predicts future social media attention, but it has no predictive ability for future social media sentiment. Furthermore, the significant positive association between ESG and social media attention holds for both ESG downgrade events and ESG upgrade events. Moreover, the positive association between ESG and social media attention is driven by the environmental and social factors, whereas the uncorrelation between ESG and social media sentiment is determined by the social and governance factors. These findings urge managers to pay close attention to keeping and improving their firms’ ESG advantage. They help managers shed light on the picture of the return of their firms’ investment in ESG by taking investor behavior into account. Besides, ESG’s inability in predicting social media sentiment also indicates retail investors’ limited awareness of the importance of ESG currently. Therefore, it is pressing for regulators to take actions to boost the function of sustainable investing and ESG values.

When Gig Workers No Longer Gig: The Impact of California Assembly Bill 5 on the Online Labor Market

2025-10-15T00:00:00+00:00

Information Systems Research
The rapid growth of the gig economy has intensified debates over how to classify workers. California’s Assembly Bill 5 (AB5) reclassifies many independent contractors as employees, yet its practical effects on gig workers remain unclear. Using data from a major online labor platform and a difference-in-differences design, we provide one of the first empirical assessments of AB5’s impact on workers’ earnings. We find that California gig workers’ monthly earnings rose relative to workers in other states, but this increase was driven by longer working hours, offsetting a drop in hourly pay. These results highlight the complex trade-offs of reclassification: although workers may gain access to employee benefits, they may also experience reduced hourly rates and increased workloads. For policymakers, our findings offer evidence to guide similar initiatives under consideration in other states and underscore the need for nuanced, context-sensitive regulation. For platform managers, the results suggest opportunities to align platform design and worker education with evolving labor laws to support compliance and sustainable growth. Together, these insights inform future policy and platform strategies aimed at balancing worker protection with flexibility in the gig economy.

Programming Tasks Impact Responses to Moral Dilemmas for Novice Programmers

2025-10-15T00:00:00+00:00

Information Systems Research
The rapid diffusion of programming skills across education and industry may impact how individuals consider moral dilemmas. Across a series of experiments, we show that performing even simple programming tasks shifts novice programmers’ evaluation of the classic trolley problem toward utilitarian responses. After solving a programming problem, respondents are more willing to sacrifice one life to save many. This effect arises because programming induces a deliberative, rule-based cognitive style. However, the effect diminishes with greater programming experience and can be mitigated through interventions, such as time delays or moral nudges. These findings highlight that organizations training employees in coding should be aware that programming tasks may temporarily alter moral reasoning, potentially influencing judgments in ethically charged contexts (e.g., product design, risk management, or AI development). Incorporating reflective cooling-off periods or explicit ethical reinforcement may reduce bias toward utilitarian reasoning. As programming becomes a baseline skill across the workforce, its cognitive spillovers could shape societal attitudes toward contested moral dilemmas. These include ethical trade-offs in settings such as autonomous vehicles and artificial intelligence systems.

Common purpose advantage: Reviving a managerial theory of the firm?

2025-10-16T00:00:00+00:00

Strategic Management Journal
What is the most effective way to distribute organizational objectives across managers? While prior work suggests managers should each focus on a single objective, we draw on Barnard's original insights on corporate purpose to identify conditions when managers pursuing the full set of objectives is advantageous. Using a computational model, we find that moderate strategic diversity amongst managers enables practice sharing to generate sufficiently valuable distant search to offset the additional complexity incurred during local search, creating a “common purpose advantage.” The advantage is stronger with fewer objectives, moderate objective correlation, less diversification, and moderate turbulence. Under other conditions, it dissipates or reverses. This work unifies scattered findings on multi‐objective firms, contributes to diversification research, and revives interest in the Managerial Theory of the Firm.Managerial SummaryHow should a firm distribute its objectives across its managers? Should each manager focus on a single objective, or should all collectively pursue the full set? Our research identifies the conditions for a “common purpose advantage,” where all managers pursuing the full set of objectives is superior. Using a computational model, we demonstrate this advantage arises when moderate strategic diversity amongst managers enables the sharing of valuable practices, which generates performance gains that offset the complexity of handling multiple goals. This advantage is strongest with fewer objectives, moderate environmental turbulence, and in less diversified firms. Under other conditions—such as high turbulence, many objectives, or high diversification—this advantage dissipates or reverses, making each manager focusing on a single objective more effective.

Why Do Traditional and Shadow Banks Coexist?

2025-10-16T00:00:00+00:00

The Review of Financial Studies
Traditional and shadow banks interacted in similar ways in the 2007 and COVID-19 crises, when both assets and liabilities flew out of shadow banks and into traditional banks. We explain these facts in a model of the coexistence of traditional and shadow banks in which liabilities and assets flow from the former to the latter in good times, avoiding regulation, and move the other way in a crisis, alleviating fire sales. The model sheds light on how regulations for traditional banks have (unintended) consequences on the shadow banking sector. (JEL G01, G21, G23, G38)

Confident Risk Premiums and Investments Using Machine Learning Uncertainties

2025-10-16T00:00:00+00:00

The Review of Financial Studies
This paper derives ex-ante confidence intervals for stock risk premium forecasts that are based on a wide range of linear and machine learning models. Exploiting the cross-sectional variation in the precision of risk premium forecasts, I provide improved investment strategies. The confident-high-low strategies that take long-short positions exclusively on stocks with precise risk premium forecasts outperform traditional high-low strategies in delivering superior out-of-sample returns and Sharpe ratios across all models. The outperformance increases (decreases) with the model complexity (bias). The confident-high-low strategies are economically interpretable as trading strategies of ambiguity-averse investors who account for confidence intervals around risk premium forecasts. (JEL G11, G12, C45, C11, and C13)

Uncertainty, Risk, and Capital Growth

2025-10-16T00:00:00+00:00

The Review of Financial Studies
We find that high productivity-based macroeconomic uncertainty is associated with greater accumulation of physical capital despite a reduction in investment and valuations. To reconcile this puzzling evidence, we show that uncertainty predicts lower aggregate depreciation of existing capital, which dominates the investment slowdown. We explain these findings by developing a quantitative production-based model in which firms implement precautionary savings through reducing utilization rather than raising investment. Through this novel intensive-margin mechanism, uncertainty shocks command a quarter of the equity premium in general equilibrium. Flexibility in utilization adjustments also helps explain uncertainty risk exposures in the cross-section of industry returns. (JEL G12, E32, D81, D50)

The Quantity-Quality Tradeoff: How Incentives and Monitoring Shape Gender Differences at Work

2025-10-16T00:00:00+00:00

Organization Science
Why do women and men approach the same work differently? Prior research across occupations shows that men tend to emphasize quantity and produce more, whereas women prioritize quality. Researchers have attributed these differences to individual-level factors, such as gender-specific preferences, caregiving responsibilities, and evaluator biases. We propose that organizational practices, specifically production incentives and quality monitoring, also influence these patterns. Using data from the U.S. Patent and Trademark Office (USPTO), we conceptualize the quantity-quality tradeoff using examiner leniency and leverage discontinuities in incentives and monitoring to assess their effects. We theorize and find that stronger production incentives lead men to be more lenient than women, prioritizing quantity. Under heightened monitoring, women are less lenient than men, emphasizing quality. Further, monitoring moderates the relationship between incentives and gender differences in leniency such that the largest gender gap occurs under strong incentives and weak monitoring. Our study demonstrates that organizational practices interact with worker gender to shape the quantity-quality tradeoff, indicating that incentive and monitoring systems—though not designed to affect gender inequality—produce distinct and unintended effects that are essential to understanding and addressing workplace disparities.Funding: We greatly appreciate funding support from the Gender & Work Initiative at the Johns Hopkins Carey Business School.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.17754 .

Commentary on “Getting Down to Business: Chain Ownership and Fertility Clinic”

2025-10-16T00:00:00+00:00

Management Science
History: Accepted by Christoph Loch, commentary.

“Be the Buyer”—Leveraging the Wisdom of the Crowd in E-Commerce Assortment Planning

2025-10-16T00:00:00+00:00

Management Science
E-commerce retailers often need to make inventory decisions for new products under high uncertainty. We study a new business practice of using crowdvoting, wherein a retailer first seeks input from customers on the desirability of the product and then bases the purchasing decision on their votes. We collaborated with a subscription-based apparel rental platform and obtained a proprietary data set comprising the platform’s products and users. We leverage the staggered introduction of crowdvoting in different product categories to identify whether and, if so, by how much the adoption of crowdvoting improves business performance. We find that, after the adoption, both short- and long-term rental outcomes increase. We also uncover several mechanisms that drive this improvement. We find that the platform uses the wisdom of the crowd to make better inventory depth decisions, and the products are inherently a better match with users’ tastes. Moreover, we find that brands bought through crowdvoting are more likely to be newer brands compared with items that are bought solely through expert input. In other words, the diversity of the brands carried on the platform also improves. We also find that voters become more engaged with the platform: they post more reviews and are less likely to cancel their subscription after participating in crowdvoting. Our results have important implications for retailers who may be considering similar crowd-based strategies to improve their decision making.This paper was accepted by Victor Martínez-de-Albéniz, operations management.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01928 .

Early Internationalization: A Meta‐Analysis of Antecedents, Dimensions, and Performance

2025-10-16T00:00:00+00:00

Journal of Management Studies
More than three decades after Oviatt and McDougall’s pioneering 1994 paper ‘Towards a theory of international new ventures’, the study of early internationalizing firms continues to captivate international business scholars. The research questions we address involve the antecedents of early internationalization, the dimensions of this phenomenon and its performance outcomes. In the present study, we include all three issues in a comprehensive meta‐analysis, thereby gaining a more complete understanding of the early internationalization process while building upon the various partial pathways identified in extant research. We use meta‐analytic structural equation modelling (MASEM) and build upon 426 samples from 378 empirical studies. We distinguish between the effects of individual‐level and firm‐level antecedents on the main dimensions of early internationalization – speed, scope, and intensity – and we assess the impact thereof on post‐entry performance. Our results provide a comprehensive overview of the constructs used in prior research, thereby laying the foundation for future empirical studies on early internationalization.

Digital Distractions with Peer Influence: The Impact of Mobile App Usage on Academic and Labor Market Outcomes

2025-10-17T00:00:00+00:00

The Quarterly Journal of Economics
Concerns about excessive mobile phone use among youth are mounting. We present estimates of both behavioral and contextual peer effects, along with comprehensive evidence on how students’ own and their peers’ app usage affect academic performance, physical health, and labor market outcomes. Our analysis draws on administrative data from a Chinese university covering three student cohorts over four years. We exploit random roommate assignments, differential exposure to a policy shock (gaming restrictions for minors), and differential exposure to a discrete event (the introduction of a blockbuster video game) for identification. App usage is contagious: a one s.d. increase in roommates’ in-college app usage raises own usage by 5.8%. High app usage is harmful across all measured outcomes. A one s.d. increase in app usage reduces GPAs by 36.2% of a within-cohort-major s.d. and lowers wages by 2.3%. Roommates’ app usage reduces a student’s GPAs and wages through both disruptions and behavioral spillovers, generating a total negative effect that exceeds half the magnitude of the impact from the student’s own app usage. Extending China’s three-hour-per-week gaming restriction for minors to college students would boost their initial wages by 0.9%. High-frequency GPS and app usage data show that heavy app users spend less time in study halls, are more frequently late or absent from class, and get less sleep.

Unintended Consequences of Closing Pay Gaps Across Multiple Groups: A Formal Modeling and Simulation Analysis of Allocation Methods

2025-10-17T00:00:00+00:00

Organization Science
In recent years, many firms have prioritized both pay equity (i.e., closing pay gaps associated with target groups such as women and racial minorities) and equitable representation (i.e., ensuring these target groups are fairly represented across a firm’s hierarchy). We use formal modeling and simulations to show how efforts to close pay gaps across multiple groups can undermine equitable representation. Specifically, our analysis suggests that pressure for pay equity creates a cost-based financial incentive to enact a subtle form of tokenism: A firm may minimize the cost of closing pay gaps if it maintains a workforce with a small number of minority women whom it pays well in order to compensate for underpaying larger numbers of majority women and minority men who resemble each other in terms of job attributes and personal qualifications. A firm can avoid these outcomes if it focuses on ensuring that employees from target groups are equitably rewarded for job attributes and personal qualifications rather than minimizing cost. But an equitable-rewards approach can be substantially more expensive than a cost-minimization approach, especially if pay gaps are larger in high-wage jobs or if there are many target groups. We conclude by offering testable empirical predictions and recommending a practical solution, namely to include terms for intersectional categories (e.g., minority women) in the regressions used to estimate pay gaps.Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2023.18306 .

Mutual Fund Revenue Sharing in 401(k) Plans

2025-10-17T00:00:00+00:00

Management Science
Recordkeepers in defined contribution (DC) pension plans are often paid indirectly in the form of revenue sharing from third-party funds on the menu. We show that these arrangements affect the investment menu of 401(k) plans. Revenue-sharing funds are more likely to be added to the menu and are less likely to be deleted. Overall, revenue-sharing plans are more expensive, as higher expense ratios are not offset by lower direct fees or by superior performance. Rebates increase with the market power of the recordkeeper, suggesting that third-party funds may share revenues to gain access to retirement assets.This paper was accepted by Camelia Kuhnen, finance.Funding: The research reported herein was performed pursuant to a grant from the TIAA-CREF Institute through the Pension Research Council/Boettner Center (PRC) of the Wharton School of the University of Pennsylvania.Supplemental Material: The internet appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01560 .

Contextual Offline Demand Learning and Pricing with Separable Models

2025-10-17T00:00:00+00:00

Management Science
This paper, inspired by a collaboration with a leading consumer electronics retailer in the Middle East, explores the challenge of demand learning and pricing using separable demand models. The data scarcity issue, characterized by limited price changes and low sales volumes, renders traditional models ineffective in deriving reasonable price elasticity. To address this issue, we advocate a separable model that leverages two submodels to distinctly capture the effects of price and contextual information. The separable structure enables us to invest special emphasis on the role of price and impose specific structural assumptions on the submodel for pricing effects, such as the monotone decreasing property. Theoretical analysis sheds light on the statistical complexity of demand learning with the separable structure, highlighting its capacity to reduce the necessary sample size to achieve a desired level of accuracy. We also introduce a computationally efficient iterative algorithm for deriving submodels from offline datasets, complete with convergence guarantees. In an empirical context, we demonstrate how our method can yield meaningful price elasticity estimations and revenue increase based on real sales data from the retailer.This paper was accepted by J. George Shanthikumar, data science.Funding: This work was supported by funding from the MIT Data Science Lab, Hong Kong Research Grants Council (RGC) General Research Fund [CityU11508223], and Hong Kong Research Grants Council (RGC) Early Career Scheme [CityU21505825].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.04026 .

Political Heterogeneity and Societal Polarization Impair Individual Performance: Evidence from Random Assignment in Professional Golf

2025-10-17T00:00:00+00:00

Management Science
We examine how political heterogeneity in groups affects individual performance in settings where people work alongside others. Leveraging the random assignment of golfers to groups in Professional Golfers’ Association Tour tournaments, we find that golfers score 0.2 strokes better per round when playing in politically homogeneous versus heterogeneous groups. This corresponds to a five-rank improvement before the tournament cut and an additional $13,000–$23,400 in tournament earnings. The effect intensifies during periods of high societal political polarization and diminishes when polarization is low. We propose that politically heterogeneous groups create a more stressful and less psychologically safe environment, reducing focus and leading to reduced performance. Consistent with this mechanism, analyses of shot-level data reveal that this effect is strongest during driving and putting shots when players are in close physical proximity. Our study contributes to the understanding of how political heterogeneity in groups affects individual performance in competitive settings, with implications for managing ideological differences in organizations.This paper was accepted by Sameer Srivastava, organizations.Funding: The authors appreciate financial help from Yale University and Fox International [fellowship].Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.01798 .

Incentivizing Information Exchange Within Groups: The Role of Voting Protocols in U.S. Food and Drug Administration Advisory Committees

2025-10-17T00:00:00+00:00

Management Science
Complex and important decisions are often made with advice from a committee of experts. But how do a committee’s “rules of engagement” affect the way individuals discuss, how they vote, and ultimately the quality of their collective recommendation? Compiling verbatim transcripts from U.S. Food and Drug Administration advisory committee meetings, we study how a 2007 switch from sequential to simultaneous voting procedures changed discussions, information exchange, and decision making. Consistent with past findings, we show that, compared with a sequential voting protocol, simultaneous voting led to a reduction in the likelihood of unanimous votes. Importantly, we show novel evidence that the majority of this reduction in unanimity was mediated by changes in discussion patterns—specifically, by the increased diversity of information surfaced during discussions. We also find evidence of behavioral and linguistic changes that support our theory that voting protocols changed the incentives for members to elicit more diverse information from each other: under simultaneous voting, members exhibited greater equality in talking time, directed a greater proportion of questions to each other, and adopted language that was more positive, authentic, and equal in projecting status and confidence. Finally, we show that recommendations under simultaneous voting were more likely to be accurate, as drugs recommended and approved were less likely to encounter safety-related postmarket events. In sum, voting protocols affect the incentives for individuals to engage in robust discussions, leading to marked improvements in how information is exchanged between individuals, and in the process by which groups of experts arrive at joint recommendations.This paper was accepted by Sridhar Tayur, entrepreneurship and innovation.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03649 .

The Competitive Ratio of Threshold Policies for Online Unit-Density Knapsack Problems

2025-10-17T00:00:00+00:00

Management Science
We study a wholesale supply chain ordering problem. In this problem, the supplier has an initial stock and faces an unpredictable stream of incoming orders, making real-time decisions on whether to accept or reject each order. What makes this wholesale supply chain ordering problem special is its knapsack constraint; that is, we do not allow partially accepting an order or splitting an order. The objective is to maximize the utilized stock. We model this wholesale supply chain ordering problem as an online unit-density knapsack problem. We study randomized threshold algorithms that accept an item as long as its size exceeds the threshold. We derive two optimal threshold distributions, the first is 0.4324-competitive relative to the optimal off-line integral packing, and the second is 0.4285-competitive relative to the optimal off-line fractional packing. Both results require optimizing the cumulative distribution function of the random threshold, which are challenging infinite-dimensional optimization problems. We also consider the generalization to multiple knapsacks, in which an arriving item has a different size in each knapsack. We derive a 0.2142-competitive algorithm for this problem. We also show that any randomized algorithm for this problem cannot be more than 0.4605-competitive. This is the first upper bound strictly less than 0.5, which implies the intrinsic challenge of the knapsack constraint. We show how to naturally implement our optimal threshold distributions in the warehouses of a Latin American chain department store. We run simulations on its order data that demonstrate the efficacy of our proposed algorithms.This paper was accepted by George Shanthikumar, data science.Funding: This work was supported by the Massachusetts Institute of Technology–Accenture Alliance for Business Analytics.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01577 .

Appearing Authentic: How Dress Formality Influences Perceived Authenticity in Investment Evaluations

2025-10-17T00:00:00+00:00

Journal of Management
This article explores the important but understudied topic of authenticity in investment evaluations. Building on research in authenticity and signaling theory, we theorize how visual first impressions, such as clothing, can generate perceptions of authenticity that lead investors to overlook later quality signals, including a lack of prior experience. We found support for our theory in two field studies and a randomized experiment: investors tend to perceive entrepreneurs who are casually dressed as more authentic than those formally dressed, which is associated with higher investor evaluations. Moreover, perceptions of authenticity generated by casual clothes crowd out later signals: Casually dressed entrepreneurs are evaluated highly regardless of their entrepreneurial experience, but formally dressed entrepreneurs are penalized for perceived inexperience. We discuss the implications of our findings for authenticity research, the temporal order of signals, and early-stage investments.

Presidential Address: Housing Betas

2025-10-17T00:00:00+00:00

The Journal of Finance
This paper documents new stylized facts about returns and cashflow growth rates on stocks and housing over decade‐long holding periods. While cashflow growth rates on the two assets comove positively, their returns comove negatively until the Global Financial Crisis and positively thereafter. These facts present a puzzle for representative‐agent models that imply positive return comovement for assets with similar cashflows. I consider a heterogeneous‐agent model with segmented stock and housing markets connected through credit. News about the aggregate economy generates negative return comovement. Recent shifts such as wealthier homebuyers and institutional housing purchases reduce the importance of credit and segmentation.

To Own or to Rent? The Effects of Transaction Taxes on Housing Markets

2025-10-18T00:00:00+00:00

Review of Economic Studies
Using sales and leasing data, this paper finds three novel effects of a higher property transaction tax: higher buy-to-rent transactions alongside lower buy-to-own transactions despite both being taxed, a lower sales-to-leases ratio, and a lower price-to-rent ratio. This paper explains these facts by developing a search model with entry of investors and households, households choosing to own or rent in the presence of credit frictions, and homeowners deciding when to move house. A higher transaction tax reduces homeowners’ mobility and increases demand for rental properties, which explains the empirical facts and leads to a lower homeownership rate. The deadweight loss is large at 111% of tax revenue, with more than half of this due to distorting decisions to own or rent.

Conceptual and Theoretical Perspectives on the Human Resource Management–Leadership–Well‐Being Link: Reviewing 20 Years of Empirical Research

2025-10-18T00:00:00+00:00

Human Resource Management
Human resource management (HRM) practices and leadership (LS) both impact the functioning and experiences of employees at work, or, in other words, their well‐being (WB). Over the last two decades, the body of empirical research on employee WB that considers aspects of HRM and LS has been growing. There is a myriad of theoretical perspectives, such as job resource theories, social exchange theory, and HRM theories, that can serve as the foundation for empirical inquiry. In addition, the interplay between HRM and LS in impacting employee WB can be conceptualized in many different ways, for example, parallel effects, moderation, and mediation. This literature review takes stock of two decades of empirical HRM–LS–WB research, examines its theoretical and conceptual assumptions, and its temporal developments. We find that the field views the link between HRM, LS, and WB predominantly as an exchange between employee and employer, has a strong tendency to combine social exchange theory with other theoretical frameworks, and is shifting to theories that place the employees at the center of inquiry (e.g., motivational theories). In terms of the interplay between HRM, LS, and WB, we observe a shift toward conceptualizations that focus on the enabling potential of LS and HRM for each other as well as models that focus on the indirect—rather than direct—effects of HRM and LS on WB. We discuss the findings and implications for future research.

The Devil is in the Details: Zooming out in Leadership Research

2025-10-19T00:00:00+00:00

Journal of Management Studies
Leadership research has evolved towards increasing conceptual and methodological precision, yielding refined constructs and robust empirical insights. However, this editorial argues that a singular focus on precision risks fragmenting the field and distancing scholarship from the complex realities of organizational life. Drawing on contributions fromJMS, this thematic collection illustrates how leadership is a dynamic, contextually embedded phenomenon shaped by interdependent forces. By ‘zooming out’, scholarship can better reflect the messy, adaptive nature of leadership and offer more actionable insights for leaders navigating today’s organizational challenges. We propose a multidimensional framework – breadth, depth, and height – to reintroduce complexity into leadership studies. Breadth captures the diversity of leadership styles and disciplinary perspectives; depth explores the psychological, symbolic, and relational undercurrents of those diverse perspectives; and height examines how diverse perspectives play out differently across hierarchical levels and systems.

The Double‐Edged Sword Effect of Green Human Resource Management Practices on Employees' Green Behaviors at Home

2025-10-02T00:00:00+00:00

Human Resource Management
While increasing evidence supports the workplace benefits of green human resource management (HRM) practices, this research explores how and when employees' experiences with these practices influence their green behaviors at home. Drawing on the work‐home resource model, this study examines the dual mechanisms of green job demands and resources while also exploring the moderating role of proactive vitality management. Study 1, a four‐wave time‐lagged survey, revealed that experienced green HRM practices were associated with both green job demands and green job resources. On the one hand, green job demands led to increased green job fatigue, which in turn reduced green behaviors at home. On the other hand, green job resources fostered green self‐efficacy, which subsequently enhanced green behaviors at home. Importantly, the negative indirect relationship between green HRM practices and green behaviors at home via green job demands and green job fatigue was stronger when employees' proactive vitality management was low, whereas the positive indirect relationship via green job resources and green self‐efficacy was stronger when proactive vitality management was high. Study 2, a four‐wave cross‐lagged survey, replicated the findings of Study 1 and further clarified the causal direction of these relationships. This research contributes to the literature on green HRM practices by uncovering their cross‐domain implications and highlighting both their benefits and costs.

From wells to windmills: Resource redeployment and new technology investment in the energy sector

2025-10-21T00:00:00+00:00

Strategic Management Journal
This study examines how multi‐business firms redeploy resources following an industry shock. Using the case of oil and gas firms diversified into wind power, I show that firms reduced expenditure in oil and gas—particularly on complex offshore projects—while increasing investment in wind after the 2014 oil price crash. These investments tended to involve newer, more powerful technologies (turbines) when co‐located with existing offshore oil and gas assets. The study provides detailed empirical evidence of resource redeployment and documents conditions under which firms shifted away from one industry and pursued more demanding projects in another. The findings underscore the role of asset colocation in shaping redeployment patterns. They also highlight that market‐based inducements may not be sufficient in driving the energy transition.Managerial SummaryHow should firms respond when a core industry experiences a downturn? This study shows that multi‐business firms—specifically oil and gas companies diversified into wind power—responded to the 2014 oil price crash by cutting investment in oil and gas, especially in offshore projects, and increasing investment in wind power. Importantly, firms were more likely to invest in newer, higher‐capacity wind technologies when they could co‐locate these with existing offshore oil and gas assets. These findings suggest that firms facing industry shocks can redeploy resources into more promising sectors, but their propensity to do so may depend on the possibility of leveraging existing assets across domains.

Price and Volume Divergence in China’s Real Estate Markets: The Role of Local Governments

2025-10-21T00:00:00+00:00

The Review of Financial Studies
During the COVID-19 pandemic (2020-2022), Chinese cities witnessed a paradox: residential land and new house prices surged while transaction volumes plummeted. We attribute this to local governments’ active price management through supply controls, land acquisitions by local government financing vehicles (LGFVs), and limits on new home sales permits. Cities more dependent on land sales and land-backed debt before the pandemic experienced greater price increases and price–volume divergence, with LGFVs buying more land at higher prices than other buyers. These interventions helped sustain fiscal financing but deepened developers’ financial distress, revealing unintended consequences of local governments’ fiscal strategies during downturns.

The Boundary of Open Data: Implications for the Financial Market and Real Efficiency

2025-10-21T00:00:00+00:00

Management Science
We analyze the optimal boundary for open data in an economy where financial and real-sector participants access both open and private data. The distinctive features of open access and nonrivalrous usage of open data enable its dual roles as a public information source and innovation input but raise privacy concerns. Our model reveals a novel tradeoff: Although enhanced private data precision and data skills substitute for open data’s information source role, its ability to amplify innovation benefits (via improved investment efficiency) establishes a crucial complementary relationship. This induces a crowding-in effect on the optimal open data boundary under low uncertainty but a crowding-out effect under high uncertainty. The innovation role of open data further generates nonmonotonic effects, yielding complex nonlinear impacts on market and real efficiency. These findings highlight critical policy tradeoffs in balancing innovation, market efficiency, and privacy in the digital age.This paper was accepted by Bo Becker, finance.Funding: Z. Wang acknowledges financing from the National Natural Science Foundation of China [Grants 72442025 and 72272028] and the Graduate Education Reform of Dongbei University of Finance and Economics [Grant yjzd202309]. Z. Qiu acknowledges financing from the Major Program of the National Natural Science Foundation of China [Grant 72192804] and the National Key Research and Development Program of China [Grant 2023YFC3304701].Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.03679 .

Firms’ Response to Credit Supply: Evidence from Upsized Corporate Bond Offerings

2025-10-21T00:00:00+00:00

Management Science
Firms often respond to information about investor demand, learned when underwriters build the book to place corporate bonds, by “upsizing” the offering amount. We examine the factors that predict two measures of realized credit supply (oversubscription and yield tightening) and show that the unexpected component of credit supply can explain firms’ upsizing decisions. Because firms’ fundamentals and need for capital are unchanged in the few hours of bookbuilding, upsizing provides a bond-level measure that can be used to study the impact of credit supply on postissuance leverage and investment. Firms use the sizeable additional proceeds to reduce bank debt and increase cash holdings; net increases in leverage are temporary for riskier issuers. Our evidence does not support concerns of overinvestment in periods of accommodative credit markets.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.2023.00153 .

Dynamic Portfolio Selection Under Quantile Maximization

2025-10-21T00:00:00+00:00

Management Science
Although maximizing quantiles is intuitively appealing and has an axiomatic foundation, it is difficult to find the optimal portfolio strategy because of time inconsistency. Using an intrapersonal equilibrium approach and focusing on the class of time-varying affine strategies, we find that the only viable outcome is from the median maximization because for other quantiles, either the equilibrium does not exist or there is no investment in risky assets. We also prove that maximizing the median endogenizes the use of portfolio insurance. The calibration of the model uncovers a new empirical phenomenon: “portfolio share smile.”This paper was accepted by Giesecke Kay, finance.Funding: This research was supported by the General Research Fund of the Research Grants Council of Hong Kong SAR [Grant 14207620], Early Career Scheme of the Research Grants Council of Hong Kong SAR [Grant 25213424], the National Natural Science Foundation of China [Grant 12401622], and the Hong Kong Polytechnic University [Grant P0042708].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.03182 .

When Do Individuals Believe in Themselves Rather Than in Artificial Intelligence? Insights from Longitudinal Investigations in Corporate Credit‐Rating Contexts

2025-10-21T00:00:00+00:00

Journal of Management Studies
Individuals often prioritize their own judgements rather than heeding the advice of artificial intelligence (AI). This study draws on the literature on anchoring theory and cognitive biases to explore the theoretical mechanisms underlying individuals’ reliance on AI advice and how this reliance affects decision performance. Specifically, we examined situations in which (1) individuals’ knowledge accumulated over time, (2) multiple information sources were available, and (3) AI could emulate users’ decisions. We developed a ‘corporate credit‐rating’ AI system that could provide more accurate advice than users. We then conducted two main longitudinal studies and four supplementary ones – six in total – with each study comprising three sessions. Our findings demonstrated that individuals’ initial estimates became more similar to AI advice over time. As the difference between individuals’ initial estimates and AI advice increased, individuals were more inclined to revise their initial judgements but showed lower relative dependence on AI. This effect, however, depended on the individuals’ experience in decision‐making. Additionally, introducing additional information reduced the similarity between the initial estimate and AI advice, but the proximity of additional information to AI advice facilitated individuals’ adjustment to the advice. We discuss the theoretical and practical implications of these results.

Welcome, stranger

2025-10-03T00:00:00+00:00

Strategic Management Journal
How can organizations establish collaboration between their established members and a newly hired member? We address this question by studying firms undergoing scaling using a multiple‐case study. We find that widely involving the new hire into the established managers' activities backfires. Such extensive involvement is intended to build the same kind of strong, personal relationships with the new hire that the established managers share amongst themselves and, in doing so, establish collaboration. But the established managers' relationships turn out to beirreplicable. Being extensively involved without possessing the same kind of relationships, the new hire becomes perceived as anintruder. In contrast, involving the new hire more selectively led to the new hire becoming respected as a relationally distant but professionally appreciated “stranger,” which engendered effective collaboration.Managerial SummaryCollaboration between a company's newly hired and established managers is necessary for it to scale but difficult to establish. Many firms mistakenly attempt to involve a new hire in the established managers' activities as much as possible, hoping to build strong personal bonds quickly. We show that this strategy often backfires. The kind of relationships that the established managers have is not easy to replicate, and widely involving the new hire in the absence of such relationships can spur the established managers to perceive the new hire as an intruder. Instead, limiting the new hire's involvement to only the activities directly linked to his or her job may result in the new hire becoming respected as a professional “stranger.” Doing so avoids the discomfort of forced closeness and facilitates effective collaboration.

EXPRESS: The Value of Blending - Managing Ameliorating Inventory Using Deep Reinforcement Learning

2025-10-03T00:00:00+00:00

Production and Operations Management
Stocks of some food products, such as whiskey, cheese, or port wine, ameliorate during storage, facilitating product differentiation according to age. This induces a trade-off between immediate revenues and further maturation. Inventory management decisions include purchasing volumes of agricultural produce and production volumes for age-differentiated products. Because products can be blended from stocks of different ages, issuance decisions offer operational flexibility. However, whereas some industries (port wine, sherry) only request that the product labels refer to the average age of issued stocks, others (whiskey, rum) have stricter blending regulations, requiring that the product labels represent the minimum age of all components. Further, producers must deal with multiple uncertainties. Purchase prices of agricultural commodities depend on volatile climate-dependent harvest seasons, stocks decay during maturation, and sales market conditions fluctuate. We solve this inventory management problem using a deep reinforcement learning algorithm with three key innovations: (i) a novel actor pipeline that decomposes the action space and flexibly partitions decision dimensions between a neural network and a lookahead optimization model, (ii) an algorithm explicitly maximizing average rewards, and (iii) reward-handling techniques that exploit structural problem insights. Our approach yields near-optimal policies that consistently outperform benchmark heuristics. Beyond the algorithmic contributions, our results offer new managerial insights into the value of blending under uncertainty. Minimum-age blending substantially enhances the profits of firms as compared to no blending because companies can adjust their purchasing policy in response to price fluctuations. The more flexible average-age regime further improves profits by 8.7% on average, suggesting that whiskey and rum regulators may wish to reconsider their strict blending rules. We mine black-box policies from deep reinforcement learning using supervised machine learning and Shapley values to analyze near-optimal decision drivers. Exploiting the value of blending requires producers to install sufficient processing capacity, especially when dealing with large variations in harvest seasons. Additionally, blending entails increased planning complexity because the inventory management decisions are driven by a large number of factors.

EXPRESS: Unveiling the Human Touch: Enhancing Customer Satisfaction through Personal Profiles of Social Media Customer Service Agents

2025-10-03T00:00:00+00:00

Production and Operations Management
Firms are rapidly adopting social media platforms to optimize their customer service operations. Given the central role of social media as a primary point of contact with customers and the critical importance of maintaining high levels of customer satisfaction, it is imperative to craft positive experiences during service interactions. To enhance customer interaction with a personal touch, U.S. telecom giant T-Mobile replaced standardized profiles with personal profiles for its social media customer service agents on Twitter. Leveraging this exogenous change, we investigate how these personal profiles affect customer behaviors within service operations. We adopt a Difference-in-Differences empirical strategy in this research. The results show that implementing personal profiles for customer service agents increases positive sentiment in customer tweets, reduces the likelihood of complaints, and improves overall satisfaction. Further analyses suggest that the effects vary across customer groups, with greater impact among verified Twitter users and female customers. While personalized agent profiles can enhance satisfaction, they also heighten expectations for timely responses, making delays more detrimental than with standardized profiles. To explore the underlying mechanism, we conduct an online randomized experiment. In addition to reinforcing the causal inference from our secondary data analysis, causal mediation analysis of the experimental data shows that personal agent profiles influence satisfaction and the likelihood of customers expressing gratitude through the perceived warmth and perceived competence of the agents. Interestingly, while the effect on gratitude is mediated by humanization, we do not find a similar mediation effect on satisfaction. This suggests distinct pathways through which humanization shapes different aspects of the customer experience.

EXPRESS: Conformity or Differentiation? How Consumers Respond to the (In)consistency between Product Ratings and Review Sentiments in the US and China

2025-10-03T00:00:00+00:00

Production and Operations Management
This research investigates the joint impact of numeric ratings and review sentiments in prior product reviews on consumers’ product evaluations and how this impact varies between individualist and collectivist cultures. Using data on 115,231 consumer reviews of 167 American movies released both in the US and China, the authors find that the joint impact of movie ratings and review sentiments varies with the consistency between the two information sources, as well as their valence. Furthermore, their analysis reveals that the joint impact differs between the two cultures. The authors suggest that these findings may arise because consumers’ perception of information credibility varies depending on the information consistency and their cultural background. The findings offer important implications for firms in managing UGC platforms for consumers’ product reviews and social media across global markets.

Beyond Cookies: Evidence About Team Coproduction and Engagement Retention From Girl Scouts Cookie Program

2025-10-03T00:00:00+00:00

Production and Operations Management
Retention is a critical challenge for organizations, especially nonprofits, which often face higher turnover than for-profit firms. Unlike many for-profits, nonprofits have fewer financial resources to retain participants, so continued participation depends more on team climate and opportunities to learn by working together. We study these dynamics in the Girl Scouts Cookie Program. We collect sales and troop membership information between 2016 and 2018 from a local Girl Scout council consisting of approximately 30,000 members. We examine the effects of a group of three team diversity features: Disparity, variety, and separation, on a Girl Scout’s decision to return to sell cookies the following year. Our results suggest that a more evenly distributed sales performance within the troop (i.e., low sales disparity) is associated with higher retention, with larger gains for lower sellers. In addition, greater grade level (i.e., age) variety is associated with higher retention for both younger and older participants. Furthermore, mixing newcomers with returnees (i.e., high return-status separation) has asymmetric dual effects: High return-status separation tends to discourage new girls from returning while encouraging returning girls to stay. Finally, we find that returning participants tend to sell more in subsequent years, consistent with learning-by-doing. These empirical results have implications for the Girl Scouts of the USA and other similar nonprofit organizations to compose teams and organize collaboration activities to improve engagement and enhance learning.

EXPRESS: No News about Climate Action Is Good News for Low-Polluting Firms

2025-10-03T00:00:00+00:00

Production and Operations Management
Media plays a crucial role in shaping public perception of firms, significantly impacting their operations and performance. Firms often attempt to influence media channels to showcase their climate action initiatives, aiming to enhance their public image, reputation, and stakeholder trust. While firms cannot directly control their media coverage, intentional or unintentional dissemination of their climate action efforts can thrust them into the media spotlight. The implications of this media spotlight remain uncertain. While firms may anticipate positive public relations benefits from such exposure, it may also raise environmental expectations for the firm and risk highlighting less favorable aspects of their environmental practices. Despite previous research on the impact of media exposure on firms’ financial outcomes, a notable gap exists in understanding how the media spotlight on firms’ climate actions affects their operational and financial performance. A clear hurdle is the lack of a systematic and objective measurement of such a spotlight. Our study addresses this research gap by developing a machine learning-based framework to derive a climate action vocabulary as a novel information artifact. The vocabulary is subsequently used to measure the intensity of media attention on a firm’s climate actions. Our research reveals that an increased media spotlight on climate actions, regardless of their sentiment, has an adverse effect on firms’ financial performance, primarily due to the rise in operational costs. Furthermore, we find that the impact of media spotlight is heterogeneous. Low-polluting firms experience negative financial consequences as the downside of the heightened media spotlight. In contrast, high-polluting firms and those operating in polluting industries may witness an overall positive financial impact. We also find that firms’ market orientation (B2B vs. B2C), durability classification, index constituency (i.e., S&P 500), and greenwashing status significantly moderate the relationship. Our research highlights key considerations for corporate leaders with respect to the drawbacks for low-polluting firms in seeking media attention for their climate actions. Given that the media captures society’s limited attention, our research suggests that firms should refrain from promoting superficial narratives about climate change that distract society from more impactful sustainability conversations.

Capacity Planning in Stable Matching

2025-10-03T00:00:00+00:00

Operations Research
Optimizing School Seat Allocation to Improve Access and FairnessA growing shortage of public school seats in Chile has left thousands of students unassigned each year. In their forthcoming Operations Research paper, “Capacity Planning in Stable Matching,” Bobbio et al. (2025) develop a novel framework that jointly determines where to expand school capacities and computes a student-optimal stable assignment in the enlarged market. The study develops exact and heuristic methods that make this theoretically complex problem tractable in practice. Using rich administrative data from the Chilean school choice system, the framework demonstrates how adding a limited number of seats can trigger improvement chains benefiting multiple students, also revealing diminishing marginal returns to capacity expansion. Beyond the Chilean context, the framework provides a versatile toolkit that can be adapted to other constrained allocation problems, offering a rigorous foundation for data-driven policy design in education and beyond.

EXPRESS: Improving the Discriminant Validation of Multi-Item Scales

2025-10-03T00:00:00+00:00

Journal of Marketing Research
Discriminant validation examines to what extent constructs measured with multi-item scales, which are hypothesized to be conceptually distinct, are empirically distinct. A literature review of published scale development studies shows that a variety of criteria and approaches to assess discriminant validity are in use. However, the requirements for an appropriate criterion have not been spelled out, which has led to the use of problematic criteria. The present research introduces three requirements that an appropriate discriminant validation criterion should satisfy, concerning the correlation, comparison standard, and comparison method. It shows that the common Fornell and Larcker criterion is based on an inappropriate comparison standard and method and that alternative criteria have weaknesses as well. The authors therefore propose an improved comparison standard, congeneric reliability (CR), and develop a systematic discriminant validation procedure based on CR and an existing criterion (Phi), both of which satisfy the three requirements. The procedure provides continuous measures of support for discriminant validity and accounts for measurement and sampling error. A detailed case study and reanalyses of seven published scale development articles demonstrate the application and strengths of the procedure. Example code and an online application facilitate its implementation.

The Double-Edged Roles of Generative AI in the Creative Process: Experiments on Design Work

2025-10-03T00:00:00+00:00

Information Systems Research
Generative AI (GenAI) promises to revolutionize creative work, but its value is not universal. Using controlled lab settings with students and real-world tests with professional designers, our research shows that GenAI is a double-edged tool. In the initial brainstorming (ideation) stage, GenAI reliably boosts creativity for all users. However, in the execution (implementation) stage, whereas novice designers continue to benefit from GenAI’s assistance, expert designers encounter inefficiencies—spending significantly more time without improving creativity, because GenAI’s methods conflict with experts’ well-established routines. For firms, this means adoption strategies must be nuanced. GenAI delivers the greatest value when applied to brainstorming, early concept development, and work by less-experienced employees. In contrast, deploying GenAI in later-stage production tasks, especially with seasoned professionals, may reduce efficiency. Managers and tool designers should avoid blanket promotion of GenAI across all tasks and instead develop targeted adoption strategies that align with employees’ expertise and the stage of the creative process. By tailoring GenAI use, organizations can harness its creative potential while minimizing risks of counterproductive outcomes.

Family‐Friendly Work Systems: A Systematic Review, Critical Assessment, and Future Research Agenda of the Work‐Life Benefits Literature

2025-10-03T00:00:00+00:00

Human Resource Management
The increasing awareness and use of family‐friendly work activities (FFWAs), also known as work‐life benefits, highlights their importance for both employees and organizations. Despite the importance of these activities for both employees and organizations, the existing literature is fragmented, lacking a clear consensus on their conceptualization and measurement. In this review, we content analyze conceptual and methodological aspects of the FFWA literature. Specifically, applying the systems perspective from the strategic human resource management (SHRM) literature, we introduce and conceptualize family‐friendly work systems (FFWS), define their key domains, specify the FFWAs within them, and clarify their hierarchical structure (i.e., policies, practices, and processes). Building on the FFWS model, we evaluate potential sources of heterogeneity in current research. By identifying inconsistencies as well as strengths and weaknesses in the existing literature, this review provides a timely contribution that can guide future research and offer practical recommendations for policymakers and organizations striving to create more family‐friendly workplaces.

Bridging Moral Aspirations and the Mundane Reality: A Grounded Study of the Process of Radical Purpose Adaptation in a Business School

2025-10-04T00:00:00+00:00

Journal of Management Studies
In previous research, scholars have often highlighted the important role of leaders in defending and protecting a historical organizational purpose. However, adopting such a ‘backward‐looking’ perspective, researchers have devoted much less attention to understanding how an organizational purpose can be deliberately changed and leveraged to justify novel moral commitments, thereby bridging the moral and the mundane. We theorize these activities as a process of radical purpose adaptation, whereby an established organization deliberately and radically changes its purpose to align with its commitment to society. We draw on a single, longitudinal case study of a business school as it engaged in the process of changing its organizational purpose. Adopting a social‐symbolic work lens, we conceptualize purpose as a social‐symbolic object and theorize purpose work, which captures leaders’ efforts to establish new organizational aspirations. We find that proactive purpose work leads to the unintended emergence of self‐reinforcing, competing demands that threaten the new purpose, which are tackled through reactive purpose work. Thus, a recursive process emerges in which proactive and reactive purpose work operate in tandem: proactive work generates novel aspirations and tensions, while reactive work contains and redirects them, enabling organizations to stabilize new commitments without abandoning their transformative intent.

Concentration in cross‐border research collaborations and MNCs' knowledge creation in a host country

2025-10-05T00:00:00+00:00

Strategic Management Journal
This study elucidates the previously underexplored structural heterogeneity inherent in multinational corporations' (MNCs) internal linkages by examining the concentration of cross‐border collaborations among inventors within host countries. Building on the boundary spanning literature, we develop a two‐stage framework identifying the knowledge distortion mechanism arising from this concentration: information overload in the cross‐country knowledge absorption stage and long transmission paths and knowledge hoarding in the within‐country diffusion stage. Both hinder local knowledge creation. We further propose that cross‐country and within‐country network structures serve as contingencies moderating this relationship. The negative effects of collaboration concentration are exacerbated by structural holes in cross‐country networks but attenuated by the reach and density of within‐country networks. Empirical results based on American pharmaceutical MNCs from 1980 to 2008 support our hypotheses.Managerial SummaryEffectively structuring internal cross‐border R&D collaborations is crucial for MNCs seeking to enhance local innovation outcomes. Although many firms focus on increasing cross‐border linkages, this study highlights that overlooking how collaborations are distributed among inventors can obscure key drivers of innovation performance. This research shows that given the number of cross‐border linkages, their concentration in the hands of a few inventors within a host country hinders local knowledge creation. The negative effect is amplified when the host country spans many structural holes in the cross‐country network. A well‐structured within‐country network with high reach or high density can help mitigate the effect by facilitating knowledge diffusion. Our findings highlight the importance of considering the structural and geographic configuration of internal MNC networks in global R&D strategy.

An Analysis of Laparoscopic and Robotic Minimally Invasive Surgeries: Surgeon Experience, Learning, and Task Performance

2025-10-05T00:00:00+00:00

Journal of Operations Management
The study examines the transfer of learning in the context of different surgical methods used to complete surgical procedures. Surgeons' total experience is characterized by the procedure (i.e., focal or different) and the surgical technology or method used (i.e., laparoscopic‐assisted minimally invasive surgery [LAS] or robot‐assisted minimally invasive surgery [RAS]). Using data from a large US university hospital with specialized surgical departments, and drawing on task‐technology fit and fit appropriation model theories, we propose three novel hypotheses that focus on different facets of how learning transfers across methods and tasks for individuals. The findings contribute to research on individual learning by distinguishing between method learning (how the task is performed) and task learning (the knowledge of the task itself). We find the following key findings. First, the experience from the RAS (LAS) method has a significant (no) effect in reducing LAS (RAS) duration for the same procedure. Second, learning from other procedures is contingent on the method used to complete the task. Specifically, the experience from other procedures completed using the LAS (RAS) method increases (decreases) the LAS (RAS) duration. Overall, the results indicate that the transfer of learning from RAS to LAS is greater than from LAS to RAS. This suggests that learning transfer across technologies is asymmetrical and requires careful consideration regarding how accumulated surgical experience from various technologies impacts task performance. From a task‐technology fit and fit appropriation model theory perspective, our study highlights the importance of technologies' capabilities in knowledge transfer across methods.

Internal venturing as a signal: How entrepreneurial employees gain career benefits in organizations

2025-10-06T00:00:00+00:00

Strategic Entrepreneurship Journal
Do employees benefit from acting entrepreneurially in a corporate environment? Drawing on signaling theory, we propose that entrepreneurial behaviors lead to tangible career benefits through the creation of new internal ventures, which serve as a credible signal of an employee's leadership potential. Using a time‐lagged design with a sample of 643 employees, we found in Study 1 that employees engaging in higher levels of entrepreneurial behaviors are more likely to create new internal ventures, which subsequently lead to more promotions and—in larger organizations—higher compensation. Study 2 employed a within‐subjects design to directly evaluate the signaling value of new internal venture creation. Together, our findings highlight internal venturing as a key mechanism through which entrepreneurial employees can gain career benefits within established organizations.Managerial SummaryEntrepreneurial employees are often seen as organizational misfits. Yet, our research shows that acting entrepreneurially in a corporate environment can enhance employees' career success through new internal venture creation. In two studies, we find that employees engaging in higher levels of entrepreneurial behaviors—asking questions to challenge the status quo, observing with fresh perspectives, exchanging ideas across diverse networks, and experimenting with new approaches—are more likely to launch new internal corporate ventures. The act of new internal venture creation, in turn, leads to more promotions and—in larger organizations—higher compensation, because it sends a positive signal of an employee's leadership potential. Our findings offer practical insights for both entrepreneurial employees and organizations seeking to foster entrepreneurial spirit.

Educating Investors about Dividends

2025-10-06T00:00:00+00:00

The Review of Financial Studies
We educate investors about the benefits of dividend reinvestment and costs of misperceiving dividends as free income. The intervention increases planned dividend reinvestment in survey responses. Using trading records, we observe a causal increase in dividend reinvestment in the field of roughly 50 cents for every euro received. This holds relative to investors’ prior behavior and various control samples. Investors who learned the most from the intervention update their trading the most. The results suggest the free dividends fallacy is a significant source of dividend demand. Our study demonstrates that simple, targeted, and focused educational interventions can affect investment behavior.

Collateral Effects: The Role of FinTech in Small Business Lending

2025-10-06T00:00:00+00:00

The Review of Financial Studies
This paper investigates the impact of introducing junior unsecured loans (i.e., FinTech loans) into the small business lending market. Using French administrative data, we find that firms experience a 13% increase in bank credit after receiving a FinTech loan. We use propensity score matching procedures and a shift-share instrument to account for credit demand. The credit increase only occurs when FinTech borrowers invest in new assets, and Fintech borrowers are subsequently more likely to pledge collateral to banks. This suggests that firms use FinTech loans to acquire assets that they then pledge to banks, thereby increasing total borrowing capacity.

Patents, News, and Business Cycles

2025-10-06T00:00:00+00:00

Review of Economic Studies
We exploit information in patent applications to construct an instrumental variable for the identification of technology news shocks that relaxes all the identifying assumptions traditionally used in the literature. The instrument recovers news shocks that have no effect on aggregate productivity in the short-run, but are a significant driver of its trend component. The shock prompts a broad-based expansion in anticipation of the future increase in total factor productivity (TFP), with output, consumption, and investment all rising well before any material increase in TFP is recorded. Despite the positive conditional comovements, the shock only accounts for a modest share of fluctuations of macroeconomic aggregates at business cycle frequencies. Financial markets price-in news shocks on impact, while most of the macro aggregates respond with some delay.

The Origins and Control of Forest Fires in the Tropics

2025-10-06T00:00:00+00:00

Review of Economic Studies
Environmental externalities – uncompensated damages imposed on others – lie at the root of climate change, pollution, deforestation and biodiversity loss. Empirical evidence is limited, however, as to how externalities drive private decision making. We study one such behavior, illegal tropical forest fires, using 15 years of daily satellite data covering over 107,000 fires across Indonesia. Weather-induced variation in fire spread risk and variation in who owns surrounding land allow us to identify how far externalities influence the decision to use fire. Relative to when all spread risks are internalized, we find that firms overuse fire when surrounded by unleased government lands where property rights are weak. In contrast, and consistent with the Coase Theorem, firms treat risks to nearby private concessions similarly to risks to their own land. Government sanctions, concentrated on fires spreading to populated areas, also deter fires, consistent with Pigouvian deterrence.

The Macroeconomic Consequences of Exchange Rate Depreciations

2025-10-06T00:00:00+00:00

The Quarterly Journal of Economics
We study the consequences of “regime-induced” exchange rate depreciations by comparing outcomes for peggers versus floaters to the U.S. dollar in response to a dollar depreciation. Pegger currencies depreciate relative to floater currencies and these depreciations are strongly expansionary. The boom is associated with a fall in net exports, and (if anything) an increase in interest rates in the pegger countries. This suggests that expenditure switching and domestic monetary policy are not the main drivers of the boom. We show that a large class of existing models cannot match our estimated responses and develop a model with imperfect financial openness that can. Following a depreciation, uncovered interest parity deviations lower the costs of borrowing from abroad and stimulate the economy, as in the data. The model is consistent with (unconditional) exchange rate disconnect and the Mussa fact, even though exchange rates have large effects on the economy.

Retargeting Social Media Outreach for SNAP Take-Up

2025-10-06T00:00:00+00:00

Management Science
In a California field experiment, I investigated the impact of a Facebook outreach campaign aimed at increasing enrollment in the Supplemental Nutrition Assistance Program (SNAP). The campaign used a promising marketing strategy known as “retargeting,” where ads were delivered to a randomly selected subset of over 16,000 eligible nonparticipants who had nearly completed the SNAP application process, while a control group remained unaffected. Despite leveraging ad content developed in collaboration with nonprofit and government partners, the campaign did not produce statistically or economically significant increases in enrollment, even when considering the extreme values of estimated confidence intervals.This paper was accepted by Jean-Pierre Dube, marketing.Funding: This work was supported by Code for America and the National Institute on Aging [Grant T32-AG000186].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06312 .

Unlocking Privacy in Healthcare: The Impact of Explanations on Privacy Concerns and Self‐Disclosure to Conversational Technologies

2025-10-06T00:00:00+00:00

Journal of Operations Management
While artificial intelligence (AI)‐based conversational technologies offer exciting prospects in healthcare, the lack of transparency and elevated privacy concerns in using such technologies remain a challenge and make much‐needed information difficult to obtain while administering patient care. Approaches that emphasize transparency and interpretability of AI systems provide a promising avenue to address these concerns. In this study, we explore the role of transparency‐enhancing explanations as a way for caregivers to elicit truthful disclosure of otherwise private information from patients. Specifically, we explore how automated explanations provisioned by conversational technologies can help reduce the user's privacy concerns and bring about self‐disclosure, thus helping to improve key outcomes such as accurate diagnosis and effective treatment. Through an online experiment with 556 participants in a healthcare context, we uncover the mediating effects of two critical factors, informational justice and perceived relevance, on privacy concerns. We find that explanations foster perceptions of informational justice and perceived relevance in the user, which help reduce privacy concerns and bring about self‐disclosure. The study's findings have implications for researchers as well as practitioners who leverage conversational technologies in healthcare and other service contexts.

Subtle Discrimination

2025-10-06T00:00:00+00:00

The Journal of Finance
We introduce the concept ofsubtle discrimination—biased acts that cannot be objectively ascertained as discriminatory. When candidates compete for promotions by investing in skills, firms' subtle biases induce discriminated candidates to overinvest when promotions are low‐stakes (to distinguish themselves from favored candidates) but underinvest in high‐stakes settings (anticipating low promotion probabilities). This asymmetry implies that subtle discrimination raises profits in low‐productivity firms but lowers them in high‐productivity firms. Although subtle biases are small, they generate large gaps in skills and promotion outcomes. We derive further predictions in contexts such as equity analysis, lending, fund flows, banking careers, and entrepreneurial finance.

Going for Broke: Bank Reputation and the Performance of Opaque Securities

2025-10-06T00:00:00+00:00

The Journal of Finance
Can banks’ reputational concerns improve the quality of opaque, off‐balance sheet securities, such as mortgage‐backed securities? We study this question in a uniquely parsimonious setting. In the 1760s, Dutch banking partnerships securitized West‐Indian plantation mortgages that were risky and opaque. High‐reputation banks originated better mortgages and issued securities that, on average, retained 17.5% more of their value during a market collapse. Reputational effects are attenuated when the managing partners were married into wealth or received a large share of profits in the short term, suggesting that bank reputation only works if bankers are personally exposed to (long‐run) reputational losses.

The Stock Market and Bank Risk‐Taking

2025-10-06T00:00:00+00:00

The Journal of Finance
Using confidential supervisory risk ratings, we document that banks increase risk after going public compared to a control group of banks that filed to go public but withdrew their filings for plausibly exogenous reasons. The increase in risk improves short‐term performance at the expense of long‐term performance. We argue that the increase in risk stems from pressure to maximize short‐term stock prices and earnings once the bank is publicly traded. After going public, banks owned by investors that place greater value on short‐term performance increase risk more, and those managed by CEOs with more short‐term compensation also increase risk more.

Unveiling the Strategic Impacts of Extending Membership-Based Free Shipping Programs Beyond the Online Marketplaces

2025-10-06T00:00:00+00:00

Information Systems Research
Online marketplaces are increasingly extending their membership-based free shipping (MFS) programs to include external sellers, transforming logistics capabilities into a “logistics-as-a-service” (LaaS) model. This study uses a game-theoretic approach to analyze the implications of such extensions, with Amazon as a leading example. Contrary to the widespread belief that LaaS is a stand-alone profit center, our findings reveal that the primary value of extended MFS lies in enhancing the marketplace’s core business. By attracting member consumers and optimizing fulfillment operations, marketplaces can increase commission revenues and reduce per-order logistics costs—even if LaaS itself operates at a loss. Importantly, this strategy can benefit the broader marketplace ecosystem, including both internal and external sellers and member consumers, while potentially disadvantaging nonmembers. For practitioners and policymakers, these results underscore the need to rethink competitive dynamics and pricing strategies in digital platforms. Rather than viewing extended MFS solely as a logistics monetization tool, it should be seen as a strategic lever for shaping marketplace structure, seller participation, and consumer behavior.

Anti‐labor environments and employee entrepreneurship: Evidence from right‐to‐work laws

2025-10-07T00:00:00+00:00

Strategic Entrepreneurship Journal
We explore how changes in labor unions and related labor environments affect employees' likelihood of starting a new business. We suggest that the enactment of stringent anti‐union laws reduces incentives for employees to stay with their respective workplaces and increases the attractiveness of becoming self‐employed. Using the adoption of right‐to‐work (RTW) laws in Michigan and Indiana as a quasi‐natural experiment, we find that the likelihood of employees becoming self‐employed increased by 53% compared with that of states without RTW laws. Moreover, this tendency is more pronounced for blue‐collar and low‐wage workers who start unincorporated businesses. These findings offer novel insights on the relationship between anti‐labor environments and necessity‐driven entrepreneurship by focusing on individual‐level incentives in non‐knowledge‐intensive sectors.Managerial SummaryChanges in employment conditions influence employees to consider starting their own businesses, yet our understanding of how these changes drive individuals toward entrepreneurship remains limited. This study explores how weakened labor union power affects workers' engagement in entrepreneurial activities, with a focus on the types of employees impacted and the businesses that they start. By examining the adoption of RTW laws in Michigan and Indiana, we find that weakened labor union power disproportionately affects blue‐collar and low‐wage workers, increasing their likelihood of starting unincorporated businesses. These results suggest that managers and policymakers should consider the challenges faced by these workers and how changes in employment conditions may shape their career choices.

Regulating CEO Pay: Evidence from the Nonprofit Revitalization Act

2025-10-07T00:00:00+00:00

The Review of Financial Studies
This paper examines CEO pay at nonprofits. Using compensation data for 14,111 nonprofits, we find that CEO pay dropped by 2% after legislation in New York reduced CEOs’ ability to influence their own pay. Despite lower pay, CEOs exerted more effort, and nonprofit performance improved. The effects were stronger at commercial nonprofits than at charities and for male CEOs than female CEOs. These findings are consistent with a model where some nonprofit CEOs derive meaning from their work and compensation can be rigged. Overall, our results suggest that regulation that targets the pay-setting process can improve organizational outcomes at nonprofits. (JEL G30, G32)

Anticipatory Trading Against Distressed Mega Hedge Funds

2025-10-07T00:00:00+00:00

The Review of Financial Studies
Stocks expected to be sold by distressed mega hedge funds (MHFs) face anticipatory institutional selling and increased short interest. However, no evidence of anticipatory trading is found in stocks held by nondistressed MHFs, distressed non-MHFs, or stocks confidentially held by distressed MHFs, suggesting that public portfolio disclosure by large and closely followed distressed investors, and not common investment signals, drives anticipatory trading. Distressed MHFs with greater exposure to such anticipatory trading suffer 2.21% lower style-adjusted returns. Stocks subject to anticipatory trading experience negative abnormal returns followed by reversals, indicating the price destabilizing effect of anticipatory trading. (JEL G12, G20, G23)

What Do Policies Value?

2025-10-07T00:00:00+00:00

Review of Economic Studies
When a policy prioritizes one person over another, is it because they benefit more, or because they are preferred? This paper develops a method to uncover the values consistent with observed allocation decisions. We estimate how much each individual benefits from an intervention, and then reconcile the allocation with (i) the welfare weights assigned to different people; (ii) heterogeneous treatment edects of the intervention; and (iii) weights on different outcomes. We demonstrate this approach by analyzing Mexico’s PROGRESA anti-poverty program. The analysis reveals that while the program prioritized certain subgroups — such as indigenous households — the fact that those groups benefited more implies that the program did not actually assign them a higher welfare weight. We also find evidence that the policy valued outcomes differently from households. The PROGRESA case illustrates how the method makes it possible to audit existing policies, and to design future policies that better align with values.

What Happens to Corporate Investment in Bad Times?

2025-10-07T00:00:00+00:00

Management Science
Recent studies suggest monitoring increases during economic downturns. In this study, we test whether firms’ abnormal investment activity changes across the business cycle. Focusing on recessions, we find that firms not only curtail overinvestment but also reduce underinvestment, with the combined effect representing a significant 9% of average investment. Employing various proxies for monitoring intensity, we demonstrate that stronger governance mechanisms are associated with more pronounced reductions in abnormal investment. Importantly, the influence of governance on abnormal investment is magnified during recessions relative to other periods. These results are robust to a wide array of control variables, methodologies, and potential endogeneity concerns. Our findings underscore the time-varying benefits of corporate monitoring and highlight the periods when governance mechanisms may be most effective.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.2024.04350 .

CEO Stress, Aging, and Death

2025-10-07T00:00:00+00:00

The Journal of Finance
We assess the long‐term effects of managerial stress on aging and mortality. Using a difference‐in‐differences design, we apply neural network–based machine‐learning techniques to CEOs' facial images and show that exposure to industry distress shocks during the Great Recession produces visible signs of aging. We estimate a one‐year increase in “apparent” age. Moreover, using data on CEOs since the mid‐1970s, we estimate a 1.1‐year decrease in life expectancy after an industry distress shock, but a two‐year increase when antitakeover laws insulate CEOs from market discipline. The estimated health costs are significant, both in absolute terms and relative to other health risks.

Value without Employment

2025-10-07T00:00:00+00:00

The Journal of Finance
Young firms' contribution to aggregate employment has been underwhelming. We show that a similar trend is not apparent, however, in their contribution to aggregate sales or stock market capitalization, implying that these firms have exhibited a high average‐to‐marginal revenue product of labor. We study the implications of a gradual shift in the average‐to‐marginal revenue product of labor within a model of dynamic firm heterogeneity. We show that this shift provides (i) a unified explanation for several aspects of the decline in dynamism and (ii) a possible explanation for why large declines in young‐firm employment may have only a moderate effect on aggregate output and consumption.

Asset Pricing and Risk‐Sharing Implications of Alternative Pension Plan Systems

2025-10-07T00:00:00+00:00

The Journal of Finance
We show that incorporating defined benefit pension funds in an incomplete markets asset pricing model improves its ability to match the historical equity premium and riskless rate and has important risk‐sharing implications. We document the importance of the pension fund's size and asset demands, and a new risk channel arising from fluctuations in the fund's returns. We use our calibrated model to study the implications of a shift to an economy with defined contribution plans. The new steady state is characterized by a higher riskless rate and a lower equity premium. Consumption volatility increases for retirees but decreases for workers.

Beyond Pairwise Network Interactions: Implications for Information Centrality

2025-10-07T00:00:00+00:00

Information Systems Research
Organizations and policymakers increasingly rely on network metrics to decide whom to inform, monitor, or support. Yet most networks treat interactions as pairs, even when the underlying activity occurs in groups—project teams, chat channels, meetings, or news articles that mention multiple firms. Collapsing groups into one-to-one links can misidentify who matters. We propose a practical alternative: Model group interactions directly as a hypergraph and compute centrality from a two-step diffusion process that captures how information moves across and within groups. The approach provides a transparent way to incorporate domain knowledge (e.g., whether people enter large or small groups first) and produces testable interpretable rankings. We evaluate the method in three settings—open-source software, a high school interaction study, and financial comentions—and find that hypergraph-based, theory-informed centrality better explains outcomes such as project success, student popularity, and same-day returns than standard graph centralities. For practice and policy, this yields more effective targeting, earlier warning signals, and improved allocation of attention and resources in collaborative work, public health, and market surveillance. We release an open-source Python package (HyperCentral) to support adoption.

Tight, Loose, or Denied Holding: How Interpersonal Holding Shapes Innovators’ Responses to Innovation Obstacles

2025-10-08T00:00:00+00:00

Organization Science
Innovating at work often requires persistence through distressing obstacles and failures. When innovators experience such distress, they may engage colleagues for interpersonal holding—a process in which the colleague (i.e., “holder”) helps contain the innovator’s distress and provides new ways of understanding the obstacle that incited that distress. Prior research has made great strides in explaining what holding processes share in common across different individuals and in different contexts. However, through an inductive study based on 91 semistructured interviews with 74 innovators in a large hospital system, we find significant variation in the dynamics of interpersonal holding. Our analysis uncovered three distinct “interpersonal holding trajectories”—tight holding, loose holding, and denied holding trajectories. At the heart of these trajectories are distinct interpersonal holding episodes. Each episode varies by how holders engage with the innovators’ distress and the obstacles that caused the distress. These distinct episodes uniquely reinforced (or not) our informants’ innovator identities, ultimately influencing divergent responses to the obstacles that they faced. By building theory from the perspective of those who seek holding, our findings highlight important divergences in how interpersonal holding may unfold and identify important implications for innovators and their organizations.Funding: This work was supported by Globoforce.

Intraday Liquidity and Money Market Dislocations

2025-10-08T00:00:00+00:00

Management Science
This paper proposes a new model of monetary policy implementation to account for two key developments: (i) the introduction of intraday liquidity requirements and (ii) the decreasing relevance of the federal funds market in favor of repurchase agreement (repo) markets with nonbank participants. Our paper studies how liquidity requirements prevent banks from arbitraging between the fed funds and repo markets and generate large repo spikes. We propose a simple measure of excess intraday reserves. Consistent with our theory, this metric is close to zero in 2019Q2, when U.S. repo markets experienced a spike of 400 basis points.This paper was accepted by Lukas Schmid, finance.Funding: This work was supported by Fama-Miller Center for Research in Finance, Booth School of Business, University of Chicago.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.04037 .

Overcoming Deceptive Evasions in Earnings Calls: The Role of Investor Suspicion

2025-10-08T00:00:00+00:00

Management Science
Evasive responses enable managers to escape difficult questions in earnings calls without lying. Although such tactics are common in corporate communication and other important settings, we still know little about how investors and other listeners can avoid being misled by them. Drawing on theories from multiple disciplines, I predict that a common type of nonanswer leads to equivocal interpretations, whereas artful dodges escape detection in earnings calls. However, when investors adopt a suspicious state of mind—characterized by suspended judgment, balanced information search, and consideration of plausible rival possibilities—they are better able to distinguish potentially deceptive evasive tactics from proper responses. My experimental results support these predictions, showing that suspicious thinking allows investors to overcome nonanswers and dodges without punishing adequate responses. I also provide evidence that nonanswers and dodges are unique evasive strategies and that simple interventions aligned with the context of earnings calls can prompt suspicion. These findings contribute to research on the informational role of earnings calls and offer new insights into how suspicion influences deception judgments and into previous research on evasive responses in earnings calls.This paper was accepted by Ranjani Krishnan, accounting.Funding: The author acknowledges financial support from the Deloitte Foundation, the Roberto C. Goizueta Foundation, the W. P. Carey School of Business, and the Sheth Fellowship Fund.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2025.01197 .

Shareholderism Around the World: Corporate Purpose, Culture, and Law

2025-10-08T00:00:00+00:00

Management Science
We provide the first comprehensive analysis of directors’ shareholderism: their principled stance toward shareholders and stakeholders in forming strategy. We develop an analytical framework that links shareholderism to individual and institutional factors and test our theoretical predictions using a sample of more than 900 directors originating from 55 countries and serving in 23 countries. Directors’ shareholderism varies according to their individual values; their cultural heritage of egalitarianism, harmony, and embeddedness; and their status as expatriate directors. Directors’ shareholderism does not appear to depend on the distinction between common and civil law. Instrumental variable regressions that address the endogeneity of directors’ expatriate status suggest that expatriates’ and local directors’ shareholderism reflect different cultural emphases. To be effective, current approaches to ensuring corporations do the “right” thing through legal injunctions may need to be mindful of the stability and resilience of individual values and culture.This paper was accepted by David Simchi-Levi, business strategy.Funding: A. N. Licht acknowledges financial support from the Israeli Science Foundation [Grant 342/08].Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2222.00463 .

Painful Prices: The Moral Harm Model of Price Fairness

2025-10-08T00:00:00+00:00

Journal of Consumer Research
Consumers’ responses to seller’s prices, including perceptions of price fairness (PPF) and unfairness, are a crucial aspect of the marketplace. Although past literature has uncovered a variety of factors that influence PPF, the lack of an overarching conceptual framework has constrained understanding of when and why consumers are more likely to perceive prices as fair or unfair. The authors develop a conceptual model of PPF as moral judgments and propose that these moral PPF arise from consumer inferences of potential harm from a price. The conceptualization suggests that inferred harm—and thereby, PPF—is influenced by consumer vulnerability, product welfare impact and firm price strategy (e.g., costs and prices, differential pricing, and price promotions). The authors also propose that consumer political orientation and inferred firm self-defense motives moderate the relationship between inferred harm and PPF and that inferred firm motives for prices influence PPF. Eight studies test this conceptualization. The results support the moral harm model and provide novel insights, showing when unchanged prices, price increases, and price decreases are likely to be perceived as more unfair and when differential prices (including paying more than others) are likely to be perceived as fairer than equal prices.

Are All ESG Funds Created Equal? Only Some Funds Are Committed

2025-10-09T00:00:00+00:00

The Review of Financial Studies
Environmental, social, and governance (ESG) funds have heterogeneous incentives to engage with portfolio firms. If funds view ESG as a value driver, then these incentives will affect funds’ behavior and thus their impact on firms. We compare ESG funds with similar levels of ESG investments but different incentives to engage. Funds with higher incentives to engage, that is, committed ESG funds, conduct more ESG-related information acquisition, pursue longer term investment strategies, engage more intensely on ESG issues, and have greater real impacts. Moreover, committed ESG funds have outperformed other ESG funds within subportfolios with higher and more effective ESG engagement.

EXPRESS: Reducing Hospital Procurement Costs through Vendor Contract Optimization: A Decision-Support Framework for GPOs

2025-10-09T00:00:00+00:00

Production and Operations Management
Group Purchasing Organizations (GPOs) play a crucial intermediary role in the U.S. healthcare supply chain by consolidating purchasing power across multiple healthcare providers. However, increasing competition from peer organizations and hospitals’ insourcing efforts has placed significant pressure on GPOs to enhance their value propositions. This study presents a data-driven framework designed to help GPOs reduce medical supply costs for hospitals by addressing inefficiencies in vendor tier contracts, a complex form of quantity discount based on market share rather than absolute quantity. The framework consists of reference matrices that define feasible adjustment spaces for tier prices and thresholds, followed by mixed-integer programming models designed to optimize contract parameters. It enables GPOs to (1) identify misalignments between vendor contracts and hospital operational realities, (2) guide vendors in improving their tier contracts to lower procurement costs for hospitals while supporting their own financial interests, and (3) evaluate the potential for tailoring contracts to individual health systems within existing tier structures to achieve additional savings. Applied to four health systems within a Midwest-based GPO, the model demonstrates up to 50% potential savings compared to current IDN spend and 14% savings relative to the optimal spend under existing tier thresholds. In addition, while prior studies suggest hospital-direct contracts fail to deliver net savings due to high transaction costs, our research shows that some hospitals could potentially benefit from GPO-managed custom contracts.

EXPRESS: Bonus Competition in the Gig Economy

2025-10-09T00:00:00+00:00

Production and Operations Management
The success of a gig platform is crucially driven by its ability to compete for labor supply. However, gig workers are independent contractors whose working schedules are not fully controlled by the platform. To overcome this challenge, gig platforms have commonly relied on bonus strategies to drive the participation of gig workers. We study the impact of bonus strategies on gig platforms and their welfare implications. We consider two types of bonus strategies used by gig platforms: 1) fixed bonus that is paid in addition to commissions as long as a service provider participates, and 2) contingent bonus that is paid only if a service provider participates consistently over time. We develop a game theory model to study platform competition with bonus strategies. Our analysis shows that the two types of bonuses will arise in equilibrium under different market conditions. First, when labor supply is thick, fixed bonus will be offered. In this case, fixed bonus improves platform profit by eliminating a prisoner’s dilemma that arises when the platforms compete only on commissions. However, social welfare will be reduced because the utilization of the labor supply is reduced due to the softened platform competition. Second, when labor supply is thin, contingent bonus will be offered. In this case, contingent bonus reduces platform profit because it intensifies platform competition and traps the platforms in a prisoner’s dilemma where they are forced to offer too much bonus. It further causes inefficiency in matching labor supply with demand and hence reduces social welfare.

Single-Leg Revenue Management with Advice

2025-10-09T00:00:00+00:00

Operations Research
Machine learning algorithms are becoming increasingly powerful, but with that power comes greater complexity and opacity. As these models become more sophisticated, they become increasingly difficult to understand—and, crucially, harder to anticipate when and how they might fail. This makes it essential to incorporate their predictions in ways that remain robust to errors. In “Single-Leg Revenue Management with Advice,” S. Balseiro, C. Kroer, and R. Kumar develop an algorithm for the classical single-leg revenue management problem that robustly incorporates predictions. They uncover a fundamental tradeoff: Placing greater trust in predictive models can yield high performance when predictions are accurate but also makes algorithms vulnerable when predictions are off. The proposed algorithm achieves the optimal tradeoff between these goals, allowing decision makers to leverage machine learning predictions while guarding against their potential inaccuracies. By doing so, this work provides a principled approach to integrating powerful yet imperfect forecasts into real-world decision making.

Residential Battery Storage—Reshaping the Way We Do Electricity

2025-10-09T00:00:00+00:00

Operations Research
Household investments in renewable energy technologies like rooftop solar and battery storage can be driven by motivations beyond mere financial returns. In “Residential Battery Storage— Reshaping the Way We Do Electricity,” Christian Kaps and Serguei Netessine develop a structural estimation model that separates observed electricity demand from underlying consumption preferences, enabling the estimation of a nonfinancial utility that households derive from using more self-generated solar power rather than grid-procured electricity. The authors call this utility nonmarket valuation; provide evidence that it is driven by sustainability and autarky desires; and link it to the early adoption of residential storage. Applying their model to a novel data set of German households with solar and storage installations, they find that the median household has a nonmarket valuation of 0.29 euros per kilowatt-hour. Additionally, the authors demonstrate that residential storage can have unexpected effects. They show a “rebound effect,” whereby households with storage increase their overall electricity consumption by 4%. Counterintuitively, under Germany’s observed grid mix, residential storage on average increases carbon emissions. However, they also find that demand from the grid decreases by 38% for the average household equipped with solar and storage.

The Role of Networks in Loan Syndicate Markets

2025-10-09T00:00:00+00:00

Management Science
Several large, well-connected banks jointly underwrite the vast majority of syndicated loans. Although syndication reduces risk by spreading large loans across multiple banks and may benefit borrowers, the process may also facilitate collusive pricing. Disentangling these two effects requires a network view of loan syndicates as traditional measures of market concentration do not capture the collaborative nature of syndication. We find that well-connected banks offer 5- to 15-basis-point-lower loan rates. Well-connected lenders leverage their network position to structure larger, more dispersed syndicates with fewer coarrangers, allowing them to earn higher fee income and reduce their loan risk exposure. We address potential selection biases by exploiting the stickiness in firm-bank relationships and the transfer of credit relationships around forced mergers during the 2007–2009 financial crisis. Using new supervisory data on borrowers’ loan repayment and on-site inspections, we find little evidence that connectedness is related to superior monitoring or performance. Our findings suggest that connectivity is instrumental in lowering loan prices rather than facilitating collusive pricing.This paper was accepted by Kay Giesecke, finance.Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06313 .

EXPRESS: The Effects of Mergers and Acquisitions on Marketing Decisions and Effectiveness: Evidence from the Biopharma Industry

2025-10-09T00:00:00+00:00

Journal of Marketing Research
Mergers and acquisitions (M&As) may trigger adjustments to firms’ marketing decisions and their outcomes. Yet, prior literature provides little empirical insight regarding the nature of these adjustments. We address this gap in the context of the biopharma industry, analyzing data on sales, prices, and detailing spending for 375 branded drugs acquired in 73 M&A deals between 2007 and 2020. We find that, on average, acquiring firms (1) reduce detailing spending on target drugs, (2) increase target drug prices, and (3) achieve increases in detailing elasticity for target drugs after the M&A, compared to before. The younger the target drugs and the more experience the acquirer has in marketing drugs in the drugs’ therapeutic category, (1) the more likely we are to see reductions in detailing and increases in prices, and (2) the greater the likelihood that acquirers experience larger increases in detailing elasticity and reductions in price elasticity. For our 375 target drugs, acquirers generated over $23 billion more in revenue in the two post-deal years while spending over $1 billion less on detailing compared to the two pre-deal years. The paper provides a framework for firms regarding commercial returns on M&As and informs the debate on regulatory responses to M&As.

EXPRESS: The Decision-making Process and Impact of Individual Decisions for Joint Consumption

2025-10-09T00:00:00+00:00

Journal of Marketing Research
Consumers make individual decisions for their own, others’, and joint consumption. This research introduces a framework for understanding the process of making individual decisions for joint consumption by comparing them to individual decisions for the self and for others (e.g., gifts). Seven experiments show that individual decisions for joint consumption, which involve considering one’s own and others’ preferences, consistently increase felt responsibility for unsatisfactory outcomes and decrease confidence in ability to make satisfactory choices compared to decisions for the self. Knowledge of others’ preferences plays a critical role in differentiating between individual decisions for joint versus others’ consumption; (in)congruent preferences (decrease) increase confidence in decisions for joint consumption, while any knowledge of others’ preferences – regardless of congruity – increases confidence in decisions for others. Three managerially-relevant downstream consequences are identified that differ among individual decisions for joint, self, and others’ consumption: decision anxiety, choice of assortment options, and choice of popular options. These insights offer valuable strategies for marketers to tailor their product offerings and communications to consumers engaged in individual decisions for joint, own, or others’ consumption.

Marching to the Beat: The Role of Complementor Alignment in the Architectural Evolution of Ecosystems

2025-10-09T00:00:00+00:00

Journal of Management
The evolution of innovation ecosystems hinges on the effective coordination between ecosystem leaders and complementors. While ecosystem-sponsored architectural innovations create new technological opportunities for complementors, they may unintentionally disrupt the performance of complementor products that were originally developed based on legacy architectural designs. This study provides empirical evidence of these disruptive effects and explores how complementors’ alignment with the ecosystem leader mitigates such challenges. Focusing on Apple’s release of Core ML—a proprietary artificial intelligence module—in its mobile ecosystem, we employ a difference-in-differences design to investigate variations in complementor performance after adopting this ecosystem-sponsored architectural innovation. Our findings reveal that complementors’ technological and flow alignment with the ecosystem leader is critical for minimizing performance disruptions and enhancing value creation during ecosystem evolution. This study enriches our understanding of architectural changes and complementor heterogeneity in innovation ecosystems.

Brand Faith: How Spiritual Relationships Develop Between Consumers and Brands

2025-10-09T00:00:00+00:00

Journal of Consumer Research
Consumers increasingly seek spiritual satisfaction and existential meaning through brands. However, despite the rising prominence of secular forms of spirituality, consumer-brand relationship research largely overlooks the processes by which consumers initiate, develop, and maintain spiritual connections to brands. Using the concept of faith as a theoretical lens, this paper explores how consumer-brand relationships take on spiritual dimensions. Drawing on an interpretive biographic analysis of in-depth interviews and netnographic data, the authors examine spiritual relationship development processes as they unfold between consumers and brands over time. Findings identify five phases of brand faith development (intuition, association, reflection, affirmation, universalization), which progress from initial attraction to deep conviction. Consumers cultivate faith in brands across these phases through a process of believing in, valuing, and committing to a brand as a sacred entity that acts as a center of spiritual meaning. These findings offer a more nuanced understanding of spiritual relationships between consumers and secular brands than current literature provides. The analysis also examines factors that facilitate or inhibit brand faith development, contributing a contextual understanding of brand faith that accounts for influences arising from an interplay between personal, brand, and marketplace factors that affect consumer spirituality.

Do We Think Differently When Tapping the Screen or Clicking the Mouse? Effects of Computer Interfaces on Level of Construal

2025-10-09T00:00:00+00:00

Information Systems Research
The touchscreen has become the de facto interface for individuals to interact with digital devices. This research investigates the implications of the profound shift from the mouse-based, nontouch interface to the touch-based interface for human thinking and behavior. Ten studies reveal that using touchscreens, as opposed to a mouse, fosters a more concrete low-level construal. Specifically, using touch interfaces on devices such as iPads and tablets prompts people to interpret actions in a detailed, hands-on manner, viewing locking a door as inserting a key into a lock rather than as a broader concept such as securing a house. Touchscreens also encourage a narrow categorization of concepts and a reliance on local, granular attributes. The concrete mindset evoked by the touch interface elevates individuals’ preference for practicality over complexity, such as choosing a compact camera over an advanced one, and receptiveness to persuasive attempts with feasibility appeals. Given that mental construals fundamentally influence how we perceive and engage with the world, our findings underscore the wide-ranging impacts of touch interfaces. This research provides a theoretical foundation for exploring the broader implications of the widespread adoption of touch technology, especially as digital devices become increasingly integrated into our digitally transformed daily life worldwide.