Acknowledges Financial Support Research Articles

Indirect Value of Public Infrastructure Technology

Although prior research has primarily focused on the direct value of information technology (IT) and IT adoption by individuals and firms, this study explores the indirect value of IT in the form of public infrastructure technology. By exploiting a spatial discontinuity in water monitoring stations, we discover that firms located immediately upstream of water monitoring stations exhibit significantly lower levels of corruption than firms located immediately downstream. These findings are particularly noteworthy given that water monitoring stations have the potential to generate significant indirect value as they are not explicitly designed to mitigate corruption. Further analyses reveal that public infrastructure technology alone does not hold the key to mitigating corporate corruption. Instead, it is the synergistic interplay between public infrastructure technology and organizational change that drives the outcome. These findings contribute to a deeper understanding of the broader IT value landscape, emphasizing the indirect value of technological advancements in public infrastructure that were not originally intended for such benefit. Additionally, our findings highlight the benefits of leveraging existing infrastructure technology to address emerging societal needs. This paper was accepted by D. J. Wu, information systems. Funding: J. Liu acknowledges financial support from the National Natural Science Foundation of China [Grant 72402127], Shanghai Pujiang Program [Grant 23PJC059] and the Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission [Grant 23CGA10]. S. Pei acknowledges financial support from the National Natural Science Foundation of China [Grant 72302139]. X. (M.) Zhang acknowledges financial support from the Hong Kong Research Grants Council [Grants GRF 14500521, GRF 14501320, GRF 165052947, and TRS:T31-604/18-N]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.01145 .

COMONOTONICITY AND PARETO OPTIMALITY, WITH APPLICATION TO COLLABORATIVE INSURANCE

Two by-now folkloric results in the theory of risk sharing are that (i) any feasible allocation is convex-order-dominated by a comonotonic allocation; and (ii) an allocation is Pareto optimal for the convex order if and only if it is comonotonic. Here, comonotonicity corresponds to the so-called no-sabotage condition, which aligns the interests of all parties involved. Several proofs of these two results have been provided in the literature, all based on a version of the comonotonic improvement algorithm of Landsberger and Meilijson (1994) and a limit argument based on the Martingale Convergence Theorem. However, no proof of (i) is explicit enough to allow for an easy algorithmic implementation in practice; and no proof of (ii) provides a closed-form characterization of Pareto optima. In addition, while all of the existing proofs of (i) are provided only for the case of a two-agent economy with the observation that they can be easily extended beyond two agents, such an extension is far from being trivial in the context of the algorithm of Landsberger and Meilijson (1994) and it has never been explicitly implemented. In this paper, we provide novel proofs of these foundational results. Our proof of (i) is based on the theory of majorization and an extension of a result of Lorentz and Shimogaki (1968), which allows us to provide an explicit algorithmic construction that can be easily implemented beyond the case of two agents. In addition, our proof of (ii) leads to a crisp closed-form characterization of Pareto-optimal allocations in terms of α-quantiles (mixed quantiles). An application to peer-to-peer insurance, or collaborative insurance, illustrates the relevance of these results.Acknowledgements: The authors thank the Editor and two anonymous Referees for numerous suggestions which helped to improve the text compared to its previous versions. We are grateful to K.C. Cheung for comments on an earlier version of this paper, and to Christopher Blier-Wong for his excellent research assistance in the numerical example. We thank the Associate Editor and two anonymous reviewers for comments and suggestions. Michel Denuit and Jan Dhaene gratefully acknowledge funding from the FWO and F.R.S.-FNRS under the Excellence of Science (EOS) programme, project ASTeRISK (40007517). Jan Dhaene acknowledges the financial support of BOF KU Leuven (project C14/21/089). Mario Ghossoub acknowledges financial support from the Natural Sciences and Engineering Research Council of Canada NSERC Grant No. 2018-03961 and 2024-03744).

Auditor Skill Demands and Audit Quality: Evidence from Job Postings

This study empirically examines the relation between audit quality and auditors’ cognitive and social skills. Using a novel data set of online job postings by accounting firms, we document substantial variation in the stated demand for auditors’ cognitive and social skills, suggesting that audit offices are not homogeneous in their preferences for such skills. We find a positive relation between audit quality and the prevalence of cognitive and social skills within an audit office’s job postings. This association is stronger for audit engagements that are more complex or require greater coordination, suggesting that cognitive and social skills are particularly important in engagements where effective communication and knowledge transfer, as well as sound professional judgment and skepticism, are needed. The association is also stronger for audit offices with greater investments in new technology, consistent with the complementary relation between cognitive and social skills and the use of technology. Overall, our study offers empirical evidence linking specific auditor skills to audit quality. This paper was accepted by Suraj Srinivasan, accounting. Funding: C. Ham acknowledges financial support from the Blanche “Peg” Philpott Faculty Fellowship. R. N. Hann acknowledges financial support from KPMG. W. Wang acknowledges the financial support from the Hong Kong Research Grant Council [Grant 11503720]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01640 .

Organizational Selection of Innovation

Budgetary constraints force organizations to pursue only a subset of possible innovation projects. Identifying which subset is most promising is an error-prone exercise, and involving multiple decision makers may be prudent. This raises the question of how to most effectively aggregate their collective nous. Our model of organizational portfolio selection provides some first answers. We show that portfolio performance can vary widely. Delegating evaluation makes sense when organizations employ the relevant experts and can assign projects to them. In most other settings, aggregating the impressions of multiple agents leads to better performance than delegation. In particular, letting agents rank projects often outperforms alternative aggregation rules—including averaging agents’ project scores and counting their approval votes—especially when organizations have tight budgets and can select only a few project alternatives out of many. Funding: L. Böttcher acknowledges financial support from hessian.AI and the Army Research Office [Grant W911NF-23-1-0129]. Supplemental Material: The data files are available at https://doi.org/10.1287/orsc.2023.17357 .

The Deterrence Effects of Tax Whistleblower Laws: Evidence from New York’s False Claims Acts

In this study, we provide evidence on the effects of state tax whistleblower laws. We exploit a novel 2010 amendment to New York’s False Claims Acts (FCA) that explicitly extended whistleblower incentives to corporate income tax whistleblowers. We identify treated firms (firms exposed to New York’s FCA) using establishment-level data and descriptive analyses. Using a sample of firms exposed to New York and neighboring states, we find evidence that New York’s FCA reduced state tax avoidance. In cross-sectional tests, we find that effects are increasing in firms that grant fewer employee stock options and industry regulation, consistent with deterrence increasing in employee and regulator monitoring. We also find evidence that New York’s FCA deterred federal tax avoidance, consistent with positive vertical tax externalities. Next, we focus on particular tax strategies and find evidence of a reduced probability of Double Irish tax structures, reduced relationships to tax planning banks, reduced use of special purpose vehicles, and reduced outbound tax-motivated income shifting. We also find evidence that firms with the lowest (highest) cost of relocation (1) reduced (did not change) establishment counts in New York but (2) did not change (reduced) state tax avoidance. Finally, we disentangle general ex ante deterrence from ex ante peer deterrence using hand-collected New York tax whistleblower press releases from the Attorney General. We find evidence of both types of deterrence. Overall, this study provides policy-relevant evidence on the deterrence effects of tax whistleblower laws. This paper was accepted by Suraj Srinivasan, accounting. Funding: Y. Lee acknowledges financial support from the College of Business at California State University, Long Beach. S. Ng acknowledges financial support from Singapore Management University. T. Shevlin acknowledges financial support from the University of California, Irvine [the Paul Merage Chair and the Merage School of Business]. A. Venkat acknowledges financial support from the McCombs School of Business at the University of Texas, Austin. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.02999 .

Conditional Lead-Time Flexibility in an Assemble-to-Order System

Problem definition: We introduce and formalize a concept termed conditional lead-time flexibility (CLF), which refers to the industry practice where a manufacturer requests that its upstream suppliers dynamically adjust the pipeline orders’ remaining lead times. Over a finite horizon, an assemble-to-order manufacturer makes joint decisions on inventory replenishment and lead-time adjustment to minimize the total discounted expected cost. Methodology/results: The problem is formulated as a multiperiod dynamic programming with an enlarged state space to track the adjustable pipeline orders. The replenishment and lead-time adjustment decisions are made sequentially in each period. The analysis reveals that (i) the optimal cost-to-go function is both convex and additively separable, that (ii) both the optimal replenishment and lead-time adjustment decisions follow general base-stock policies, and that (iii) the convexity and additive separability allow us to perform a derivative analysis on the optimality equations and design an efficient algorithm. Managerial implications: Using real industry data, we numerically find that (i) CLF achieves notable cost savings over a wide range of parameters, that (ii) the value of CLF comes from both the order expediting and deferring, and that (iii) CLF outperforms dual sourcing when the unit adjustment cost is less than 40% of the unit ordering cost from the express source. Our findings underscore the importance of CLF. Funding: T. Deng acknowledges financial support from the National Key Research and Development Program of China [Grant 2022YFB3305602] and the National Natural Science Foundation of China (NSFC) [Grant 72188101]. Supplemental Material: The electronic companion is available at https://doi.org/10.1287/msom.2023.0520 .

Penny Wise and Pound Foolish: Does Striving to Meet Earnings Expectations by Manipulating Real Activities Trigger Product Recalls?

We examine whether managers’ activities in striving to reach earnings targets through real earnings manipulation affect their firms’ product recalls. Our evidence implies that firms suspected of manipulating real activities in trying to meet earnings benchmarks exhibit a higher likelihood and frequency of product recalls. In cross-sectional results consistent with expectations, we find that the impact of exploiting real activities to attain earnings benchmarks on product recalls intensifies for firms whose managers have stronger incentives to manage earnings and subsides for firms subject to greater customer power and firms with more growth opportunities. Additional analysis shows that lowering product quality to meet or beat earnings expectations undermines firms’ future performance. This paper was accepted by Ranjani Krishnan, accounting. Funding: Y. Chen acknowledges the General Research Fund of the Research Grants Council of Hong Kong [Project 15504219] for financial support. L. Ma acknowledges financial support from the Ministry of Education Project of Humanities and Social Sciences [Project 22YJC630099] and the Young Scholars Grant Program of the University of International Business and Economics [Project 20YQ06]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.04035 .

Does Online Fundraising Increase Charitable Giving? A Nationwide Field Experiment on Facebook

Does online fundraising increase charitable giving? Using the Facebook advertising tool, we implemented a natural field experiment across Germany, randomly assigning almost 8,000 postal codes to Save the Children fundraising videos or to a pure control. We studied changes in the donation revenue and frequency for Save the Children and other charities by postal code. Our geo-randomized design circumvented many difficulties inherent in studies based on click-through data, especially substitution and measurement issues. We found that (i) video fundraising increased donation revenue and frequency to Save the Children during the campaign and in the subsequent five weeks, that (ii) the campaign was profitable for the fundraiser, and that (iii) the effects were similar independent of video content and impression assignment strategy. However, we also found some crowding out of donations to other similar charities or projects. Finally, we demonstrated that click data may be an inappropriate proxy for donations and recommend that managers use careful experimental designs that can plausibly evaluate the effects of advertising on relevant outcomes. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: M. Adena acknowledges financial support from the Deutsche Forschungsgemeinschaft [Grants 417014946 and CRC TRR 190 (Project 280092119)]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2020.00596 .

Aversion to Hiring Algorithms: Transparency, Gender Profiling, and Self-Confidence

We run an online experiment to study the origins of algorithm aversion. Participants are in the role of either workers or managers. Workers perform three real-effort tasks: task 1, task 2, and the job task, which is a combination of tasks 1 and 2. They choose whether the hiring decision between themselves and another worker is made by a participant in the role of a manager or by an algorithm. In a second set of experiments, managers choose whether they want to delegate their hiring decisions to the algorithm. When the algorithm does not use workers’ gender to predict their job-task performance and workers know this, they choose the algorithm more often than in the baseline treatment where gender is employed. Feedback to the managers about their performance in hiring the best workers increases their preference for the algorithm relative to the baseline without feedback, because managers are, on average, overconfident. Finally, providing details on how the algorithm works does not increase the preference for the algorithm for workers or for managers. This paper was accepted by Elena Katok, special issue on the human-algorithm connection. Funding: D. Kübler acknowledges financial support from the Deutsche Forschungsgemeinschaft [CRC TRR 190], R. Hakimov acknowledges financial support from the Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung [Project 100018_189152], and M.-P. Dargnies acknowledges financial support from the Agence Nationale de la Recherche (ANR JCJC TrustSciTruths). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02774 .

Trading Gamification and Investor Behavior

We study the effect of gamification on retail traders’ behavior using a randomized online experiment. Participants with lower financial literacy prefer platforms with hedonic gamification elements, such as confetti and achievement badges. On average, hedonic gamification increases trading volume by 5.17%. However, the difference in trading activity between gamified and nongamified platforms is driven primarily by self-selection (70%) rather than gamification (30%). Participants who prefer hedonic gamification exhibit noisy trading strategies, whereas those favoring nongamified platforms display stronger contrarian behavior. Further, price trend notifications enhance learning for investors with accurate beliefs, but they reinforce trading mistakes for those with incorrect beliefs. This paper has been This paper was accepted by Jean-Edouard Colliard for the special issue on the human-algorithm connection. Funding: P. Chapkovski acknowledges funding from the Deutsche Forschungsgemeinschaft [Germany’s Excellence Strategy—EXC 2126/1-390838866]. M. Khapko and M. Zoican acknowledge the Social Sciences and Humanities Research Council of Canada [Insight Development Grant 430-2018-00125] and the Canadian Securities Institute Research Foundation [research grant]. M. Zoican acknowledges financial support from the Quantitative Management Research Initiative (QMI) under the aegis of the Fondation du Risque, a joint initiative by Université Paris-Dauphine, l’École Nationale de la Statistique et de l’Administration ParisTech, and LFIS, France. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02650 .

Like Stars: How Firms Learn at Scientific Conferences

Scientific conferences are an underexplored channel by which firms can learn from science. We provide empirical evidence that firms learn from scientific conferences in which they participate but also that this is conditional on intense participation. Using data from conference papers in computer science since the 1990s, we show that corporate investments in participation are both frequent and highly skewed, with some firms contributing to a given conference scientifically, some as sponsors, and some doing both. We use direct flights as an instrumental variable for the probability that other scientists participate in the same conference as a firm, altering the knowledge set to which the firm is exposed. We find that a firm’s use of scientists’ knowledge increases when they participate in the same conferences. Greater participation efforts, where the firm seeks the spotlight by both sponsoring the conference and contributing to its scientific discourse, foretell research collaborations and a stronger learning effect. Such learning is disproportionately concentrated among the most prominent firms and scientists rather than benefitting those without alternative interaction channels. Therefore, on average, firms learn from scientists that they encounter at conferences, but the substantial heterogeneity of the effect reflects the influence of reputation mechanisms in social interactions. This paper was accepted by Ashish Arora, entrepreneurship and innovation. Funding: S. Baruffaldi acknowledges financial support from the Swiss Science National Foundation (Reference No.: P2ELP1-161847). Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01373 .

Industry Peer Information and the Equity Valuation Accuracy of Firms Emerging from Chapter 11

Valuation plays a central role in determining Chapter 11 reorganization outcomes. However, obtaining accurate valuation estimates of reorganized firms is challenging because of limited firm-specific market-based information and the oft-conflicting incentives of claimholders. We examine the role of industry peer information in reducing misvaluations and its implications for unintended interclaimant wealth transfers and postreorganization performance. First, we find that the availability of relevant industry peer information is negatively associated with equity valuation errors for firms emerging from Chapter 11. Cross-sectional results suggest that the relation between industry peer information and valuation errors varies substantially with debtors’ information environment and case characteristics. Second, we find that industry peer information quality is associated with better ex post financial performance of emerged firms because of lower overvaluation. Finally, we document the role of industry peer information in substantially reducing the frequency and magnitude of unintended wealth transfers between claimants arising from equity valuation errors. This paper was accepted by Suraj Srinivasan, accounting. Funding: The authors appreciate financial support from the Social Sciences and Humanities Research Council of Canada [Grant 435-2020-0583] and the Canadian Academic Accounting Association. B. Fang acknowledges financial support from the Della Suantio Fellowship. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01233 .

Target Firm Advertising and Firm Value

Consistent with hypotheses underlying firm advertising, we find that targets with pretakeover advertising obtain higher premiums, whereas their acquirers earn lower announcement returns. These economically significant effects suggest that through advertising, targets increase their profile and negotiating power. Further, targets that advertise are more likely to initiate their takeovers, attract multiple bidders, receive enhanced bids, capture more merger rents, and even in failed acquisitions, experience a 1% permanent revaluation. The latter result differentiates between information asymmetry and behavioral explanations for the target advertising. Overall, the results support the hypothesis that management advertises to transmit information to investors and potential acquirers. This paper was accepted by Victoria Ivashina, finance. Funding: A. L. Tran acknowledges financial support from the Mergers and Acquisitions Research Centre at Bayes Business School. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01534 .

Bidder-Specific Synergies and the Evolution of Acquirer Returns

Largely constant average acquirer returns over the past four decades mask fundamental changes in the takeover market. Controlling for bidder composition, the common component of acquirer returns has increased by five percentage points relative to the 1980s. Offsetting this increase, the average bidder-specific component has declined. We propose a theory of bidder-specific synergies to help interpret these opposing trends. In our theory and in the data, acquirer returns increase with the extent to which synergies are unique to that bidder. The composition effect reflects bidder uniqueness. Overall, the evidence is consistent with rising merger synergies that have become less bidder specific. This paper was accepted by Victoria Ivashina, finance. Funding: A. Golubov acknowledges financial support from the Bank of Canada [Governor’s Award]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02208 .

Patents, Freedom to Operate, and Follow-on Innovation: Evidence from Post-Grant Opposition

We study the blocking effect of patents on follow-on innovation by others. We posit that follow-on innovation requires freedom to operate (FTO), which firms typically obtain through a license from the patentee holding the original innovation. Where licensing fails, follow-on innovation is blocked unless firms gain FTO through patent invalidation. Using large-scale data from post-grant oppositions at the European Patent Office, we find that patent invalidation increases follow-on innovation, measured in citations, by 16% on average. This effect exhibits a U-shape in the value of the original innovation. For patents on low-value original innovations, invalidation predominantly increases low-value follow-on innovation outside the patentee’s product market. Here, transaction costs likely exceed the joint surplus of licensing, causing licensing failure. In contrast, for patents on high-value original innovations, invalidation mainly increases high-value follow-on innovation in the patentee’s product market. We attribute this latter result to rent dissipation, which renders patentees unwilling to license out valuable technologies to (potential) competitors. This paper was accepted by Ashish Arora, entrepreneurship and innovation. Funding: This work was supported by the Deutsche Forschungsgemeinschaft [Collaborative Research Center TRR 190]. F. Gaessler acknowledges financial support from the Spanish Agencia Estatal de Investigación through the Severo Ochoa Programme for Centres of Excellence in R&D [Barcelona School of Economics CEX2019-000915-S]. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2019.02294 .

Correlated Equilibria for Mean Field Games with Progressive Strategies

In a discrete space and time framework, we study the mean field game limit for a class of symmetric N-player games based on the notion of correlated equilibrium. We give a definition of correlated solution that allows us to construct approximate N-player correlated equilibria that are robust with respect to progressive deviations. We illustrate our definition by way of an example with explicit solutions. Funding: O. Bonesini acknowledges financial support from Engineering and Physical Sciences Research Council [Grant EP/T032146/1]. M. Fischer acknowledges partial support through the University of Padua [Research Project BIRD229791 “Stochastic mean field control and the Schrödinger problem”].

Nonperforming Loan Disposals Without Resolution

Using proprietary data on nonperforming loan (NPL) transactions in China, we document that banks conceal NPLs in disposal transactions that are supposed to resolve NPLs. In these transactions, banks provide financing and retain the credit risks and debt collection obligations. Transaction prices contradict underlying credit risks: Despite being delinquent for 4.5 years, the median NPL package is sold at face value with zero haircut. The majority of NPL packages are resold at a premium to banks’ non–government-owned borrowers, further supporting the concealment view. Banks under stricter regulation conceal NPLs more and engage in more illicit concealment. NPL-concealing banks increase zombie lending, suggesting that an ineffective resolution exacerbates credit misallocation. Recognizing the hidden NPLs implies the total NPLs in China is two to three times the reported amount. This paper was accepted by Victoria Ivashina, finance. Funding: B. Charoenwong acknowledges financial support from the Singapore Ministry of Education [AcRF Tier 1 Research Grant A-8000760-00-00]. T. Ruan acknowledges financial support from the National University of Singapore (NUS) [Start-Up Grant A-0003870-00-00]. B. Charoenwong and T. Ruan acknowledge financial support from the NUS Business School Financial Database [Grant N-311-000-251-001]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02163 .

Taylor Approximation of Inventory Policies for One-Warehouse, Multi-Retailer Systems with Demand Feature Information

We consider a distribution system in which retailers replenish perishable goods from a warehouse, which, in turn, replenishes from an outside source. Demand at each retailer depends on exogenous features and a random shock, and unfulfilled demand is lost. The objective is to obtain a data-driven replenishment and allocation policy that minimizes the average inventory cost per time period. The extant data-driven methods either cannot guarantee a feasible solution for out-of-sample feature observations or generate one with excessive computational time. We propose a policy that resolves these issues in two steps. In the first step, we assume that the distributions of features and random shocks are known. We develop an effective heuristic policy by using Taylor expansion to approximate the retailer’s inventory cost. The resulting solution is closed-form, referred to as Taylor Approximation (TA) policy. We show that the TA policy is asymptotically optimal in the number of retailers. In the second step, we apply the linear quantile regression and kernel density estimation to the TA solution to obtain the data-driven policy called Data-Driven Taylor Approximation (DDTA) policy. We prove that the DDTA policy is consistent with the TA policy. A numerical study shows that the DDTA policy is very effective. Using a real data set provided by Fresh Hema, we show that the DDTA policy reduces the average cost by 11.0% compared with Hema’s policy. Finally, we show that the main results still hold in the cases of correlated demand features, positive lead times, and censored demand. This paper was accepted by J. George Shanthikumar, data science. Funding: Y. Yang acknowledges financial support from the NSFC [Grants 72125004, 71821002]. W. Zhou acknowledges financial support from the NSFC [Grants 72192823, 71821002]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2021.04241 .

A Better Estimate of Internally Generated Intangible Capital

Internally developed intangibles are not included in reported assets under U.S. generally accepted accounting principles. The omission of this increasingly important class of assets reduces the usefulness and relevance of financial statement analysis, conducted with reported values of equity and assets. Recent studies overcome this deficiency by capitalizing research and development (R&D) expenses to estimate the value of knowledge capital and by capitalizing selling, general, and administrative (SG&A) expenses to estimate the value of organization capital. Those two estimates are then added to reported values for financial statement analysis. For convenience, many studies rely on two rules of thumb and assume them to be equally applicable in all instances: (1) 30% of SG&A and 100% of R&D expenses are investments, and (2) the useful life of SG&A and R&D investments is three and five years, respectively. We propose a more flexible approach by estimating the capitalization and amortization parameters on an industry–year–specific basis. Our modified values of total assets and equity, inclusive of the value of capitalized intangibles, exhibit greater association with future returns and investments compared with as-reported values and values estimated with uniform rules of thumb. We provide a better estimate of intangible capital for the consumers of financial statements. This paper was accepted by Ranjani Krishnan, accounting. Funding: A. Srivastava and R. Zhao acknowledge financial support from the Social Sciences and Humanities Research Council of Canada. A. Srivastava acknowledges financial support from the Canada Research Chairs Program of the Government of Canada. A. Iqbal acknowledges financial support from the Canadian Securities Institute Research Foundation and Chartered Professional Accountants (Alberta) Education Foundation. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.01703 .

Fintech Platforms and Mutual Fund Distribution

We document a novel platform effect caused by the emergence of fintech platforms in the intermediation of financial products. In China, platform distributions of mutual funds emerged in 2012 and grew quickly into a formidable presence. Utilizing the staggered entrance of funds onto platforms, we find a marked increase of performance chasing driven by the centralized information flow unique to fintech platforms. This pattern is further confirmed using proprietary data from a top platform. Examining the platform impact on fund managers, we find that incentivized by the amplified performance chasing, fund managers increase risk-taking to enhance their probability of getting onto the top ranking. This paper was accepted by William Cong, finance. Funding: X. Lu acknowledges financial support from the National Natural Science Foundation of China [Grant 72003126]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01966 .