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We consider a principal who periodically offers a fixed and costly nonmonetary reward to agents to incentivize them to invest effort over the long run. An agent's output, as a function of his effort, is a priori uncertain and is worth a fixed per-unit value to the principal. The principal's goal is to design an attractive reward policy that specifies how the rewards are to be given to an agent over time based on that agent's past performance. This problem, which we denote by P , is motivated by practical examples from both academia (e.g., a reduced teaching load) and industry (e.g., "Supplier of the Year" awards). The following "limited-term" (LT) reward policy structure has been quite popular in practice. The principal evaluates each agent periodically; if an agent's performance over a certain (limited) number of periods in the immediate past exceeds a predefined threshold, then the principal rewards him for a certain (limited) number of periods in the immediate future. When agents' outputs are deterministic in their efforts, we show that there always exists an optimal policy that is an LT policy and also, obtain such a policy. When agents' outputs are stochastic, we show that the class of LT policies may not contain any optimal policy of problem P but is guaranteed to contain policies that are arbitrarily near optimal. Given any ϵ > 0 , we show how to obtain an LT policy whose performance is within ϵ of that of an optimal policy. This guarantee depends crucially on the use of sufficiently long histories of the agents' outputs. We also analyze LT policies with short histories and derive structural insights on the role played by (i) the length of the available history and (ii) the variability in the random variable governing an agent's output. We show that the average performance of these policies is within 5% of the optimum, justifying their popularity in practice. We then introduce and analyze the class of "score-based" reward policies; we show that this class is guaranteed to contain an optimal policy and also, obtain such a policy. Finally, we analyze a generalization in which the principal has a limited number for rewards in any given period and show that the class of score-based policies, with modifications to accommodate the limited availability of the rewards, continues to contain an optimal solution for the principal. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4482. [ABSTRACT FROM AUTHOR]

Companies that are investing in blockchain technology to enhance supply chain transparency face challenges in fostering collaborations with others and deciding what information to share. Transparency over the actions of supply chain partners can improve operational decisions, but sharing own data on the blockchain can put firms at a competitive disadvantage. In this paper, we investigate the resulting questions of when blockchain should be adopted in a supply chain and how it should be designed by analyzing two ways that it can enhance supply chain transparency: making the manufacturer's sourcing cost transparent to the buyers (i.e., vertical cost transparency) and making the ordering status of buyers transparent to each other (i.e., horizontal order transparency). Given such transparency, firms can design a smart contract that automates transactions contingent on the revealed information and enables them to realize better equilibrium outcomes. We find that blockchain increases supply chain profit only when the manufacturer's capacity is large and decreases supply chain profit otherwise. If the capacity is sufficiently large to eliminate the buyers' competition, blockchain leads to a win–win–win and the incentives of all participants are naturally aligned. If the capacity is only moderately large, the manufacturer needs to compensate the buyers to facilitate a blockchain implementation. However, if the capacity is small, horizontal order transparency enabled by the blockchain mitigates the buyers' overorder incentive to compete for the manufacturer's capacity and increases double marginalization. For such cases, we show that a blockchain that only enables vertical cost transparency should (and can) still be adopted in a range of small capacity cases, and we propose an access control layer for the logistics data to implement such a blockchain. This paper was accepted by David Simchi-Levi, operations management. Funding: J. Liu was supported by the National Natural Science Foundation of China [Grant 72101110] and The MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grant 20YJC630084]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4851. [ABSTRACT FROM AUTHOR]

Because of a growing population and shrinking arable land, the world is facing a global food crisis. One important solution could be to subsidize farmers to sustain their production so that they can produce more food for consumers and earn more money for themselves. An efficient subsidy program should also aim to reduce income inequality among farmers, as measured by the Gini coefficient of farmers' income. In this paper, we examine and compare the effects of input and output farm subsidy programs. The input subsidy reduces the farmers' input purchasing costs, whereas the output subsidy reduces the farmers' output processing costs. By considering a continuum of infinitesimal price-taking farmers who are heterogeneous in their average yield rates, our equilibrium analysis of a game-theoretical model yields three results. First, both subsidy schemes reduce the aggregate income inequality measured by the Gini coefficient. However, they create the following "opposite" effects: the input subsidy decreases the income gap among farmers (under mild conditions), whereas the output subsidy increases it. Second, farmers with low yield rates prefer the input subsidy, whereas farmers with high yield rates prefer the output subsidy. Third, the output subsidy scheme is more effective in improving the total farmer income than the input subsidy scheme, whereas the input subsidy scheme is more effective in reducing income disparities and improving consumer surplus than the output subsidy scheme. Our results provide new insights for policymakers who are crafting subsidy schemes. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71971184, 71972025, and 72032001], the Departmental General Research Fund of the Hong Kong Polytechnic University [Grant P0008761], and the Research Grants Council of Hong Kong [Grants 15504615 and 15500820]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4850. [ABSTRACT FROM AUTHOR]

Retailers managing both online and offline channels have to decide whether to adopt the uniform (i.e., charging the same price online and offline) or dual (i.e., charging different prices online and offline) pricing strategy. This decision is made even more challenging as consumers are increasingly multirooming as they may search offline and then purchase online (showrooming) or the other way around (webrooming). In this paper, we develop an analytical model to examine such a decision. The model takes into consideration (1) consumers' uncertainty about digital and nondigital product attributes, (2) consumers' costs of showrooming as well as webrooming, and (3) the prevalence of costly product return. We show that uniform pricing can be optimal for a monopoly retailer even though consumers have different costs for shopping online versus offline and there is no intrinsic disutility against price discrimination by consumers. In addition, when the uniform price is optimal, it can be lower than both the offline and online prices under optimal dual pricing. This is because, compared with dual pricing, uniform pricing eliminates consumers' uncertainty about the offline store's price so that they are more likely to search the nondigital attribute at the offline store and buy the fitted product. Moreover, a relatively higher online price has to be used under dual pricing to encourage consumers to search offline for the purpose of reducing the product return costs. This paper was accepted by Dmitri Kuksov, marketing. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71922008, 71972043, 72025102, and 72091211] and the Sci-Tech Innovation Foundation of School of Management at Fudan University [Grant 20210202]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4849. [ABSTRACT FROM AUTHOR]

In this paper, we identify product market competition as a driver of privatization. Using product market shocks caused by trade liberalization of China, which has the world's largest state sector, we find that subjecting state-owned enterprises (SOEs) to higher competition leads to an increase in private ownership. This response is strengthened when SOEs operate in industries with large technology or productivity gaps from those in the frontier economies or when SOEs impose large fiscal burdens on local governments. Our findings are consistent with politicians' incentives to boost economic growth for better career development and to shed burdens when rents decrease. This paper was accepted by Tomasz Piskorski, finance. Funding: C. Lin acknowledges financial support from the National Natural Science Foundation of China [Grant 72192841]. Q. Hu acknowledges financial support from the Fundamental Research Funds for the Central Universities and the Renmin University of China [Grant 21XNF002]. W. Li acknowledges financial support from the Major Project of the Ministry of Education [Grant 22JZD007] and the National Natural Science Foundation of China [Grant 72132002]. L. Wei acknowledges financial support from the Research Grants Council, University Grants Committee [Grant 13501619]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4847. [ABSTRACT FROM AUTHOR]

Substantial funding is provided to the healthcare systems of low-income countries. However, an important challenge is to ensure that this funding is used efficiently. This challenge is complicated by the fact that a large share of healthcare services in low-income countries is provided by nonprofit health centers that often lack (i) effective governance structures and (ii) organizational know-how and adequate training. In this paper, we argue that the bundling of performance-based incentives with auditing and feedback (A&F) is a potential way to overcome these obstacles. First, the combination of feedback and performance-based incentives—that is, feedback joined with incentives to act on this feedback and achieve specific health outcomes—helps address the knowledge gap that may otherwise undermine performance-based incentives. Second, coupling feedback with auditing helps ensure that the information underlying the feedback is reliable—a prerequisite for effective feedback. To examine the effectiveness of this bundle, we use data from a randomized governance program conducted in the Democratic Republic of Congo. Within the program, a set of health centers was randomly assigned to a "governance treatment" that consisted of performance-based incentives combined with A&F, whereas others were not. Consistent with our prediction, we find that the governance treatment led to (i) higher operating efficiency and (ii) improvements in health outcomes. Furthermore, we find that funding is not a substitute for the governance treatment; health centers that only receive funding increase their scale but do not show improvements in operating efficiency or health outcomes. This paper was accepted by Lamar Pierce, organizations. Funding: This research was supported by the Agence Nationale de la Recherche [Grant Investissements d'Avenir (LabEx Ecodec)]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4846. [ABSTRACT FROM AUTHOR]

This paper studies a dynamic principal–agent setting in which the principal needs to dynamically schedule an agent to work or be suspended. When the agent is directed to work and exert effort, the arrival rate of a Poisson process is increased, which increases the principal's payoff. Suspension, on the other hand, serves as a threat to the agent by delaying future payments. A key feature of our setting is a switching cost whenever the suspension stops and the work starts again. We formulate the problem as an optimal control model with switching and fully characterize the optimal control policies/contract structures under different parameter settings. Our analysis shows that, when the switching cost is not too high, the optimal contract demonstrates a generalized control-band structure. The length of each suspension episode, on the other hand, is fixed. Overall, the optimal contract is easy to describe, compute, and implement. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis. Funding: The work of P. Cao is financially supported by the National Natural Science Foundation of China [Grants 72122019 and 71771202]. The work of F. Tian is financially supported by the Hong Kong Research Grants Council (RGC) funding (RGC Early Career Scheme 2022/23) [Grant 27500822]. Supplemental Material: The e-companion and data are available at https://doi.org/10.1287/mnsc.2023.4845. [ABSTRACT FROM AUTHOR]

A significant proportion of the world's population has no access to grid-based electricity and so relies on off-grid lighting solutions. Rechargeable lamp technology is gaining popularity as an alternative off-grid lighting model in developing countries. In this paper, we explore consumer behavior and the operational inefficiencies that result under this model. Specifically, we are interested in (i) measuring the impact of inconvenience (of traveling to recharge the lamp) along with the impact of liquidity constraints (because of poverty) on lamp usage and (ii) evaluating the efficacy of strategies that address these factors. We build a structural model of consumers' recharge decisions that incorporates several operational features of the low-income regions. We conducted large-scale field experiments in Rwanda in partnership with a local rechargeable lamp operator and use the resultant data to estimate and test our model. We find that the complete removal of inconvenience and liquidity constraints from the current business model results in 73% and 126% increases in both recharges and revenue, thereby suggesting that these constraints are major sources of inefficiency. By implementing simple operations-based strategies—such as starting more recharge centers, visiting consumers periodically to collect their lamps for recharge, and allowing consumers to partially recharge their lamps and pay flexibly for the recharge—more than half the benefit of completely eliminating the inefficiencies can be attained. By contrast, the price- and capacity-based strategies that vary the economic variables (i.e., the amount paid per recharge and the amount of light obtained in return) but not the operational model perform far worse than the aforementioned strategies. Overall, our analysis emphasizes the importance of managing operations effectively even in markets with cash-constrained consumers, in which firms may have a natural tendency to focus more on reducing prices. This paper was accepted by Vishal Gaur, operations management. Funding: This work was supported by the International Growth Centre; Wharton School, University of Pennsylvania; and Institut Européen d'Administration des Affaires; The Environment and Energy Partnership; Grand Challenges Canada (Stars in Global Health); INSEAD's Emerging Markets Institute; INSEAD's Randomized Controlled Trials Laboratory; the INSEAD–Wharton Alliance, and International Growth Centre. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4844. [ABSTRACT FROM AUTHOR]

Unusual events trigger persistent spikes in uncertainty. Standard models cannot match these dynamic patterns. This paper presents a unified framework, motivated by the literature on inattention. Agents choose whether and how to prepare for different possible states of the world by collecting information. Agents optimally ignore sufficiently unlikely events, so the occurrence of such events does not resolve, but rather increases, uncertainty. Uncertain agents have dispersed beliefs, making it harder to focus future preparation. Thus, uncertainty begets uncertainty for an inattentive agent, endogenously persisting. In a financial application, this framework matches patterns in volatility, volume of trade, belief dispersion, and spreads. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data file is available at https://doi.org/10.1287/mnsc.2023.4836. [ABSTRACT FROM AUTHOR]

People often need to plan how to allocate their attention across different tasks. In this paper, we run two experiments to study a stylized version of this attention-allocation problem between strategic tasks. More specifically, we present subjects with pairs of 2 × 2 games, and for each pair, we give them 10 seconds to decide how they would split a fixed time budget between the two games. Then, subjects play both games without time constraints, and we use eye-tracking to estimate the fraction of time they spend on each game. We find that subjects' planned and actual attention allocation differ and identify the determinants of this mismatch. Further, we argue that misallocations can be relevant in games in which a player's strategy choice is sensitive to the time taken to reach a decision. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: Work on this project was provided by the National Science Foundation [Grant SES 1724550] "Collaborative Research: Attention in Games and Decisions," awarded to A. Schotter and E. R. Schotter. The work of M. Ribeiro and M. Zou was supported by the Center for Experimental Economics Social Science at New York University. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4834. [ABSTRACT FROM AUTHOR]

This paper studies a canonical general scheduling model that captures the fundamental trade-off between processing jobs and performing diagnostics (testing). In particular, testing reveals the required processing time and urgency of need-to-schedule jobs to inform future scheduling decisions. The model captures a range of important applications. Prior work focused on special cases (e.g., jobs with independent and identically distributed processing time) to devise optimal policies. In contrast, the current paper studies the most general form of the model and describes two simple heuristics to solve it; adaptive weighted shortest processing time is an adaptive generalization of Smith's rule that optimally solves several important extensions of previously studied models, whereas index policy optimally solves a closely related stochastic optimization bandit problem. The latter achieves an approximation guarantee that quickly approaches a constant factor that is bounded by two as the number of jobs grows and approaches optimally when the testing time decreases. Extensive numerical experiments suggest that our policies effectively solve the general setting (under 0.1% from optimal on average and under 10% from optimal in rare, worst-case instances). This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4833. [ABSTRACT FROM AUTHOR]

In this paper, we explore an employee workaround widespread in K–12 schools: compensating for insufficient funding with partnerships to nonprofit organizations (NPOs). We take an equity perspective and ask the following questions. (i) How do partnering workarounds differ across schools with different levels of socioeconomic advantage? (ii) What can education and NPO leaders do to ensure these workarounds do not exacerbate educational inequities? To answer these questions, we use Little's Law: a school's long-run average number of resource-supplementing partnerships (L) is a function of its average annual partnership formation rate (λ) and partnership cycle time (W). We collect and analyze interview (n = 62) and survey (n = 140) data from six strategically sampled schools with different levels of socioeconomic advantage to compare differences in λ and W and understand the implications for educational equity. We find wealthier schools have higher λ, making them more productive. We also find schools have equal W independent of wealth, but this problematically amplifies differences in λ. The difference in partnering productivity translates to educational inequities. We find that poorer schools report about 35% greater utility per partnership, but that is not enough to offset the disadvantage of fewer partnerships. Moreover, we find that differences in partnering productivity are particularly large for curricular partnerships, which are harder for poorer schools to form because of the high demand for wrap-around partnerships. Our findings contribute new knowledge on workarounds which supplement organizational resources and on the relationship between workarounds and equity. This paper was accepted by Jay Swaminathan, operations management. Funding: This work was supported by the National Science Foundation [Grant 1344266]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4829. [ABSTRACT FROM AUTHOR]

This paper challenges two common views of brand dilution: first, that it is exclusively the unintended consequence of a poorly executed strategy of brand extension and, second, that its likelihood is heightened by brand licensing. Using a new theoretical model, we show that brand dilution can be seen not just as an unfortunate development to be avoided, but as an opportunity to monetize the brand. We further show that, at the relevant margin, switching from in-house development to licensing reduces the risk of brand dilution. The model offers a novel perspective on some important managerial choices and generates a series of empirically testable hypotheses. This paper was accepted by Dmitri Kuksov, marketing. Funding: Financial support from PRIN 20157NHSTP004 is gratefully acknowledged. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.00852. [ABSTRACT FROM AUTHOR]

Educational inequality undermines the pivotal role of education in increasing the ability of the poor to move up the income ladder. This paper investigates educational inequality that arises from low-income students' lack of monetary resources that higher-income students invest in education. We show low-income students' inability to make monetary investments in education reduces their incentive to study and contributes to educational inequality. In the context of developing markets, we study implications of a reservation policy that aims to reduce inequality by reserving some college seats for students of the disadvantaged group. The policy essentially transfers college seats from the advantaged student group to the disadvantaged student group and as a result increases the welfare of students from the disadvantaged group. In some cases, the seat transfer also improves the welfare of higher-income students. We show such a transfer, if small, can enhance overall student welfare in developing markets. However, a large transfer may reduce overall student welfare. Finally, we show the welfare-maximizing transfer is usually smaller than inequality-minimizing transfer of seats. This paper was accepted by Dmitri Kuksov, marketing. Funding: J. Ni was partially supported by the National Natural Science of China Grant [71832010]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2021.00249. [ABSTRACT FROM AUTHOR]

Based on a representative sample of consumer financial transaction data, this paper studies the consumption and savings response to a 2015 permanent increase in the marginal income tax of the high-income taxpayers. Using difference-in-differences regressions, controlling for individual and time fixed effects, we show robust results that the affected consumers experienced little change in their spending. The pattern is prevalent across consumer demographics and is found even among consumers who are sophisticated, have high levels of debt, or register little income changes. Furthermore, the tax increase financed fiscal redistribution leads to a long-lasting increase in the consumption of the lower-income population. This paper was accepted by Lukas Schmid, finance. Funding: The authors gratefully acknowledge financial support from Social Science Research Thematic Grant in Singapore [Future-Proofing Singapore: An Economic Approach MOE2019-SSRTG-024]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4823. [ABSTRACT FROM AUTHOR]

We conducted a randomized, controlled trial with small- and medium-sized enterprises in Kenya to estimate the causal impact of an electronic payment (e-payment) technology on business finance. Using an encouragement design, we exogenously increased e-payment usage among a random subset of firms by relaxing adoption transaction costs and information barriers. Sixteen months after the intervention, we find that the e-payment technology increased access to mobile loans (in the number of loans as well as in the amount borrowed) by at least 50% (0.17 standard deviation), likely because of the reduction of information asymmetries brought by an increase in digital transactions. We find no effect of the e-payment technology on sales and profits, but we do find a reduction of sales volatility and precautionary investment, especially for smaller firms. This suggests that mobile loans help smaller firms cope with short-term negative shocks. We provide a stylized model of business finance that rationalizes these findings. This paper was accepted by Bruno Biais, finance. Funding: This paper was produced under the framework of the "Enabling Innovation and Productivity Growth in Low Income Countries (EIP-LIC/PO5639)" project, funded by the Department for International Development (DFID) of the United Kingdom and implemented by Tilburg University. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4821. [ABSTRACT FROM AUTHOR]

This paper examines mutual funds' dual role as both clients and shareholders of broker banks. Mutual funds are more likely to hold and significantly overweight stocks of their broker banks. In line with the portfolio decisions, fund voting is biased toward broker management in contentious proposals. Such voting bias is inconsistent with maximizing broker banks' shareholder value yet significantly affects voting outcomes and the presence of contentious proposals at the banks' shareholder meetings. Furthermore, we show that although client funds are rewarded with preferential initial public offering allocations from connected brokers for their voting support, fund managers' engagement in reciprocal practices is ultimately determined by the economic tradeoffs they face. Our study not only uncovers a new mechanism—being brokers' friendly shareholders—through which the two parties maintain their quid pro quo relationships but also raises a broader concern about governance of important financial institutions. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4820. [ABSTRACT FROM AUTHOR]

Disputes over transactions on two-sided platforms are common and usually arbitrated through platforms' customer service departments or third-party service providers. This paper studies crowd-judging, a novel crowdsourcing mechanism whereby users (buyers and sellers) volunteer as jurors to decide disputes arising from the platform. Using a rich data set from the dispute resolution center at Taobao, a leading Chinese e-commerce platform, we aim to understand this innovation and propose and analyze potential operational improvements with a focus on in-group bias (buyer jurors favor the buyer, likewise for sellers). Platform users, especially sellers, share the perception that in-group bias is prevalent and systematically sways case outcomes as the majority of users on such platforms are buyers, undermining the legitimacy of crowd-judging. Our empirical findings suggest that such concern is not completely unfounded: on average, a seller juror is approximately 10% likelier (than a buyer juror) to vote for a seller. Such bias is aggravated among cases that are decided by a thin margin and when jurors perceive that their in-group's interests are threatened. However, the bias diminishes as jurors gain experience: a user's bias reduces by nearly 95% as experience grows from zero to the sample median level. Incorporating these findings and juror participation dynamics in a simulation study, the paper delivers three managerial insights. First, under the existing voting policy, in-group bias influences the outcomes of no more than 2% of cases. Second, simply increasing crowd size through either a larger case panel or aggressively recruiting new jurors may not be efficient in reducing the adverse effect of in-group bias. Finally, policies that allocate cases dynamically could simultaneously mitigate the impact of in-group bias and nurture a more sustainable juror pool. This paper was accepted by Vishal Gaur, operations management. Funding: S. A. Yang and A. Zhang acknowledge the support of the Hong Kong General Research Fund [Grant "Decentralizing Platform Governance: Innovations from China; Project 17614921]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4818. [ABSTRACT FROM AUTHOR]

This paper studies the effects of default risk on expected equity option returns. In the cross-section, expected delta-hedged equity option returns have a negative relation with default risk measured by credit ratings or default probability. In the time series, credit rating downgrades (upgrades) lead to a decrease (increase) in the firm's delta-hedged option return. Our results are consistent with a stylized capital structure model in which the negative relation between option returns and default risk is driven by firm leverage and asset volatility. This paper was accepted by Lukas Schmid, finance. Funding: A. Vasquez thanks the Asociación Mexicana de Cultura A.C. for financial support. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4796. [ABSTRACT FROM AUTHOR]

This paper studies whether credit ratings can alleviate the hold-up problem in the loan market. We exploit a refinement of the rating information produced by a certifier that rates private bank-dependent firms in France on a vast scale. The refinement causes some firms to receive a positive rating surprise that is not due to an improvement in firm fundamentals. We show that affected firms become less reliant on lenders that have greater ability to extract informational rents. These firms receive greater and less expensive bank credit from new and less informed lenders and invest more. We deduce that credit ratings reduce the monopoly power of informed banks, helping firms to expand their access to bank credit. This paper was accepted by David Sraer, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4779. [ABSTRACT FROM AUTHOR]

This paper studies network market problems in which firm(s)/platform(s) sets quality in addition to price. A well-established result in the network economics literature is that a profit-maximizing firm concerns only how quality is valued by the marginal consumer but not by inframarginal consumers, aka the Spence effect/distortion. For markets with strong network effects under which multiple market-tipping equilibria exist, I show that the validity of the previous result depends on the choice of the equilibrium selection criterion. Precisely, I show that all criteria commonly used in this literature give rise to the Spence effect, whereas the well-justified risk dominance criterion in game theory and its generalizations do not. Novel quality strategies are derived based on the latter criteria. This paper was accepted by Joshua Gans, business strategy. [ABSTRACT FROM AUTHOR]

One advantage of online retail is that a large number of products can be displayed at low cost. However, online retailers must decide which of these products to carry in inventory (stock items) and which to order from suppliers when a customer places an order (nonstock items). In this paper, we empirically investigate how carrying a product in inventory affects its online sales. We use data from a European furniture and interior design retailer consisting of daily sales transactions and inventory data covering 18 months. We use a quasi-natural experiment—random transitions of products in and out of inventory at the retailer's central warehouse—to estimate the causal effect of carrying inventory on sales. Our results show a strong and statistically significant increase in sales of, on average, 65% associated with having the product available in stock. More interestingly, this effect differs between products and is moderated by the price of the product: sales of more expensive products are less sensitive to the product being in stock. We use these results to draw insights on which types of items to carry in inventory. This paper was accepted by Victor Martínez-de-Albéniz, operations management. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2023.4777. [ABSTRACT FROM AUTHOR]

This paper extends the methodology of statistically extracting latent factors in settings with return-predictive firm characteristics as conditional covariances (betas) between returns and factors. The main feature is that the pricing errors (alphas) are specified to be orthogonal to the affine-transformed firm characteristics as the betas with one component of pricing errors lying outside the space spanned by the firm characteristics. The specification is shown to make substantial differences with the extant literature as the zero pricing error hypothesis is strongly rejected for various models with commonly used firm characteristics. This paper was accepted by Agostino Capponi, finance. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2023.4768. [ABSTRACT FROM AUTHOR]

This paper provides evidence from a natural experiment on the relationship between positive affect and productivity. We link highly detailed administrative data on the behaviors and performance of all telesales workers at a large telecommunications company with survey reports of employee happiness that we collected on a weekly basis. We use variation in worker mood arising from visual exposure to weather—the interaction between call center architecture and outdoor weather conditions—to provide a quasi-experimental test of the effect of happiness on productivity. We find evidence of a positive impact on sales performance, which is driven by changes in labor productivity—largely through workers converting more calls into sales and to a lesser extent by making more calls per hour and adhering more closely to their schedule. We find no evidence in our setting of effects on measures of high-frequency labor supply such as attendance and break-taking. This paper was accepted by Yuval Rottenstreich, behavioral economics and decision analysis. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4766. [ABSTRACT FROM AUTHOR]

This paper studies how competition affects the role of reputation in encouraging sellers to exert effort. More competition disciplines sellers, but at the same time, it erodes reputational premia. This paper identifies whether one effect dominates the other using data from Airbnb. I exploit the introduction of a short-term rental regulation effective in San Francisco in 2017 that halved the number of short-term listings on the platform. I focus on hosts who are present on the platform before and after the regulation, and I identify a negative causal effect of the number of competitors on ratings about hosts' effort. I extend this result with two other measures of effort: hosts' response rate and response time. I confirm that hosts exert less effort when the number of competitors increases. The rate of responses within 24 hours decreases, and response time increases. This paper was accepted by Matthew Shum, marketing. Funding: This work was supported by the Ministerio de Economía, Industria y Competitividad (Spain) [Grant ECO2016-78632-P]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4758. [ABSTRACT FROM AUTHOR]

In this paper, we solve a class of two-stage distributionally robust optimization problems that have the property of supermodularity. We exploit the explicit worst case expectation of supermodular functions and derive the worst case distribution for the robust counterpart. This enables us to develop an efficient method to obtain an exact optimal solution to these two-stage problems. Further, we provide a necessary and sufficient condition for checking whether any given two-stage optimization problem has the supermodularity property. We also investigate the optimality of the segregated affine decision rules when problems have the property of supermodularity. We apply this framework to several classic problems, including the multi-item newsvendor problem, the facility location problem, the lot-sizing problem on a network, the appointment-scheduling problem, and the assemble-to-order problem. Whereas these problems are typically computationally challenging, they can be solved efficiently under our assumptions. Finally, numerical examples are conducted to illustrate the effectiveness of our approach. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the National Natural Science Foundation of China [Grant 71971187], and Hong Kong Research Grants Council [Collaborative Research Fund (C6103-20GF), General Research Fund (14210821, 16204521, 16212419)]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4748. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of information sharing between a retail platform and a manufacturer in a supply chain. We develop a stylized model salient to which is that the product's quality is a priori unknown to customers, who can infer it from customer-generated reviews. The platform, in turn, has access to private information concerning the relationship between quality and demand, and the manufacturer can choose to acquire said information to help determine the quality of its product accordingly. Our analysis yields three main insights. First, information sharing in and of itself induces the manufacturer to improve quality. Second, under a wholesale price contract, information sharing and product reviews together have a negative effect on product quality: When each firm is able to adjust its price in response to the quality signal, it benefits the manufacturer and hinders the platform. Consequently, the presence of reviews discourages the platform from sharing information, and the manufacturer tends to produce a lower-quality product. Finally, the negative effect of product reviews on the supply chain can be mitigated when the platform can share less accurate information or when the platform and manufacturer make a commission contract, rather than a wholesale price contract. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: D. Shin received financial support from the Hong Kong University of Science and Technology [grant IGN17BM09]. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4746. [ABSTRACT FROM AUTHOR]

The rapid adoption of artificial intelligence (AI) technologies by many organizations has recently raised concerns that AI may eventually replace humans in certain tasks. In fact, when used in collaboration, machines can significantly enhance the complementary strengths of humans. Indeed, because of their immense computing power, machines can perform specific tasks with incredible accuracy. In contrast, human decision makers (DMs) are flexible and adaptive but constrained by their limited cognitive capacity. This paper investigates how machine-based predictions may affect the decision process and outcomes of a human DM. We study the impact of these predictions on decision accuracy, the propensity and nature of decision errors, and the DM's cognitive efforts. To account for both flexibility and limited cognitive capacity, we model the human decision-making process in a rational inattention framework. In this setup, the machine provides the DM with accurate but sometimes incomplete information at no cognitive cost. We fully characterize the impact of machine input on the human decision process in this framework. We show that machine input always improves the overall accuracy of human decisions but may nonetheless increase the propensity of certain types of errors (such as false positives). The machine can also induce the human to exert more cognitive efforts, although its input is highly accurate. Interestingly, this happens when the DM is most cognitively constrained, for instance, because of time pressure or multitasking. Synthesizing these results, we pinpoint the decision environments in which human-machine collaboration is likely to be most beneficial. This paper was accepted by Jeannette Song, operations management. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4744. [ABSTRACT FROM AUTHOR]

This paper evaluates liquidity requirements and public liquidity injections in the context of financial crises, using a model that includes near-money assets. Some key effects are transmitted through liquidity premia and the price of liquid assets, producing a heterogeneous impact that depends on an agent's holdings of liquid assets. In addition, some agents prefer policies that do not fully relax their liquidity constraints because these policies are associated with higher prices. Liquidity requirements and liquidity injections have the opposite impact on liquidity premia and combining them leads to Pareto improvements that cannot be achieved by each policy separately. This paper was accepted by Gustavo Manso, finance. Funding: This work was supported by the Wisconsin Alumni Research Foundation. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4737. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology to price bonds jointly issued by a group of countries—Eurobonds in the euro-area context. We consider two types of bonds; the first is backed by several and joint guarantees (SJGs), and the second features several but not joint guarantees (SNJGs). The pricing of SJG and SNJG bonds reflects different assumptions regarding the pooling of debtors' fiscal resources. We estimate fiscal limits for the six largest euro-area economies over 2008–2021 and deduce counterfactual Eurobond prices. For the five-year maturity, SNJG bond yield spreads would have been about three times larger than SJG ones over the estimation sample. Hence, issuing SJG bonds could result in gains at the aggregate level. Notwithstanding, our model also predicts that gains may temporarily vanish in periods of acute fiscal stress. We finally envision postissuance redistribution schemes, whereby gains stemming from the issuance of SJG bonds could be shared among participating countries; we argue that these schemes may alleviate the reduction in market discipline resulting from common bonds issuance. This paper was accepted by David Sraer, finance. Funding: This work has benefited from financial support from the Swiss National Science Foundation [Grant 182293]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4740. [ABSTRACT FROM AUTHOR]

Start-ups are increasingly using social media to signal quality and provide information to potential investors. However, the effectiveness of social media on venture capital (VC) financing is likely to be heterogeneous, differing by demographic and network characteristics of the founders. In this paper, we examine whether social media use can improve funding outcomes for firms founded by women and by other people also lacking connections to the investor network, two groups that face greater difficulties in securing VC financing. Using Twitter data and data on VC investment in start-ups from Crunchbase, we explore the interaction effect between Twitter usage and gender and between Twitter usage and the network constraint measure. Overall, we show that social media can mitigate some disparities in financing experienced by these firms through improving information access. We find that this effect is stronger for first-time entrepreneurs than for experienced ones, stronger for attracting new investors than repeat ones, and stronger in more competitive markets. Collectively, these results suggest that social media could primarily help women and less connected individuals obtain financing by alleviating information asymmetry between founders and investors. This paper was accepted by D. J. Wu, information systems. Funding: The authors thank Wharton Mack Institute of Innovation Management for funding support. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4728. [ABSTRACT FROM AUTHOR]

This paper studies an emerging subscription model called ship-then-shop. Leveraging its predictive analytics and artificial intelligence (AI) capability, the ship-then-shop firm curates and ships a product to the consumer, after which the consumer shops (i.e., evaluates product fit and makes a purchase decision). The consumer first pays the up-front ship-then-shop subscription fee prior to observing product fit and then pays the product price afterward if the consumer decides to purchase. We investigate how the firm balances the subscription fee and product price to maximize its profit when consumers can showroom. A key finding is the ship-then-shop firm's nonmonotonic surplus extraction strategy with respect to its prediction capability. As prediction capability increases, the firm first switches from ex ante to ex post surplus extraction (by lowering fees and raising prices). However, if the prediction capability increases further, the firm reverts to ex ante surplus extraction (by raising fees and capping prices). We also find that the ship-then-shop model is most profitable when (i) the prediction capability is advanced, (ii) the search friction in the market is large, or (iii) the product match potential is large. Finally, we show that the marginal return of AI capability on the firm's profit decreases in search friction but increases in product match potential. Taken together, we provide managerially relevant insights to help guide the implementation of the innovative subscription model. This paper was accepted by Dmitri Kuksov, marketing. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4723. [ABSTRACT FROM AUTHOR]

Through repeated interactions, firms today refine their understanding of individual users' preferences adaptively for personalization. In this paper, we use a continuous-time bandit model to analyze firms that recommend content to multihoming consumers, a representative setting for strategic learning of consumer preferences to maximize lifetime value. In both monopoly and duopoly settings, we compare a forward-looking recommendation algorithm that balances exploration and exploitation to a myopic algorithm that only maximizes the quality of the next recommendation. Our analysis shows that, compared with a monopoly, firms competing for users' attention focus more on exploitation than exploration. When users are impatient, competition decreases the return from developing a forward-looking algorithm. In contrast, development of a forward-looking algorithm may hurt users under monopoly but always benefits users under competition. Competing firms' decisions to invest in a forward-looking algorithm can create a prisoner's dilemma. Our results have implications for artificial intelligence adoption and for policy makers on the effect of market power on innovation and consumer welfare. This paper was accepted by Dmitri Kuksov, marketing. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4722. [ABSTRACT FROM AUTHOR]

Highly skilled workers are not only a crucial and relatively scarce input into firms' productive and innovative processes, but are also a critical resource determining competitive advantage. An increasingly high proportion of these workers in the United States were born abroad and permitted to work on skilled worker visas. How do multinational firms respond when artificial constraints, namely, policies restricting skilled immigration, are placed on their ability to hire scarce human capital? This paper combines visa microdata and comprehensive data on U.S. multinational firm activity to demonstrate that firms respond to restrictions on H-1B immigration by increasing foreign affiliate employment at the intensive and extensive margins, particularly in China, India, and Canada. The most impacted jobs were R&D-intensive ones, but there is some evidence that non-R&D employment was also affected. The paper highlights a means by which firms can circumvent constraining policies and mitigate country-level risk, and it also suggests that, for the average multinational company (MNC), this means is imperfect; for every visa rejection, they hire 0.4 employees abroad. The most globalized MNCs are the most likely to respond to these restrictions by offshoring, highlighting that firm capabilities—in the form of prior internationalization—shape the decision and ability to offshore in response to skilled immigration restrictions; indeed, these firms hire 0.9 employees abroad for every visa rejection. More broadly, the paper provides evidence of a push factor for internationalizing knowledge activity: artificial constraints on resources result in firms circumventing restrictive policies in ways that may not be anticipated by policy makers. This paper was accepted by Alfonso Gambardella, business strategy. Funding: This work was supported by the Mack Institute for Innovation Management. Supplemental Material: The online appendix and data are available at https://doi.org/10.1287/mnsc.2023.4715. [ABSTRACT FROM AUTHOR]

Unemployment risk influences workers' incentives to invest in firm-specific human capital. This paper investigates the impact of unemployment risk on chief executive officers (CEOs)' risk-taking incentive compensation. Exploiting state-level changes in unemployment benefits, we find that after unemployment insurance benefits become more generous, boards increase the convex payoff structure of CEO pay to encourage risk taking. The increase in CEOs' convexity payoff is stronger in firms with more independent and diverse boards, higher ownership of long-term shareholders, and in industries requiring highly skilled labor. Our findings suggest that boards internalize workers' interests in firms' risk-taking decisions and executive compensation is one mechanism used. This paper was accepted by David Simchi-Levi, finance. Funding: K. Zhang acknowledges financial support from the National Natural Science Foundation of China [Grants 72272099 and 71902115]. Supplemental Material: Data and the online appendix are available at https://doi.org/10.1287/mnsc.2023.4714. [ABSTRACT FROM AUTHOR]

This paper provides empirical evidence on predictable time variations in out-of-sample bond return predictability. Bond return predictability is associated with periods of high (low) economic activity (uncertainty), which implies that violations of the expectations hypothesis are state dependent and linked to features of the business cycle. These state dependencies in predictability, established by introducing a new multivariate test for equal conditional predictive ability, can be used in real time to improve out-of-sample bond risk premia estimates and investors' economic utility through a novel dynamic forecast combination scheme that uses predicted forecasting performance to identify the best set of methods to include in the combined forecast. Dynamically combined forecasts exhibit strong countercyclical behavior and peak during recessions. This paper was accepted by Lukas Schmid, finance. Funding: This work was supported by the Danish Council of Independent Research [Grants DFF 7024–00020B and DFF 9033–00003B] and the Danish Finance Institute. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4713. [ABSTRACT FROM AUTHOR]

Exhibiting altruism toward and cooperativeness with others is a key ingredient for successful work relationships and managerial decision making. Rising political polarization creates a hazard because it ruptures this fabric and impedes the interaction of employees, especially across political isles. This paper's focus is to examine various behavioral-, belief-, and norm-based layers of (non)strategic decision making that are plausibly affected by polarization. I quantify this phenomenon via five preregistered studies in the context of Donald J. Trump, comprising 15 well-powered behavioral experiments and a diverse set of over 8,600 participants. To capture the pervasiveness of polarization, I contrast the findings with various political and nonpolitical identities. Overall, I consistently document strong heterogeneous effects: ingroup-love occurs in the perceptional domain (how close one feels toward others), whereas outgroup-hate occurs in the behavioral domain (how one helps/harms/cooperates with others). The rich setting also enables me to examine the mechanisms of observed intergroup conflict, which can be attributed to one's grim expectations regarding cooperativeness of the opposing faction, rather than one's actual unwillingness to cooperate. For the first time, the paper also tests whether popular behavioral interventions (defaults and norm-nudges) can reduce the detrimental impact of polarization in the contexts studied here. The tested interventions improve prosociality but are ineffective in closing the polarization gap. This paper was accepted by Yan Chen, behavioral economics and decision analysis. Funding: This work was supported by Deutsche Forschungsgemeinschaft [Grant EXC 2126/1– 390838866]. Supplemental Material: Data and the online appendix are available at https://doi.org/10.1287/mnsc.2023.4701. [ABSTRACT FROM AUTHOR]

In this paper, I analyze the joint design of capital requirements and fair value reporting rules for financial institutions with illiquid assets. I specifically examine how prudential regulation aimed at solving agency problems affects financial institutions' incentives to use Level 2 versus Level 3 fair value reporting, as well as financial stability. Crucially, Level 3 reporting allows financial institutions to use their private information, whereas Level 2 fair values are only measured with public information. Interestingly, my analysis shows regulators may leave to financial institutions the discretion to report illiquid assets at Level 2 or Level 3. Financial institutions then report at Level 3 only if they have good private information about the assets' quality. Moreover, prudential rules that only rely on Level 2 fair values may be efficient at solving agency problems within financial institutions but may also decrease financial stability. By contrast, prudential rules that leave to financial institutions the discretion to report illiquid assets at Level 2 or Level 3 while relaxing capital requirements may increase financial stability. This paper was accepted by Suraj Srinivasan, accounting. Funding: This work was supported by the H2020 European Research Council [Grant 669217]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4692. [ABSTRACT FROM AUTHOR]

This paper studies intertemporal asset pricing in network economies when distress shocks can propagate through the network, similarly to epidemic outbreaks. Two classes of equilibria exist. In the first, idiosyncratic shocks are diversifiable and do not affect valuations; the consumption capital asset pricing model applies. In the second, idiosyncratic shocks generate nondiversifiable long-run cascades of shocks (financial pandemics) that introduce a new risk premium component unexplained by traditional systematic factors. We derive closed solutions for asset prices as a function of the network properties and discuss their properties. After a structural break (1984), we find evidence of a network risk premium that is statistically and economically significant. This paper was accepted by Agostino Capponi, finance. Funding: This work was supported by Ministero dell'Istruzione, dell'Università e della Ricerca [Grant PRIN-2017TA7TYC] and Baffi CAREFIN. C. Tebaldi is a fellow of Baffi CAREFIN and Innocenzo Gasaprini Institute for Economic Research Centers. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4687. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the economic value of a blockchain application. In the context of asset-backed securities (ABS) issuance in China, where some ABS are issued with blockchain technology and others are not, we find that the use of blockchain significantly reduces the coupon yield at issuance. Compared with other ABS, those issued using blockchain technology experience a decrease of 31.4 basis points in the yield spread, which corresponds to a relative decrease of 13%. We further document that the effect of blockchain is more pronounced for ABS deals rated by less reputable credit rating agencies and agencies that rely more on issuers for their rating business, for revolving ABS, and for ABS with a larger number of underlying assets. We also find that the use of blockchain can reduce the level of retained interest and number of credit enhancement mechanisms. This paper contributes to the literature by providing a small-sample analysis of the economic value of a blockchain application in financial markets. This paper was accepted by Brian Bushee, accounting. Funding: X. Chen and Q. Cheng acknowledge funding provided by the Lee Kong Chian Professorship at Singapore Management University. This work was supported by Singapore Ministry of Education [Grant MOE-T2EP40120-0005]. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2023.4671. [ABSTRACT FROM AUTHOR]

This paper studies how a tick size change affects market quality, price discovery, and the competition for liquidity provision by dealers and high-frequency trading firms (HFTs) in the U.S. Treasury market. Using difference-in-differences regressions around the November 19, 2018, tick size reduction in the 2-year Treasury note and a similar change in the 2-year futures eight weeks later, we find significantly improved market quality. Moreover, dealers become more competitive in liquidity provision and price improvement, consistent with the hypothesis that HFTs find liquidity provision less profitable in the smaller tick size environment. Last, we find a significant shift in short-run price discovery toward the cash market, which then reverses when the futures market tick size is reduced, suggesting that the finer pricing grid in the cash market allows traders to act on small information signals that are not profitable to exploit in the larger-tick futures market. Our findings suggest that reducing the tick size in tick-constrained and highly liquid markets like the Treasury market is on balance beneficial. This paper was accepted by Bruno Biais, finance. Funding: F. Ruela acknowledges support from the National Science Foundation Graduate Research Fellowship Program [Grant DGE-1746045]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4663. [ABSTRACT FROM AUTHOR]

This paper studies the cost of capital effect of a major regulatory technology, or RegTech, event: the staggered implementation of the Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system of the Securities and Exchange Commission in the period from 1993 to 1996. This event represents a largely exogenous shock to corporate information dissemination technologies, resulting in a considerable reduction in information acquisition costs for investors. Using a difference-in-differences research design, we show that the cost of equity capital declines substantially after a firm switches from paper filing to mandatory electronic filing in EDGAR. The effect is stronger for small firms and firms with low analyst coverage and low institutional ownership. We identify three channels through which EDGAR affects a firm's cost of capital: the liquidity, risk-taking, and corporate governance channels. EDGAR implementation also improves a firm's investment efficiency significantly. We find evidence that the marginal value of a firm's capital investment and cash is higher during the post-EDGAR period. This paper was accepted by Suraj Srinivasan, accounting. Funding: C. Lin acknowledges financial support from the National Science Foundation of China [Grant 72192841] and the Research Grants Council of the Hong Kong Special Administration Region, China [Project HKU R7054-18 and T35/710/20R]. S. Lai acknowledges financial support from the Ministry of Science and Technology, Taiwan [Grants 107-2410-H-002-038-MY3 and 110-2410-H-002-079-MY2] and the E. Sun Academic Award. X. Ma acknowledges research support from the University of Macau [Grants SRG2019-00158-FBA and MYRG2020-00259-FBA]. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2022.4660. [ABSTRACT FROM AUTHOR]

How do firms address complex collective action problems effectively? Institutional and stakeholder research suggests that firms may avoid the tragedy of the commons by aligning the interests of critical proximate stakeholders in ways that governments cannot accomplish. This phenomenological paper investigates this possibility by analyzing Amazon rainforest preservation by Natura, a Brazilian cosmetics company. The results indicate that Natura internalized environmental externalities by linking ecologically conscious consumers with rural Amazonian communities. A differences-in-differences analysis compares forest preservation and fire activity in the municipalities that Natura entered with those in which it did not enter. Natura's impact is identified through an instrumental variable analysis using missing satellite images, which Natura relied upon to decide which municipalities to enter. Quantitative results tie Natura's entry into municipalities with forest preservation. Analysis of three mechanisms associates Natura's involvement with stakeholder decisions to cultivate diverse forest-generated crops instead of clearing the land for conventional agriculture. This study contributes to the management literature by suggesting how firms can address important global challenges, such as rainforest preservation, by investing in stakeholder capability development and by creating institutional arrangements in line with those envisioned elsewhere. This paper was accepted by George Serafeim, Special Section of Management Science on Business and Climate Change. Funding: This work was supported by the Clarkson Centre for Business Ethics [CAD 7,500.00] and Canada's Social Sciences and Humanities Research Council. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4884. [ABSTRACT FROM AUTHOR]

Immigration has proven to be a major force driving entrepreneurial dynamics. In this paper I investigate how the geographical distribution of immigrants within a given country, and in particular the presence of "enclaves," affects the relationship between immigration and entrepreneurship. I examine the impact of Polish immigration to Great Britain following the unprecedented migration wave caused by the European Union enlargement in 2004. I address omitted variable concerns by using information on the location of historical Polish military settlements and the occupational composition and growth of Polish immigration in Ireland to construct instruments for enclaves and location choices of immigrants. The econometric results indicate, on the one hand, that immigration does increase immigrant entrepreneurship, but not in existing immigrant enclaves. On the other hand, immigrant entrepreneurs outside enclaves tend to achieve worse growth outcomes than those in enclaves. Further analyses provide an explanation to these findings due to blocked labor markets and to the higher prevalence of "necessity entrepreneurship" outside of enclaves. These results offer new insights to understand the influence of geography on entrepreneurship in the presence of immigration. This paper was accepted by Toby Stuart, entrepreneurship and innovation. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4776. [ABSTRACT FROM AUTHOR]

Private sector innovation is critical to mitigating and adapting to climate change. This paper studies innovation in solar energy technology, a key source of clean energy that has experienced rapid price declines over the past decade. To understand the causes and effects of innovation, I estimate a dynamic structural model of competition among solar panel manufacturers. The model captures important features of the industry, including the role of government subsidies for solar adoption, and I employ a unique measure of technological progress that is observable and verifiable. The results produce two main insights. First, ignoring innovation by firms can generate biased estimates of the effects of government policy. Second, decentralized government intervention in a global market generates spillovers; a subsidy in one country causes international firms to innovate more, leading to lower prices and increased adoption elsewhere. This spillover underscores the need for international coordination by governments and the private sector to address climate change. This paper was accepted by Erica Plambeck, Special Section of Management Science on Business and Climate Change. Funding: The author acknowledges support from the U.S. Environmental Protection Agency [Science to Achieve Results (STAR) Fellowship Assistance Agreement FP-91769401-0] and Harvard [Joseph Crump Fellowship]. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4662. [ABSTRACT FROM AUTHOR]

This paper shows how green investing spurs companies to mitigate their carbon emissions by raising the cost of capital of the most carbon-intensive companies. Companies' emissions decrease when the wealth share of green investors and their sensitivity to climate externalities increase. We show that the impact of green investors primarily governs companies' long-run emissions. Companies are further incentivized to reduce their emissions when green investors anticipate tighter climate regulations and climate-related technological innovations. However, heightened uncertainty regarding future climate risks alleviates green investors' pressure on the cost of capital of companies and pushes them to increase their emissions. Calibrated on U.S. data, our model suggests that, albeit effective, the impact of green investors remains limited given their current wealth share and practices. This paper was accepted by George Serafeim, Special Section of Management Science on Business and Climate Change. Funding: This work was supported by the Europlace Institute of Finance. T. De Angelis received funding from the Engineering and Physical Sciences Research Council [Grant EP/R021201/1], and P. Tankov received funding from the Finance for Energy Markets research initiative of the Institut Europlace de Finance. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2022.4472. [ABSTRACT FROM AUTHOR]