Publications

In late 2018, GigaCloud CEO Larry Wu (Yale MBA, 2002) sat reviewing his company’s operating metrics with senior managers at the company’s headquarters in Los Angeles. Wu and his team had begun selling furniture from Asia to the US in 2014. As a pioneer in cross-border e-commerce, Wu’s company, GigaCloud, procured directly from Asian manufacturers, taking advantage of the rich SKU assortment and competitive price to attract a wide array of U.S. customers.

All went well until mid-2018 when demand suddenly dipped amid higher interest rates and rising tariffs. Not only did demand decline, but the Asian manufacturers also started to sell directly to other U.S. retailers to stay profitable during the challenging time. Operating income slipped; the company went from earning hundreds of thousands of dollars per month to going into the red by August.

Reviewing the sales data and the company’s cash position, the senior management team agreed to sell inventory at a loss to pull GigaCloud through the crisis. Then, looking to the future, Wu proposed a rather radical pivot: build a B2B service business in addition to the company’s existing B2C business by attracting Asian manufacturers to offer their wares through the GigaCloud website to other U.S. retailers. Many of GigaCloud’s senior management team were opposed to the proposal, believing the service would cause GigaCloud’s retail business to collapse. These managers thought GigaCloud could weather the storm and return to the business as usual – nothing fundamental needed to change.

However, Wu believed the business would inevitably run into trouble down the road, and it was the right time to make some fundamental changes. Wu and his team debated the sharp change in the business model late into the night. Even if the company decided to shift its business model, how would GigaCloud implement the change?
 

Nature provides essential inputs to the economy through ecosystem services. In Asia and the Pacific, accelerating biodiversity loss is eroding these services, increasing vulnerability to shocks, and creating new risks for investors and governments.

The Securities and Exchange Commission (SEC) reviews firms’ financial reports and issues comment letters to ensure compliance with applicable disclosure and accounting requirements. We explore the nature, determinants, and consequences of SEC comment letters that refer to information disclosed in voluntary earnings conference calls. Using hand-collected data, we document that the SEC primarily references these voluntary disclosures to illustrate insufficiencies and, less commonly, inconsistencies in mandatory filings across a wide range of topics. These letters are more likely to be issued when filing reviews are more complex, SEC staff are less resource constrained, and for firms with more institutional investors and analysts. Conference call-related comments tend to occur during higher-quality review processes and require greater remediation costs than other comments. The SEC’s use of call disclosures also leads to more pronounced changes in firms’ subsequent mandatory filings, particularly when the firm indicates agreement with SEC comments. However, we observe a mixed effect on the overall information environment, consistent with possible unintended consequences for the quality of firms’ voluntary disclosures.

Trump’s Ten Commandments: Strategic Lessons from the Trump Leadership Toolbox offers a provocative and penetrating look inside the mind of one of history’s most controversial leaders. Written by Jeffrey Sonnenfeld, celebrated Yale leadership scholar and advisor to five U.S. presidents, this book reveals the ten guiding principles—or “commandments”—that define Donald Trump’s decision-making across business, media, and politics.

Drawing from decades of personal interactions with Trump as advisor, critic, and confidant, Sonnenfeld moves beyond gossip and ideology to decode the predictable patterns behind Trump’s seemingly chaotic style. There are critiques and salutes through history of the impact of the imperial presidency but no existing current or past analysis of how such leadership operates until this deep dive into Trump’s toolkit. Sonnenfeld exposes how Trump’s playbook—built on domination, disruption, and relentless self-promotion—breaks every conventional rule of leadership yet often achieves results through sheer force of will.

From the boardroom to the Oval Office, Sonnenfeld distills lessons in power, persuasion, and performance—lessons that illuminate not only Trump’s successes and failures but also timeless truths about human ambition, influence, and control. Whether you admire or abhor him, understanding Trump’s Ten Commandments reveals how he built empires, dismantled institutions, and redefined leadership in his own image.

Part insider analysis, part leadership case study, Trump’s Ten Commandments helps readers grasp how Trump thinks, how he leads, and what his methods teach us—about both the dangers and the undeniable magnetism of power used without restraint.

For anyone seeking to understand America’s most unpredictable leader, this is the definitive guide to Trump’s strategy, psychology, and legacy.

In most evaluation systems—such as those governing the allocation of prestigious awards—the evaluator’s primary task is to reward the highest quality candidates. However, these systems are imperfect; top performers may not be acknowledged and thus be underrecognized, and low performers may receive unwarranted recognition and thus be overrecognized. An important feature of many evaluation systems is that people alternate between being candidates and being evaluators. How does experiencing misrecognition as a candidate affect how people subsequently evaluate others? We develop novel theory that underrecognition and overrecognition lead people to reproduce those experiences when they are evaluators. Across three studies—a quasi-natural experiment and two preregistered, multistage experiments, we find that underrecognized evaluators are less likely to grant recognition to others—even to the highest-performing candidates. Conversely, overrecognized evaluators are more likely to grant rewards to others—even to the lowest-performing candidates. Whereas underrecognized evaluator behavior is driven by individuals’ perceptions that their experience was unfair, overrecognized evaluator behavior is driven by the informational cues people glean on how to evaluate others. Thus, in evaluation processes where people oscillate between being the evaluated and being the evaluator, we show how and why seemingly innocuous initial inefficiencies are reproduced in subsequent evaluations.

Should central banks’ inflation targets remain set in stone? We study a dynamic mechanism
design problem between a government (principal) and a central bank (agent). The central
bank has persistent private information about structural shocks. Firms learn the state from the
central bank’s reports and form inflation expectations. A dynamic inflation target implements the
full-information commitment allocation. The central bank is delegated the authority to adjust
the level and flexibility of its target as long as it does so one period in advance. All history
dependence of the mechanism is summarized by the current period’s target. We show that
a declining natural interest rate and a flattening Phillips curve imply opposite optimal target
adjustments. We leverage our framework to study longer-horizon time consistency problems
and speak to practical policy questions of inflation target design.

A strategic tension between consumers in a monopolistic market arises when many high-value consumers want to pool with a few lower-value consumers in order to obtain low prices from the seller. We study the interaction between consumers and the resulting market segmentation into consumer groups as the outcome of a cooperative game between the consumers. We introduce two new solution concepts, the weakened core and stability, which coincide with the core whenever it is nonempty. We show that these concepts are in fact equivalent and non-empty, and are characterized by efficiency and saturation. A segmentation is saturated if shifting consumers from a segment with a higher price to a segment with a lower price leads the seller to optimally increase the lower price. We show that stable segmentations that maximizes average consumer surplus (across all segmentations) always exist

This paper develops a theory-based, explainable deep learning convolutional neural network (CNN) classifier to predict the time-varying emotional response to music. We design novel CNN filters that leverage the frequency harmonics structure from acoustic physics known to impact the perception of musical features. Our theory-based model is more parsimonious, but it provides comparable predictive performance with atheoretical deep learning models while performing better than models using handcrafted features. Our model can be complemented with handcrafted features, but the performance improvement is marginal. Importantly, the harmonics-based structure placed on the CNN filters provides better explainability for how the model predicts emotional response (valence and arousal) because emotion is closely related to consonance—a perceptual feature defined by the alignment of harmonics. Finally, we illustrate the utility of our model with an application involving digital advertising. Motivated by YouTube’s midroll ads, we conduct a laboratory experiment in which we exogenously insert ads at different times within videos. We find that ads placed in emotionally similar contexts increase ad engagement (lower skip rates and higher brand recall rates). Ad insertion based on emotional similarity metrics predicted by our theory-based, explainable model produces comparable or better engagement relative to atheoretical models.

This article concerns itself with fees that Apple and Google might charge to business users in their respective mobile ecosystems. We lay out the economic analysis behind the goals of the DMA—contestability and fairness—as they apply to third-party app store access fees. We focus on the access fees for alternatives to the Apple App Store, as this has become contentious in the early enforcement of the DMA. Much of our analysis, however, also applies also to Google and/or any other designated gatekeeper.

For more than 150 years, the founding mission of the American Society for the Prevention of Cruelty to Animals (ASPCA) guided the organization while enabling it to address evolving challenges in animal welfare. Under Matt Bershadker, ASPCA’s president and CEO, the company faced mounting pressure to engage with a growing stream of societal matters far afield from its core purpose. The case explores Bershadker’s initiative to develop a clear, strategic framework for considering which societal issues to address. This effort would clarify the ASPCA’s approach to these issues by evaluating them against the organization’s strategy, history, policies, and key stakeholder relationships, ensuring consistency, transparency, and mission-driven decision-making.

We study a retirement savings plan with a default contribution rate of 12% of income, which is much higher than previously studied defaults. Twenty-five percent of employees had not opted out of this default 12 months after hire; a literature review finds that the corresponding fraction in plans with lower defaults is approximately one-half. Because only contributions above 12% were matched by the employer, 12% was likely to be a suboptimal contribution rate for employees. Employees who remained at the 12% default contribution rate had average income that was approximately one-third lower than would be predicted from the relationship between salaries and contribution rates among employees who were not at 12%. Defaults may influence low-income employees more strongly in part because these employees face higher psychological barriers to active decision making.

Bayer AG is a German multinational pharmaceutical and life sciences company founded in 1863. It operates globally in over 90 countries with approximately 100,000 employees as of 2024. Bayer is structured into three main business segments: Pharmaceuticals, Consumer Health, and Crop Science, with significant global operations and an extensive patent portfolio. The company is a leader in agricultural products, prescription medicines, and over-the-counter health products. It also focuses on innovative solutions for healthcare and agricultural challenges.

The current dilemma for students to address are issues related to Bayer’s transition to a new operating model called Dynamic Shared Ownership (DSO). This model, introduced under the leadership of CEO Bill Anderson, aims to flatten the corporate hierarchy and create a nimbler, customer-centric organization. The transition involves removing the existing hierarchical structure, which previously consisted of 12 management layers, and replacing it with self-managed teams. This structural change was referred to internally as the "hardware."

The initial steps under DSO included substantial organizational redesign, involving layoffs and the establishment of self-managed teams. The Board of Management successfully halved the number of management layers to five or six and replaced thousands of middle managers with self-managed teams. A complementary aspect of DSO, labeled the "software," focused on fostering cultural changes to promote new mindsets, norms, and behaviors among Bayer’s nearly 100,000 employees.

Notwithstanding several early wins, the Board of Management is now grappling with implementing new talent management and personnel policies that align with the DSO model. Existing HR processes and systems, which are designed for a hierarchical organization, need to be reinvented. Questions about compensation, career pathing, and performance metrics must be addressed to ensure these new systems support the DSO framework effectively.

A critical element of word of mouth (WOM) or buzz marketing is to identify seeds, often central actors with high degree in the social network. Seed identification typically requires data on the relevant network structure, which is often unavailable. We examine the impact of WOM seeding strategies motivated by the friendship paradox, which can obtain more central nodes without knowing network structure. Higher degree nodes may be less effective as seeds if these nodes communicate less with neighbors or are less persuasive when they communicate; therefore, whether friendship paradox–motivated seeding strategies increase or reduce WOM and adoption remains an empirical question. We develop and estimate a model of WOM and adoption using data on microfinance adoption across village social networks in India. Counterfactuals show that the proposed strategies with limited seeds are about 13%–30% more effective in increasing adoption relative to random seeding. These strategies are also on average 5%–11% more effective than the firm’s leader seeding strategy. We also find these strategies are relatively more effective when we have fewer seeds.

We hypothesize that “low-contrast categories” (those lacking sharp differentiation from adjacent categories) catalyze the creation of groundbreaking inventions by influencing two key stages in the life of an invention: (1) idea-creation and (2) idea-positioning. During “idea-creation,” low-contrast categories increase the likelihood that descendant inventions will combine the focal invention with more (a) boundary-spanning, (b) novel, (c) original, and (d) atypical knowledge inputs. During “idea-positioning,” they allow greater leeway in articulating how descendant inventions depart from the focal invention’s lineage and chart new technological directions. We find robust support for our hypothesis using data from the United States Patent and Trademark Office’s classification system spanning nearly four decades. Further analyses demonstrate that the catalyzing effect of low-contrast categories has important material consequences: inventions classified in low-contrast categories spur descendant inventions that generate substantially higher economic value and exert more enduring technological impact than those in high-contrast categories. By introducing the concept of catalyzing categories, this study offers a novel theoretical perspective on the genesis of groundbreaking inventions and the role of categorical structures in the inventive process.

The 2020 revisions to the Federal Reserve’s monetary policy framework included a shift in the Fed’s policy focus to shortfalls (rather than deviations) from maximum employment and a commitment to “flexible average inflation targeting.” The new framework, and the associated guidance and asset purchases with which it was implemented, were tested by the surge in inflation in 2021 and 2022. We consider the lessons learned from this experience. We conclude that the changes to the framework were too focused on the experience following the financial crisis and hence were not robust in the face of unexpected changes in economic circumstances. We also argue that the Fed made mistakes with the calibration and communication of the tools used to implement the framework—the forward guidance on the policy rate and the asset purchase program. We recommend a broad framework that would be appropriate in a wide range of policy environments, with the specific policy approach to be taken in any given circumstance to be communicated through forward guidance and asset purchase announcements. We suggest ways in which the Fed could implement these tools with better calibration and communication, in order to avoid having its policy commitments exacerbate costly economic outcomes.

The credit-implied volatility (CIV) surface is introduced as an organizing framework for analysis of credit spreads, providing a description of CDS spreads for firms across the credit spectrum, of varying maturities, and at all points throughout the credit cycle.

We model the optimal resolution of insolvent firms in general equilibrium. Collateral- constrained banks lend to (i) solvent firms to finance investments and (ii) distressed firms to avoid liquidation. Liquidations create negative fire-sale externalities. Liquidations also re- lieve bank balance-sheet congestion, enabling new firm loans that generate positive collateral externalities by lowering bank borrowing rates. Socially optimal interventions encourage liqui- dation when firms have high operating losses, high leverage, or low productivity. Surprisingly, larger fire sales promote interventions encouraging more liquidations. We study synergies be- tween insolvency interventions and macroprudential regulation, bailouts, deferred loss recog- nition, and debt subordination. Our model elucidates historical crisis interventions.

The origin of the modern joint-stock company is typically traced to the concomitant appearance of large-scale maritime trading companies in England and the Netherlands in the early seventeenth century. Highlighting medieval cases in southern Europe, we claim that the joint-stock company emerged earlier in history. These prior appearances support the theory of convergent evolution towards the joint-stock company. We document alternative and largely independent developmental paths that suggest the joint-stock company can emerge in a variety of legal, political and socioeconomic contexts. This evidence has implications for identifying the necessary background underlying the emergence of the joint-stock company, and for the debate regarding the link between business institutions and economic growth.