Research
My research focuses on entrepreneurial strategy, particularly how startups scale and why there are international differences in scaling. Specifically, it assesses the role of strategic technological and market choices in driving convergence and divergence in entrepreneurial growth around the world.
Publications
Can accelerators pick the most promising startup ideas no matter their provenance? Using unique data from a global accelerator where judges are randomly assigned to evaluate startups headquartered across the globe, we show that judges are less likely to recommend startups headquartered outside their home region by 4 percentage points. Back-of-the-envelope calculations suggest this discount leads judges to pass over 1 in 20 promising startups. Despite this systematic discount, we find that—in contrast to many past studies—judges can discern startup quality and are no better at evaluating local firms. These differences emerge because the pool of startups accelerator judges evaluate is both broader and less “local,” suggesting that judging ability depends on the composition of the companies they are tasked with evaluating.
This is the first study to consider the relationship between open source software (OSS) and entrepreneurship around the globe. This study measures whether country-level participation on the GitHub OSS platform affects the founding of innovative ventures, and where it does so, for what types of ventures. We estimate these effects using cross-country variation in new venture founding and OSS participation. We propose an approach using instrumental variables, and cannot reject a causal interpretation. The study finds that an increase in GitHub participation in a given country generates an increase in the number of new technology ventures within that country in the subsequent year. The evidence suggests this relationship is complementary to a country’s endowments, and does not substitute for them. In addition to this positive change in the rate of entrepreneurship, we also find a change in direction—OSS contributions lead to new ventures that are more mission- and global-oriented and are of a higher quality. Together, the results suggest that OSS can boost entrepreneurial activity, albeit with a human capital prerequisite. We consider the implications for policies that encourage OSS as a lever for stimulating entrepreneurial growth.
Technology startups often scale by entering new markets. Doing so nearly at once as a full commitment allows them to gain more users to spur network effects, while doing so experimentally by staging market entries enables more learning. (When) do startups expand into new markets as full commitments or experimentally? We assess this question in the context of international expansion decisions. As the first study to track digital startup internationalization worldwide, we use BuiltWith data of website language tool adoption by nearly 50,000 software firms from 2001-2022. Startups, on average, adopt foreign language tools gradually across their lifecycle, even from smaller markets and with platform business models (characterized by network effects). Experimentation by smaller market startups with greater expansion incentives predicts greater internationalization. These results suggest that startups pursue market expansion experimentally.
Selected Working Papers
Prior work highlights the importance of cognitive approaches to strategy formation for startup growth. They enable entrepreneurs to strategically reason—logically and convincingly formulate their strategic choices before executing them. However, whether the value of strategic reasoning generalizes across contexts, particularly different financing environments, remains unclear. While practitioners and scholars have popularized less-reasoning-oriented approaches, like the Lean Startup movement, in financing-rich contexts like Silicon Valley, they have suggested mixed results with such approaches elsewhere. Through interviewing 253 scaling software startups from 34 economies and scoring how well they reason through market, moat, and organizational choices, this study theorizes that strategic reasoning is more valuable in less-financing-rich contexts, where bad investments—that reasoning can help avoid—are more irreversible. However, these contexts also have less prior scaling successes to learn from, making strategic reasoning harder to develop. Findings show that higher reasoning scores more strongly predict startup growth in less-financing-rich cities. Yet, startups there do not have higher reasoning scores, despite the greater need. These results suggest that local financing—and irreversibility more generally—are critical boundary conditions for strategic cognition theories. Moreover, where strategic reasoning is more valuable, it is also harder to develop, contributing to global scaling disparities.
How does participating in open source software (OSS) communities spur entrepreneurial growth? To address this question, we analyze novel data matching accounts from GitHub—the largest OSS hosting platform—to the universe of global software venture-backed firms identified by PitchBook. We find a robustly positive relationship between OSS contributions and entrepreneurial growth. These effects stem from mechanisms related to OSS contributions helping firms shape the direction of code, signal to potential acquirers and investors, and engage clients, rather than those related to learning about new software developments or cutting costs in software production. Consistent with these mechanisms, human capital, OSS policies, and market size positively moderate these effects, suggesting that OSS complements supply-side and demand-side country endowments. This research reveals that contributing to OSS can lead to entrepreneurial growth worldwide since sophisticated entrepreneurs can take strategic advantage of nudging code in a direction that fits their commercial interests as well as attracting acquirers and users. Further, we discuss important implications for policy and entrepreneurial strategy.
Entering new markets is crucial for technology startups to scale. But it is not clear which initial users help startups learn about demand in these target, often foreign, markets. While local users can typically offer clearer signals, foreign ones can offer more transferable ones. This raises the question: How does the local vs. foreign composition of initial users shape startups' subsequent foreign user growth? I test this question on a digital product platform. Taking advantage of variation in feature timing, I find that startups with a higher share of local initial users achieve more foreign user growth after they feature on the platform. This effect magnifies among startups in more familiar and representative local contexts, where local signals are even clearer and more transferable. Consistent with these results, a supplementary experiment shows that foreign users prefer products that incorporate clearer and more transferable local feedback. Together, these findings underscore the importance of choosing initial users who offer both clear and transferable signals, with implications for entrepreneurial experimentation and strategy.
How does international exposure shape entrepreneurial pivots? Through a field study of 84 startups across 27 countries, we develop a model that uncovers how international exposure not only spurs ventures to update their understandings of the international market but also generates pivots in the addressed market. Structural differences between markets and entrepreneurs' cognitive openness makes new information about the international market more salient. This new information opens ventures' eyes to novel opportunities. Ventures then realize that the same opportunities always existed in the addressed market, but their initial taken-for-granted market assumptions blinded them. This prompts pivots in startups' core customer profile or offering. Together, the study shows that new market exposure is an important mechanism shaping entrepreneurial pivoting, with implications for entrepreneurial experimentation and strategy.
Does AI cheapen talk? Theory and evidence from global entrepreneurship and hiring (w/ Bo Cowgill and Pablo Hernandez-Lagos)
Screening human capital based on signals such as job applications or entrepreneurial pitches is crucial for organizations. Signals are often informative insofar as they require differential knowledge and effort to produce. Generative AI (GAI) complicates screening by lowering the cost of producing impressive signals. We model the informational effects of GAI, showing that applicants' access to GAI can increase—but also decrease—an evaluator's screening mistakes. This result depends on how GAI affects experts' signals compared to non-experts'. Using experiments in hiring and startup investing, we estimate that senders' access to GAI (ChatGPT) lowers screening accuracy by 4-9% for employers and startup investors. Consistent with our model, senders' access to GAI also improves screening accuracy in some settings—in our case, among senders from non-English-speaking countries. These results show that GAI can profoundly shape screening accuracy.
The impact of communicating strategy on employee ideas: Evidence from a global startup field experiment (w/ F. Christopher Eaglin)
What is the impact of communicating strategy to employees in scaling ventures? As entrepreneurial ventures grow and add headcount, misalignment among employees can emerge, leading to inefficient and potentially detrimental decisions. Communicating strategy can realign employees' ideas to the firm's core framework but divert them from more distant and potentially optimal possibilities, constraining flexibility. Through a pre-registered field experiment involving 480 employees across 25 companies in 14 countries, we analyze the effects of a simple strategy communication intervention. We find that sharing the company's strategy increases the alignment of employees' ideas with company goals by 6% and enhances their differentiation from other firms by 2%. These effects are more pronounced in firms operating in lower-income contexts and non-regulated sectors where flexibility might be critical. Together, our findings suggest that communicating strategy presents a key trade-off for ventures, boosting efficiency, but at the potential expense of flexibility.
The mid-sized market trap in entrepreneurial scaling (w/ Ed Saiedi)
Why do startups from mid-sized markets struggle to scale? We theorize that their home market is big enough to gain early traction, which incentivizes them to delay targeting new markets necessary for growth. This delay, however, allows adaptation costs to grow too large. We test this by exploring international expansions using interview and large-scale website language data of up to 20,000 software startups from around the world. Consistent with our theory, we find that startups headquartered in mid-sized markets delay targeting their websites to English-speaking markets that are crucial for software growth, subsequently incurring higher localization costs. Those that do orient toward these markets near their founding ultimately attract higher valuations and funding. These results suggest that startups from mid-sized markets face a "satisficing" dilemma that can constrain their growth.
Strategic targeting and unequal global adoption of artificial intelligence (w/ Dafna Bearson)
The rise of low-cost artificial intelligence (AI) technologies offers significant potential for businesses globally, yet AI adoption remains uneven. What shapes this unequal adoption? While prior work attributes adoption patterns to demand-side factors including physical costs and complementary assets, we theorize that AI entrepreneurs' strategic choice to target specific markets creates both search and perceived-fit frictions for firms outside of those markets. We test this supply-side theory using unique data tracking the adoption of standardized AI tools—which require lower physical costs and fewer complementary assets—across approximately 88,000 firms worldwide from 2012 to 2023. Consistent with our targeting theory, firms based in non-English-speaking (i.e., non-targeted) markets are 16 percent less likely to adopt AI tools. These firms are even less likely to adopt AI when they serve different markets than the AI entrepreneurs—even though these firms observe a stronger relationship between AI adoption and subsequent performance. The findings highlight the strategic market choices of technology entrepreneurs as a key mechanism driving the unequal diffusion of frontier technologies.
Do disruptive startups attract better talent? Evidence from a hiring field experiment in India (w/ Nina Teng and Olenka Kacperczyk)
We examine how a startup's strategic positioning—specifically, whether it communicates a disruptive or collaborative stance toward incumbents—affects its ability to attract talent. Although prior research has examined how this positioning influences investors, its impact on potential employees remains less clear. We conduct a field experiment with an early-stage climate technology startup in India, randomly assigning job seekers to a disruptive or collaborative positioning condition. By examining job applications and salary expectations from software engineers, we assess the direct effects of strategic positioning and the underlying mechanisms driving candidates' behaviors. Our results show that disruptive positioning reduces application rates by 6 percentage points. Applicants who do apply demand 5% higher cash compensation. This compensation premium occurs largely because applicants who are fully employed explore fewer job opportunities and are likely to seek compensation for having to leave their stable, full-time employment. These findings contribute to the emerging literature on startup talent acquisition by demonstrating how strategic communication choices significantly influence human capital attraction, a critical yet understudied dimension of new venture success.