My research specializes in entrepreneurship, labor markets, and inequality, using unique data and cutting-edge methodologies that combine traditional qualitative and econometric methods with computational linguistics and machine learning. I am on the 2022-2023 job market.
My research agenda focuses on how individuals acquire the crucial human and financial resources to create startups, and, simultaneously, how investors evaluate and select early-stage startups in different market settings ranging from Silicon Valley to Africa. Ultimately, this work helps to identify underlying and often subconscious drivers of bias and inequality in startup funding, as well as how entrepreneur and investor practices can be effective in remediating such biases and inequities while creating and funding high-potential startups. I further examine the consequences of valuation and evaluation practices on organizational misconduct and innovation in the startup context. A second stream of related research similarly explores how cultural processes undergird evaluations in labor markets, and the effects of these processes on labor market inequality.
At the GSB, I am part of the Equity by Design Lab, which drives research on structural and cultural contributors to inequality in organizations and market settings including startup funding using a data-driven approach. Prior to my doctoral studies, I worked as a Research Associate at the Harvard Business School. Before joining HBS, I worked on the legal side of funding rounds with early-stage startups at Goodwin Proctor LLP in Boston. I received my A.B. from Harvard University.
- Labor Markets
- Economic Sociology
- Inequality, Culture, Ethics
Job Market Paper
Prior literature demonstrates that evaluators rely on quantification – the conveyance of information through numbers – to impose a standardized definition of quality in assessments. These studies focus on how and why contemporaneous conditions of reality are measured and synthesized. In this paper, I uniquely consider an information-scarce, prospective context by examining how entrepreneurs quantify their early-stage ideas based on unknowable, hypothetical future states of the world, and why. I ask, how is the value of an entrepreneurial idea determined, quantified, and assessed? To unpack these questions, I triangulate three types of data: an observational field study of 64 early-stage startups across two years of a Silicon Valley pitch competition; archival data on 144 startup participants, including 337 unique pitch decks, across four total years of the competition; and 42 interviews with early-stage startup investors. I inductively uncover a joint valuation-evaluation process, which I term performative standardization. I define this as the process through which the value of an idea projected into a hypothetical future via quantification is deciphered, assigned, and assessed according to implicit standards held by potential future stakeholders. Rather than viewing numbers as objective conveyors of information, investors interpret this quantification as subjective and the truth unknowable. Paradoxically, investors concurrently act upon these numbers as if they are true. Illuminating this paradox, I find that standardization performs a coordinating function that offers legitimacy to entrepreneurs and investors. By developing theory on how entrepreneurial ideas are evaluated, this study contributes to literature on entrepreneurship and cultural evaluation processes, while also considering the implications on resource allocation and inequality in new business formation.
(with Adina D. Sterling) While sociologists have long noted that gender and sex are analytically distinct, a practical limitation in studies of labor markets is that gender and sex are empirically confounded. Using computational linguistics techniques and data from nearly 20,000 applicants for a white-collar sales position at a global firm, the authors are able to, for the first time in the literature, disentangle candidates’ perceived gender from their self-categorized sex in a real-world setting. The authors find evidence that decision-makers perceive a candidate’s gender through personal scrutiny—i.e., they glean gendered inferences using the personal information candidates supply on job applications. This has two main effects. First, it permits decision-makers to hire in gendered ways that discount femininity. Decision-makers select more masculine candidates (of any sex category) over more feminine candidates. Second, disentangling gender from sex allows decision-makers to obfuscate how gender influences their selection decisions. Namely, it allows decision-makers to appear sex-neutral or even progressive as they hire, while still selecting for gender. Ultimately, this study demonstrates how decision-makers’ ability to disentangle gender and sex contributes to maintaining the gender status quo and the effects this has on labor market inequality.
How do entrepreneurs’ cognitions shape their ventures? While research has established that founders’ backgrounds and prior experiences shape their firms and firm outcomes with long-lasting consequences, these studies have largely taken for granted the underlying founder cognitions that transfer individual-level variation to the firm level. Little is known about how entrepreneurs think, and how their cognitions affect firm-level outcomes such as revenue. To uncover entrepreneurial cognition, this study uses a novel mixed methods approach. Using applications submitted online by entrepreneurs seeking funding from a nonprofit accelerator, an inductive grounded theory analysis reveals two diverging cognitions – an exchange construal and an organization construal – that reflect differences in how entrepreneurs think about themselves and their ventures. These findings are then scaled across 139,806 applications from entrepreneurs across Africa, using a supervised machine learning method, to test whether and how these construals influence firm-level outcomes. The results indicate that entrepreneurs’ construals are significantly associated with differences in firm revenue and acceptance into the accelerator. These findings suggest that entrepreneurial cognition at the time of founding is imprinted into the firm, illuminating a contributing factor to heterogeneity in new venture outcomes. The findings further suggest that founder background, including gender, contributes to differences in founder construals.
Work in Progress
Natasha N. Overmeyer
Natasha N. Overmeyer and Adina D. Sterling
Natasha N. Overmeyer and Adina D. Sterling
Solene Delecourt, Anne Boring, and Natasha N. Overmeyer