Research | Seyeon Kim

Seyeon Kim. “Sorting into Startups: Unpacking Supply‑ and Demand‑Side Dynamics in Hiring.”

In Preparation for Submission
Using a proprietary dataset of 7 million job applications and hiring outcomes from a Korean digital hiring platform (2015‑2024), my job‑market paper traces how sorting into startups unfolds across the pipeline. I introduce a framework of applicant search and employer evaluation and show that startups’ lower-credentialed workforce emerges largely from applicants’ targeted search. Startups broaden their funnel by considering candidates across the educational distribution, creating a pipeline inefficiency: startups are more likely to interview middle-status applicants, yet these candidates are the least likely to apply. Together, these contributions clarify when and for whom hiring outcomes reflect mutual selection, and when they result from broader search on one or both sides of the labor market.

Seyeon Kim. “From Founder to Follower: The Return Journey to Paid Employment.”

In Preparation for Submission
I use text network analysis to investigate how employers interpret entrepreneurial experience versus conventional employment. While prior research tends to assume uniformly negative beliefs about former founders, I collect and analyze open-ended employer evaluations of simulated resumes to uncover how such beliefs are structured. Using topic co-occurrence networks and community detection, I find that beliefs about employees tend to cluster cleanly—positive traits like leadership, competence, and stability co-occur, while negative ones remain separate. In contrast, founder resumes evoke more cognitively complex and ambivalent evaluations. Founder resumes activate similar positive traits such as initiative, but these often co-occur with concerns about self-orientation or defiance of authority. These findings suggest that founder experience invites more interpretive ambiguity than prior research has captured, and that the meaning of the same signal may shift depending on the evaluative context.

Seyeon Kim and Jon Atwell. “Bundled Signals and Hiring Risk: Experimental Evidence on the Entrepreneur-to-Employee Transition.” — running pilot experiments
Kylie J Hwang and Seyeon Kim. “Attracting Talent When You're the Underdog: Startups and Labor Market Signaling.” — data analyses
Seyeon Kim. “Micro-Dynamics of Job Search: How Feedback and Perceived Ability Shape Search Intensity and Direction.” — early stage (ideation/theorizing)
Seyeon Kim. “Beyond the Homogeneous Firm: Theorizing the Effects of Firm Age and Size on Hiring.” — early stage
Seyeon Kim. “Experience, Education, and the Role of Startups as Career Bridges.” — early stage