When do startups scale? Large-scale evidence from job postings

• 成果类型: Article
• 署名作者: Lee, Saerom (Ronnie); Kim, J. Daniel
• 署名单位: University of Pennsylvania; University of Pennsylvania
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.3596
• 发表日期: 2024
• 页码: 1633-1669
• 关键词: Entrepreneurship; human capital; organization design; timing; venture scaling

摘要

Research SummaryScaling at the right time is a crucial challenge for startups. Conceptualizing scaling as the entrepreneurial process of acquiring and committing resources to implement the core business idea and expand the customer base, this study examines how scaling early may decrease imitation risk at the expense of increasing commitment risk. As startups typically hire managers and sales personnel when they begin to scale, we propose that this timing can be empirically measured by when startups first post these jobs. Leveraging a dataset of job postings, we find that early scalers are more likely to fail, but no evidence of a countervailing benefit in terms of successful exit. Additional analyses suggest that the commitment risk in scaling early outweighs the benefit of reducing imitation risk.Managerial SummaryIn recent years, a few high-growth startups (e.g., Facebook and Uber) that made their fortune by scaling early-an approach often referred to as blitzscaling-have received much interest among academics and practitioners. However, this study presents large-sample evidence that scaling early is positively associated with a higher rate of firm failure, especially for platform companies. These findings imply that, despite its potential benefits of preventing imitation by competitors, scaling early can suppress startup performance by prematurely curtailing learning through experimentation and committing to a business idea that lacks product-market fit. In sum, our work cautions startups against prioritizing scaling early before finding product-market fit, and instead highlights the importance of spending sufficient time on experimentation before scaling.