Research

Publications

Ding, Y., Åstebro, T., & Braguinsky, S. (2023). Declining science‐based startups: Strategic human capital and the value of working in startups versus established firms. Strategic Entrepreneurship Journal, 17(4), 830-856. 

Abstract: How does strategic human capital relate to startup formation? We document that since 1997, the rate of startup formation has precipitously declined for firms operated by U.S. Ph.D. recipients in science and engineering. To explain this decline, we build on the strategic human capital literature showing that increasing knowledge complexity is associated with less entrepreneurship and examine the associated time trends. We find that the decline in startup formation is accompanied by earnings decline, increasing work complexity in R&D, and more administrative work for founders. Thus, founding a startup is becoming harder, while established firms are becoming increasingly more attractive workplaces for PhDs. There is a silver lining, however, as more recent startups appear to be of higher quality and grow faster, conditional on survival.

Working Papers

Ding, Yuheng. (2023). "Complex Innovation and the “Visible Hand”: the Role of Knowledge Interdependence in Employee Entrepreneurship". Ed Snider Center Working Paper No.7. [Revise and Resubmit at Management Science]

Abstract: How does growing knowledge interdependence in firm innovation activities affect potential entrepreneurs' decision to start their own business ventures? To answer this question, I adopt an abductive approach and leverage matched employee-employer data from the U.S. Census Bureau between 2000-2014. Results show that higher knowledge interdependence is negatively associated with employee entrepreneurship, and the negative effect is even stronger, not weaker, among the highest-performing individuals. This indicates that knowledge interdependence does not merely raise the bar of entry. Instead, firms implement better pay-for-performance compensation schemes to retain valuable human assets, which also leads to greater compensation dispersion within firms with higher knowledge interdependence. Together, these create a strong selection on the quality of spin-outs being formed especially by individuals ranked highest on the human capital distribution. I use an economic model to summarize these empirical insights and show that knowledge interdependence could also raise between-firm income inequality when it generates large enough profits on the product market.

*Assenova, Valentina, Yuheng Ding, and Audra Wormald. (2024). "Beyond Technology Adoption: The Critical Role of Digital Technology Integration in SME Growth and Scalability". [Under Review]

Abstract: This study addresses a critical theoretical gap in understanding how digital technology integration drives the growth of Small and Medium-sized Enterprises (SMEs). While existing literature often focuses on the adoption of digital technologies, it overlooks the distinction between technology adoption (extensive margin) and the depth of technology integration across business functions (intensive margin). Drawing on the resource-based and knowledge-based views of the firm, we explore how these dimensions of technology use influence SME growth and scalability. Using data on 14,313 firms across 30 countries from the Global State of Small Business Survey, our analysis reveals that SMEs are significantly less likely than larger firms to integrate digital technologies intensively, which is essential for realizing growth benefits. Furthermore, we demonstrate the primacy of organizational factors—such as firm size, age, and internal capabilities—over regional and country-specific factors in explaining variation in digital technology integration and firm performance. These findings challenge the conventional focus on technology adoption by emphasizing the role of organizational design and internal resource allocation in achieving competitive advantage through digital transformation. Our study contributes to the ongoing discourse on digital technology use, offering new insights for theory and practice in fostering SME growth and scalability.

*Braguinsky, Serguey, Joonkyu Choi, Yuheng Ding, Karam Jo, and Seula Kim. (2023). "Mega Firms and Recent Trends in the U.S. Innovation: Empirical Evidence from the U.S. Patent Data". NBER Working Paper No. 31460.

Abstract: We use the U.S. patent data merged with firm-level datasets to establish new facts about the role of mega firms in generating “novel patents”—innovations that introduce new combinations of technology components for the first time. While the importance of mega firms in novel patents had been declining until about 2000, it has strongly rebounded since then. The timing of this turnaround coincided with the ascendance of firms that newly became mega firms in the 2000s, and a shift in the technological contents, characterized by increasing integration of Information and Communication Technology (ICT) and non-ICT components. Mega firms also generate a disproportionately large number of “hits”—novel patents that lead to the largest numbers of follow-on patents (subsequent patents that use the same combinations of technology components as the first novel patent)—and their hits tend to generate more follow-on patents assigned to other firms when compared to hits generated by non-mega firms. Overall, our findings suggest that mega firms play an increasingly important role in generating new technological trajectories in recent years, especially in combining ICT with non-ICT components.

*Ding, Yuheng, Karam Jo and Seula Kim. (2022). "Improving Patent Assignee-Firm Bridge with Web Search Results". CES Working Paper No. 22-31.

Abstract: This paper constructs a patent assignee-firm longitudinal bridge between U.S. patent assignees and firms using firm-level administrative data from the U.S. Census Bureau. We match granted patents applied between 1976 and 2016 to the U.S. firms recorded in the Longitudinal Business Database (LBD) in the Census Bureau. Building on existing algorithms in the literature, we first use the assignee name, address (state and city), and year information to link the two datasets. We then introduce a novel search-aided algorithm that significantly improves the matching results by 7% and 2.9% at the patent and the assignee level, respectively. Overall, we are able to match 88.2% and 80.1% of all U.S. patents and assignees respectively. We contribute to the existing literature by 1) improving the match rates and quality with the web search-aided algorithm, and 2) providing the longest and longitudinally consistent crosswalk between patent assignees and LBD firms. 

Ding, Yuheng. (2022). "The Burdens of Technology Adoption on Entrepreneurship – How Does the Adoption of EHRs Impact Physician Self-employment in the U.S. Healthcare Sector?". 

Abstract: In the past two decades, there has been a trend of rapid adoption and implementation of health information technology (HIT), namely the Electronic Health Records (EHRs) in the U.S. healthcare sector. Meanwhile, the share of self-employed physicians dropped drastically with increasing market concentration for hospitals. I argue that efficient knowledge hierarchies and complementary capabilities of HIT in hospitals help mitigate burdens following the adoption and implementation of EHRs better than independent physician-owned practices. Preliminary results using publicly available data indicate that a higher level of adoption of EHRs at nearby hospitals is associated with a lower level of self-employment as well as lower returns to self-employment in the same county. To further investigate the causal relationship, I implement a Diff-in-diffs design and an instrument variable approach by linking the HIMSS analytics survey to the employer-employee matched dataset of the U.S. Census Bureau and the American Community Survey (ACS) to trace EHRs adoption, job mobility, and entrepreneurial activities of physicians employed at a near census of non-federal hospitals in 29 U.S. states between 2005 and 2014.  Results are being prepared for disclosure clearance by the U.S. Census Bureau. 

* All authors contributed equally.

Works in Progress


Contributions to Crowd-Sourced Research Projects