Publications
Publications
- 2023
- HBS Working Paper Series
Mapping Organizational-Level Networks Using Individual-Level Connections: Evidence from Online Professional Networks
By: Shelley Xin Li, Frank Nagle and Aner Zhou
Abstract
Organization-level networks facilitate the flow of information and business activities in the
economy. Prior research relies solely on high-level connections to measure these networks. Therefore, to
understand the role of employee connections at all job levels in firm outcomes, we construct and describe
a comprehensive network for 7,715 publicly traded U.S. firms from 2004 to 2018, using data on over 9
million people with 2 billion connections from the professional social network LinkedIn. We identify the
most closely connected industries and companies in the U.S. economy. Although employees do not
necessarily make connections for the company’s benefit, we find that companies’ centrality in the employee
network positively predicts company value. This effect is largely driven by mid-level employees.
Furthermore, company centrality in the employee network predicts company innovation inputs (R&D
spending), and controlling for these inputs, predicts the quantity, scientific impact, and economic value of
companies’ patented innovation outcomes.
Keywords
Networks; Value; Social and Collaborative Networks; Innovation and Invention; Knowledge Sharing; Employees; Social Media
Citation
Li, Shelley Xin, Frank Nagle, and Aner Zhou. "Mapping Organizational-Level Networks Using Individual-Level Connections: Evidence from Online Professional Networks." Harvard Business School Working Paper, No. 24-010, August 2023.