Risk Transmission Mechanisms and Risk Mitigation Pathways in Cross-border Technology Investment: Evidence From the China–U.S. Market
Abstract
Against the backdrop of accelerating cross-border mobility of global technological factors, the scale of China–U.S. cross-border technology investment has continued to expand, yet the investment failure rate reaches 37.2%, significantly higher than that of domestic technology investment (18.5%). Addressing key challenges such as multidimensional risk complexity, covert transmission pathways, and high difficulty of prevention and control, this study draws on risk transmission theory, technology diffusion theory, and institutional distance theory to develop a four-dimensional risk identification framework covering technology, market, institution, and finance. Using a dataset of 486 China–U.S. cross-border technology investment projects from 2018 to 2023, we empirically reveal a three-stage risk transmission mechanism characterized by “chain triggering–network diffusion–compound amplification.” The results show that institutional risk is the core initial risk (contribution rate 38.6%), transmitting through a chain of “institutional differences → impeded technological adaptation → market entry barriers → tightened funding chains.” Cross-transmission between technology risk and market risk increases the probability of investment failure by 2.3 times. Furthermore, the strength of intellectual property protection and the signing status of bilateral investment treaties exert significant moderating effects on risk transmission, with moderation coefficients of −0.27 and −0.31, respectively. Based on the empirical findings, this paper proposes targeted solutions from three perspectives—risk early warning, pathway blocking, and collaborative governance—providing theoretical support and practical guidance for reducing risk losses in China–U.S. cross-border technology investment.
Fields of Study & Subjects
International Business and FDI
Private Equity and Venture Capital
Capital Investment and Risk Analysis
Publication details
- Journal / source
- Journal of Intelligence and Engineering Technology
- Volume
- 1
- Issue
- 1
- Pages
- 40–49
- Publication date
- 5 February 2026
- Language
- EN