Trade, AI-robot adoption, and manufacturing transformation: cross-national determinants of firm-level automation in heterogeneous institutional contexts
Year: 2026
Type: article
Abstract: It investigates the multi-dimensional determinants of AI-driven robot adoption among manufacturing firms to examine how perceived benefits, industry peer pressure, and international trade exposure jointly shape firm-level automation decisions across heterogeneous institutional contexts during 2016–2024. Using a firm-level 12,000 manufacturer panel data, it employs PPML estimation with high-dimensional fixed effects, instrumental variables using historical tariffs and partner-country demand shocks to address trade endogeneity, and System GMM to capture dynamic adjustment. The analytical framework integrates TAM, institutional isomorphism theory, and Melitz’s heterogeneous firm model. Empirical results show the strongest adoption driver, with long-run effects nearly double short-run estimates. Industry peer pressure accelerates diffusion through competitive mimicry and network density. Trade exposure causally stimulates automation, exporters respond to quality demands, import-competing firms automate defensively. Cross-country analysis reveals Germany’s highest benefit responsiveness, Korea’s strongest peer effects, and China’s policy-coordinated balanced patterns. It provides the first integrated cross-national empirical analysis of behavioral, institutional, and trade-related automation mechanisms within a single framework, demonstrating that effective automation policy must verify benefit perceptions, industry coordination, and trade integration across diverse institutional contexts. First published online 19 October 2026
Author: Chang Hwan Choi
Institution: Dankook University
Topic: Global trade and economics
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $727
OpenAlex ID: W7222961376