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How AI innovation shapes supplier concentration under the triple helix framework: Evidence from emerging markets

供应链 产业组织 业务 新兴市场 杠杆(统计) 背景(考古学) 上游(联网) 晋升(国际象棋) 营销 供应链管理 相关性(法律) 经验证据 构造(python库) 经济 供应商关系管理 实证研究 数字化转型 资产专用性 知识管理 控制(管理) 创业 新兴技术 创新管理 结构方程建模 联动装置(软件) 政府(语言学) 三螺旋 操作化 下游(制造业) 产品创新 多元化(营销策略) 测量数据收集 制造业
作者
Wei Wu,Jing Xu,Ying Li,Yali Fan,Shiyu Tang
出处
期刊:Technological Forecasting and Social Change [Elsevier BV]
卷期号:226: 124579-124579 被引量:1
标识
DOI:10.1016/j.techfore.2026.124579
摘要

This study investigates how artificial intelligence innovation influences supplier concentration and management efficiency among firms in emerging markets. Using patent data from Chinese A share listed companies between 2014 and 2023, we construct firm level measures of AI innovation and examine their association with upstream supply chain outcomes. The empirical analysis employs fixed effects regression models to control for unobserved firm heterogeneity and common temporal shocks. Results indicate that AI related patents are positively and significantly associated with supplier concentration, suggesting that firms with stronger AI capabilities tend to rely on fewer upstream partners. We also find that AI innovation is positively associated with supplier management efficiency, as reflected in higher inventory turnover and faster accounts payable cycles. Further analysis reveals that these relationships are contingent on firm characteristics: digital maturity and operational risk exposure amplify the effects of AI innovation on both supplier concentration and efficiency outcomes. We interpret these findings through the lens of the Triple Helix framework, which emphasizes the institutional context of government policy, academic knowledge production, and industrial application that characterizes innovation ecosystems in emerging markets. The study contributes to the literature by shifting attention from operational performance to structural supply chain outcomes, identifying boundary conditions that shape technology driven supply chain restructuring, and demonstrating the relevance of institutional perspectives for understanding digital transformation in interfirm relationships. Practical implications are discussed for managers seeking to leverage AI for supply chain optimization and for policymakers aiming to balance innovation promotion with supply chain resilience. • This study examines how intelligent technology adoption influences supplier concentration. • Firm-level patent data from Chinese A-share listed companies (2014–2023) are utilized. • Intelligent innovation significantly enhances supplier concentration and management efficiency. • Digital maturity amplifies, while firm risk conditions, the effect of intelligent adoption. • Findings provide new evidence on technological drivers of supply chain restructuring.
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