双灵巧性
自举(财务)
创业
敏捷软件开发
知识管理
探索性研究
业务
新企业
过程(计算)
概念模型
动态能力
营销
测量数据收集
商业模式
考试(生物学)
探索性分析
数字化转型
转化(遗传学)
微观基础
产业组织
对偶(语法数字)
商业智能
规范性
创新管理
商业研究
出处
期刊:Industrial Management and Data Systems
[Emerald Publishing Limited]
日期:2026-08-26
卷期号:: 1-28
标识
DOI:10.1108/imds-07-2025-1051
摘要
Purpose This study examines how artificial intelligence (AI) capabilities influence innovation ambidexterity, comprising exploratory and exploitative innovation, and how these innovation strategies contribute to business model transformation and key entrepreneurial outcomes, including new venture performance and entrepreneurial resilience. Design/methodology/approach A three-wave longitudinal survey of 218 high-tech entrepreneurial ventures in Vietnam was conducted. Polynomial regression and response surface analysis were used to test a temporally ordered process model grounded in the dynamic capabilities framework. Findings The results indicate that AI capabilities significantly enhance both exploratory and exploitative innovation. These innovation types independently and jointly foster business model transformation. Bootstrapping results are consistent with indirect relationships from AI capabilities to entrepreneurial outcomes through exploratory innovation, exploitative innovation, and business model transformation. The response surface results further show that when exploratory and exploitative innovation increase together, business model transformation improves in a positive and largely additive manner. By contrast, incongruence between the two innovation modes does not exhibit a strong detrimental effect, although a small directional effect is observed. Practical implications The findings provide practical guidance for entrepreneurs and managers on integrating AI into organizational routines and reinforcing both exploratory and exploitative innovation, and remaining agile in adapting business models to seize new opportunities and withstand external shocks. Originality/value This study contributes to research on AI and entrepreneurship by showing how AI capabilities activate dual innovation pathways and by clarifying that the configurational effect of innovation ambidexterity on business model transformation is mainly additive, while the effect of incongruence is weak and directional rather than strongly penalizing.
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