人工智能创新对可持续知识的影响：企业弹性的双重作用

IF 15.5 1区管理学 Q1 BUSINESS

Journal of Innovation & Knowledge Pub Date : 2025-09-28 DOI:10.1016/j.jik.2025.100832

Shaofeng Wang , Liang Ma , Feifei Hao , Hao Zhang

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引用次数: 0

摘要

人工智能（AI）的快速发展为全球数字商务的知识创造和可持续创新提供了前所未有的机遇。本研究探讨了人工智能编排能力如何产生新的知识形式，推动跨境电子商务跨国企业的可持续发展，企业弹性作为关键的知识转化机制。基于资源调度理论，采用混合方法，采用偏最小二乘结构方程模型（PLS-SEM）、重要性-绩效图分析、模糊集定性比较分析（fsQCA）和高管访谈等方法，分析了来自中国和欧洲444家企业的数据。我们的研究结果表明，人工智能编排能力——包括规划、集成和重新配置维度——创造了可操作的知识，通过企业弹性直接或间接地显著增强了可持续发展。企业弹性作为一种双重功能能力出现，它不仅可以调节人工智能系统和可持续性结果之间的知识流动，还可以放大人工智能产生的见解的创新潜力。区域分析揭示了不同的知识创造途径：中国企业擅长将人工智能能力转化为基于弹性的知识，而欧洲企业则擅长将基于弹性的知识转化为可持续性创新。配置分析确定了人工智能能力和弹性维度的多种等效组合，从而产生高影响力的可持续创新。这项研究促进了我们对数字技术如何为可持续发展创造持久知识的理解，为创新知识动态提供了新的理论见解，并为利用人工智能作为数字经济中可持续业务转型的催化剂提供了实践指导。

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Artificial intelligence innovation to sustainable knowledge: The dual role of enterprise resilience

The rapid evolution of artificial intelligence (AI) presents unprecedented opportunities for knowledge creation and sustainable innovation in global digital commerce. This study investigates how AI orchestration capability generates new forms of knowledge that drive sustainable development in cross-border e-commerce multinational enterprises, with enterprise resilience serving as a critical knowledge transformation mechanism. Drawing on resource orchestration theory and employing a mixed-methods approach, we analyze data from 444 enterprises across China and Europe using partial least squares-structural equation modeling (PLS-SEM), importance–performance map analysis, and fuzzy-set qualitative comparative analysis (fsQCA), and executive interviews. Our findings reveal that AI orchestration capability—encompassing planning, integration, and reconfiguration dimensions—creates actionable knowledge that significantly enhances sustainable development both directly and indirectly through enterprise resilience. Enterprise resilience emerges as a dual-function capability that not only mediates knowledge flows between AI systems and sustainability outcomes but also amplifies the innovation potential of AI-generated insights. Regional analysis uncovers distinct knowledge creation pathways: Chinese enterprises excel at transforming AI capabilities into resilience-based knowledge, while European firms demonstrate superior translation of resilience-derived knowledge into sustainability innovations. Configurational analysis identifies multiple equifinal combinations of AI capabilities and resilience dimensions that generate high-impact sustainable innovations. This research advances our understanding of how digital technologies create enduring knowledge for sustainability, offering novel theoretical insights into innovation–knowledge dynamics and practical guidance for leveraging AI as a catalyst for sustainable business transformation in the digital economy.

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来源期刊

Journal of Innovation & Knowledge Multiple-

CiteScore

16.10

自引率

12.70%

发文量

118

审稿时长

37 days

期刊介绍： The Journal of Innovation and Knowledge (JIK) explores how innovation drives knowledge creation and vice versa, emphasizing that not all innovation leads to knowledge, but enduring innovation across diverse fields fosters theory and knowledge. JIK invites papers on innovations enhancing or generating knowledge, covering innovation processes, structures, outcomes, and behaviors at various levels. Articles in JIK examine knowledge-related changes promoting innovation for societal best practices. JIK serves as a platform for high-quality studies undergoing double-blind peer review, ensuring global dissemination to scholars, practitioners, and policymakers who recognize innovation and knowledge as economic drivers. It publishes theoretical articles, empirical studies, case studies, reviews, and other content, addressing current trends and emerging topics in innovation and knowledge. The journal welcomes suggestions for special issues and encourages articles to showcase contextual differences and lessons for a broad audience. In essence, JIK is an interdisciplinary journal dedicated to advancing theoretical and practical innovations and knowledge across multiple fields, including Economics, Business and Management, Engineering, Science, and Education.