产业技术变革下跨国企业知识网络规模与效率的跨周期韧性效应

李飞, 曾凡芮, 杨晓旭

管理学报 ›› 2026, Vol. 23 ›› Issue (7) : 1348.

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PDF(1238 KB)
管理学报 ›› 2026, Vol. 23 ›› Issue (7) : 1348.
信息与知识管理

产业技术变革下跨国企业知识网络规模与效率的跨周期韧性效应

  • 李飞,曾凡芮,杨晓旭
作者信息 +

The Cross-Cycle Resilience Effects of Knowledge Network Scale and Efficiency of Multinational Enterprises under Industrial Technological Change

  • LI Fei,ZENG Fanrui,YANG Xiaoxu
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文章历史 +

摘要

利用2013~2022年中国移动通信跨国企业的面板数据,考察产业技术变革背景下跨国企业知识网络规模与效率对组织韧性的跨周期影响,以及国际化经验的调节作用。研究发现,知识网络规模对组织韧性具有显著的正向影响,但该效应在技术转型期相较于稳定期有所衰减;知识网络效率能够有效提升组织韧性,且该效应在不同技术周期中保持稳定;调节效应检验表明,国际化经验显著增强了知识网络规模对组织韧性的促进效应,但未对知识网络效率与组织韧性的关系产生明显影响。

Abstract

Using panel data of Chinese multinational enterprises in the mobile communications industry from 2013 to 2022, this study examines the cross-cycle effects of knowledge network scale and efficiency on organizational resilience amid industrial technological change, and tests the moderating role of international experience. The results show that knowledge network scale significantly enhances organizational resilience, although this effect weakens in transition periods relative to stable periods. Knowledge network efficiency also significantly enhances organizational resilience, and this effect remains stable across technology cycles. International experience significantly strengthens the positive effect of knowledge network scale on organizational resilience, but does not significantly moderate the relationship between knowledge network efficiency and organizational resilience.

关键词

知识网络 / 组织韧性 / 技术周期 / 国际化经验 / 移动通信跨国企业

Key words

knowledge network / organizational resilience / technological cycle / international experience / mobile communication multinational enterprises

引用本文

导出引用
李飞, 曾凡芮, 杨晓旭. 产业技术变革下跨国企业知识网络规模与效率的跨周期韧性效应[J]. 管理学报. 2026, 23(7): 1348
LI Fei, ZENG Fanrui, YANG Xiaoxu. The Cross-Cycle Resilience Effects of Knowledge Network Scale and Efficiency of Multinational Enterprises under Industrial Technological Change[J]. Chinese Journal of Management. 2026, 23(7): 1348

基金

国家自然科学基金资助项目(7247020468);教育部人文社会科学研究规划基金资助项目(24YJA790020);北京邮电大学AI4S探索计划资助项目(2025AI4S13)


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