Learning ambidexterity and technology innovation: The moderating effect of knowledge network modularity

IF 3.7 3区 管理学 Q2 BUSINESS Journal of Engineering and Technology Management Pub Date : 2024-03-19 DOI:10.1016/j.jengtecman.2024.101812
Ziyi Zhao , Yulan Shen
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Abstract

The aim of this paper is to investigate the impact of learning ambidexterity on firms’ technological innovation, especially in the context of varying degrees of modularity in firms’ knowledge networks. By combining temporal and cognitive aspects, this study focuses on the micro-level utilization of knowledge and redefines exploratory and exploitative learning as learning unfamiliar and familiar knowledge, respectively. Building upon previous research, we classify learning ambidexterity into combined and balanced forms, further investigate their influence on innovation performance. Utilizing a panel data set spanning 10 years of 63 semiconductor firms listed in the US market, our findings reveal that combined learning ambidexterity effectively harnesses the complementary effects of both learning patterns, resulting in a positive influence on technological innovation. Conversely, balanced learning ambidexterity hampers knowledge transferability between these two patterns leading to a negative impact on technological innovation. Additionally, we employ patent data to measure the degree of modularity within firms’ knowledge networks. Our results indicate that higher levels of modularity enhance the positive effect of combined learning ambidexterity on innovation while mitigating its negative impact for balanced learning ambidexterity. These findings suggest the importance for firms to strategically manage and dynamically orchestrate learning ambidexterity alongside double-loop learning practices, while continuously structuring and facilitating reuse within organizational knowledge networks to create favorable circumstances for the effective implementation of learning ambidexterity.

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学习灵活性与技术创新:知识网络模块化的调节作用
本文旨在研究学习灵活性对企业技术创新的影响,尤其是在企业知识网络模块化程度不同的背景下。通过结合时间和认知两个方面,本研究侧重于微观层面的知识利用,并将探索性学习和利用性学习分别重新定义为学习陌生知识和熟悉知识。在前人研究的基础上,我们将学习模糊性分为组合形式和平衡形式,并进一步研究它们对创新绩效的影响。我们利用 63 家在美国市场上市的半导体公司 10 年的面板数据集,研究结果表明,组合型学习灵活性能有效利用两种学习模式的互补效应,从而对技术创新产生积极影响。相反,均衡学习的灵活性则会阻碍这两种学习模式之间的知识转移,从而对技术创新产生负面影响。此外,我们还利用专利数据来衡量企业知识网络的模块化程度。我们的研究结果表明,较高的模块化程度会增强综合学习型灵活性对创新的积极影响,同时减轻其对平衡学习型灵活性的消极影响。这些研究结果表明,企业必须对学习灵活性与双环学习实践进行战略管理和动态协调,同时不断构建和促进组织知识网络内的再利用,为有效实施学习灵活性创造有利条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.00
自引率
6.20%
发文量
29
审稿时长
>12 weeks
期刊介绍: The Journal of Engineering and Technology Management (JET-M) is an international scholarly refereed research journal which aims to promote the theory and practice of technology, innovation, and engineering management. The journal links engineering, science, and management disciplines. It addresses the issues involved in the planning, development, and implementation of technological capabilities to shape and accomplish the strategic and operational objectives of an organization. It covers not only R&D management, but also the entire spectrum of managerial concerns in technology-based organizations. This includes issues relating to new product development, human resource management, innovation process management, project management, technological fusion, marketing, technological forecasting and strategic planning. The journal provides an interface between technology and other corporate functions, such as R&D, marketing, manufacturing and administration. Its ultimate goal is to make a profound contribution to theory development, research and practice by serving as a leading forum for the publication of scholarly research on all aspects of technology, innovation, and engineering management.
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