{"title":"Learning ambidexterity and technology innovation: The moderating effect of knowledge network modularity","authors":"Ziyi Zhao , Yulan Shen","doi":"10.1016/j.jengtecman.2024.101812","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":50209,"journal":{"name":"Journal of Engineering and Technology Management","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering and Technology Management","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0923474824000171","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 0
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.
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.