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The impact of knowledge base on firm performance: an empirical study based on listed firms in the digital industry

基础(拓扑) 实证研究 控制论 计算机科学 知识库 知识管理 业务 产业组织 人工智能 数学 统计 数学分析
作者
Haimeng Liang,Changrong Dong
出处
期刊:Kybernetes [Emerald Publishing Limited]
标识
DOI:10.1108/k-11-2024-3076
摘要

Purpose This study aims to examine the relationship between knowledge base and the performance of digital firms, as well as the roles of innovation openness and market volatility in this relationship. Based on the size and structural characteristics of the knowledge base, two dimensions of knowledge stock and knowledge diversity are selected for the study. Design/methodology/approach In this study, 334 listed firms in the digital industry in China are used to test the hypotheses using the Ordinary Least Squares model. Findings Knowledge stock in the knowledge base promotes the performance of digital firms, while knowledge diversity has an asymmetric inverted U-shaped relationship with the performance of digital firms, indicating a “diversity trap.” Furthermore, innovation openness and market volatility positively moderate the effect of knowledge stock on digital firm performance. They also sharpen the inverted U-shaped relationship between knowledge diversity and performance, exacerbating the “diversity trap” and steepening the curve. Additionally, market volatility encourages firms to achieve over-performance, shifting the curve upward. Originality/value This study innovatively focuses on the digital industry and explores the relationship between knowledge base and enterprise performance based on two dimensions: knowledge stock and knowledge diversity. Compared to labor-intensive industries, the digital industry is technology-intensive and highly reliant on knowledge resources. Therefore, examining firms in this industry offers more representative and practical insights. At the same time, a more detailed and deeper study of the economic effects of the knowledge base can complement the research on the knowledge base and propose more targeted countermeasures for a good match between the knowledge base and the environment of digital enterprises.
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