How does digital transformation empower knowledge creation? Evidence from Chinese manufacturing enterprises

数字化转型 业务 转化(遗传学) 知识管理 产业组织 过程管理 计算机科学 万维网 生物化学 基因 化学
作者
Yufen Chen,X. Pan,Pian Liu,Wim Vanhaverbeke
出处
期刊:Journal of Innovation & Knowledge [Elsevier BV]
卷期号:9 (2): 100481-100481 被引量:63
标识
DOI:10.1016/j.jik.2024.100481
摘要

Knowledge creation is the foundation for indigenous innovation in manufacturing enterprises; however, the effects of digital transformation on knowledge creation are still not well understood. Nonaka put forward the model of knowledge creation, which includes four processes: socialization, externalization, combination, and internalization, known as the famous SECI model. Based on the SECI model, this study analyzes the effects of digital transformation on four knowledge creation processes, using panel data from Chinese listed manufacturing enterprises from 2007 to 2020. The study provides several novel findings. First, digital transformation positively affects all knowledge creation processes, with the effects on knowledge combination capability being particularly notable. Second, the effects of digitalization inputs on externalization and combination are insignificant but exert a negative impact on socialization and internalization. Third, a heterogeneity analysis reveals that the facilitating effect of digital transformation is more significant in state-owned and large enterprises. Moreover, it primarily acts as the ''cherry on top,'' significantly benefiting enterprises that already have strong knowledge creation capabilities. A low level of digital technology development in the region where an enterprise is located will inhibit the role of digital transformation in promoting knowledge socialization. Furthermore, enterprise innovation culture and regional innovation environments play positive moderating roles. This study contributes to further understanding of how digital transformation affects enterprises’ knowledge creation activities.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
zxf完成签到,获得积分10
刚刚
刚刚
九九发布了新的文献求助10
1秒前
卡乐瑞咩吹可完成签到,获得积分0
1秒前
2秒前
2秒前
A水暖五金批发张哥完成签到,获得积分10
2秒前
科研通AI6.4的应助被Shanwq采纳,获得10
2秒前
2秒前
hnxhl完成签到,获得积分10
2秒前
997发布了新的文献求助10
3秒前
莲花盛开的应助被刘陌陌采纳,获得10
3秒前
3秒前
3秒前
虚拟的小笼包完成签到,获得积分10
4秒前
qingshan完成签到,获得积分10
4秒前
4秒前
5秒前
滴滴答答发布了新的文献求助10
5秒前
5秒前
茹茹完成签到,获得积分10
5秒前
111发布了新的文献求助10
6秒前
小黑给小黑的求助进行了留言
7秒前
XXX发布了新的文献求助10
7秒前
7秒前
sheng发布了新的文献求助10
7秒前
7秒前
失眠飞鱼完成签到,获得积分10
8秒前
跑爷给yuanzi的求助进行了留言
9秒前
9秒前
9秒前
geold发布了新的文献求助10
9秒前
852的应助被爱学习的小钟采纳,获得10
9秒前
9秒前
Jiatong7发布了新的文献求助30
10秒前
whzqzlh完成签到 ,获得积分10
10秒前
10秒前
研友_ndVY48完成签到,获得积分20
11秒前
杨旭给杨旭的求助进行了留言
11秒前
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Les Mantodea De Guyane 2000
Narrative Disclosure and Earnings Performance: Evidence from R&D Disclosures 1050
内視鏡下経鼻経蝶形骨洞手術術後SIADHに対する予防的水制限の安全性と有効性の検討 1000
Positive Psychology 600
Problems and Solutions for Integer and Combinatorial Optimization: Building Skills in Discrete Optimization 600
Organizational Behavior 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8006282
求助须知:如何正确求助?哪些是违规求助? 9457007
关于积分的说明 21164238
捐赠科研通 7578837
什么是DOI,文献DOI怎么找? 3382295
关于科研通互助平台的介绍 2515005
邀请新用户注册赠送积分活动 2417188