亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

What determines the performance of digital transformation in manufacturing enterprises? A study on the linkage effects based on fs/QCA method

数字化转型 联动装置(软件) 过程(计算) 制造工程 过程管理 制造业 定性比较分析 先进制造业 计算机集成制造 计算机科学 新产品开发 转化(遗传学) 产品(数学) 质量(理念) 工业工程 业务 工程类 营销 生物化学 化学 哲学 几何学 数学 认识论 机器学习 操作系统 万维网 基因
作者
Meng Shang,Chunjie Jia,Luyang Zhong,Junwei Cao
出处
期刊:Journal of Cleaner Production [Elsevier]
卷期号:450: 141856-141856 被引量:30
标识
DOI:10.1016/j.jclepro.2024.141856
摘要

The achievement of high-quality development in the manufacturing industry can be effectively realized through the process of digital transformation. The enhancement of digital transformation performance in manufacturing enterprises has emerged as a prominent topic of interest for both corporate entities and the academic community. Drawing upon the theoretical framework of the TOE model, this article presents a comprehensive analytical framework aimed at understanding the performance of digital transformation in manufacturing enterprises. By assessing a sample of 180 manufacturing enterprises currently undergoing digital transformation, this study employs the fuzzy-set qualitative comparative analysis (fs/QCA) methodology to study the interrelated effects and strategic choices pertaining to technology, organizational structure, and environmental conditions, all of which contribute to the improvement of digital transformation performance in manufacturing enterprises. The findings of the research indicate the following: (1) The attainment of high performance in digital transformation in manufacturing enterprises does not solely rely on a single condition, whether it pertains to the optimization of manufacturing processes or the development of new products. (2) High performance in digital transformation is the result of multiple interacting factors. Various causal configurations, such as "organization-environment oriented", "all-factor driven", and "technology-environment oriented", which have the characteristics of "multiple concurrency" and "different paths leading to the same goal." (3) In comparison, achieving high performance in manufacturing process optimization requires a higher degree of complexity than attaining high performance in new product development. Additionally, it is challenging to achieve high performance in new product development with a sole reliance on a single technological foundation and external environmental support. These research conclusions contribute to the existing body of knowledge on digital transformation performance, enhancing our understanding of the complex factors that underlie high performance in digital transformation in manufacturing enterprises. Importantly, they hold practical significance in improving the performance of digital transformation in the manufacturing sector.
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
14秒前
东溟渔夫发布了新的文献求助10
20秒前
牛牛月饼完成签到,获得积分10
27秒前
Akim应助东溟渔夫采纳,获得10
27秒前
BBQ关闭了BBQ文献求助
28秒前
29秒前
1分钟前
v哈哈发布了新的文献求助10
1分钟前
脑洞疼应助科研通管家采纳,获得10
1分钟前
Ming发布了新的文献求助10
1分钟前
SciGPT应助Ming采纳,获得10
2分钟前
瘦瘦的师发布了新的文献求助10
2分钟前
大模型应助zhengzhster采纳,获得10
2分钟前
2分钟前
量子星尘发布了新的文献求助10
2分钟前
自律发布了新的文献求助10
2分钟前
自律完成签到,获得积分10
3分钟前
BBQ发布了新的文献求助10
3分钟前
Ezekiel给Ezekiel的求助进行了留言
3分钟前
科研通AI2S应助科研通管家采纳,获得10
3分钟前
BBQ完成签到,获得积分10
3分钟前
lim完成签到,获得积分10
4分钟前
4分钟前
zhengzhster发布了新的文献求助10
4分钟前
小邓完成签到,获得积分10
4分钟前
可乐发布了新的文献求助30
4分钟前
量子星尘发布了新的文献求助10
4分钟前
小于完成签到,获得积分10
4分钟前
5分钟前
Ezekiel发布了新的文献求助10
5分钟前
上官枫完成签到 ,获得积分10
5分钟前
5分钟前
Ming发布了新的文献求助10
5分钟前
小于完成签到,获得积分10
5分钟前
Ming完成签到,获得积分10
5分钟前
merrylake完成签到 ,获得积分10
5分钟前
科研通AI2S应助科研通管家采纳,获得10
5分钟前
vivishe发布了新的文献求助10
5分钟前
vivishe完成签到,获得积分10
5分钟前
George发布了新的文献求助10
5分钟前
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
Binary Alloy Phase Diagrams, 2nd Edition 8000
Building Quantum Computers 800
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Natural Product Extraction: Principles and Applications 500
Exosomes Pipeline Insight, 2025 500
Qualitative Data Analysis with NVivo By Jenine Beekhuyzen, Pat Bazeley · 2024 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5664448
求助须知:如何正确求助?哪些是违规求助? 4862399
关于积分的说明 15107785
捐赠科研通 4823068
什么是DOI,文献DOI怎么找? 2581898
邀请新用户注册赠送积分活动 1536037
关于科研通互助平台的介绍 1494433