Blockchain technology adoption and sustainable performance in Chinese manufacturing: insights on learning and organizational inertia

块链 知识管理 供应链 独创性 持续性 杠杆(统计) 供应链管理 组织学习 业务 结构方程建模 组织绩效 过程管理 营销 计算机科学 创造力 机器学习 生物 生态学 法学 计算机安全 政治学
作者
Xianglu Hua,Jie Zhou,Reham Eltantawy,Liangqing Zhang,Bin Wang,Yifan Tian,Zuopeng Zhang
出处
期刊:Industrial Management and Data Systems [Emerald Publishing Limited]
卷期号:125 (2): 604-626 被引量:7
标识
DOI:10.1108/imds-08-2023-0552
摘要

Purpose Achieving sustainability and sustainable performance has emerged as a critical area of focus for both academic research and practice. However, this pursuit faces challenges, particularly concerning the inadequacy of supply chain information. To address this issue, our study employs the organizational information processing theory to explore how adopting blockchain technology enables firms to learn from and collaborate with their supply chain partners, ultimately facilitating their sustainable performance even in the presence of organizational inertia. Design/methodology/approach Underpinned by the organizational information processing theory and drawing data from 220 manufacturing firms in China, we use structural equation modeling to test our conceptual model. Findings Our results demonstrate that blockchain technology adoption can significantly enhance sustainable performance. Furthermore, supply chain learning acts as a mediator between blockchain technology adoption and sustainable performance, while organizational inertia plays a negative moderating role between blockchain technology adoption and supply chain learning. Originality/value These findings extend the existing literature on blockchain technology adoption and supply chain management, offering novel insights into the pivotal role of blockchain in fostering supply chain learning and achieving sustainable performance. Our study provides valuable practical implications for managers seeking to leverage blockchain technology to enhance sustainability and facilitate organizational learning.
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
QiQi发布了新的文献求助10
1秒前
1秒前
蔡宇滔发布了新的文献求助10
3秒前
5秒前
直率的晓亦完成签到,获得积分10
5秒前
kzh发布了新的文献求助10
7秒前
RO发布了新的文献求助10
9秒前
9秒前
杨咩咩发布了新的文献求助10
10秒前
CodeCraft应助研友_ndDGVn采纳,获得10
11秒前
11秒前
JIRUIYI完成签到,获得积分10
12秒前
hoang19发布了新的文献求助10
12秒前
kk完成签到,获得积分10
12秒前
若一发布了新的文献求助30
13秒前
月见清和发布了新的文献求助10
13秒前
蔡宇滔发布了新的文献求助10
15秒前
栗荔完成签到 ,获得积分10
15秒前
kzh完成签到,获得积分10
16秒前
小蘑菇应助白白采纳,获得10
16秒前
张欢馨完成签到,获得积分0
16秒前
17秒前
小蘑菇应助孤独鹰采纳,获得10
19秒前
NovaZ发布了新的文献求助10
19秒前
仁爱思天完成签到,获得积分20
19秒前
乐乐应助周南采纳,获得10
19秒前
宫城良官完成签到 ,获得积分10
20秒前
华仔应助OB采纳,获得10
22秒前
qq发布了新的文献求助10
25秒前
25秒前
NovaZ完成签到,获得积分10
26秒前
汉堡包应助绿叶采纳,获得10
27秒前
乌冬面完成签到,获得积分10
27秒前
Hello应助派大星采纳,获得10
27秒前
28秒前
月见清和发布了新的文献求助10
28秒前
若一发布了新的文献求助30
28秒前
田様应助杨咩咩采纳,获得10
29秒前
Dr.Yang发布了新的文献求助10
33秒前
34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
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
Comparative Elite Sport Development Systems, Structures and Public Policy 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
What is the Future of Psychotherapy in Digital Age? Technology, AI Bots, and Psychotherapy after Covid 444
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7637984
求助须知:如何正确求助?哪些是违规求助? 9211325
关于积分的说明 19758495
捐赠科研通 7204970
什么是DOI,文献DOI怎么找? 3275767
关于科研通互助平台的介绍 2437385
邀请新用户注册赠送积分活动 2272936