Untangling the cumulative impact of big data analytics, green lean six sigma and sustainable supply chain management on the economic performance of manufacturing organisations

六西格玛 大数据 精益制造 供应链 精益六西格玛 供应链管理 分析 业务 制造工程 过程管理 运营管理 工程类 计算机科学 数据科学 营销 数据挖掘
作者
Arsalan Fayyaz,ChenGuang Liu,Yan Xu,Fahad Khan,Selim Ahmed
出处
期刊:Production Planning & Control [Informa]
卷期号:: 1-18 被引量:1
标识
DOI:10.1080/09537287.2024.2348517
摘要

Big data analytics provides up-to-date information to facilitate organisational decision-making and boost economic performance. However, an organisation's big data analytical capability must be investigated to determine its importance in driving economic performance through continuous improvement and sustainability-related tools such as green lean six sigma and sustainable supply chain management. We conducted an empirical study and obtained 443 effective responses from managerial staff working in small and medium-sized organisations in Pakistan. Using structural equation modelling and artificial neural networks, we investigate the effects of big data analytics, green lean six sigma and sustainable supply chain management on economic performance. Our result shows that green lean six sigma and sustainable supply chain management partially mediate the relationship between big data analytics and economic performance. Although the implementation of sustainable supply chain management is identified, it is supported by technological but not cultural compatibility in the current operating environments of the organisations. As a theoretical contribution, this study enriches the literature on digitisation by relating it to the dynamic capability theory. As per practical contribution, this study reveals that the amalgamation of big data analytics, green lean six sigma, and sustainable supply chain management strengthen the organisation's economic performance.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
华仔应助LEMON采纳,获得10
1秒前
121703完成签到,获得积分10
2秒前
烟花应助如寄采纳,获得10
3秒前
大个应助庸人自扰采纳,获得10
8秒前
Ava应助zhouyi采纳,获得10
8秒前
8秒前
8秒前
Ganlou应助xzy998采纳,获得10
8秒前
121703关注了科研通微信公众号
11秒前
善学以致用应助快乐大炮采纳,获得10
11秒前
瞿霞发布了新的文献求助10
11秒前
zhaoying发布了新的文献求助150
12秒前
cocolu应助科研通管家采纳,获得10
13秒前
Owen应助科研通管家采纳,获得10
13秒前
Ekkoye完成签到,获得积分10
13秒前
13秒前
FashionBoy应助科研通管家采纳,获得10
14秒前
华仔应助科研通管家采纳,获得10
14秒前
CipherSage应助科研通管家采纳,获得10
14秒前
打打应助科研通管家采纳,获得10
14秒前
14秒前
研友_VZG7GZ应助科研通管家采纳,获得10
14秒前
14秒前
14秒前
14秒前
14秒前
Owen应助着急的听南采纳,获得10
16秒前
16秒前
卡卡光波完成签到,获得积分10
16秒前
慕青应助聪慧的从云采纳,获得10
16秒前
OcRyf5完成签到 ,获得积分20
16秒前
dd完成签到,获得积分10
16秒前
不配.应助瞿霞采纳,获得20
18秒前
19秒前
20秒前
我是屈原在世完成签到,获得积分10
20秒前
小刘爱读文献完成签到 ,获得积分10
21秒前
zhouyi发布了新的文献求助10
21秒前
情怀应助469459442采纳,获得10
22秒前
小熊完成签到,获得积分10
24秒前
高分求助中
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger Heßler, Claudia, Rud 1000
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 1000
Natural History of Mantodea 螳螂的自然史 1000
A Photographic Guide to Mantis of China 常见螳螂野外识别手册 800
Barge Mooring (Oilfield Seamanship Series Volume 6) 600
ANSYS Workbench基础教程与实例详解 500
Spatial Political Economy: Uneven Development and the Production of Nature in Chile 400
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 内科学 物理 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 免疫学 细胞生物学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 3325577
求助须知:如何正确求助?哪些是违规求助? 2956275
关于积分的说明 8579868
捐赠科研通 2634243
什么是DOI,文献DOI怎么找? 1441821
科研通“疑难数据库(出版商)”最低求助积分说明 667952
邀请新用户注册赠送积分活动 654755