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 [Taylor & Francis]
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.
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