供应链
大数据
适度
供应链管理
结构方程建模
计算机科学
分析
数据科学
过程(计算)
业务
过程管理
知识管理
营销
数据挖掘
机器学习
操作系统
作者
Smaïl Benzidia,Naouel Makaoui,Omar Bentahar
标识
DOI:10.1016/j.techfore.2020.120557
摘要
Big data analytics and artificial intelligence (BDA-AI) technologies have attracted increasing interest in recent years from academics and practitioners. However, few empirical studies have investigated the benefits of BDA-AI in the supply chain integration process and its impact on environmental performance. To fill this gap, we extended the organizational information processing theory by integrating BDA-AI and positioning digital learning as a moderator of the green supply chain process. We developed a conceptual model to test a sample of data from 168 French hospitals using a partial least squares regression-based structural equation modeling method. The findings showed that the use of BDA-AI technologies has a significant effect on environmental process integration and green supply chain collaboration. The study also underlined that both environmental process integration and green supply chain collaboration have a significant impact on environmental performance. The results highlight the moderating role of green digital learning in the relationships between BDA-AI and green supply chain collaboration, a major finding that has not been highlighted in the extant literature. This article provides valuable insight for logistics/supply chain managers, helping them in mobilizing BDA-AI technologies for supporting green supply processes and enhancing environmental performance.
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