Title |
The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance |
ID_Doc |
19144 |
Authors |
Benzidia, S; Makaoui, N; Bentahar, O |
Title |
The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance |
Year |
2021 |
Published |
|
DOI |
10.1016/j.techfore.2020.120557 |
Abstract |
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. |
Author Keywords |
Big data analytics; Artificial intelligence; Environmental performance; Green supply chain process; Green digital learning; Organizational information processing theory; Healthcare |
Index Keywords |
Index Keywords |
Document Type |
Other |
Open Access |
Open Access |
Source |
Social Science Citation Index (SSCI) |
EID |
WOS:000618756500012 |
WoS Category |
Business; Regional & Urban Planning |
Research Area |
Business & Economics; Public Administration |
PDF |
http://manuscript.elsevier.com/S0040162520313834/pdf/S0040162520313834.pdf
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