<abstract xmlns="http://www.w3.org/1999/xhtml">

<bold>Aim/purpose</bold> – This research aims to design an analytical framework to investigate the dimensions, factors, and key indicators affecting the green supply chain based on the innovative technology of Artificial Intelligence of Everything (AIoE). Understanding the cause-and-effect relationships of all actors in this smart and sustainable system is also one of the critical goals of this research. Also, examining the key features of AIoE technology as a new hybrid technology is one of this research’s most essential features.
<bold>Design/methodology/approach</bold> – This research has tried to extract and refine the most critical parameters affecting the green supply chain based on technology by reviewing the literature and examining the opinions of active experts in the field of study. Then, by using the focus group, it has been tried to provide an analytical framework to express the cause-and-effect relationships of all actors active in this system by examining the basic features of AIoE. Finally, this framework was validated and approved using experts’ opinions and the focus group, emphasizing integrity, comprehensiveness, and effectiveness.
<bold>Findings</bold> – This research identified the dimensions, components, and indicators affecting the smart, green, and sustainable supply chain based on Artificial Intelligence (AI). It also presented an analytical framework that shows the cause-and-effect relationships of all active actors in this system.
<bold>Research implications/limitations</bold> – This research simultaneously offers significant insights into implementing intelligent and sustainable process-oriented systems. However, it is important to note the limitations. One of the most significant challenges in presenting the framework was finding experts with sufficient awareness, knowledge, and experience and participants to analyze cause-and-effect relationships.
<bold>Originality/value/contribution</bold> – This research provides a practical analysis of AIoE technology for the first time. The results strongly support the argument that hybrid AIoE technology can tremendously impact the sustainability and greenness of supply chain processes.
</abstract>

Aim/purpose – This research aims to design an analytical framework to investigate the dimensions, factors, and key indicators affecting the green supply chain based on the innovative technology of Artificial Intelligence of Everything (AIoE). Understanding the cause-and-effect relationships of all actors in this smart and sustainable system is also one of the critical goals of this research. Also, examining the key features of AIoE technology as a new hybrid technology is one of this research’s most essential features.
Design/methodology/approach – This research has tried to extract and refine the most critical parameters affecting the green supply chain based on technology by reviewing the literature and examining the opinions of active experts in the field of study. Then, by using the focus group, it has been tried to provide an analytical framework to express the cause-and-effect relationships of all actors active in this system by examining the basic features of AIoE. Finally, this framework was validated and approved using experts’ opinions and the focus group, emphasizing integrity, comprehensiveness, and effectiveness.
Findings – This research identified the dimensions, components, and indicators affecting the smart, green, and sustainable supply chain based on Artificial Intelligence (AI). It also presented an analytical framework that shows the cause-and-effect relationships of all active actors in this system.
Research implications/limitations – This research simultaneously offers significant insights into implementing intelligent and sustainable process-oriented systems. However, it is important to note the limitations. One of the most significant challenges in presenting the framework was finding experts with sufficient awareness, knowledge, and experience and participants to analyze cause-and-effect relationships.
Originality/value/contribution – This research provides a practical analysis of AIoE technology for the first time. The results strongly support the argument that hybrid AIoE technology can tremendously impact the sustainability and greenness of supply chain processes.

Green Supply Chain Management based on Artificial Intelligence of Everything

Journal of Economics and Management

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

{"article-title":"Green Supply Chain Management based on Artificial Intelligence of Everything"}

Aim/purpose – This research aims to design an analytical framework to investigate the dimensions, factors, and key indicators affecting the green supply chain...

Green Supply Chain Management based on Artificial Intelligence of Everything

Data publikacji: 20 cze 2024

Zakres stron: 171 - 188

Otrzymano: 25 mar 2024

Przyjęty: 09 cze 2024

DOI: https://doi.org/10.22367/jem.2024.46.07

Słowa kluczowe
green supply chain, sustainable supply chain, Artificial Intelligence of Everything (AIoE), AIoE-based supply chain

© 2024 Hamed Nozari, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

Green Supply Chain Management based on Artificial Intelligence of Everything

Data publikacji: 20 cze 2024

Zakres stron: 171 - 188

Otrzymano: 25 mar 2024

Przyjęty: 09 cze 2024

DOI: https://doi.org/10.22367/jem.2024.46.07

Słowa kluczowegreen supply chain, sustainable supply chain, Artificial Intelligence of Everything (AIoE), AIoE-based supply chain

© 2024 Hamed Nozari, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License.

Słowa kluczowe
green supply chain, sustainable supply chain, Artificial Intelligence of Everything (AIoE), AIoE-based supply chain