Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics
The study aims to explore the direct and indirect effects of artificial intelligence on resilience and performance in a modern supply chain evolution environment. The email survey reached 208 companies from Jordan registered with the Jordanian Industry and Commerce, and results were collected using...
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| Format: | Article |
| Language: | English |
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LLC "CPC "Business Perspectives"
2025-03-01
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| Series: | Problems and Perspectives in Management |
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| Online Access: | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/21920/PPM_2025_01_Taha.pdf |
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| author | Adnan Taha Sarwar Khawaja Fayyaz Qureshi Firas Rashed Wahsheh |
| author_facet | Adnan Taha Sarwar Khawaja Fayyaz Qureshi Firas Rashed Wahsheh |
| author_sort | Adnan Taha |
| collection | DOAJ |
| description | The study aims to explore the direct and indirect effects of artificial intelligence on resilience and performance in a modern supply chain evolution environment. The email survey reached 208 companies from Jordan registered with the Jordanian Industry and Commerce, and results were collected using structural equation modeling analysis. The results show the impact of artificial intelligence on overall supply chain performance. However, similar output is only achievable using its equipage capability to return data to promote the resilience of supply and performance. This paper provides additional standpoints on how to use artificial intelligence to ensure supply chain performance; however, longitudinal research offers deeper insights. Furthermore, this analysis addresses the existing gap in the literature regarding synthetic intelligence. While this study has taken critical measures throughout the research process to ensure safety, it is necessary to note that it is still susceptible to some common boundaries found in survey designs. A longitudinal study might expand the research to examine further aspects of the phenomenon. |
| format | Article |
| id | doaj-art-8dce87302cd14a809c211656bc2a44d2 |
| institution | DOAJ |
| issn | 1727-7051 1810-5467 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | LLC "CPC "Business Perspectives" |
| record_format | Article |
| series | Problems and Perspectives in Management |
| spelling | doaj-art-8dce87302cd14a809c211656bc2a44d22025-08-20T02:50:23ZengLLC "CPC "Business Perspectives"Problems and Perspectives in Management1727-70511810-54672025-03-0123174175210.21511/ppm.23(1).2025.5521920Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamicsAdnan Taha0https://orcid.org/0000-0002-0393-1842Sarwar Khawaja1https://orcid.org/0009-0004-7792-4794Fayyaz Qureshi2https://orcid.org/0000-0003-1305-9493Firas Rashed Wahsheh3https://orcid.org/0009-0009-5728-3738Dr., Senior Business Lecturer, Oxford Business CollegeProfessor, Chairman of the Director’s Strategic Borad, Oxford Business CollegeDr., Head of Research and Innovation, Oxford Business College; PGR (Doctoral) Supervisor/ Director of Studies, University of Wales Trinity SaintPh.D., Assistant Professor, Department of Management Information Systems, Faculty of Business, Ajloun National UniversityThe study aims to explore the direct and indirect effects of artificial intelligence on resilience and performance in a modern supply chain evolution environment. The email survey reached 208 companies from Jordan registered with the Jordanian Industry and Commerce, and results were collected using structural equation modeling analysis. The results show the impact of artificial intelligence on overall supply chain performance. However, similar output is only achievable using its equipage capability to return data to promote the resilience of supply and performance. This paper provides additional standpoints on how to use artificial intelligence to ensure supply chain performance; however, longitudinal research offers deeper insights. Furthermore, this analysis addresses the existing gap in the literature regarding synthetic intelligence. While this study has taken critical measures throughout the research process to ensure safety, it is necessary to note that it is still susceptible to some common boundaries found in survey designs. A longitudinal study might expand the research to examine further aspects of the phenomenon.https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/21920/PPM_2025_01_Taha.pdfartificial intelligenceCOVID-19performancesourcingvisibility |
| spellingShingle | Adnan Taha Sarwar Khawaja Fayyaz Qureshi Firas Rashed Wahsheh Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics Problems and Perspectives in Management artificial intelligence COVID-19 performance sourcing visibility |
| title | Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics |
| title_full | Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics |
| title_fullStr | Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics |
| title_full_unstemmed | Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics |
| title_short | Employing artificial intelligence to improve the supply chain’s resilience and performance: Moderating the impact of supply chain dynamics |
| title_sort | employing artificial intelligence to improve the supply chain s resilience and performance moderating the impact of supply chain dynamics |
| topic | artificial intelligence COVID-19 performance sourcing visibility |
| url | https://www.businessperspectives.org/images/pdf/applications/publishing/templates/article/assets/21920/PPM_2025_01_Taha.pdf |
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