AI-DRIVEN WORKLOAD OPTIMIZATION TO ENHANCE ECONOMIC SUSTAINABILITY:

Simple item page
dc.contributor.authorMUHAMMAD ASIM SOHAIB
dc.date.accessioned2025-09-20T07:52:10Z
dc.date.available2025-09-20T07:52:10Z
dc.date.issued2025
dc.description.abstractThe application of Artificial Intelligence-Driven Workload Optimization is reshaping the management of operations in organizations, but still little is understood about its overall effects on sustainable performance.
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/6652
dc.language.isoen
dc.publisherumt.lahore
dc.titleAI-DRIVEN WORKLOAD OPTIMIZATION TO ENHANCE ECONOMIC SUSTAINABILITY:
dc.title.alternativeTHE MEDIATING ROLE OF EMPLOYEE WELL BEING AND EMPLOYEE PRODUCTIVI
dc.typeThesis
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
MUHAMMAD ASIM SOHAIB.pdf
Size:
1.44 MB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
2025