Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | en_US |
| dc.contributor.advisor | Sumbal, Muhammad Saleem (ISE) | en_US |
| dc.creator | Wang, Shuqi | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/13372 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | en_US |
| dc.rights | All rights reserved | en_US |
| dc.title | Exploring the impact of generative AI on knowledge management processes for improved organizational performance | en_US |
| dcterms.abstract | With the integration of digital technologies into manufacturing and industrial processes, the importance of the knowledge-based economy has become increasingly prominent, emphasizing intellectual capital, innovation, and information as key drivers of economic growth. In this context, the rapid development of GenAI technology has brought about the explosive growth of data volume and has demonstrated strong content creation capabilities, reshaping the way knowledge is created and acquired. However, the application of GenAI in knowledge management also brings challenges, such as cognitive confusion and the accuracy of knowledge content. This paper aims to explore how GenAI influences processes such as knowledge creation, acquisition, and sharing in an organizational context, and to analyze its combined impact on knowledge management to eventually improve organizational performance. Given that academia is a knowledge-intensive field, this research work focuses on the impact of GenAI on knowledge management in academia, in order to provide useful insights and support for academic institutions and individuals to better use and manage knowledge resources and enhance performance. | en_US |
| dcterms.extent | 106 pages : color illustrations | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2024 | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.LCSH | Artificial intelligence | en_US |
| dcterms.LCSH | Knowledge management | en_US |
| dcterms.LCSH | Industrial management | en_US |
| dcterms.LCSH | Organizational learning | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 7855.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.46 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/13372