Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/111656
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Industrial and Systems Engineering | - |
| dc.creator | Sumbal, MS | - |
| dc.creator | Amber, Q | - |
| dc.creator | Tariq, A | - |
| dc.creator | Raziq, MM | - |
| dc.creator | Tsui, E | - |
| dc.date.accessioned | 2025-03-04T08:21:25Z | - |
| dc.date.available | 2025-03-04T08:21:25Z | - |
| dc.identifier.issn | 0263-5577 | - |
| dc.identifier.uri | http://hdl.handle.net/10397/111656 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Emerald Publishing Limited | en_US |
| dc.rights | ©Emerald Publishing Limited. This AAM is provided for your own personal use only. It may not be used for resale, reprinting, systematic distribution, emailing, or for any other commercial purpose without the permission of the publisher. | en_US |
| dc.rights | The following publication Sumbal, M.S., Amber, Q., Tariq, A., Raziq, M.M. and Tsui, E. (2024), "Wind of change: how ChatGPT and big data can reshape the knowledge management paradigm?", Industrial Management & Data Systems, Vol. 124 No. 9, pp. 2736-2757 is published by Emerald and is available at https://doi.org/10.1108/IMDS-06-2023-0360. | en_US |
| dc.subject | Big data | en_US |
| dc.subject | ChatGPT | en_US |
| dc.subject | Decision making | en_US |
| dc.subject | Explicit knowledge | en_US |
| dc.subject | Knowledge management | en_US |
| dc.subject | Tacit knowledge | en_US |
| dc.title | Wind of change : how ChatGPT and big data can reshape the knowledge management paradigm? | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 2736 | - |
| dc.identifier.epage | 2757 | - |
| dc.identifier.volume | 124 | - |
| dc.identifier.issue | 9 | - |
| dc.identifier.doi | 10.1108/IMDS-06-2023-0360 | - |
| dcterms.abstract | Purpose: The new disruption in the form of ChatGPT can be a valuable tool for organizations to enhance their knowledge management and decision-making capabilities. This article explores how ChatGPT can enhance organizations' KM capability for improved decision-making and identifies potential risks and opportunities. | - |
| dcterms.abstract | Design/methodology/approach: Using existing literature and a small-scale case study, we develop a conceptual framework for implementing artificial intelligence on the internal organizational knowledge base of big data and its integration with a larger knowledge base of ChatGPT. | - |
| dcterms.abstract | Findings: This viewpoint conceptualizes integrating knowledge management and ChatGPT for improved organizational decision-making. By facilitating efficient information retrieval, personalized learning, collaborative knowledge sharing, real-time decision support, and continuous improvement, ChatGPT can help organizations stay competitive and achieve business success. | - |
| dcterms.abstract | Research limitations/implications: This is one of the first studies on the integration of organizational knowledge management systems with ChatGPT. This research work proposes a conceptual model on integration of knowledge management with generative AI which can be further tested in actual work settings to check it's applicability and make further modifications. | - |
| dcterms.abstract | Practical implications: The study provided insights to managers and executives who, in collaboration with IT professionals, can devise a mechanism for integrating existing knowledge management systems in organizations with ChatGPT. | - |
| dcterms.abstract | Originality/value: This is one of the first studies exploring the linkage between ChatGPT and knowledge management for informed decision-making. | - |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Industrial management and data systems, 2024, v. 124, no. 9, p. 2736-2757 | - |
| dcterms.isPartOf | Industrial management and data systems | - |
| dcterms.issued | 2024 | - |
| dc.identifier.scopus | 2-s2.0-85200159733 | - |
| dc.identifier.eissn | 1758-5783 | - |
| dc.description.validate | 202503 bcch | - |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | a3431 | en_US |
| dc.identifier.SubFormID | 50124 | en_US |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | The Hong Kong Polytechnic University, Hong Kong under project ID: P0045771-UARL | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Sumbal_Wind_Change_How.pdf | Pre-Published version | 1.07 MB | Adobe PDF | View/Open |
Page views
17
Citations as of Apr 14, 2025
Downloads
12
Citations as of Apr 14, 2025
SCOPUSTM
Citations
16
Citations as of Dec 19, 2025
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.



