Alsharhan, AM, Salloum, S ORCID: https://orcid.org/0000-0002-6073-3981 and Shaalan, K
ORCID: https://orcid.org/0000-0003-0823-8390
2022,
Implementing a talent management system in a group of companies - a case study from UAE
, in: International Conference on Emerging Technologies and Intelligent Systems (ICETIS 2021), 5th-6th April 2021, Online.
Abstract
This case study aims to examine the status quo of an information system in the context of talent management (TM), in a leading group of companies that is under the ports and industrial lands sector in the United Arab Emirates. This study identified the major issues encountered by the target organization from the perspective of the employee. It also analyzed prominent state-of-the-art tools that can solve issues related to TM in the targeted organization, and proposed recommended solutions on a TM system implementation. The data obtained was mainly collected using open-ended interviews with the group employees, as well as qualitative information collection by the researcher through participant observation of mergers and acquisitions in the group. In addition, information from previous studies was also leveraged to formulate the case. The findings indicate that the major issues related to TM include career development plan, learning management system, succession plan, data island, and mobile-first. The study concluded that although it might be easier for the organization to extend their current solution to cover TM, a system such as “BambooHR” and “Ceridian Dayforce” may be worth considering to solve the current organizational TM issues. The outcomes of this case study shed light on the current TM challenges faced by a group of companies during mergers and acquisitions, and offer an essential case study for researchers in TM, HR, information systems and knowledge management.
Item Type: | Conference or Workshop Item (Paper) |
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Schools: | Schools > School of Computing, Science and Engineering |
Journal or Publication Title: | Proceedings of International Conference on Emerging Technologies and Intelligent Systems |
Publisher: | Springer |
Series Name: | Lecture Notes in Networks and Systems |
ISBN: | 9783030859893 (softcover); 9783030859909 (ebook) |
ISSN: | 2367-3370 |
Related URLs: | |
Depositing User: | USIR Admin |
Date Deposited: | 04 Mar 2022 11:22 |
Last Modified: | 04 Mar 2022 11:25 |
URI: | http://usir.salford.ac.uk/id/eprint/63311 |
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