A Method for Human Resource Risk Management in Mobile Workforce Brokering Systems
Arash Mousavi1, Md. Jan Nordin1, Zulaiha Ali Othman1 & Riza Sulaiman1 Show affiliations
- School of Computer Science, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Malaysia
American Journal of Applied Sciences, Volume 8, Issue 12, pp. 1287–1294 · doi.org/10.3844/ajassp.2011.1287.1294
Abstract
Problem statement: Human Resource Risk Management is one of the crucial issues in Mobile Workforce Management Systems (MWM) in general, and in Mobile Workforce Brokering Systems (MWBS) in Particular. It is important because, if not properly managed, it will cause reduction in accuracy of the automated MWBS, which in turn necessitates more human involvement in the task allocation process. Thus, no reliable planning and scheduling schema can be made or achieved. Approach: However, a proven approach to tackle this problem is via contingency planning. In this study, we examined a specific type of HR risk called Unexpected Absence of mobile workforces in the context of an ontology-driven and multiagent-based MWBS. Our contingency plan that mainly consists of a statistical method is incorporated into the body of a coordination medium represented in OWL ontology format. Results: The proposed statistical method evaluates the past history and the current claims of an MW in order to find out a realistic plan for the next period of the system's run. Conclusion: Finally, via a case study we have illustrated that this method increases the accuracy and reliability of a periodical plan, made for MWBS in its initialization phase.
Licence and reuse
Free to read. This article carries the publisher’s copyright, as printed on it: © 2011 Science Publications. It is free to read; ask us before reusing it.
How to reuse this articleResponses (0)
About this article
Mousavi, A., Nordin, M. J., Othman, Z. A. & Sulaiman, R. (2011). A Method for Human Resource Risk Management in Mobile Workforce Brokering Systems. American Journal of Applied Sciences, 8(12), 1287–1294. https://doi.org/10.3844/ajassp.2011.1287.1294
- Licence
- © Science Publications
- Issue
- Volume 8, Issue 12
- Policies
- Editorial independenceUse of generative AIData availabilityAppeals and complaints
- Version
- Version of record
