A method for Human Resource Risk Management in Mobile Workforce Brokering Systems

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2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1287-1294
Number of pages8
JournalAmerican Journal of Applied Sciences
Volume8
Issue number12
DOIs
Publication statusPublished - 2011

Fingerprint

Risk management
Ontology
Statistical methods
Personnel
Planning
Scheduling

Keywords

  • Human Resource (HR)
  • Mobile Workforce Brokering System (MWBS)
  • Mobile Workforce Brokering Systems (MWBS)
  • Mobile Workforces (MW)
  • Processes performed
  • Task Allocation Agent (TAA)

ASJC Scopus subject areas

  • General

Cite this

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title = "A method for Human Resource Risk Management in Mobile Workforce Brokering Systems",
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.",
keywords = "Human Resource (HR), Mobile Workforce Brokering System (MWBS), Mobile Workforce Brokering Systems (MWBS), Mobile Workforces (MW), Processes performed, Task Allocation Agent (TAA)",
author = "Arash Mousavi and Nordin, {Md. Jan} and {Ali Othman}, Zulaiha and Riza Sulaiman",
year = "2011",
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AU - Nordin, Md. Jan

AU - Ali Othman, Zulaiha

AU - Sulaiman, Riza

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AB - 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.

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