An ontology based multi-agent system to support HABIO outsourcing framework
SHARP, Bernadette and ATKINS, Anthony and KOTHARI, H. (2011) An ontology based multi-agent system to support HABIO outsourcing framework. Expert Systems with Applications, 38 (6). pp. 6949-6956. ISSN 09574174Full text not available from this repository.
Abstract or description
In recent years the widespread application of outsourcing to help improve finance and maintain competitiveness is growing rapidly, and has been accompanied by a growth of academic research in this field. Most of the outsourcing literature has focused primarily on the social and cultural impacts, the organisational and management perspectives of outsourcing and very few tools have been developed to assist managers in making outsourcing decisions. Incorrect decision-making in outsourcing can lead to devastating consequences for their business. To guide decision makers in managing the complexity of outsourcing a holistic approach to outsourcing has been developed by taking business, information and organisational perspectives (HABIO). The purpose of this paper is to demonstrate how HABIO can be applied to help managers evaluate the impact of their decision-making by providing them with a set of ‘what-if’ scenarios, which are enacted by intelligent agents. The case example, discussed in this paper, demonstrates that HABIO can be applied effectively using a multi-agent system to analyse the outsourcing decision for a call centre sector in the retail industry. A prototype of the multi-agent system is presented where intelligent agents are endowed with specific domain ontologies, appropriate to solve a specific problem, and with a reasoning mechanism to achieve specific goals and to collaborate together to produce a set of “what-if scenarios” to the outsourcing managers.
|Subjects:||G400 Computer Science|
|Faculty:||Faculty of Computing, Engineering and Sciences > Computing|
|Depositing User:||Bernadette SHARP|
|Date Deposited:||30 Apr 2013 12:21|
|Last Modified:||30 Apr 2013 12:21|
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