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Automated game approach to wage negotiation and decision problems

Oderanti, F.O., De Wilde, Philippe (2011) Automated game approach to wage negotiation and decision problems. In: Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS. 2011 Annual Meeting of the North American Fuzzy Information Processing Society. . IEEE, El Paso, TX ISBN 978-1-61284-967-6. (doi:10.1109/NAFIPS.2011.5752015) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:58018)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://doi.org/10.1109/NAFIPS.2011.5752015

Abstract

We proposed a profit sharing strategic game approach to wage negotiation and decision problems in business organisations. In the scheme, both the employer and the union choose their strategies and the game is played in five rounds. We refer to our model as automated game approach to wage negotiation and decision problems (AGAW). Our method proposes profit (positive or negative) sharing sequential game approach in modeling wage increase decisions within a firm in a competitive industry and this game is played between the firm's management and the union. The proposed approach is illustrated with a case study. The procedure and methodology proposed in this research may be easily implemented by business organisations in their wage bargaining and decision processes.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/NAFIPS.2011.5752015
Uncontrolled keywords: bargaining; business games; decision; employees; employers; salary; zero sum, Data processing; Decision theory; Game theory; Information dissemination; Profitability, Wages
Subjects: Q Science
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Philippe De Wilde
Date Deposited: 19 Dec 2022 16:32 UTC
Last Modified: 05 Nov 2024 10:49 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58018 (The current URI for this page, for reference purposes)

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