Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10878-011-9424-0
Title: A new two-party bargaining mechanism
Authors: Gu, Y.H.
Goh, M. 
Chen, Q.L.
Souza, R.D.
Tang, G.C.
Keywords: Balance
Bargaining mechanism
Bargaining model
Bargaining solution set
Project
Issue Date: 2013
Source: Gu, Y.H., Goh, M., Chen, Q.L., Souza, R.D., Tang, G.C. (2013). A new two-party bargaining mechanism. Journal of Combinatorial Optimization 25 (1) : 135-163. ScholarBank@NUS Repository. https://doi.org/10.1007/s10878-011-9424-0
Abstract: If resources and facilities from different partners need to be engaged for a large-scale project with a huge number of tasks, any of which is indivisible, decision on the number of tasks assigned to any collaborating partner often requires a certain amount of coordination and bargaining among these partners so that the ultimate task allocation can be accepted by any partner in a business union for the project. In the current global financial crisis, such cases may appear frequently. In this paper, we first investigate the behavior of such a discrete bargaining model often faced by service-based organizations. In particular, we address the general situation of two partners, where the finite Pareto efficient (profit allocation) set does not possess any convenient assumption for deriving a bargaining solution, namely a final profit allocation (corresponding to a task assignment) acceptable to both partners. We show that it is not appropriate for our discrete bargaining model to offer the union only one profit allocation. Modifying the original optimization problem used to derive the Nash Bargaining Solution (NBS), we develop a bargaining mechanism and define a related bargaining solution set to fulfil one type of needs on balance between profit-earning efficiency and profit-earning fairness. We then show that our mechanism can also suit both Nash's original concave bargaining model and its continuous extension without the concavity of Pareto efficient frontier on profit allocation. © 2011 Springer Science+Business Media, LLC.
Source Title: Journal of Combinatorial Optimization
URI: http://scholarbank.nus.edu.sg/handle/10635/43984
ISSN: 13826905
DOI: 10.1007/s10878-011-9424-0
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