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A win–win method for multi‐party negotiation support
Author(s) -
Kuula Markku,
Stam Antonie
Publication year - 2008
Publication title -
international transactions in operational research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.032
H-Index - 52
eISSN - 1475-3995
pISSN - 0969-6016
DOI - 10.1111/j.1475-3995.2008.00641.x
Subject(s) - negotiation , pareto principle , stalemate , preference , computer science , process (computing) , complete information , order (exchange) , win win game , point (geometry) , microeconomics , operations research , economics , political science , law , politics , operations management , mathematics , geometry , finance , operating system
In this paper, we introduce an interactive multi‐party negotiation support method for decision problems that involve multiple, conflicting linear criteria and linear constraints. Most previous methods for this type of problem have relied on decision alternatives located on the Pareto frontier; in other words, during the negotiation process the parties are presented with new Pareto optimal solutions, requiring the parties to sacrifice the achievement of some criteria in order to secure improvements with respect to other criteria. Such a process may be vulnerable to stalemate situations where none of the parties is willing to move to a potentially better solution, e.g., because they perceive – rightly or wrongly − that they have to give up more than their fair share. Our method relies on “win–win” scenarios in which each party will be presented with “better” solutions at each stage of the negotiations. Each party starts the negotiation process at some inferior initial solution, for instance the best starting point that can be achieved without negotiation with the other parties, such as BATNA (best alternative to a negotiated agreement). In subsequent iterations, the process gravitates closer to the Pareto frontier by suggesting an improved solution to each party, based on the preference information (e.g., aspiration levels) provided by all parties at the previous iteration. The preference information that each party needs to provide is limited to aspiration levels for the objectives, and a party's revealed preference information is not shared with the opposing parties. Therefore, our method may represent a more natural negotiation environment than previous methods that rely on tradeoffs and sacrifice, and provides a positive decision support framework in which each party may be more comfortable with, and more readily accept, the proposed compromise solution. The current paper focuses on the concept, the algorithmic development, and uses an example to illustrate the nature and capabilities of our method. In a subsequent paper, we will use experiments with real users to explore issues such as whether our proposed “win–win” method tends to result in better decisions or just better negotiations, or both; and how users will react in practice to using an inferior starting point in the negotiations.