In any negotiation process, there are always constraints involved and decision making process involves an analysis of the gains and tradeoffs one has to go through to reach the best optimal solution.
Decision making process is not just a psychological process as perceived by many but more of a game theory because both the bidder and the negotiator are faced by various constraints, which both have to develop a model with both constraints and targets and later iterate to obtain an optimum solution.
Here, again, BATNA (best alternative to a negotiated agreement) comes into play; both parties must go for a sacrifice. None gets exactly what he wants but goes for a better alternative. The opportunity cost of leaving the job must be lower than the cost of taking it in order for the candidate to stop negotiating.
Although negotiation in most cases is ubiquitous, research has suggested that negotiation behavior is usually far from optimal. While negotiators often feel they have successfully "negotiated" with other parties, research has demonstrated that untrained negotiators are not good at getting the best agreement, even when obliged to do so. Movement towards an optimal solution is consequential since it may end up with additional gains to either party involved in negotiating terms. Research here has shown how to improve negotiators in these tasks, though it has not demonstrated how to best get these negotiators to task.
In this case, negotiation is viewed neither strictly as a computational formalism nor as a mathematical game, but as a problem solving task. Therefore, when negotiators engage in such a game, they in fact, are relying on the normal problem solving apparatus for cognitive tasks. Two negotiators together attempt to obtain a solution to which both parties stand to benefit. The task of negotiation described below involves two parties (a dyad; in this case and throughout the model description I will take the place of the dyad and negotiator one and negotiator two will, therefore, be the prospective employer) having a challenge of reaching a common consensus (e.g. how to make a better earning). Reaching a compromise requires multiple issues be decided (e.g. opportunity cost, fare/transportation, cost of leaving and previous earning, level of competency and training), each of which has several alternatives (e.g., profession; accounts, human resource; transportation; car, bus, taxicab, level of education; diploma, bachelors, masters). The values for each of the alternatives to every party are well-defined preference-equivalents proposed to each negotiator as "points," though never shared between them. The negotiators both have opposing preferences for issue alternatives (e.g., bus versus personal car) and consider part of the concerns differentially significant to the ultimate decision expectation (e.g., the first negotiator is very concerned about the location and returns from the chosen job than the means of transport available; whereas Negotiator 2 is seriously concerned about the cost of hiring/salary and level of education experience). Differential significance assigned to the issues allows for tradeoffs and ranks of preferences as a means to improving value for the two parties. Mutually beneficial tradeoffs take precedence when issues of differential significance are exchanged such that both parties concede grounds on less important issue in order to gain value on relevant issues. Chances for potentially improving value in the case of both parties’ turns into a non-zero sum game.
With the objective to the attainment goal, negotiators here are motivated to maximize their utility subject to constraints, which is accomplished through orienting instructions (e.g., "maximize the points earned in the negotiated solution") and the rewards (e.g., "payment will be based on the points earned in the negotiated solution."). As a consequence, the attainment goals, and the operators generating outcomes that tend to move towards the goal, have an influence on the search for solutions. However, this agreement goal may alter the search for solutions that occur within the fundamental problem space. More specifically, as solutions tend to unfold, they must incorporate the aspects of search by the other parties--the duo mutually inform and also constrain one another.
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