Optimal quantity decision for an industrial buyer in a multistage dynamic bargaining model

• Main Authors: Dyogi, Marilou S., Lim, Jane Ann, Sy, Charina S.
• Format: text
• Language: English
• Published: Animo Repository 1997
• Subjects: Decision-making > Mathematical models; Dynamic programming; Stochastic processes; Costs, Industrial; Make-or-buy decisions; Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/6959
• Institution: De La Salle University

People in all walks of life need to deal with conflict and resolve issues on a continual basis. In any situation where there is an opportunity for agreement, the manner how one negotiates can make a difference coming to terms and not, or between an outcome that one finds favorable and one that is merely acceptable. Hence, in a buyer-seller system, there are good reasons why both parties should bargain. This study focuses on the development of a mathematical model for the use of the buyer in a buyer-seller system who is engaged in a dynamic bargaining process. The model would aid the buyer in coming up with a quantity decision at every stage of the bargaining process that would yield the least expected total cost. The bargaining activity is said to be a stochastic process since the behavior and strategies employed by the seller is not explicitly stated. That is why, the study made use of probability distributions to represent the uncertainty of demand, the bargaining time transpiring in each stage of the bargaining process, and also the responding attitude of the seller through price concessions. This study used dynamic programming in modeling the system due to the fact that what has transpired in the previous stage has a bearing on the next stage, and also to represent that as each offer and counteroffer by both parties go along, there will eventually be an optimal quantity to be chosen by the buyer. The primary objective of the mathematical model is to aid the buyer in computing for his total cost such that he can decide at which quantity to settle for, given the different price concessions by the seller. The solution procedure for the model developed was simulated due to the difficulty encountered in coming up with a conditional probability distribution function for concession given the order quantity of the buyer and the bargaining stage. A numerical example was used to validate the model. The results arrived at depicted that the termination time for the bargaining activity is greatly influenced by