• Journal of Labour Economics
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• v.24 no.2
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• pp.197-225
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• 2001

Bargaining theory with asymmetric information is widely accepted to explain labor disputes. Even though it secures theoretical consistency, it needs to be supplemented to explain disputes and negotiation more accurately. This paper shows that it may be assisted by bargaining theories based on the economics of psychology as well as theories on bargaining practices which are popular in other academic fields. The former suggests the occurrence of asymmetric information is related with the perception of the players of bargaining. The latter does they do not exchange offers as the typical theory of bargaining with asymmetric information assumes. When the latter is applied to explain the labor disputes of the public sector, it explains clearly their features and the differences from those of the private sector.

• Korea Trade Review
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• v.44 no.3
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• pp.105-121
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• 2019

This study applies diverse game theories to the US-China Trade War. The US-China Trade War can be analyzed as a game situation because the strategic decision-making process to maximize one's profit while considering the reaction of the other party is a game situation. However, related research suffered from some mistakes in applying the US-China Trade War as it is to classic game theory, because while the prisoners dilemma is based on the situation of No Communication, No Trust, No Cooperation, the US-China Trade War has a precondition different from that of prisoners dilemma, since it mutually communicates information and negotiation is repeated several times in a cooperative situation. The result of the trade negotiation will likely end as 'cooperate-cooperate'. Further, considering trade volume, trade interdependence, bargaining power based on economy, and the scale of damage caused by the Trade War, the US-China Trade War is progressing with the bargaining power of the US being higher than that of China. Since the current US-China Trade War is in an asymmetrical situation under the dominant bargaining power of the US, it is likely to reach 'US defect-China cooperative' in the long run.

• The KIPS Transactions:PartC
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• v.18C no.2
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• pp.97-102
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• 2011

Since the game theory provides a theoretical ground to distribute a shared resource between demanding users in a fair and efficient manner, it has been used for the bandwidth allocation problem in a network. However, the bandwidth allocation schemes with different game theory assign different amount of bandwidth in the same operational environments. However, only the mathematical framework is adopted when a bandwidth allocation scheme is devised without quantitatively comparing the results when they applied to the bandwidth allocation problem. Thus, in this paper, we compare the characteristics of the bandwidth allocation schemes using the bankrupt game theory and the bargaining game theory when they applied to the situation where nodes are competing for the bandwidth in a network. Based on the numerical results, we suggest the future research direction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1683-1689
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• 2013

Applying Markov Stochastic Process theory, this paper attempts to suggest a tentative model explaining how private information may cause bargaining delay. It is shown that the bargaining delay is critically dependent on the specification of information. It turns out that the delay tends to be longer in bargaining where information is imperfect. This means that bargaining models frequently can have an infinite delay under imperfect information while they have finite delay of bargaining before reaching the agreements if information is perfect. Other interesting result is that bargaining delay may depend on who makes the offer first. And it is also shown that bargaining tends to end earlier if both players (seller and buyer) can make offers in turn than the case where only one side make a offer.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.209-222
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• 1997

In this paper, we study a bargaining order problem where one buyer sequentially bargains with two sellers whose reservation prices are unknown to the buyer but correlated. Our main question is who the buyer should bargain first with to maximize his expected payoff. This type of problem is widely applicable to business and political situations where one party negotiates with multiple parties sequentially. One of the most important element in a sequential bargaining is "linkage effect" which exists when the aggreement of the previous bargaining affects the outcome of the following bargaining. To examine "linkage effect", we assume that the sellers'objects are similar so that the sellers' reservation prices are correlated. In addition, to consider incomplete information aspect regarding reservation prices, it is assumed that the sellers' reservation prices are unknown to the buyer. That is, we deal with one sided incomplete information case. In our model, there are two stages in each of which the buyer meets one seller. Since we are concerned with the bargaining order, we consider two different bargaining orders. Using game theory, we find a perfect Bayesian equilibrium and compute the buyer's expected payoff for each bargaining order. Finally we identify the advantageous bargaining order for the buyer by comparing the expected payoffs obtained under two different bargaining orders. Our results are as follows: the advantageous bargaining order depends on the prior probability of the seller type. However, in general, the buyer should bargain first with the seller whose object is less valuable to the buyer. The basic reason for our result is that the buyer wants to experiment in the first stage to find out the sellers' reservation prices and in doing so, to minimize the experimental cost and maximize potential gain in case of negotiation failure in the first stage. in the first stage.

• ETRI Journal
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• v.33 no.6
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• pp.957-960
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• 2011

We present a fair and efficient solution for selfish readers with the Nash bargaining solution (NBS) to mitigate the effects of RFID frequency interference. We compare the NBS with a solution derived by the max log-sum scheme that maximizes total utility and show that for selfish and rational readers, the NBS brings success in bargaining on resource allocation between readers unlike the max log-sum scheme, although the NBS has less total payoff compared to the max log-sum scheme.

• Information and Communications Magazine
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• v.26 no.7
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• pp.24-29
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• 2009

협동적 게임 이론(cooperative game theory)은 다중 사용자들이 어떻게 하면 한정된 자원을 효율적이고 공평하게 공유할 수 있는지에 촛점을 맞추며 이론적인 바탕을 제공한다. 본고에서는 다수의 멀티미디어 사용자들이 협동적 게임 이론중 협상 해법(bargaining solutions)을 이용하여 어떻게 통신 및 네트워크 자원을 효율적이고 공평하게 공유할 수 있는지 알아본다. 또한, 이러한 협상 해법들을 바탕으로 한 자원 공유가 멀티미디어 사용자에게 어떠한 의미를 갖는지 알아보도록 한다. 마지막으로, 이러한 게임 이론을 이용한 자원 관리가 다양한 형태의 통신 및 네트워크에 어떻게 사용될 수 있으며, 미래의 활용 가능성을 알아보도록 한다.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.93-100
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• 2021

The Ethereum shard system for solving the scalability problem of the blockchain has a load balancing issue, which is modeled as a graph partitioning problem. In this paper, we propose an adaptive online weighted graph partitioning algorithm that can negotiate between two utility of the shard system using the game theory's bargaining solution. The bargaining solution is an axiomatic solution that can fairly determine the points of conflict of utility. The proposed algorithm was improved to apply the existing online graph partitioning algorithm to the weighted graph, and load balancing was performed efficiently through the design considering the situation of the sharding system using the extension of Nash bargaining solution, which is extended to apply solution to non-convex feasible set of bargaining problem. As a result of the experiment, it showed up to 37% better performance than typical load balancing algorithm of shard system.

• The Journal of the Korea Contents Association
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• v.14 no.11
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• pp.549-557
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• 2014

Recently, analysis of bargaining game using evolutionary computation is essential issues in field of game theory. In this paper, we observe a bargaining game using co-evolution between two heterogenous artificial agents. In oder to model two artificial agents, we use a particle swarm optimization and a differential evolution. We investigate algorithm parameters for the best performance and observe that which strategy is better in the bargaining game under the co-evolution between two heterogenous artificial agents. Experimental simulation results show that particle swarm optimization outperforms differential evolution in the bargaining game.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.228-229
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• 2016

Bargaining power or negotiation power departing from negotiators' economical beneficial point of view has long been an important research subject in a number of industries, and it has been widely studied by focusing on the various kinds of game theory. Although existing papers are mainly based on the strategies and results of bargaining process, ${\cdots}$(중략)${\cdots}$.