• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.145-153
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• 2014

In this paper, we study the bargaining strategy of a manufacturer who sells a product through the online and offline distribution channels. To do this, we derive and analyze the equilibrium solutions for both simultaneous and sequential bargaining games. The result shows that the optimal bargaining strategy heavily depends on the size of the online distribution channel's loyal customers and the difference between the retail prices of the online and the offline distribution channels. It is also shown that, in some cases, the online distribution channel has incentive to downsize its loyal customers and its retail price for a better bargaining outcome.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.31-39
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• 2015

In this paper, we study the bargaining strategy of a distributor who sells vertically differentiated, i.e. high and low brand products. We derive and analyze the equilibrium solutions for both simultaneous and sequential bargaining games among the distributor, the high brand product manufacturer and the low brand product manufacturer. The result shows that the optimal bargaining strategy for the distributor heavily depends on the relative quality and price level of the low brand product comparing to those of the high brand product. It is also shown that, for more bargaining profit, the distributor has strong motivation to prefer a low brand product which has lower quality level per unit price.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.172-179
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• 2006

Over the past few years, a considerable number of studies have been conducted on modeling the bargaining game using artificial agents on within-model interaction. However, very few attempts have been made at study on between-model interaction. This paper investigates the interaction and co-evolutionary process among heterogeneous artificial agents in the bargaining game. We present two kinds of the artificial agents participating in the bargaining game. They play some bargaining games with their strategies based on genetic algorithm (GA) and reinforcement learning (RL). We compare agents' performance between two agents under various conditions which are the changes of the parameters of artificial agents and the maximal number of round in the bargaining game. Finally, we discuss which agents show better performance and why the results are produced.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.80-87
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• 2015

The proliferation of the Internet and communication technologies and applications, besides the conventional retailers, has led to a new form of distribution channel, namely home sopping through the telephone, TV, catalog or the Internet. The conventional and new distribution channels have different transaction costs perceived by the consumers in the following perspectives: the accessibility to the product information, the traffic cost and the opportunity cost for the time to visit the store, the possibility of 'touch and feel' to test the quality of the product, the delivery time and the concern for the security for the personal information. Difference in the transaction costs between the distribution channels results in the different selling prices even for the same product. Moreover, distribution channels with different selling prices necessarily result in different business surpluses. In this paper, we study the multilateral bargaining strategy of a manufacturer who sells a product through multiple distribution channels with different transaction costs. We first derive the Nash equilibrium solutions for both simultaneous and sequential bargaining games. The numerical analyses for the Nash equilibrium solutions show that the optimal bargaining strategy of the manufacturer heavily depends not only on the degree of competition between the distribution channels but on the difference of the business surpluses of the distribution channels. First, it is shown that there can be four types of locally optimal bargaining strategies if we assume the market powers of the manufacturer over the distribution channels can be different. It is also shown that, among the four local optimal bargaining strategies, simultaneous bargaining with the distribution channels is the most preferred bargaining strategy for the manufacturer.

• Journal of Digital Convergence
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• v.14 no.8
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• pp.293-303
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• 2016

Analysis of bargaining games utilizing evolutionary computation in recent years has dealt with important issues in the field of game theory. In this paper, we investigated interaction and coevolution process among heterogeneous artificial agents using evolutionary computation in the bargaining game. We present three kinds of evolving-strategic agents participating in the bargaining games; genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE). The co-evolutionary processes among three kinds of artificial agents which are GA-agent, PSO-agent, and DE-agent are tested to observe which EC-agent shows the best performance in the bargaining game. The simulation results show that a PSO-agent is better than a GA-agent and a DE-agent, and that a GA-agent is better than a DE-agent with respect to co-evolution in bargaining game. In order to understand why a PSO-agent is the best among three kinds of artificial agents in the bargaining game, we observed the strategies of artificial agents after completion of game. The results indicated that the PSO-agent evolves in direction of the strategy to gain as much as possible at the risk of gaining no property upon failure of the transaction, while the GA-agent and the DE-agent evolve in direction of the strategy to accomplish the transaction regardless of the quantity.

• The KIPS Transactions:PartC
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• v.17C no.4
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• pp.385-390
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• 2010

Fair and efficient bandwidth allocation methods using the coalition game theory and the bargaining game theory following the axiomatic approach have been proposed when sending nodes with different traffic input rate try to share the bandwidth. These methods satisfy the axiomatic fairness provided by the mathematical ground of the game theories. However, since the axioms of the two game models are different from one another, the allocated bandwidths to each sending nodes become different even in the same communication environments. Thus, in this paper, we model the bandwidth allocation problem with these game theories, and quantitatively compare and analyze the allocated bandwidth and loss rate of each sending nodes in various communication environments. The results show that the bargaining game allocates relatively less bandwidth to a node with a higher sending rate than that with a lower sending rate while coalition game allocates bandwidth according to the sending rate of each node.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1006-1022
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• 2010

In this paper, a cross-layer resource allocation mechanism is proposed for wireless multimedia service. In particular, a game theory based on quality of service (QoS) for multimedia users is introduced to deal with the fairness of network resource allocation in wireless networks. Moreover, the channel states of wireless users are additionally regarded under the cross-layer design in WiMAX environment. In details, the bargaining solution is adopted to discover the efficient and fair resource allocation strategy for multimedia service in considering QoS in the peak signal-to-noise ratio (PSNR) and the channel states in the carrier-to-interface ratio (CINR). The proposed mechanism is illustrated and evaluated by simulation results of transmitting video sequences in WiMAX environment.

• Korea Trade Review
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• v.44 no.1
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• pp.31-44
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• 2019

This study examines the normalization of Korean GM management between the Korean government and GM in terms of external negotiation game and internal negotiation game using Putnam's Two-Level Games. In addition, GM's Win-set change and negotiation strategy were analyzed. This analysis suggested implications for the optimal negotiation strategy for mutual cooperation between multinational corporations and local governments in the global business environment. First, the negotiation strategy for Korea's normalization of GM management in Korea can be shifted to both the concession theory and the opposition theory depending on the situation change and the government policy centered on the cautious theory. Second, GM will maximize its bargaining power through 'brink-end tactics' by utilizing the fact that the labor market is stabilized, which is the biggest weakness of the Korean government, while maintaining a typical Win-set reduction strategy. GM will be able to restructure at any time in terms of global management strategy, and if the financial support of the Korean government is provided, it will maintain the local factory but withdraw the local plant at the moment of stopping the support. In negotiations on the normalization of GM management in Korea, it is necessary to prepare a problem and countermeasures for various scenarios and to maintain a balance so that the policy does not deviate to any one side.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.269-278
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• 2010

In the clustering protocol, lifetime of the cluster members radically decrease because frequency interference between clusters make every cluster member consume a lot of energy to maintain or increase its transmission rate. In this paper, we analyze the frequency interference among the clusters with the game theory which deals with resource bargaining problems between players, and present a rational power allocation strategy. Both the cases that each cluster tries to selfishly occupy and cooperatively share the resource are analyzed in terms of non-cooperative and cooperative games. In simulation, we compare the cooperative game with non-cooperative game in terms of the node lifetime.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.4
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• pp.400-406
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• 2014

In this paper, we propose an approach to minimizing total power consumption by deploying multiple clean-up robots simultaneously in a given area. For this, we propose to use the cooperative game theoretic approaches (i.e., Nash bargaining solution (NBS)) such that the robots can optimally and fairly negotiate the area division based on available resources and characteristics of the area, thereby leading to the minimum total power consumption. We define a utility function that includes power consumptions for characteristics of areas and the robots can agree on a utility pair based on the NBS. Simulation results show that the proposed approach can reduce the total average power consumption by 15-30% compared to a random area division approach.