转让定价视角下的我国企业对外投资战略博弈

我国企业通过对外投资可以拥有在分处国内外的两个实体间开展转让定价的机会,以此来对抗跨国公司在华通过转让定价谋求战略竞争优势,获取公平竞争机会.以单市场双寡头古诺竞争下的转让定价决策模型为基础,构建了我国企业对外投资后在国内和国外两个市场与跨国公司进行战略性转让定价博弈模型,发现无论我国企业与跨国公司相比是否具有成本优势,都应该通过对外投资获取开展战略性转让定价机会,与跨国公司进行公平竞争.     

基于Bertrand模型的企业广告投放策略研究

广告投入水平是企业进行广告竞争战略中的重要决策环节,只有合理的广告投入才能够为企业带来利润的增长.广告投入又分为广告的制作投入和播放投入两部分,因此企业在广告竞争中面临着如何选择最佳的投入策略问题.基于此,构建了生产同一种商品的2家企业,在完全信息静态条件下,广告投放策略选择的博弈模型,并求出其均衡解.通过对相关参数赋值进行模拟分析,分别求出博弈参与双方在广告内容制作投入和广告播放频率投入两方面进行策略选择时的收益矩阵,进而找出企业应对竞争对手广告投放策略发生变化时的最优策略向量,减少广告投入浪费;分析结果还表明企业对产品的广告投放选择策略组合时获得的产品利润高于选择单一策略的利润情况.     

Share functions for cooperative games with levels structure of cooperation

In a standard TU-game it is assumed that every subset of the player set N can form a coalition and earn its worth. One of the first models where restrictions in cooperation are considered is the one of games with coalition structure of Aumann and Drèze (1974). They assumed that the player set is partitioned into unions and that players can only cooperate within their own union. Owen (1977) introduced a value for games with coalition structure under the assumption that also the unions can cooperate among them. Winter (1989) extended this value to games with levels structure of cooperation, which consists of a game and a finite sequence of partitions defined on the player set, each of them being coarser than the previous one.     

Absolute optimal solution for a compact and convex game

This paper investigates the existence of absolute optimal solutions for a partition P in continuous and quasiconcave games. We show that the P-consistency property introduced in the paper, together with the quasiconcavity and continuity of payoffs, permits the existence of P-absolute optimal solutions in games with compact and convex strategy spaces. The P-consistency property is a general condition that cannot be dispensed with for the existence of P-absolute optimal solutions. We also characterize the existence of P-absolute optimal solutions by providing necessary and sufficient conditions. Moreover, we suggest an algorithm for efficiently computing P-absolute optimal solutions.     

Optimal selection of retailers for a manufacturing vendor in a vendor managed inventory system

A Vendor Managed Inventory (VMI) system consists of a manufacturing vendor and a number of retailers. In such a system, it is essential for the vendor to optimally determine retailer selection and other related decisions, such as the product’s replenishment cycle time and the wholesale price, in order to maximize his profit. Meanwhile, each retailer’s decisions on her willingness to enter the system and retail price are simultaneously considered in the retailer selection process. However, the above interactive decision making is complex and the available studies on interactive retailer selection are scarce. In this study, we formulate the retailer selection problem as a Stackelberg game model to help the manufacturer, as a vendor, optimally select his retailers to form a VMI system. This model is non-linear, mixed-integer, game-theoretic, and analytically intractable. Therefore, we further develop a hybrid algorithm for effectively and efficiently solving the developed model. The hybrid algorithm combines dynamic programming (DP), genetic algorithm (GA) and analytical methods. As demonstrated by our numerical studies, the optimal retailer selection can increase the manufacturer’s profit by up to 90% and the selected retailers’ profits significantly compared to non-selection strategy. The proposed hybrid algorithm can solve the model within a minute for a problem with 100 candidate retailers, whereas a pure GA has to take more than 1 h to solve a small sized problem of 20 candidate retailers achieving an objective value no worse than that obtained by the hybrid algorithm.     

Non-cooperative joint replenishment under asymmetric information

We consider jointly replenishing n ex-ante identical firms that operate under an EOQ like setting using a non-cooperative game under asymmetric information. In this game, each firm, upon being privately informed about its demand rate (or inventory cost rate), submits a private contribution to an intermediary that specifies how much it is willing to pay for its replenishment per unit of time and the intermediary determines the maximum feasible frequency for the joint orders that would finance the fixed replenishment cost. We show that a Bayesian Nash equilibrium exists and characterize the equilibrium in this game. We also show that the contributions are monotone increasing in each firm’s type. We finally conduct a numerical study to compare the equilibrium to solutions obtained under independent and cooperative ordering, and under full information. The results show that while information asymmetry eliminates free-riding in the contributions game, the resulting aggregate contributions are not as high as under full information, leading to higher aggregate costs.     

Variational Inequalities for Combined Control and Stopping Game

Abstract

We study a nonlinear elliptic variational inequality associated with the combined stochastic control problem. By using the dynamic programming principle and the method of penalization, we establish the existence of a unique viscosity solution of the variational inequality and describe it as the value function of the corresponding combined stochastic game problem.     

Partially Observable Semi-Markov Games with Discounted Payoff

Abstract

We study partially observable semi-Markov game with discounted payoff on a Borel state space. We study both zero sum and nonzero sum games. We establish saddle point equilibrium and Nash equilibrium for zero sum and nonzero sum cases, respectively.     

Nonlinear modeling and performance analysis of a closed-loop supply chain in the presence of stochastic noise

ABSTRACT

We study four-echelon supply chains consisting of manufacturer, wholesaler, retailer and customer with recovery center as hybrid recycling channels. In order to gain a larger market share, the retailer often takes the sales as a decision-making variable. For this purpose, in this supply chain, the retailer limits the forecast of market demand in future periods with expected logic. It also manages demand by leveraging prices and choosing market. In this paper, first, we investigate the state-space model of this supply chain system and examine the effect of complex dynamic and stochastic noise on the bullwhip effect. We analytically prove that this factor leads to the bullwhip effect. So, first, we filtered the information between nodes with extended Kalman filter after which we regulated the destructive effects of the bullwhip phenomenon by designing a non-linear quadratic Gaussian optimal controller. Eventually, the simulation results indicate the efficiency of the proposed method.     

变时延移动Ad-Hoc网络容量非合作规划博弈模型的渐近稳定性

移动Ad-Hoc网络容量的稳定性是保证其服务质量的关键性质之一.本文提出一种新颖的考虑时变传播时延的非合作规划博弈移动Ad-Hoc网络容量分析模型稳定性控制技术.首先求得加入时变传播时延项的非合作规划博弈移动Ad-Hoc网络容量分析模型的源节点发送流量速率演化方程组—–一类非线性时变时滞微分方程组,在此基础上采用描述器技术结合线性矩阵不等式技术得到该模型的渐进稳定性准则,并设计了模型稳定性控制的迭代算法.由于是基于等价模型变换,所提出的渐近稳定性判别准则具有较小的保守性.仿真实验验证了本算法的有效性.本建模与分析方法虽以具体的非合作规划博弈移动Ad-Hoc网络容量分析模型为例,但其可以应用于一般的移动Ad-Hoc网络容量稳定性控制问题.