不同渠道权力结构下的双渠道闭环供应链定价与协调决策

在双渠道环境下,针对不同渠道权力结构对闭环供应链最优决策的影响情况,构建了三种分散化(制造商主导的Stackelberg博弈、零售商主导的Stackelberg博弈以及由制造商和零售商构成的Nash均衡博弈)和一种集中化的闭环供应链决策模型,并得出了相关的均衡策略。在此基础上进一步有针对性的设计了两种契约相结合的契约机制协调供应链,并利用数值算例分析验证所得结论以及契约机制的有效性与可实践性,同时分析模型中的一些重要参数如渠道替代系数、传统渠道所占市场份额、废旧产品回收率、再制造成本节约等对双渠道供应链各项最优决策及渠道利润的影响。     

Complexity analysis of dynamic noncooperative game models for closed-loop supply chain with product recovery

In this paper, we consider a closed-loop supply chain (CLSC) with product recovery, which is composed of one manufacturer and one retailer. The retailer is in charge of recollecting and the manufacturer is responsible for product recovery. The system can be regarded as a coupling dynamics of the forward and reverse supply chain. Under different decision criteria, two noncooperative game models: Stackelberg game model and peer-to-peer game model are developed. The dynamic phenomena, such as the bifurcation, chaos and sensitivity to initial values are analyzed through bifurcation diagrams and the largest Lyapunov exponent (LLE). The influences of decision parameters on the complex nonlinear dynamics behaviors of the two models are further analyzed by comparing parameter basin plots, and the results show that with the improvement of retailer’s competitive position, the CLSC system will be more easier to enter into chaos.     

基于风险厌恶零售商的双渠道闭环供应链运作策略

在对称信息框架下,针对零售商存在风险厌恶特性的双渠道闭环供应链,基于Stackelberg博弈理论探讨了不同的回收再制造模式下(制造商不回收再制造、制造商独立回收再制造、制造商依托零售商回收再制造)供应链各主体的运作决策。研究发现,在不同回收再制造模式下,制造商与风险厌恶的零售商合作能够获得更多收益。市场波动的增大对供应链各主体并非始终是有害的,随着市场波动的增大,带有风险厌恶的零售商收益不断减小,而风险中性的双渠道制造商收益逐步增大,零售商风险厌恶特性为制造商带来了更多的收益。制造商独立回收再制造以及通过零售商进行回收再制造时,双渠道产品定价均低于不进行任何回收再制造模式下的定价,双渠道需求和利润均高于不进行任何回收再制造模式下的渠道需求和利润,即回收再制造模式不仅为下游顾客带来了更多的消费实惠,同时也为供应链各主体带来了更多的收益。     

考虑政府约束的再制造闭环供应链差别定价博弈模型

本文考虑政府对废弃产品回收的奖惩约束措施,针对一类由制造商、零售商构成的再制造闭环供应链系统,基于博弈论方法研究了新产品和再制造品存在定价差别时集中决策和分散决策模式下的定价策略,得出了闭环供应链成员的最优定价策略和利润,并分析了政府约束措施对闭环供应链运作的影响。研究表明:集中决策下供应链效率高于Stackelberg博弈分散决策,为此设计了一个收益共享协调定价契约实现了闭环供应链的协调,进而分析了政府回收约束情况下再制造过程利润超过制造过程的再制造优先条件。算例分析验证了定价策略及协调机制的有效性。     

消费者非均匀偏好条件下高校项目开发策略

为了探究教育项目消费者随机需求条件下的不同层次高校的竞优策略, 运用Stackelberg博弈方法, 构建了消费者偏好服从非均匀分布的不同层次高校开发同类教育项目的定位设计模型, 分析了消费者偏好行为对教育项目收益的影响规律以及双方的竞优策略。结果显示, H型高校(声誉较高)不受消费者偏好等市场因素影响, 始终选择最大差异化策略。L型高校(声誉较低)在消费者无差异偏好偏向自己一方时也不受市场因素影响采取最大差异化策略; 而在消费者无差异偏好偏向它方时, 若市场需求概率小于0.5则选择最大差异化策略, 否则其决策将受到自身初始位值、市场概率等因素的综合影响, 并适时选择最大差异化、有限差异化或有限趋同化策略。     

动态 Stackelberg 诱导对策问题

Stackelberg 诱导(Incentive)对策,以简单的二人对策来说,是讨论对一个具有递阶决策结构的系统,处于领导地位的决策者,如何通过选择和宣布适当的策略,来诱导处于随从地位的决策者采取对领导最为有利行动的问题.自从文[1]从控制理论的观点讨论了 Incentive 的概念后,Stackelberg 诱导对策的研究受到了较多的关注,发现了不少研究成果.然而从到迄今所出现的文献来看,对概念性问题的研究较多,而较缺乏有效的,特     

Backward induction algorithm for a class of closed-loop Stackelberg games

In the paper a new deterministic continuum-strategy two-player discrete-time dynamic Stackelberg game is proposed with fixed finite time duration and closed-loop information structure. The considered payoff functions can be widely used in different applications (mainly in conflicts of consuming a limited resource, where one player, called leader, is a superior authority choosing strategy first, and another player, called follower, chooses after).     

政府奖惩机制下零售商主导的闭环供应链微分博弈策略

本文在考虑政府奖惩机制下,研究零售商主导的闭环供应链中成员的动态均衡策略,其中制造商负责回收再制造,回收率随时间动态变化。分别构建了三种模式下的Stackelberg微分博弈模型:政府不对制造商和零售商实施奖惩机制、政府只对制造商实施奖惩机制以及政府同时对制造商和零售商实施奖惩机制。运用贝尔曼连续型动态规划理论,求解了三种模式下制造商和零售商的决策均衡结果并进行了对比分析,从消费者剩余价值和成员利润的视角证明了政府实施奖惩机制的有效性。最后通过算例对成员均衡策略进行了稳态分析和非稳态分析。研究结果表明:政府的奖惩机制能够正确引导闭环供应链成员做出最优决策,有利于减缓分散决策所带来的双重边际效应,提高消费者剩余价值。零售商分担回收责任会削减政府对制造商回收的激励作用,降低闭环供应链整体利润。相比之下,政府只对制造商实施奖惩机制是最优模式选择,可以同时提高经济和环保双重效益。     

Stackelberg equilibria in managerial delegation games

Managerial compensation packages do not only influence managers’ behavior, but also have an impact on competing firms. In a managerial delegation game investigating the latter aspect, it is shown that the inherent prisoner’s dilemma situation can be resolved (without changing the normally studied setup or timing). In the first stage, owners choose an incentive function for their managers, in the second stage they choose the weights assigned to that function besides profits and in the third stage managers play a Cournot game. Solving this continuous optimization problem with the implicit function theorem shows that choosing an incentive from the set of “multiplicative incentives”, i.e. any generalized affine transformation of the product of both firms’ quantities, which includes e.g. relative profit, ensures that the Stackelberg outcome is among the set of equilibrium outcomes. Furthermore, it is the unique outcome if the rival owner opts for one of the well-known incentives like sales, revenue or market share. The general approach used allows demonstrating that with no other linear incentive a Stackelberg outcome results and that incentives like profit-to-cost ratio should be avoided. Selecting a multiplicative incentive is a dominant strategy of the game.     

Controlled predatory pricing in a multiperiod Stackelberg game: an MPEC approach

We analyze a multiperiod oligopolistic market where each period is a Stackelberg game between a leader firm and multiple follower firms. The leader chooses his production level first, taking into account the reaction of the followers. Then, the follower firms decide their production levels after observing the leader’s decision. The difference between the proposed model and other models discussed in literature is that the leader firm has the power to force the follower firms out of business by preventing them from achieving a target sales level in a given time period. The leader firm has an incentive to lower the market prices possibly lower than the Stackelberg equilibrium in order to push the followers to sell less and eventually go out of business. Intentionally lowering the market prices to force competitors to fail is known as predatory pricing, and is illegal under antitrust laws since it negatively affects consumer welfare. In this work, we show that there exists a predatory pricing strategy where the market price is above the average cost and consumer welfare is preserved. We develop a mixed integer nonlinear problem (MINLP) that models the multiperiod Stackelberg game. The MINLP problem is transformed to a mixed integer linear problem (MILP) by using binary variables and piecewise linearization. A cutting plane algorithm is used to solve the resulting MILP. The results show that firms can engage in predatory pricing even if the average market price is forced to remain higher than the average cost. Furthermore, we show that in order to protect the consumers, antitrust laws can control predatory pricing by setting rules on consumer welfare.     

Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks

Achievement of the herd immunity is essential for preventing the periodic spreading of an infectious disease such as the flu. If vaccination is voluntary, as vaccination coverage approaches the critical level required for herd immunity, there is less incentive for individuals to be vaccinated; this results in an increase in the number of so-called “free-riders” who craftily avoid infection via the herd immunity and avoid paying any cost. We use a framework originating in evolutionary game theory to investigate this type of social dilemma with respect to epidemiology and the decision of whether to be vaccinated. For each individual in a population, the decision on vaccination is associated with how one assesses the risk of infection. In this study, we propose a new risk-assessment model in a vaccination game when an individual updates her strategy, she compares her own payoff to a net payoff obtained by averaging a collective payoff over individuals who adopt the same strategy as that of a randomly selected neighbor. In previous studies of vaccination games, when an individual updates her strategy, she typically compares her payoff to the payoff of a randomly selected neighbor, indicating that the risk for changing her strategy is largely based on the behavior of one other individual, i.e., this is an individual-based risk assessment. However, in our proposed model, risk assessment by any individual is based on the collective success of a strategy and not on the behavior of any one other individual. For strategy adaptation, each individual always takes a survey of the degree of success of a certain strategy that one of her neighbors has adopted, i.e., this is a strategy-based risk assessment. Using computer simulations, we determine how these two different risk-assessment methods affect the spread of an infectious disease over a social network. The proposed model is found to benefit the population, depending on the structure of the social network and cost of vaccination. Our results suggest that individuals (or governments) should understand the structure of their social networks at the regional level, and accordingly, they should adopt an appropriate risk-assessment methodology as per the demands of the situation.     

供应链企业社会责任治理决策研究——基于SD-演化博弈分析法

采用演化博弈模型和系统动力学相结合的方法探讨不同治理措施情景下的供应链企业社会责任决策问题,并进行了仿真分析。结果表明,供应链各环节企业决策之间存在着相互影响作用;当制造商和零售商有一方具有较高的履行企业社会责任意识,另一方具有较低的履行意识时,具有较高意识的一方无论有无激励措施,最终都会趋于履行企业社会责任,而较低一方选择不履行决策,除非有力度较大的激励措施出现;当二者以中性态度对企业社会责任的履行进行决策时,激励措施的实施对制造商更有效;制造商相对于零售商履行企业社会责任,对消费者偏好所带来的市场效应更加依赖;政府补贴在短期内是较为有效的激励方式;惩罚力度越强,激励作用越好,持续时间越久;若两种激励措施搭配使用,可以更好地发挥激励作用。     

Inverse Stackelberg Public Goods Game with Multiple Hierarchies Under Global and Local Information Structures

This paper studies the inverse Stackelberg game with multiple hierarchies under global and local information structures, where the players have discrete strategy spaces. For the classic public goods game, we solve the pure-strategy inverse Stackelberg equilibria under three typical hierarchical structures. The results reveal some counterintuitive characteristics within the systems with hierarchies, such as that the cooperation does not increase with the return rate at the equilibria. Furthermore, by defining a local information structure, we give an estimate of the fewest hierarchies required for full cooperation, which can be a constant multiple of the logarithm or square root of the population size or of the population size itself, according to different information structures and return rates. This paper proposes a novel mechanism to play the game and promote cooperation. Both the formulation and analysis method are different from existing works, and the results can find their ample implications in practice, which might help decision making in hierarchical systems.     

Stochastic Stackelberg differential reinsurance games under time-inconsistent mean–variance framework

We study optimal reinsurance in the framework of stochastic Stackelberg differential game, in which an insurer and a reinsurer are the two players, and more specifically are considered as the follower and the leader of the Stackelberg game, respectively. An optimal reinsurance policy is determined by the Stackelberg equilibrium of the game, consisting of an optimal reinsurance strategy chosen by the insurer and an optimal reinsurance premium strategy by the reinsurer. Both the insurer and the reinsurer aim to maximize their respective mean–variance cost functionals. To overcome the time-inconsistency issue in the game, we formulate the optimization problem of each player as an embedded game and solve it via a corresponding extended Hamilton–Jacobi–Bellman equation. It is found that the Stackelberg equilibrium can be achieved by the pair of a variance reinsurance premium principle and a proportional reinsurance treaty, or that of an expected value reinsurance premium principle and an excess-of-loss reinsurance treaty. Moreover, the former optimal reinsurance policy is determined by a unique, model-free Stackelberg equilibrium; the latter one, though exists, may be non-unique and model-dependent, and depend on the tail behavior of the claim-size distribution to be more specific. Our numerical analysis provides further support for necessity of integrating the insurer and the reinsurer into a unified framework. In this regard, the stochastic Stackelberg differential reinsurance game proposed in this paper is a good candidate to achieve this goal.     

非零和动态对策的一类闭环合作策略

本文了研究了非零和动态对策的最优性策略问题，分析了动态对策闭环策略的最优性条件，提出了一类闭环合作策略的概念和设计方法，证明了该策略的最优性，并对线性二次型动态对策问题的闭环合作策略进行了设计。     

随机环境下再制造产品的定价策略研究

再制造产品的定价是逆向供应链中重要的决策问题之一。依据目前我国废旧品回收和再制造的运作机制,在随机环境下建立了以传统生产厂为主导、再制造工厂为从属的Stackelberg博弈模型,分析了新产品与再制造产品的差异定价策略,结合数值算例给出了最优的定价结果。并进一步将模型进行扩展,考虑了二者形成垂直纳什均衡以及存在集成厂商时的情形。研究表明:集成厂商对两种产品的定价最高,系统收益也最大,Stack-elberg情形次之,纳什均衡时最低。     

线性需求供应链中供应商参股制造商的定价与协调

企业之间通过相互参股组成股权联盟提升收益和竞争力来应对多变的环境成为企业股权改革的趋势。在实际管理实践中,供应链各节点企业通过参股战略以改善各自绩效从而提升供应链效率。本文考虑在线性市场需求环境下,构建了由供应商A与制造商B组成的二级供应链,供应商A对制造商B实施参股战略的供应链模型。引入Stackelberg博弈模型,分别讨论分散式与集中式情况下各节点企业的最优决策。研究表明,供应商A对制造商B参股不能消除供应链双重边际效应,基于此设计了收益共享和线性转移支付的协调契约。该契约通过调整批发价使供应商A与制造商B以任意比例分配系统利润,使供应链完美协调。     

财政转移支付纵向均衡问题的研究

本应用二人主从Stackelberg博弈模型研究中央政府与地方政府财政转移支付的纵向均衡问题，根据问题本身建立了一个既考虑激励机制又考虑约束机制的双层规划模型，通过模型的求解得到了确定转移支付总量的解析表达式。并对其结果给出了直观的几何解释，为研究财政转移支付纵向均衡的总量分配给出了一个可以具体操作一种思路和方法。