面向价值网络的企业协同竞争博弈模型研究

运用演化博弈理论的方法,分析价值网络模式下企业的协同竞争机制,构建企业主体间协同竞争的演化博弈模型,指出价值网络模式下企业协同竞争行为的博弈过程及特点,揭示出系统的初始状态、发展阶段及利益分配机制对演化博弈过程的影响机理。     

基于动态规划多期期货套期保值优化模型研究

通过对套期保值者头寸价值变化量的分析,采用动态规划方法,建立了多期套期保值动态模型,推导出多期套期保值进行动态跟踪调整的策略。该模型的特点一是反映了期货交易费用在套期保值中的作用,解决了现有期货套期保值策略忽略交易费用的不足,提高了模型的准确性。二是考虑保证金对期货套期保值的影响。把期货交易保证金的机会损失纳入套期保值策略内,从而使套期保值直接反映了期货保证金无利息收入、而存在机会成本的真实情况,弥补了现有研究不考虑期货交易保证金的机会损失的缺陷。三是体现了套期保值者收益最大化的原则。解决了现有模型只考虑了规避期货和现货组合的价格波动风险,忽略组合的收益的弊端,增加了模型的实用性和适用性。     

战略过程：一个基于决策的数理模型

以标准的战略管理过程模型为基础,将战略过程解释为战略状态的演变过程,其中战略状态变化被解释为战略决策和外生随机扰动共同作用的结果,应用随机动态规划模型化战略决策理性。结果表明,采用动态规划技术不仅可以确定战略状态的价值(竞争优势)与相应的最优战略制定决策和战略实施决策序列,还可以识别战略过程中的信息揭示对企业价值(竞争优势)的影响。这些结果在一定程度上逻辑一致地支持了战略管理中以理性决策为基本假设的设计学派和计划学派的观点。     

非线性需求下具有网络外部性的二级歧视定价研究

研究了非线性需求函数条件下产品存在网络外部性时,垄断企业采用对需求区间分段定价的方法进行二级歧视定价的策略。首先分析了单阶段垄断企业二级价格歧视的静态定价策略,接着给出了在一个较长时期内垄断企业分两阶段进行二级歧视的动态定价策略。结果表明网络外部性不影响最优需求区间分段单调递增的性质,但价格随网络外部性的增强而相应提高,且第一阶段的价格高于第二阶段的贴现值。     

基于变参数模型的流动性与上证综指收益率关系研究

研究了流动性与上证综合指数收益率之间的时间序列动态关系,并利用状态空间模型对流动性与上证综指收益率的动态关系进行了变参数分析。结论是:上证综指收益率对宏观流动性变动的时变弹性系数在近几年流动性过剩的背景下,呈现上升趋势。其中,能源、钢铁和金融行业时变弹性系数波动比较剧烈,而医药行业的时变弹性系数波动较小。证券市场(微观)流动性变动的时变弹性系数随着我国股票市场发展的逐步健全、完善而趋于平稳。     

Dynamic Assignment of Flexible Service Resources

Resource flexibility is an important tool for firms to better match capacity with demand so as to increase revenues and improve service levels. However, in service contexts that require dynamically deciding whether to accept incoming jobs and what resource to assign to each accepted job, harnessing the benefits of flexibility requires using effective methods for making these operational decisions. Motivated by the resource deployment decisions facing a professional service firm in the workplace training industry, we address the dynamic job acceptance and resource assignment problem for systems with general resource flexibility structure, i.e., with multiple resource types that can each perform different overlapping subsets of job types. We first show that, for systems containing specialized resources for individual job types and a versatile resource type that can perform all job types, the exact policy uses a threshold rule. With more general flexibility structures, since the associated stochastic dynamic program is intractable, we develop and test three optimization‐based approximate policies. Our extensive computational tests show that one of the methods, which we call the Bottleneck Capacity Reservation policy, is remarkably effective in generating near‐optimal solutions over a wide range of problem scenarios. We also consider a model variant that requires dynamic job acceptance decisions but permits deferring resource assignment decisions until the end of the horizon. For this model, we discuss an adaptation of our approximate policy, establish the effectiveness of this policy, and assess the value of postponing assignment decisions.     

Optimizing the Collections Process in Consumer Credit

This paper builds a dynamic programming model to optimize the collections process in consumer credit. It determines which collections actions should be undertaken and how long they should be performed, including theoretical results about the form of the optimal policy under certain conditions. Finally, a case study is described based on data from the collections department of a European bank.     

The Dynamic Pivot Mechanism

We consider truthful implementation of the socially efficient allocation in an independent private‐value environment in which agents receive private information over time. We propose a suitable generalization of the pivot mechanism, based on the marginal contribution of each agent. In the dynamic pivot mechanism, the ex post incentive and ex post participation constraints are satisfied for all agents after all histories. In an environment with diverse preferences it is the unique mechanism satisfying ex post incentive, ex post participation, and efficient exit conditions. We develop the dynamic pivot mechanism in detail for a repeated auction of a single object in which each bidder learns over time her true valuation of the object. The dynamic pivot mechanism here is equivalent to a modified second price auction.     

社区应急疏散动态协作调度优化研究

针对灾民数量和路网通行时间的动态性以及灾民疏散反应系数的随机性,本文提出了社区应急疏散协作调度优化流程,并以疏散灾民数量最大化和疏散成本最小化为目标,构建了社区应急疏散多种运输方式协作调度优化模型,并给出了求解该模型的改进多目标遗传算法。然后,论文使用Tansmodeler模拟社区应急疏散协作调度优化过程,加载疏散灾民动态需求和历史出行时间表,并对模型和算法进行验证。结果表明,该模型和算法可以在有效刻画疏散灾民数量和路网通行时间的基础上,为不同时刻的交通工具配置及疏散路径选取提供决策。     

利用和声分散搜索算法解决动态共乘的乘客选择研究

动态共乘作为一种配合解决城市交通出行难题的新模式近年来引起了人们越来越多的关注，然而在较大范围内选择合适的乘客，以便获得最佳的综合服务效果却具有相当大的挑战性。本文正是针对这一问题，建立了以乘客效用最大化和司机总行程最短为目标函数，以满足司机与乘客的时间要求和司机参与约束为限制条件的多目标0-1规划共乘模型，用于帮助司机选择最合适的乘客。根据该模型的特点，构造了加入了分散搜索机制的新的和声搜索算法。在仿真实验时，针对司机和乘客效用的两种产生方式，在较大规模的路网环境下利用该算法分别对模型进行了求解，得到了Pareto最优解集。仿真结果不仅表明了模型的合理性和算法的可行性，而且还指出基于效用函数可以发现更多合适的潜在乘客。最后，通过与文献中其它算法的对比进一步展示了本文算法的有效性。