网络外部性下质量决策与零售商经营目标选择

在网络外部性市场环境下,为研究制造商质量决策和零售商经营目标策略选择之间的影响机理,构建了制造商质量决策和单零售商群体的演化博弈模型,分析了网络外部性和可变质量成本系数对零售商经营目标选择、制造商质量决策、以及节点企业利润的影响.研究发现,1)当制造商只拥有部分市场决策权力时,其质量决策将受到零售商的经营目标策略调整的影响,而零售商经营目标的策略调整则取决于网络外部性大小.当网络外部性较小时,零售商的经营目标将演化稳定为利润最大化,此时制造商将制定较低的产品质量水平;当网络外部性处在中等水平时,零售商的经营目标将演化稳定为利润最大化和收入最大化的混合目标策略,此时制造商将制定中等产品质量水平;当网络外部性较大时,零售商的经营目标将演化稳定为收入最大化,此时制造商将制定高产品质量水平.2)当网络外部性处在中等水平时,其与可变质量成本对零售商经营目标的选择呈现出交叉影响效应,随着可变质量成本的减小,零售商经营目标策略将从利润最大化策略向混合策略,或者混合策略向收入最大化策略演变.3)网络外部性对制造商产品质量的影响效果与可变质量成本和零售商经营目标选择有关,网络外部性效应的增加并不总是使得产品的质量降低.     

考虑服务水平的供应链网络动态模型研究

本文建立了一个由多个供应商和多个零售商组成的供应链网络动态模型,利用定量手段刻画了制造商与制造商间、零售商与零售商间博弈的动态行为过程;通过制造商和零售商提供的服务水平以及产品的零售价格较为贴切的刻画消费者的选择偏好;充分考虑了需求随机产生的库存以及缺货情况;并在单调性条件下利用动态投影系统的相关理论分析了模型的稳定性.最后,通过算例验证了模型的合理性.     

基于复杂网络演化博弈的传统产业集群低碳演化模型研究

本文基于复杂网络演化博弈理论,从微观异质性主体的预期学习和自适应行为特征出发,综合运用随机博弈及博弈学习模型、多主体系统建模等方法,构建了传统产业集群低碳演化模型,并进行了产业低碳策略竞争、涌现和不同演化情景的仿真分析。研究表明,产业集群的复杂网络结构、主体的异质性预期和决策行为对集群低碳策略的涌现有着重要影响;要想在集群内推广应用新的低碳策略,集群异质性主体的低碳偏好、集群复杂网络的外部效应、低碳策略的采用成本和技术兼容性是重要影响因素。     

政府动态奖惩机制下绿色建筑供给侧演化博弈研究

从绿色建筑供给侧角度出发，构建消费者效用函数、开发商利润函数和政府与开发商的演化博弈模型，分析消费者绿色偏好、建筑绿色度、成本等因素对建筑价格、需求和利润的影响以及政府动态奖惩政策下系统的演化稳定策略。结果表明：消费者绿色偏好支付系数和建筑绿色度的增大有利于绿色建筑价格、需求和利润的提高，但高成本却使需求和利润降低；政府采用静态补贴与静态税收政策时，博弈系统不存在演化稳定策略，采用动态补贴与静态税收、静态补贴与动态税收、动态补贴与动态税收三种政策组合时，系统存在演化稳定策略；动态补贴与静态税收的政策组合在推动绿色建筑发展方面优于其他政策；开发商开发绿色建筑的概率与补贴上限值呈负相关，与税收上限值呈正相关。     

供应链中信用交易的演化博弈分析

本文运用演化博弈理论研究了供应链中信用交易的演化过程,建立了供应商和零售商信用交易的演化博弈模型。分析了两类个体在守信与失信两种策略下的行为特征,根据复制者动态方程得到了两者的行为演化规律和政府失信惩罚机制下的行为演化和演化稳定策略,给出了从根本上消灭失信动机的惩罚区间,分析了政府失信惩罚机制的有效性,探寻国内信用制度建设的发展路径。最后,通过数值分析证明了结论的正确性。     

考虑信息泄露的双渠道供应链零售商订单决策及其复杂性研究

非对称信息下考虑由一个供应商和两个市场地位不同的零售商组成的双渠道供应链,大型零售商拥有线下渠道和线上渠道,小型零售商只有线下渠道。本文基于完全理性假设,构建信号传递博弈模型,研究供应商总是将大型零售商线下渠道订单量泄露给小型零售商时零售商的最优订购量策略;基于有限理性假设,进一步构建动态博弈模型,分析零售商订购量动态演化特征。研究发现,信息泄露对双渠道供应链信息泄露策略的影响与单渠道供应链不同,线上渠道的存在避免了大型零售商在高需求与低需求市场相互模仿订购量的情形;有限理性假设下供应链系统的稳定性受订购量调整速度和线上渠道订购量对线下渠道价格敏感系数的影响,订购量调整速度较大时,供应链系统将通过倍周期分岔进入混沌状态。     

交通流演化动力学研究的一般框架及性质分析北大核心CSSCI

针对道路网络需求时变的交通流达到均衡的条件以及均衡状态的稳定性问题,运用演化博弈理论和动力系统稳定性理论,提出了流量演化动力学研究的一般框架,建立了多群体多准则出行选择流量演化系统的动力学模型,证明了流量演化动力学模型平衡点与动态交通流量分配模型均衡解之间的等价性,讨论了模型解的存在性、唯一性和稳定性.理论分析结果表明,流量演化动力系统的演化稳定策略等价于动态交通流分配模型的均衡解,流量演化动力系统在某个局部区域总存在着唯一解,并且在出行者个体收益参数满足一定条件的前提下,流量演化动力系统在平衡点附近会表现出不同的稳定性质,通过一个简单路网的数值算例说明了本文建立模型的合理性和有效性.本文在出行者博弈行为和动态交通分配之间建立了联系,有助于加深对于城市交通流演化规律的认识和理解.     

零售市场价格策略的演化博弈分析

基于一个三阶段Hotelling博弈模型:位于[0,1]线性城市两端的零售A和B第一阶段同时选择价格策略变量,第二阶段确定价格的大小,第三阶段由消费者选择零售商。应用演化博弈论进行研究,分析了零售市场价格策略的演化稳定性。     

交通流演化动力学研究的一般框架及性质分析

针对道路网络需求时变的交通流达到均衡的条件以及均衡状态的稳定性问题,运用演化博弈理论和动力系统稳定性理论,提出了流量演化动力学研究的一般框架,建立了多群体多准则出行选择流量演化系统的动力学模型,证明了流量演化动力学模型平衡点与动态交通流量分配模型均衡解之间的等价性,讨论了模型解的存在性、唯一性和稳定性． 理论分析结果表明,流量演化动力系统的演化稳定策略等价于动态交通流分配模型的均衡解,流量演化动力系统在某个局部区域总存在着唯一解,并且在出行者个体收益参数满足一定条件的前提下,流量演化动力系统在平衡点附近会表现出不同的稳定性质,通过一个简单路网的数值算例说明了本文建立模型的合理性和有效性． 本文在出行者博弈行为和动态交通分配之间建立了联系,有助于加深对于城市交通流演化规律的认识和理解．     

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。     

社会福利最大化与消费者效用最大化的关系研究

本文首先给出了消费者追求效用最大化的优化模型,然后通过K -T条件将该模型与文 [1]的政府追求社会福利最大化的优化模型的解连接起来,证明了在国家宏观目标实现的同时消费者也实现了其微观目标,最后说明在一定条件下这一结果反之也成立。     

二度价格歧视的进一步研究

系统地讨论了二度价格歧视条件下垄断厂商的收益最大化条件和利润最大化条件 .首先分别讨论了线性需求函数和非线性需求函数情形下的收益最大化问题 ,接着讨论了线性需求函数和非线性需求函数情形下的利润最大化问题 .针对上述问题 ,本文均给出了严谨的理论分析和有关的计算公式 .本文的研究成果具有较大的理论价值和应用价值     

Multi-phase Algorithms for Throughput Maximization for Real-Time Scheduling

We consider the problem of off-line throughput maximization for job scheduling on one or more machines, where each job has a release time, a deadline and a profit. Most of the versions of the problem discussed here were already treated by Bar-Noy et al. (Proc. 31st ACM STOC, 1999, pp. 622–631; http://www.eng.tau.ac.il/amotz/). Our main contribution is to provide algorithms that do not use linear programming, are simple and much faster than the corresponding ones proposed in Bar-Noy et al. (ibid., 1999), while either having the same quality of approximation or improving it. More precisely, compared to the results of in Bar-Noy et al. (ibid., 1999), our pseudo-polynomial algorithm for multiple unrelated machines and all of our strongly-polynomial algorithms have better performance ratios, all of our algorithms run much faster, are combinatorial in nature and avoid linear programming. Finally, we show that algorithms with better performance ratios than 2 are possible if the stretch factors of the jobs are bounded; a straightforward consequence of this result is an improvement of the ratio of an optimal solution of the integer programming formulation of the JISP2 problem (see Spieksma, Journal of Scheduling, vol. 2, pp. 215–227, 1999) to its linear programming relaxation.     

Analysis of Revenue Maximization Under Two Movie‐Screening Policies

A few weeks before the start of a major season, movie distributors arrange a private screening of the movies to be released during that season for exhibitors and, subsequently, solicit bids for these movies (from exhibitors). Since the number of such solicitations far exceeds the number of movies that can be feasibly screened at a multiplex (i.e., a theater with multiple screens), the problem of interest for an exhibitor is that of choosing a subset of movies for which to submit bids to the distributors. We consider the problem of the selection and screening of movies for a multiplex to maximize the exhibitor's cumulative revenue over a fixed planning horizon. The release times of the movies that can potentially be selected during the planning horizon are known a priori. If selected for screening, a movie must be scheduled through its obligatory period, after which its run may or may not be extended. The problem involves two primary decisions: (i) the selection of a subset of movies for screening from those that can potentially be screened during the planning horizon and (ii) the determination of the duration of screening for the selected movies. We investigate two basic and popular screening policies: preempt‐resume and non‐preempt. In the preempt‐resume policy, the screening of a movie can be preempted and resumed in its post‐obligatory period. In the non‐preempt policy, a movie is screened continuously from its release time until the time it is permanently withdrawn from the multiplex. We show that optimizing under the preempt‐resume policy is strongly NP‐hard while the problem under the non‐preempt policy is polynomially solvable. We develop efficient algorithms for the problem under both screening policies and show that the revenue obtained from the preempt‐resume policy can be significantly higher as compared with that from the non‐preempt policy. Our work provides managers of multiplexes with valuable insights into the selection and screening of movies and offers an easy‐to‐use computational tool to compare the revenues obtainable from adopting these popular policies.     

Determining optimal disassembly and recovery strategies

We present a stochastic dynamic programming algorithm for determining the optimal disassembly and recovery strategy, given the disassembly tree, the process-dependent quality distributions of assemblies, and the quality-dependent recovery options and associated profits for assemblies. This algorithm generalizes the one proposed by Krikke et al. (International Journal of Production Research 1998; 36(1):111–39) in two ways. First, there can be multiple disassembly processes. Second, partial disassembly is allowed. Both generalizations are important for practise.     

Optimal Control of Replenishment and Substitution in an Inventory System with Nonstationary Batch Demand

We study an inventory system in which a supplier supplies demand using two mutually substitutable products over a selling season of T periods, with a single replenishment opportunity at the beginning of the season. As the season starts, customer orders arrive in each period, for either type of products, following a nonstationary Poisson process with random batch sizes. The substitution model we consider combines the usual supplier‐driven and customer‐driven schemes, in that the supplier may choose to offer substitution, at a discount price, or may choose not to; whereas the customer may or may not accept the substitution when it is offered. The supplier's decisions are the supply and substitution rules in each period throughout the season, and the replenishment quantities for both products at the beginning of the season. With a stochastic dynamic programming formulation, we first prove the concavity of the value function, which facilitates the solution to the optimal replenishment quantities. We then show that the optimal substitution follows a threshold rule, and establish the monotonicity of the thresholds over time and with respect to key cost parameters. We also propose a heuristic exhaustive policy, and illustrate its performance through numerical examples.     

The importance of taxes in entrepreneurial decisions: an analysis of practicing physicians’ behavior

An irrational strong importance of taxes in an individual’s decision-making behavior is one of the most popular assumptions about the behavioral effects of taxation. However, empirical research about this phenomenon is rare. In a study of German physicians, this paper analyzes whether tax aspects are over weighted in entrepreneurial decision-making. Furthermore, factors that may influence the irrational decision-making behavior of actors are analyzed. As research method, a conjoint analysis is used that permits measurement of the relative importance of tax aspects in decisions. The first result of the study is that the majority of the respondents (practicing physicians) misestimate their own marginal tax rate. The main result of the study is that––in comparison to the neoclassical model of rational maximization of consumption utility––most of the respondents overweight tax aspects. No evidence can be found for any relationship between indicators of a possible tax aversion (e.g., low satisfaction with the tax system) and attention to tax aspects in the decisions analyzed.

Nondistribution Constraint and Managerial Discretion: Disentangling the Relationship

The paper questions the viewpoint of the property rights theorists that nondistribution constraint makes nonprofit firms particularly prone to managerial shirking. The possibility that utility maximized by nonprofit managers corresponds to their firms’ missions is justified by the inability of the real-world price system to ensure the perfect match between profit maximization and utility maximization. The imperfection of this match means that some consumers’ preferences cannot be gratified through the price system and therefore require nonprofit organization. The possibility of managerial on-the-job consumption in nonprofit firms is shown to be insufficient for inferring inefficiency of their property rights structure.This research has been supported by Marie Curie Incoming International Fellowship of the Sixth Framework Program of the European Community (Contact No. M1F1-CT-2005-514036). The views expressed in this publication are those of the author only. The European Commission is not liable for any use that may be made of the information contained in this publication.     

参数不确定性和效用最大化下的动态投资组合选择

标准投资组合选择理论假设投资者准确地知道与资产收益率相关的各种参数(例如均值和方差),忽视了参数不确定性引致的估计风险给投资决策带来的影响.本文研究引入参数不确定和学习时的连续时间动态投资组合选择问题,使用鞅方法求导出了具有CRRA型效用函数的投资者的最优投资策略的显式表达式.在此基础上,我们结合中国证券市场中的实际数据深入分析了参数不确定性以及投资者初始信念对最优投资策略的影响.     

需求响应下解决交叉补贴的阶梯电价方案研究——基于社会福利最大化视角

我国电价交叉补贴问题非常严重，其无论从经济效率还是公平上而言都是不合理的，必须尽快解决。通过对现行电价政策分析，阶梯电价政策可以解决交叉补贴问题，但现行方案效果不明显，因此需要调整。不仅如此，由于各档次用户对电价变化的需求响应程度存在差异，调整阶梯电价来解决交叉补贴的方案有许多，故存在一个社会福利最大化的解决方案。本文以社会福利最大化为目标，调整各档用户的电价，同时引入拉格朗日函数，设计出最优解决交叉补贴问题的阶梯电价方案，得到各档相应的电价比值。结果表明，当分档电价比值为1：1.62：2.41时社会福利存在极大值，此时阶梯电价方案是众多方案中的最优方案，社会福利全年增加约为702.00亿元。此方案在解决交叉补贴问题的基础上还兼顾了用户间公平和承受能力，对当前电价改革具有重要参考价值。