基于证据理论的风险收益评价模型及其应用

针对影响风险及收益的因素,给出了一种基于D em pster-Shafer证据理论的风险收益综合评价模型.通过对影响风险收益的不确定性多属性进行融合,可以将风险收益评价问题转化为一般的确定性多属性风险评价问题.实例表明基于证据推理对风险收益进行综合评价是可行有效的.     

中国股市长记忆的修正R/S分析

本文在比较各种长记忆检验方法优缺点的基础上,采用修正的R/S分析检验我国沪深两股市日收益和日绝对收益序列的长记忆性。结果表明在0.05的显著水平下,两股市的日收益序列均无长记忆,但深圳成指日收益序列的记忆长度比上证综指日收益序列的记忆长度长;以日绝对收益序列为代表的波动序列具有较强的长记忆性。     

一直在努力?——基金管理者买卖行为的有效性分析

通过构建收益缺口-基金的净资产收益与投资组合收益之差,探讨了我国证券市场中开放式基金管理者的买卖行为及其对基金业绩的影响.研究结果表明,在2004至2007年中,基金月收益缺口的均值显著大于零,表明基金管理者的努力总体上能增加基金的价值;投资者若模拟基金的股票构成进行投资,在熊市中,其平均回报小于基金的收益,但在牛市中,却显著地大于基金的收益,这一差异对配置型基金更明显.同时,基金收益缺口的大小与基金的类型和规模显著相关.     

套利组合的最大收益模型研究

主旨是建立套利组合最大收益的线性规划模型,使模型符合套利组合收益最大化的本意并且尽量简化.通过六个命题阐述和严格证明了套利组合收益的几个模型的一些特性,尤其是得出了使得套利组合获得最大收益的一个必要条件(命题3)和一个符合套利组合收益最大化的本意并且达到了简化目的线性规划模型(命题5).     

博弈联盟模糊收益的分配

提出了联盟模糊收益合理分配的一种新方法.首先,在模糊收益α截集上定义了α合理分配集,分析了该分配集与模糊收益Shapley值的关系.接着,给出了模糊收益的α合理Shapley分配函数,对其性质进行了讨论.然后,构造了模糊合理Shapley分配,证明其连续性,得到了联盟模糊收益与模糊合理Shapley分配具有包含关系的结论.     

基于纯粹跳跃利维过程的中外股票收益分布特征研究

本文运用无限可分纯粹跳跃的NIG模型和VG模型对沪深股市股指收益分布特征和国际上其它主要股市股指收益分布特征进行拟合分析。结果表明在拟合收益分布方面NIG模型和VG模型的拟合度远远高出正态分布假设的拟合度,NIG模型和VG模型两者之间拟合收益分布没有明显的优劣;沪深股指收益分布拟合情形和国际上主要股指收益分布拟合情形基本没有差异。     

基于演化博弈视角的植物品种权价值链合作伙伴行为协调机制研究

本文提出了植物品种权价值链合作伙伴行为协调的概念,应用演化博弈的双种群理论,研究了植物品种权价值链合作伙伴行为协调的博弈演化过程及影响因素。研究表明,协调演化方向受协调成本、协调收益、超额收益分配比例、成本分摊比例、单独合作收益、背叛收益和奖惩金额等因素的影响。提高协调收益和单方面合作收益,降低协调成本和背叛收益,保持合作双方支付的成本与双方合作超额收益的分配正相关,建立合理的超额收益分配机制,加强外部监管和惩罚力度,将会促进植物品种权价值链合作伙伴行为向全面协调的方向演化。     

基于风险的现值法

收益现值法中每期的收益都是确定的量。实际上，由于受多种因素的影响，每期的收益仅仅是当期收益的平均值。基于每期收益为正态随机变量，给出了收益现值的计算公式。由此能更好地描述经济活动的变化情况。文中给出了数字例。     

基于数字仿真的收益管理整合决策

对航空公司收益管理进行机票定价和座位存量分配的整合研究。应用计算机仿真算法动态构造民航收益管理系统中的需求预测模型,并根据航班收益最大化原则,确定价格与座位存量分配,根据需求变化实时调整价格和座位存量。仿真运算结果显示,该算法可以使航空公司不同航班收益比固定价格提高2%以上。     

协作运营网络收益协调模型与求解方案研究

为提高协作运营网络的稳定性,从收益角度,研究协作运营网络中各协作单元的收益协调问题.首先界定协作单元、协作运营、协作运营网络和协作运营网络收益概念;基于"合作博弈",建立协作运营网络收益协调数学模型,实现协作运营网络收益最大化和协作单元收益均衡化;借助"Shapley值",对协作运营网络收益协调模型进行求解,提出基于"收益补偿"的协调策略.对如何有效协调协作组织收益,提高运营过程中各协作单元的主动性和积极性具有实践价值.     

Total Reward Stochastic Games and Sensitive Average Reward Strategies

In this paper, total reward stochastic games are surveyed. Total reward games are motivated as a refinement of average reward games. The total reward is defined as the limiting average of the partial sums of the stream of payoffs. It is shown that total reward games with finite state space are strategically equivalent to a class of average reward games with an infinite countable state space. The role of stationary strategies in total reward games is investigated in detail. Further, it is outlined that, for total reward games with average reward value 0 and where additionally both players possess average reward optimal stationary strategies, it holds that the total reward value exists.     

Semi-Markov and reward fields

We introduce semi-Markov fields and provide formulations for the basic terms in the semi-Markov theory. In particular we define and consider a class of associated reward fields. Then we present a formula for the expected reward at any multidimensional time epoch. The formula is indeed new even for the classical semi-Markov processes. It gives the expected cumulative reward for fairly large classes of reward functions; in particular, it provides the formulas for the expected cumulative reward given in Masuda and Sumitau (1991), Soltani (1996) and Soltani and Khorshidian (1998).     

Possibilities of solution in stochastic decision models with recursive reward functions

A stochastic decision model with general, non-necessarily additive reward function is considered and essential properties of such reward functions are formulated which only allow a successive proceeding in the sense of dynamic programming. Conditions for recursive—additive reward functions are given which ensure the existence of optimal strategies and the usability of value iteration to find an optimal policy and the optimal total reward.     

回报计划对重复购买行为模式的影响研究

客户回报计划已成为一种重要的关系营销手段。本文在讨论回报计划如何对稳定市场结构下的重复购买行为产生影响的基础上,通过建立NBD-DM随机模型,提供了一种研究消费者重复购买行为的模型方法,并利用一组护肤品品类销售的固定样本组数据(panel data)对该方法进行了实证分析。结果表明NBD-DM模型是研究消费者重复购买行为的有效模型方法,并且证实回报计划在改变客户重复购买行为上的有效性,其是企业建立长期客户关系的有效手段。最后讨论了结论对战略及营销管理实践的意义。     

Central Limit Theorem for Nonlinear Semi-Markov Reward Processes

Abstract

In this work, we obtain a central limit theorem for reward processes defined on a finite state space semi-Markov process, when reward functions assumed to have general forms and are not of constant rates. Martingale theory is the main tool which have been used for establishing the convergence of scaled and shifted reward process to a zero mean Brownian motion. The striking point in this article is considering general forms for the reward functions which are realistic in applications. The conditions needed for these results are existence of variances for sojourn times in each state and second order integrability of reward functions with respect to sojourn times distributions.     

Reward systems for intra-organizational knowledge sharing

Knowledge sharing is one of the most critical steps in knowledge management activities. To achieve effective knowledge sharing, it is important to encourage workers to share their knowledge for the best interests of the firm. However, successfully exerting this encouragement is very challenging. In this paper, we develop a formal model and analyze reward systems for intra-organizational knowledge sharing. Specifically, two common forms of reward systems are considered; individual-based reward which is based on the individual contribution of valuable knowledge, and group-based reward which is based on the contribution of the whole group through knowledge sharing to the firm performance. Through the analysis, we derive a simple optimal individual-based reward system which depends on the amount and the productivity of shared knowledge. The system balances the benefit from knowledge sharing of each worker with the costs related with it. Next, it is found that group-based reward is not only less efficient than individual-based reward, but it also subject to a potential productivity problem, in which workers with more productive knowledge do not participate in knowledge sharing. Finally, it is shown that several organizational factors can complement reward systems in increasing the performance of KM and can mitigate the productivity problem. Insights from our analysis could help managers to understand important considerations in rewarding knowledge sharing, and could provide them with guides to implement reward systems.     

Supply chain coordination by manufacturer reward contract

We investigate how a manufacturer sets a reward contract to realize supply chain coordination when a retailer's service effort has a showrooming effect. We demonstrate that the manufacturer's reward contract increases retail prices and benefits the retailer but may hurt the manufacturer. Meanwhile, a large unit reward can soften the price competition. We also find that when the unit reward is high, a greater showrooming effect may benefit supply chain members, and the retailer provides a higher service effort.     

基于消费者异质性社交能力的推荐奖励策略

从消费者社交性的视角优化推荐奖励策略。文章基于效用理论,分析消费者的购买和推荐行为。构建了当期利润最大化基本模型和纳入远期利益的扩展模型,优化产品价格和折扣,给出高低折扣策略的适用空间,并探讨消费者社交能力对企业利润和社会绩效的影响。结果显示,消费者的社交能力差异较小时适合采取高折扣策略,否则适宜低折扣策略。当企业考虑远期利益的时候,企业的最优策略是免费策略。随着环境参数变化,最优奖励策略由高折扣调整为低折扣时会带来福利损失,但低折扣策略并不必定导致社会福利的损失。此外,还给出了实践中某些商品价格虚高的经济解释。本研究能够为企业实施推荐计划制定奖励策略提供依据。     

A game theoretical approach to sharing penalties and rewards in projects

This paper analyzes situations in which a project consisting of several activities is not realized according to plan. If the project is expedited, a reward arises. Analogously, a penalty arises if the project is delayed. This paper considers the case of arbitrary nondecreasing reward and penalty functions on the total expedition and delay, respectively. Attention is focused on how to divide the total reward (penalty) among the activities: the core of a corresponding cooperative project game determines a set of stable allocations of the total reward (penalty). In the definition of project games, surplus (cost) sharing mechanisms are used to take into account the specific characteristics of the reward (penalty) function at hand. It turns out that project games are related to bankruptcy and taxation games. This relation allows us to establish nonemptiness of the core of project games.     

Optimizing referral reward programs under impression management considerations

We examine referral reward programs (RRP) that are intended for a service firm to encourage its current customers (inductors) to entice their friends (inductees) to purchase the firm’s service. By considering the interplay among the firm, the inductor, and the inductee, we solve a “nested” Stackelberg game so as to determine the optimal RRP in equilibrium. We determine the conditions under which it is optimal for the firm to reward the inductor only, reward the inductee only, or reward both. Also, our results suggest that RRP dominates direct marketing when the firm’s current market penetration or the inductor’s referral effectiveness is sufficiently high. We then extend our model to incorporate certain key impression management factors: the inductor’s intrinsic reward of making a positive impression by being seen as helping a friend, the inductor’s concerns about creating a negative impression when making an incentivized referral, and the inductee’s impression of the inductor’s credibility when an incentive is involved. In the presence of these impression management factors, we show that the firm should reward the inductee more and the inductor less. Under certain conditions, it is optimal for the firm to reward neither the inductor nor the inductee so that the optimal RRP relies purely on unincentivized word of mouth.