基于动机的联合风险投资收益分配契约设计

从联合风险投资的领导者采取联合投资的动机出发,考虑分配给跟随者的收益份额是否能达到目的,运用优化理论建立了联合投资双方的收益分配模型,提出了联合风险投资机构之间的收益分配契约设计的一种可供参考的方法,并用实例说明了模型方法的应用。研究还表明,潜在的市场竞争可能对领导者造成的损失越大,领导者越愿意给予跟随者更多的收益份额;当项目质量信息的不确定性越高,单独投资将存在较大风险的时候,为了获得项目质量信息的补充,也使得领导者愿意给予跟随者更多的收益份额。     

公平偏好下考虑互补效应的项目投资收益分配研究

决策者的公平偏好对项目投资合作的形成和推进有重要影响。本文从创业企业和风险投资家的双重道德风险出发,选取Nash谈判解为公平偏好参照点,构建创业企业具有公平偏好的项目投资委托代理模型,研究委托方和代理方的能力存在互补效应的情形下,公平偏好对项目收益分配及双方努力水平的影响。结果表明:项目收益的最优分配比例和双方的最高努力水平均与创业企业的公平偏好程度相关。在互补效应存在时,双方的努力水平不会随收益分配比例的变化呈现单调变化趋势。如果双方的能力互补程度较小,具有公平偏好的创业企业会以Nash谈判解为自己的收益下限,风险投资家需要向其让渡更多的项目收益才能实现有效激励;如果双方的能力互补程度较大,创业企业会将Nash谈判解作为自己的收益上限,风险投资家即使不给予其大于Nash谈判解的收益也可实现有效激励。     

基于模糊模拟的风险投资项目决策

由于风险投资的高不确定性和风险性,使得人们难以准确预测风险投资项目的收益和状态概率,而只能得到其大致的区间范围。鉴于这种情况,本文将投资项目收益和状态概率描述为模糊变量,利用模糊变量的均值和方差建立了模糊风险投资决策模型,并给出利用模糊模拟方法计算的实例。     

政府补贴对风险投资的影响机制研究

建立了风险投资者与创业者之间的契约关系理论模型,研究了政府补贴政策的影响机制.研究证明政府补贴在提高风险投资者期望收益的同时,也提高了创业者的期望收益,这一政策也使得更多的投资项目值得风险资本去投资.因此,政府补贴增加了创业企业对风险资本的需求,能够促进风险投资业的发展.     

延迟期权与风险投资决策研究

本在传统投资方法基础上，通过引入延迟期权定价理论，建立风险投资项目时机选择模型，增加了风险投资项目决策的科学性。     

基于股权——债权条件下风险投资的激励机制分析

运用博弈论中委托—代理理论对股权—债权条件下风险投资的激励机制进行了系统分析.根据风险投资家提供股权—债权与风险企业家提供股权融资的假设条件构造了一个基本博弈模型,并对模型进行了推广.研究发现:风险企业家的投资不仅有融资功能,而且还可以作为一种信号传递改变风险投资家的投资信念,使之对项目前景更乐观;扩展模型比基本模型更能改善风险企业家的投资行为,使之投入更多资金和给予风险投资家更高激励;此外,扩展模型更能消除股权—债权投资比例的相互替代性.     

基于Shapley值法的三级闭环供应链收益分配模型

以合作博弈为基本研究方法,构建了由制造商、第三方物流和零售商组成的三级闭环供应链收益分配模型,不同合作方式下各合作联盟收益的特征函数的计算结果表明:在采取合作时,各合作联盟的收益均大于或等于各成员在不合作时各自的收益之和,文章验证了在三级闭环供应链收益分配模型中应用Shapley值法的可行性,说明构建的收益分配模型具有普遍适用性.然后运用Shapley值法求得三级闭环供应链收益分配的合理均衡解,最后结合算例进行了分析论证.     

具有Pareto最优性的风险投资项目组合选择方法

为解决现有风险投资项目组合选择方法未考虑资本不可细分和投资收益率难以预测的问题,首先在借鉴MV模型思想的基础上结合风险投资项目评价指标体系定义了项目组合偏好率及其方差,并将二者分别视为项目组合的产出与投入,然后基于DEA相对效率评价原理构建了能够评价出具有Pareto最优性的项目组合优选模型即VCP-DEA/AR模型,最后通过一个数值验证案例证明了该模型的科学有效性和应用可行性。     

基于VC谈判力的内生投资模型

近来,对风险投资的研究大都是从信息不对称、控制权的私有收益的角度出发,并且把首次投资水平看成是外生决定的变量.把其内生化并从谈判力的视角出发建立了一个两期信号博弈模型.通过模型分析,①得到了影响首次投资水平的关键因素:投资双方的谈判力、双方信息不对称以及事后不确定性程度;②对相关因素进行了量化分析,并讨论了投资双方谈判力的分配问题.     

新型风险投资组合选择模型

为克服现有关于风险投资的投资组合选择研究所存在的诸如相关参量在实际中不易确定、对投资风险的刻画过于粗糙等不足,本文依据风险投资的特点,提出了直接基于对风险投资项目的综合评价值来预测其未来投资效益与风险的新方法,给出了两种更合理的风险度量,并由此导出了相应的新型风险投资的投资组合选择模型,模拟结果说明了新度量和模型的合理性和实用价值.     

Flexibility in a Stackelberg leadership with differentiated goods

We study the effects of product differentiation in a Stackelberg model with demand uncertainty for the first mover. We do an ex-ante and ex-post analysis of the profits of the leader and of the follower firms in terms of product differentiation and of the demand uncertainty. We show that even with small uncertainty about the demand, the follower firm can achieve greater profits than the leader, if their products are sufficiently differentiated. We also compute the probability of the second firm having higher profit than the leading firm, subsequently showing the advantages and disadvantages of being either the leader or the follower firm.     

基于技术创新的资金约束供应链融资策略分析

新兴技术进入竞争市场时,供应链成员往往存在资金约束,为了尽早占据市场份额、获得更高的利润流,上下游企业有意愿进行供应链的内外部融资。文章对上游企业存在资金约束、下游核心企业资金充裕的供应链融资策略进行决策分析。研究表明:上下游的融资策略会使上游企业得到帕累托改进,且随上游企业自有资金的增大,下游企业的利率阈值逐渐减小;存在最优融资利率使得下游企业的期望利润达到最大。在上下游企业财务不透明的前提下,存在下游企业的融资利率区间使上游企业有隐藏真实资金状况以期获得更低融资利率的动机,文章基于博弈论的信息甄别模型给出了相应的激励合同对上游企业的期望利润进行修正,诱使上游企业提供真实的资金状况。     

基于减排成本共担期权契约的供应链协调

考虑消费者具有低碳产品偏好的情况,研究需求随机且受减排影响的期权契约,建立了由单个制造商和单个零售商组成的供应链模型。该模型中制造商处主导地位,零售商处追随地位,制造商首先提出期权契约,零售商购买期权。求解发现,由于传统双重边际化效应的存在,只有当零售价格等于期权执行价格时,才能达到供应链的协调,这时零售商利润为负,不满足参与约束。为此,从降低期权执行价格的角度,对期权契约进行补充,增加了成本共担条款。研究表明,减排成本共担的期权契约能够实现供应链的协调。最后利用算例验证了结论,计算了制造商和零售商利润及零售商分担的减排成本比例随期权价格和期权执行价格的变化情况,并对减排难度系数的敏感性做了分析。     

零售商信息分享对双渠道绿色供应链绩效影响研究

研究了零售商市场需求预测信息分享对双渠道绿色供应链绩效的影响。运用不完全信息动态博弈方法建立并求解零售商信息分享和信息不分享下的绿色供应链决策模型,得到贝叶斯均衡解和各方最优期望利润。研究发现:在双渠道绿色供应链中,若零售商对市场需求预测较为乐观,信息分享使得制造商更有动机提高产品绿色度;此外零售商信息分享总是有利于制造商利润增加,但并非总是使得零售商利润损失。当制造商绿色投资效率较高时,信息分享使得零售商利润增加,反之,信息分享使得零售商利润降低。对整个绿色供应链利润的影响取决于渠道间竞争强度、直销渠道市场份额及制造商绿色投资效率。最后用数值仿真验证了模型和结论的有效性。     

合作竞争条件下R&D项目投资决策分析

R&D项目的成功会为高新技术企业带来巨大收益,但是其研发过程中存在着技术风险、商业风险和突发风险等所带来的多种不确定性。为了应对这些不确定性,一些高新技术企业往往结成追求联盟整体利益最大化的成本共享联盟来进行R&D项目投资,然而由于不进行技术共享并争夺研发成功后的收益,联盟中的企业又会在合作的同时进行竞争,这就需要企业对R&D项目的估值非常的精确,以便在合作竞争条件下做出收益最大的最优投资决策。市场中两个合作竞争的高新技术企业各自拥有四种投资决策:成为市场先行者或跟随者,立刻与另一企业共同投资,与另一企业共同选择先等待时机再进行投资。本文以这两个高新技术企业为例,利用欧式期权理论量化了多种不确定性,建立相应的R&D项目投资决策数学模型,对R&D项目的投资时机和决策收益进行评估。当成本共享联盟整体收益最大时,得到的两个高新技术企业做出的投资决策即为在合作竞争条件下R&D项目投资中各自的最优投资决策,最后通过Shapley值的计算可对联盟中企业各自的收益进行合理分配。     

风险资本的组合投资最优化模型研究

利用委托代理理论建立了风险资本的组合投资最优化模型,通过该模型给出了项目数和收益分配比例的最优解,并分析了组合投资的项目数和收益分配比例对风险投资家和企业家努力水平的影响。     

A robust model for a leader–follower competitive facility location problem in a discrete space

This paper aims at determining the optimal locations for the leader’s new facilities under the condition that the number of the follower’s new facilities is unknown for the leader. The leader and the follower have some facilities in advance. The first competitor, the leader, opens p new facilities in order to increase her own market share. On the other hand, she knows that her competitor, the follower, will react to her action and locate his new facilities as well. The number of the follower’s new facilities is unknown for the leader but it is assumed that the leader knows the probability of opening different numbers of the follower’s new facilities. The leader aims at maximizing her own market share after the follower’s new facilities entry. The follower’s objective is also to maximize his own market share. Since the number of the follower’s new facilities is unknown for leader, “Robust Optimization” is used for maximizing the leader’s market share and making the obtained results “robust” in various scenarios in terms of different numbers of the follower’s new facilities. The optimal locations for new facilities of both the leader and the follower are chosen among pre-determined potential locations. It is assumed that the demand is inelastic. The customers probabilistically meet their demands from all different facilities and the demand level which is met by each facility is computed by Huff rule. The computational experiments have been applied to evaluate the efficiency of the proposed model.     

On a class of bilevel linear mixed-integer programs in adversarial settings

We consider a class of bilevel linear mixed-integer programs (BMIPs), where the follower’s optimization problem is a linear program. A typical assumption in the literature for BMIPs is that the follower responds to the leader optimally, i.e., the lower-level problem is solved to optimality for a given leader’s decision. However, this assumption may be violated in adversarial settings, where the follower may be willing to give up a portion of his/her optimal objective function value, and thus select a suboptimal solution, in order to inflict more damage to the leader. To handle such adversarial settings we consider a modeling approach referred to as \(\alpha \)-pessimistic BMIPs. The proposed method naturally encompasses as its special classes pessimistic BMIPs and max–min (or min–max) problems. Furthermore, we extend this new modeling approach by considering strong-weak bilevel programs, where the leader is not certain if the follower is collaborative or adversarial, and thus attempts to make a decision by taking into account both cases via a convex combination of the corresponding objective function values. We study basic properties of the proposed models and provide numerical examples with a class of the defender–attacker problems to illustrate the derived results. We also consider some related computational complexity issues, in particular, with respect to optimistic and pessimistic bilevel linear programs.     

Heuristics for the facility location and design (1|1)-centroid problem on the plane

A chain (the leader) wants to set up a single new facility in a planar market where similar facilities of a competitor (the follower), and possibly of its own chain, are already present. The follower will react by locating another single facility after the leader locates its own facility. Fixed demand points split their demand probabilistically over all facilities in the market in proportion to their attraction to each facility, determined by the different perceived qualities of the facilities and the distances to them, through a gravitational model. Both the location and the quality (design) of the new leader’s facility are to be found. The aim is to maximize the profit obtained by the leader following the follower’s entry. Four heuristics are proposed for this hard-to-solve global optimization problem, namely, a grid search procedure, an alternating method and two evolutionary algorithms. Computational experiments show that the evolutionary algorithm called UEGO_cent.SASS provides the best results.