产业集群协同创新知识共享策略的微分博弈研究

针对产业集群协同创新中核心企业和配套企业的知识共享问题, 通过构建微分博弈模型, 运用HJB方程分别考察三种知识共享博弈情形下核心企业和配套企业的最优知识共享策略。通过三种博弈结果的比较分析发现:Stackelberg主从博弈情形下, 知识共享投入补贴作为一种激励策略可促进配套企业知识共享意愿、双方各自知识共享收益以及双方知识共享总收益均优于Nash非合作情形;协同合作博弈情形下双方各自知识共享意愿、各自知识共享收益和双方知识共享总收益均优于非合作情形, 且收益分配系数α存在一个阈值, 可实现双方个体收益的帕累托最优。最后, 通过数值算例分析验证了理论推导的结果。     

协同创新视角下产学研合作行为决策机制研究

产学研合作是科技与经济结合的有效形式,协同创新理论对产学研合作提出了更高的要求。从协同创新视角出发,利用基于有限理性的演化博弈理论构建了企业与学研机构间的协同合作决策博弈模型,并对策略选择进行稳定性分析。理论研究和数值仿真结果表明:当企业和学研机构在协同合作中获得的经济收益净值大于其选择中途放弃获得的经济收益时,双方才会全部选择协同合作策略;产学研协同合作总收益、收益分配系数、赔偿系数和协同合作成本对企业和学研机构的决策结果有显著的影响,但作用机制有所不同;政府对产学研协同合作的资助和惩罚机制对企业和学研机构选择协同合作策略有促进的作用,但应将资助和惩罚力度控制在一定范围内发挥其最大激励效用。     

三级供应链内产学合作创新博弈分析

构建了一个三级供应链内产学合作模型.中游有两家企业,它们按古诺模型进行竞争生产同质产品;大学与中游企业进行成本节约型合作技术创新,企业之间存在技术溢出.研究表明:技术溢出值在一定范围变化时,两家企业创新策略为:[创新,搭便车],[创新,创新],[不创新,不创新].无论中游的一家企业还是两家企业与大学合作创新,上下游企业都可以获得创新收益.当控制技术溢出和产学合作收益分配比例时,无论中游的一家企业还是两家企业创新,都可以使产学双方,上下游企业收益增加,产品价格下降,社会福利增加,从而Pareto改进.     

基于复杂网络演化博弈的企业低碳创新合作行为网络演化机理研究

针对企业低碳创新合作所面临的复杂问题,基于现实复杂网络结构特征,运用演化博弈理论研究有限理性下企业低碳创新合作行为网络演化机理,利用Matlab仿真技术探究无标度网络载体上微观因素对低碳创新合作行为的影响。研究结果表明:低碳创新利益分配、协同效益和违约惩罚对低碳创新合作行为网络演化结果的影响最为显著,网络规模越大网络演化速度越慢,网络规模越小对协同系数和利益分配系数的敏感性越强,网络规模越大对技术溢出系数和违约惩罚的敏感性越强。研究结论可以为企业低碳创新合作策略制定提供解决依据。     

创新组织内知识共享的演化博弈

创新组织内持续知识共享可以从根本上提高创新组织的创新速度。在重点分析微观企业创新组织内知识共享特征的基础之上,采用复制动态的演化博弈来研究创新组织内知识共享行为的演化轨迹;研究发现:只有当共享主体双方协同收益均大于共享成本时,才有可能演化为双方均知识共享或均知识不共享的两种演化稳定策略,至于最终演化状态为均共享还是均不共享,又受到各模型参数变化的影响,降低共享成本、提高知识型员工的知识共享能力、共享知识量和人际关系损失成本概率、并建立一定的激励机制对于促进创新组织内知识共享行为的发生效果显著。     

考虑跟随企业搭便车行为的创新企业定价策略研究

文章通过构建博弈模型探讨了存在跟随企业搭便车行为时创新企业的定价策略及定价模式(稳定定价或动态定价),并分析了忠实消费者规模及需求溢出效应等特征对创新企业定价决策与利润的影响.结果表明,无论创新企业采用稳定定价或动态定价模式,跟随企业搭便车行为均会降低创新企业利润,需求溢出效应的增强总能使创新企业和跟随企业均获得更高的利润.动态定价模式下,当需求溢出效应较大时,创新企业会采用渗透定价策略;反之会采用撇脂定价策略.无论垄断或竞争市场情形下,均存在消费者规模阈值效应,即创新企业的利润随着忠实消费者规模的增大而先增大后减小.垄断市场下,动态定价模式能让创新企业获得更高利润;竞争市场下,当跟随企业质量处于较中间水平时,稳定定价模式能让创新企业获得更多优势.     

政府不同策略下用户创新知识交互差异化研究

知识交互是用户创新的重要环节,基于知识基础观和博弈论,考虑政府在用户创新中对企业与用户知识交互的激励作用,构建“政府-企业-用户”三方演化博弈模型,探讨政府不同策略下企业与用户之间知识交互行为的演化路径,分析不同约束条件下主体策略选择情况,并进行数值模拟。研究结果表明:政府政策激励在推动用户创新知识交互过程中有重要作用。当企业与用户知识交互紧密时,政府趋向于采取支持策略。当企业与用户知识交互收益小于某一阈值时,政府支持是决定用户创新知识交互的关键变量。当企业与用户知识交互收益处于某个范围时,政府支持并不会显著影响企业和用户的知识交互行为。     

信息非对称环境下产业创新平台多方主体博弈分析

研究产业创新平台在多方主体模式下的协同合作策略问题。我国产业创新平台发展时间较短,部分平台系统的资源共享和服务能力处于“弱势”,但通过多方主体协同合作能有效提升平台系统的技术创新水平,所以主体间的博弈会影响平台系统的存续质量与运行效率。基于此,本文构建了信息非对称环境下“产业链相关企业-各类研究型机构-政府管理部门”主要三方主体的静态博弈模型,从利益实现机制出发,强化各方主体在产业创新平台运行中的理性,以破解产业创新平台运行效率低下困局。研究表明,企业、研究机构和政府管理部门是否会严格遵循契约治理规范自身行为主要取决于各自的资源共享力度、资源共享成本以及资源共享的收益。     

基于前景理论的区块链自治组织知识共享协同合作演化博弈研究

知识共享协同合作是一个错综复杂的动态过程,在考虑到区块链自治组织利用通证来激励用户参与知识共享协同合作的背景下,本研究引入前景理论,旨在有效解释知识共享行为主体对通证收益的感知情况。为此,本文构建了知识共享协同合作收益感知矩阵,并基于该矩阵对博弈双方的行为策略进行了演化博弈分析,从而为知识共享协同合作的可持续性提供了有益建议。研究结果显示,用户对通证损益的感知价值、协同合作成本以及通证收益分配等因素,在用户持续参与知识共享方面扮演着关键角色。为促进区块链知识社区用户的知识共享协同合作稳定性,加强平台治理机制、优化通证激励模式,以及合理设置通证收益分配系数等措施被认为是十分有效的。本研究为理解区块链知识社区中涉及的复杂关系提供了新的视角,并为实现其可持续发展提供了实际可行的建议路径。     

基于关系契约视角的农户与农产品电子商务企业合作机制演化博弈分析

本文基于关系契约的视角,运用演化博弈理论,构建有限理性特性下的农户与农产品电子商务企业合作演化博弈模型,分析双方合作策略的演进过程、稳定策略及其影响因素,并通过Matlab仿真模拟分析影响双方合作策略选择的因素,验证博弈结果正确性。研究结果表明:农户和农产品电子商务企业选择合作策略与合作投入成本、实现的超额收益密切相关,博弈初始状态、再交易成本、单方不合作获得的收益及违约罚金等因素影响系统的演化稳定结果。因此完善农户与农产品电子商务企业的合作机制,需要构建合理的利益分配机制、良好的关系治理机制、有效的监督和惩罚机制和信息共享、沟通与协调机制。     

基于尖点突变的知识应用过程中溢出效应研究

本文引入“知识浓度”和“知识应用速度”两个概念,利用知识稀释效应的系统动力方程解释知识溢出机理。从突变视角分析了知识溢出的突变特性,借鉴尖点突变理论对系统动力方程进行换元变换,建立了知识溢出状态的尖点突变模型,讨论了知识稀释系统控制因子的变化与知识溢出状态间的判定规则,说明了知识应用过程中知识溢出特性如突跳、滞后效应等特性及知识溢出态和接受态之间转化的尖点突变机理。最后,利用我国31个省级行政区面板数据进行实证研究,揭示以省级行政区为对象的知识溢出状态、变化情况及发展趋势,为我国区域经济发展和知识战略提供理论指导。     

Effects of asymmetric knowledge spillovers on the stability of horizontal and vertical R&D cooperation

In order to investigate the role of asymmetric spillovers in the stability of R&D cooperation, this paper distinguishes two different types of cooperative partners, and uses a game theory approach to reveal the relationship between asymmetric spillovers and R&D investment in the horizontally and vertically related R&D cooperation. In the horizontal R&D cooperation, higher incoming spillovers and lower outgoing spillovers induce firms to invest on R&D efforts as agreed. However, it is the contradiction between horizontal firms’ attitudes towards asymmetric spillovers that leads to the inherent instability of the cooperation. In the vertical R&D cooperation, our results question the usually held opinion about the effects of asymmetric spillovers on the decision of R&D investment. The incoming spillovers are less important in the innovation process for vertically related R&D cooperation. A firm tends to under-invest on the arranged level of R&D efforts when its incoming spillovers increase. Our results also show that efficient mechanisms to restrain firms’ non-cooperative behavior are essential to improve the stability of horizontal and vertical R&D cooperation.     

基于AHP-TOPSIS评判模型的中药企业研发人员胜任力研究

研发人员作为企业中运用知识进行创新活动的群体,具有知识型员工的行为特质,因而导致研发人员的努力程度和贡献大小很难准确地测量.为了解决科学地评价研发人员胜任力的问题.在层次分析法(AHP)和逼近理想解的排序法(TOPSIS)两个理论的基础上,构建了AHP—TOPSIS综合评判指标体系模型,对3类中药企业研发人员胜任力进行综合评判优选.从职业态度、知识—技术、个人魅力、创新能力和团队合作能力5个方面综合考虑影响研发人员胜任力的评判指标,旨在为企业和不同行业全面评价以及甄选研发人才提供一种可行的方法.     

Group stability of hierarchies in games with spillovers

This paper studies the stability properties of hierarchies in cooperative problems with spillovers. The analysis builds on a recent paper by Demange [Demange, G. (2004) “On Group Stability in Hierarchies and Networks”, Journal of Political Economy 112(4), 754–778.], in which hierarchical structures are shown to attain stability by limiting the ability of certain coalitions to act autonomously and object to cooperative outcomes. We show that the stability properties of hierarchies crucially depend on the interplay of spillovers with the expectations that blocking coalitions form on the reaction of outsiders. In particular, we focus on pessimistic, passive and optimistic expectations, and on the classes of negative and positive spillovers. Under negative spillovers, hierarchies are shown to guarantee stability in all cooperative problems, but fail to sustain as stable all cooperative outcomes that are instead stable within non hierarchical organizations. Under positive spillovers we obtain opposite results: hierarchies fail to always guarantee stability, but sustain as stable all cooperative outcomes that are stable in non hierarchical organizations.     

Technological change,population dynamics,and natural resource depletion

In this paper, we integrate fertility and educational choices into a scale-invariant model of directed technological change with non-renewable natural resources, in order to reveal the interaction between population dynamics, technological change, and natural resource depletion. In line with empirical regularities, skill-biased technological change induces a decline in population growth and a transitory increase in the depletion rate of natural resources. In the long-run, the depletion rate also declines in the skill intensity. A decline in population growth is harmful for long-run productivity growth, if R&D is subject to diminishing technological opportunities. The effectiveness of economic policies aimed at sustained economic growth thus hinges on its impact on long-run population growth given the sign of intertemporal spillovers in R&D with respect to existing technological knowledge. We demonstrate that an increase in relative research productivities or an education subsidy enhances long-run growth, if R&D is subject to diminishing technological opportunities, while an increase in the teacher–student ratio is preferable in terms of positive intertemporal knowledge spillovers.     

家电企业和电商平台合作秩序的演化博弈分析

本文采用演化博弈方法对家电企业和电商平台之间的合作进行了建模,详细讨论了两者合作的成本和收益,同时考虑到违约发生时法律介入这一情况,分析了影响合作的各种因素。分析得出:合作的直接收益和谈判势力的分布对双方合作成功概率具有倒U型影响;价值创造系数、政策激励系数和合作开展深度对双方合作成功概率具有正向影响,而资本的专用性和交易成本具有负向影响;并且只有电商平台的时间折现因子会对合作成功概率产生正向影响;当违约发生时,一方通过法律援助可得到的赔偿与成功概率对双方合作成功概率具有正向影响,而法律成本具有负向影响;同时还得出,只要有一方通过法律途径可以收回自己的全部损失,那么唯一的均衡点就是都采取合作。最后指出这种家电企业和电商平台之间的合作类似哈耶克所提倡的“自发秩序”,并以此为出发点,认为政府应通过完善有利于这种“秩序”生长的外部环境来推动这种新经济成为社会发展的重要驱动力量。     

“互联网+回收”情境下基于演化博弈的电子废弃物回收合作机理研究

基于“互联网+回收”情境,研究网络回收商和流动回收小贩在电子废弃物回收中的竞合关系,构建演化博弈模型,刻画演化博弈过程,分析相关因素对演化稳定策略走向的影响。研究结果表明,网络回收商和流动回收商小贩选择合作策略的概率与违约惩罚力度、合作后的超额收益正相关,与合作后的共同成本、单独选择合作策略付出的成本以及因搭便车行为增加的收益负相关。由于分别存在最优的超额收益分配率和共同成本分摊率,网络回收商和流动回收小贩选择合作策略的概率最大。     

On the prisoner’s dilemma in R&D with input spillovers and incentives for R&D cooperation

This paper considers a standard model of strategic R&D with spillovers in R&D inputs, and extends the result that duopoly firms engaged in a standard two-stage game of R&D and Cournot competition end up in a prisoner’s dilemma situation for their R&D decisions, whenever spillover effects and R&D costs are relatively low. In terms of social welfare, this prisoner’s dilemma always works to the advantage of both consumers and society. This result allows a novel and enlightening perspective on some issues of substantial interest in the innovation literature. In particular, the incentive firms face towards R&D cooperation in the form of an R&D cartel is shown to be maximal for the case of zero spillovers, which is when the prisoner’s dilemma has the largest scope.     

Collaboration in R&D activities: Firm-specific decisions

In this paper, we study the strategic R&D collaboration by introducing a virtual player to reveal cooperative incentives and keeping investment share and market share independent of each other. Not consistently with the traditional opinions, we show that the superiority of the R&D cartel is due to the coexistence of cooperation and competition when spillovers are exogenous. Moreover, we conclude that high R&D input share must be reflected implicitly by high market share, and that firms’ R&D decisions vary with firms’ specific characteristics when spillovers is endogenous.     

A remark on multiobjective stochastic optimization via strongly convex functions

Many economic and financial applications lead (from the mathematical point of view) to deterministic optimization problems depending on a probability measure. These problems can be static (one stage), dynamic with finite (multistage) or infinite horizon, single objective or multiobjective. We focus on one-stage case in multiobjective setting. Evidently, well known results from the deterministic optimization theory can be employed in the case when the “underlying” probability measure is completely known. The assumption of a complete knowledge of the probability measure is fulfilled very seldom. Consequently, we have mostly to analyze the mathematical models on the data base to obtain a stochastic estimate of the corresponding “theoretical” characteristics. However, the investigation of these estimates has been done mostly in one-objective case. In this paper we focus on the investigation of the relationship between “characteristics” obtained on the base of complete knowledge of the probability measure and estimates obtained on the (above mentioned) data base, mostly in the multiobjective case. Consequently we obtain also the relationship between analysis (based on the data) of the economic process characteristics and “real” economic process. To this end the results of the deterministic multiobjective optimization theory and the results obtained for stochastic one objective problems will be employed.