适应性预期、复杂网络与标准扩散动力学——基于计算经济学的研究

标准扩散是现代产业经济中的重要问题.主要采用复杂网络的小世界网络模型和基于agent的计算机建模技术,结合行为博弈学习理论中的EWA算法,对网络外部性下标准扩散过程中的适应性预期进行研究.基于个体在局部网络中的交互作用和个体行为的学习演化与预期自适应调整,通过计算机仿真就适应性预期对标准扩散的影响从多方面进行分析.研究结果揭示了个体适应性预期在标准扩散中的重要作用,发现扩散中的"涌现"现象,个体邻域结构的随机性对标准扩散结果及其最终分布状态有很大的影响,个体预期能够逆转标准扩散中的先发优势,预期速度调整因子在不同预期强度下有完全不同的影响,个体对新标准的较高预期也是新标准得以扩散的必要条件.     

A note on special optimal batching structures to minimize total weighted completion time

A batch is a subset of jobs which must be processed jointly in either serial or parallel form. The algorithmic aspects of the batching scheduling problems have been extensively studied in the literature. This paper presents necessary and sufficient conditions of the existence of optimal batch sequences for the single machine, batching, total weighted completion time scheduling problems on two batching ways: (1) all jobs form one batch; (2) each batch contains a single job. This kind of conditions can help us to recognize some special optimal schedules quickly. Research supported by NSFC (10671183).     

Developing virtual team performance: an integrated perspective of social exchange and social cognitive theories

Review of Managerial Science - The emerging trend toward physically distributed work teams has necessitated a critical inquiry into the nature and roles of psychological contract and leadership in...     

Multiple L(j,1)-labeling of the triangular lattice

Let n,j,k be nonnegative integers. An n-fold L(j,k)-labeling of a graph G is an assignment f of sets of nonnegative integers of order n to the vertices of G such that, for any two vertices u,v and any two integers a∈f(u), b∈f(v), |a?b|≥j if uv∈E(G), and |a?b|≥k if u and v are distance two apart. The span of f is the absolute difference between the maximum and minimum integers used by f. The n-fold L(j,k)-labeling number of G is the minimum span over all n-fold L(j,k)-labelings of G. Let n,j,k and m be nonnegative integers. An n-fold circular m-L(j,k)-labeling of a graph G is an assignment f of subsets of {0,1,…,m?1} of order n to the vertices of G such that, for any two vertices u,v and any two integers a∈f(u), b∈f(v), min{|a?b|,m?|a?b|}≥j if uv∈E(G), and min{|a?b|,m?|a?b|}≥k if u and v are distance two apart. The minimum m such that G has an n-fold circular m-L(j,k)-labeling is called the n-fold circular L(j,k)-labeling number of G. This paper provides upper and lower bounds for the n-fold L(j,1)-labeling number and the n-fold circular L(j,1)-labeling number of the triangular lattice and determines the n-fold L(2,1)-labeling number and n-fold circular L(2,1)-labeling number of the triangular lattice for n≥3.     

网络治理研究前沿与述评

"网络治理"是一个跨学科的研究领域,是技术网络、组织网络和社会网络研究的热点问题,企业网络治理也是工商管理领域的前沿研究方向。技术网络治理、社会网络治理、组织网络治理以及三者的融合是当前组织理论和战略管理理论研究的核心命题,也是中国经济转型过程中转换企业发展模式、实现后发优势的重要课题。本文首先对技术网络治理、社会网络治理和组织网络治理近年来国内外相关研究进行回顾;进而从网络组织与网络治理的内涵、公司治理到网络治理的发展、研究内容及科学问题以及研究动因和研究方法等视角对已有研究文献进行述评;在此基础上,提出了可供研究者参考的未来研究方向。     

分支蚁群动态扰动算法求解TSP问题

蚁群优化算法是一种求解组合优化难题的强启发式算法,它利用正反馈和并行计算原理,具备很强的搜索能力。近年来,蚁群优化算法广泛应用于TSP问题的研究。本文提出分支蚁群动态扰动(DPBAC)算法,该算法主要从5个方面对基本蚁群算法做出改进:引入分支策略选取出发城市;改进状态转移规则;引入变异策略改进蚂蚁路径;改进信息素更新规则;引入条件动态扰动策略。实验表明,该算法可以有效改善基本蚁群算法搜索时间较长、容易陷入局部极小等缺点。     

A hybrid ARIMA and support vector machines model in stock price forecasting

Traditionally, the autoregressive integrated moving average (ARIMA) model has been one of the most widely used linear models in time series forecasting. However, the ARIMA model cannot easily capture the nonlinear patterns. Support vector machines (SVMs), a novel neural network technique, have been successfully applied in solving nonlinear regression estimation problems. Therefore, this investigation proposes a hybrid methodology that exploits the unique strength of the ARIMA model and the SVMs model in forecasting stock prices problems. Real data sets of stock prices were used to examine the forecasting accuracy of the proposed model. The results of computational tests are very promising.     

业务外包风险分析与控制

结合现代企业理论中的交易费用理论和“委托-代理”理论,对业务外包风险进行了深入的剖析,详细分析了外包决策和执行两个阶段的风险,并提出了相应的风险控制策略。     

基于提前期的多阶通用件库存模型

针对单个企业内部应用通用件的环境,在假定一个多阶生产系统的基础上,对应用通用件的库存量水平及其成本进行了分析,建立了多阶通用件库存模型,提出通过对采用通用件和不采用通用件的成本差异的比较,来决策多阶生产系统中在哪一阶工序采用通用件,并求解出每一阶工序优化的基本库存水平。