行政生态视角下政府组织模式的创新研究

随着信息时代的到来,行政生态环境发生了深刻的变化,传统的政府组织模式难以适应新时代的要求,组织模式变革成为政府改革的重要环节。本文从信息社会这一行政生态环境出发,探讨了电子化政府组织模式的管理理念、创新的管理方法,并对我国电子化政府组织模式的构建提出了相关的建议。     

基于多Agent系统的自调节及协同工作的组合投资模型

Agent技术特别是多Agent系统（MAS,Multi-Agent System）为解决人工智能等领域复杂问题提供了一个新途径,多Agent系统重点研究如何协调系统中的各个Agent的行为使其协同工作。针对多阶段组合投资问题,提出了一个基于多Agent系统的自调节及协同工作的组合投资策略模型。该模型系统中的各个Agent通过通讯共享知识,在求解问题的搜索空间中进行协同搜索,在更短的搜索步长内得到问题的解,极大地提高了系统性能。该模型具有不基于任何股票模型、时间复杂度低以及逼近最优投资策略速度较快等优点,实验证明具有一定的实际意义。     

基于RBAC模型实现电子政务系统业务的柔性处理

电子政务的迅速发展,加大了业务处理的复杂度,先前的系统业务处理功能虽然丰富,但随着需求的不断变更和业务处理的不断重组,使得系统的适应能力已逐渐不能满足这种变化带来的柔性需求。文中根据电子政务系统存在业务处理流程中的“固化”的现象,引进基于角色的访问控制（RBAC）模型,从顶层设计的高度,利用基于数据字典的系统实现方法,实现了系统对业务的柔性处理,增强了业务处理的灵活性,从而提高系统的适应能力,进一步使得基于电子政务的政府机构办事效率提高。     

Valuing pilot projects in a learning by investing framework: An approximate dynamic programming approach

We introduce a general discrete time dynamic framework to value pilot project investments that reduce idiosyncratic uncertainty with respect to the final cost of a project. The model generalizes different settings introduced previously in the literature by incorporating both market and technical uncertainty and differentiating between the commercial phase and the pilot phase of a project. In our model, the pilot phase requires N$N$ stages of investment for completion. With this distinction we are able to frame the problem as a compound perpetual Bermudan option. We work in an incomplete markets setting where market uncertainty is spanned by tradable assets and technical uncertainty is idiosyncratic to the firm. The value of the option to invest as well as the optimal exercise policy are solved by an approximate dynamic programming algorithm that relies on the independence of the state variables increments. We prove the convergence of our algorithm and derive a theoretical bound on how the errors compound as the number of stages of the pilot phase is increased. We implement the algorithm for a simplified version of the model where revenues are fixed, providing an economic interpretation of the effects of the main parameters driving the model. In particular, we explore how the value of the investment opportunity and the optimal investment threshold are affected by changes in market volatility, technical volatility, the learning coefficient, the drift rate of costs and the time to completion of a pilot stage.     

One-side value-added service investment and pricing strategies for a two-sided platform

To widen user participation and increase profit, two-sided platforms may invest on value-added services (VASs) for users. Due to the cross-market network externality, the investment for one side would affect the utility of users on two sides, thus affect the demand and profit of the platform. In this paper, we investigate one-side VAS investment and pricing strategies for a two-sided platform. It is revealed that it is optimal to invest at the maximum level for any marginal investing cost below a certain threshold, and to decrease the investment when the marginal investing cost increases above the threshold. We find that compared with the case of no investment, the invested user side will always be priced higher, while the uninvested user side may either be priced higher or lower, depending on the relative magnitude of mutual cross-market network externalities. If both sides are priced higher after the investment, the price increment for uninvested user side could be larger than that for invested user side.     

Evaluating learners’ motivational and cognitive processing in an online game-based learning environment

This paper describes the process and results of an evaluation on an online game-based learning environment (GBLE) by focusing on learners’ motivational processing and cognitive processing. The goal is to explore how online GBLE might initiate and support learners’ goal-setting activities and impact learners’ cognitive loads. The study surveyed 144 undergraduate students after their autonomous participation in the online game available at the Nobel Prize Foundation website teaching the Heckscher-Ohlin Theory on international trade. Grounded in the integrative theory of motivation, volition, and performance (MVP), the evaluation indicated that participants felt significantly confident in learning the subject. The perceived satisfaction, however, was lower than the rest of motivational components possibly due to heavy cognitive processing. The finding of cognitive load reported that learners perceived a significantly higher level of intrinsic load than the germane load due to the novelty of the subject matter. Data analysis further indicated a significant canonical correlation between learners’ motivational and cognitive processing. This particular finding could inform future research to investigate specific motivational processing components’ effects on learners’ cognitive load levels in online GBLEs.     

基于移动平均线组合和支持向量机的股市趋势研究

证券投资是一种高风险、高收益的理财方式,而对市场运行趋势的良好把握有助于投资者回避风险、把握机会。提出基于多条移动平均线斜率组合和支持向量机算法,判断当前市场运行趋势,从而采取相应的投资策略。模拟实验证明,该方法取得了良好的效果。     

Robust portfolio optimization via solution to the Hamilton–Jacobi–Bellman equation

We consider a problem of dynamic stochastic portfolio optimization modelled by a fully non-linear Hamilton–Jacobi–Bellman (HJB) equation. Using the Riccati transformation, the HJB equation is transformed to a simpler quasi-linear partial differential equation. An auxiliary quadratic programming problem is obtained, which involves a vector of expected asset returns and a covariance matrix of the returns as input parameters. Since this problem can be sensitive to the input data, we modify the problem from fixed input parameters to worst-case optimization over convex or discrete uncertainty sets both for asset mean returns and their covariance matrix. Qualitative as well as quantitative properties of the value function are analysed along with providing illustrative numerical examples. We show application to robust portfolio optimization for the German DAX30 Index.     

A comprehensive investigation on the relationship between information technology investments and firm diversification

This paper empirically investigates the role played by information technology in diversified firms by building a demand function for IT investments. First by reviewing the management literature, we briefly examine different types of diversification, including related diversification, unrelated diversification, and geographic diversification. After carefully developing the theoretical arguments we empirically test the relationship between IT investments and different types of diversification. We find that in general diversified firms demand more investments in information technology, but the positive relationship may also depend on the extent to which firms diversify. Our findings show that firms with diversified structures that increase the complexities of coordination and control, e.g. unrelated diversification or extensive geographic diversification, would face a lesser demand for IT investments because of the increased use of financial controls instead of strategic controls by these firms. Overall, we find that information technology can serve as an effective coordination and control mechanism for moderate levels of diversification whereas non-IT mechanisms for coordination and control becomes more suitable in a context of higher levels of diversification. The implications of these findings for research and practice are discussed.

证券投资交易系统技术实现中若干问题的研究

文章给出了一个证券交易与信托投资系统的网络结构框架和技术实现方法,并针对该类系统技术实现过程中所面临的一些关键性技术问题进行了研究与探讨,给出了相应的解决方案。这些问题与解决方案对于基于Internet的证券交易系统以及信托投资管理系统也具有一定意义。