基于Agent的物流配送决策支持系统研究

物流配送是一个涉及多种影响因素的综合性复杂问题。本文探讨了基于Agent(智能体技术)的物流配送决策支持系统设计，在该系统中的智能体模型中引入学习机制，初步建立了一个具有专家系统特点、可以不断进化的物流配送决策支持系统。     

装备器材保障信息化建设研究

结合信息技术发展，分析了装备器材保障信息化建设的现状，提出了装备器材保障信息化建设的目标，研究了系统总体构成、各级网络系统拓扑结构、各应用系统功能。并对装备器材保障信息化整体建设内容进行了规划分析。     

产业技术创新战略联盟的性质、分类与政府支持

产业技术创新战略联盟是合作研发的组织模式之一,承载着产业发展的目标,通过合作研发取得产业共性技术,并在联盟和全行业中扩散,最终实现产业竞争力的提升。产业共性技术的复杂性和准公共品性质、联盟合作创新的困境,决定了政府支持产业技术创新战略联盟的必要性。产业技术创新战略联盟有多种类型,政府应针对不同类型的联盟提供不同的支持。在明确产业技术创新战略联盟的内涵及性质的基础上,按照3个维度对其进行了分类,并借鉴国外经验给出了当前我国政府提供政策支持的建议。     

Adding Value to Applied Policy Models： The Case of the WTO and OECD Support Classification Systems

Both the OECD and the WTO have accumulated systematic data on the magnitude of support going to farmers as a result of farm policies. The datasets are collected for different purposes, but both give a detailed picture of the evolution of these policies. This paper extends recent work on the compatibility or otherwise of the two attempts at policy monitoring by considering the categorization of individual policy instruments in Norway, Switzerland, the US, and the EU. The results show how the OECD dataset, particularly with respect to the link between direct payments and production requirements, complements that of the WTO. Many payments classified in the WTO Green Box require production, raising the possibility that they may distort production and trade. Though the issue of correct notifications to the WTO is the province of lawyers, the implications for modeling and policy analysis are of interest to economists, and the broader question of improving the consistency of the two datasets is of importance in the quest for transparency in the interpretation of changes in farm policies.     

A new look at variation in employment growth in Canada: The role of industry,provincial, national and external factors

We examine fluctuations in employment growth using Canadian data from 1976 to 2010. We consider a wide range of models and examine the sensitivity of our findings to modelling assumptions. The results from our most preferred model, which we selected using the Bayesian Information Criteria, indicate that most of the variance in employment growth that is not due to the idiosyncratic error comes from domestic sources, with most of this coming from industry and provincial factors. Overall, we find that external and national factors play a much smaller role in employment fluctuations than in earlier research. We provide some possible explanations for these differences and discuss the implications of our findings for public policy and theory.     

组织信息化环境下知识流动对组织创造力的影响

通过解析知识流动和组织信息化环境的内部构成,探究知识溢出/知识扩散、高管支持/ICT应用对组织创造力的差异性影响,以及不同组织信息化环境对知识流动与组织创造力关系的调节作用。利用信息化程度较高的企业数据,使用层级回归分析进行实证检验。结果表明：组织创造力受知识流动的正向影响,知识扩散对其的正向影响更强;组织信息化正向影响组织创造力,相比ICT应用,高管支持对组织创造力的正向影响更强;高管支持在知识溢出/知识扩散与组织创造力之间的正向调节作用显著;ICT应用对知识扩散与组织创造力的强化作用显著强于对知识溢出与组织创造力之间的调节作用。     

Do capital flows drive credit growth and consumption in Central and Eastern Europe?

Domestic credit expansion in CEE economies, fuelled in part by foreign capital inflows, helped increase household welfare before the 2008 financial crisis caused a contraction across the region. How strong are the linkages between the current account, domestic credit and consumer spending? This study compiles a quarterly dataset of domestic credit as a share of GDP for 11 CEE European Union members and isolates structural breaks in the series’ growth rates that often align with the 2008 crisis. Vector autoregressive methods, particularly impulse response functions, show that increased current-account deficits lead to increased consumption in six of the 11 countries and increased credit growth in three, and that shocks to credit growth increase consumption in six countries. Capital inflows significantly increase consumption through domestic credit in Slovenia, while the Baltics show a large share of significant effects.     

Chinese competition and product variety of Indian firms

Using detailed firm-product-year data across manufacturing industries in India, and exploiting the exogenous nature of China’s entry into the WTO in 2001, we investigate the link between the impact of import penetration from China on the product variety of Indian manufacturing firms. We find: (i) robust and significant effects of product drop, with the effect coming only from competitive pressure in the domestic market; (ii) robust evidence of product drop or ‘creative destruction’ only for firms belonging to the lower-half of the size distribution; (iii) firms drop their peripheral/marginal products and concentrate on the core ones; and (iv) the result is strongest for firms producing intermediate goods. For an average Indian manufacturing firm, a 10 percentage point increase in India’s Chinese share of imports in the domestic market reduces the product scope of firms by 1.7–4.4%. In contrast, we find positive effects on product scope when firms are importing intermediate goods. We also find evidence of significant productivity effects and within-firm factor reallocation. Our results are consistent to a battery of robustness checks and IV estimation.     

A new multiscale decomposition ensemble approach for forecasting exchange rates

Due to the high complexity and strong nonlinearity nature of foreign exchange rates, how to forecast foreign exchange rate accurately is regarded as a challenging research topic. Therefore, developing highly accurate forecasting method is of great significance to investors and policy makers. A new multiscale decomposition ensemble approach to forecast foreign exchange rates is proposed in this paper. In the approach, the variational mode decomposition (VMD) method is utilized to divide foreign exchange rates into a finite number of subcomponents; the support vector neural network (SVNN) technique is used to model and forecast each subcomponent respectively; another SVNN technique is utilized to integrate the forecasting results of each subcomponent to generate the final forecast results. To verify the superiority of the proposed approach, four major exchange rates were chosen for model comparison and evaluation. The experimental results indicate that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach outperforms some other benchmarks in terms of forecasting accuracy and statistical tests. This demonstrates that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach is promising for forecasting foreign exchange rates.