基于动态AHP的企业信息化水平评价——江苏沙钢集团信息化水平案例研究

文章运用动态AHP方法研究企业信息化的发展过程,并结合江苏省沙钢集团企业信息化发展的案例,根据信息化五阶段模型,判断该企业信息化所处的发展阶段,继而对沙钢集团信息化发展提出战略性建议。希望不仅对沙钢集团有指导和推动作用,对其他企业的信息化发展也有启示和帮助。     

新疆地区税收与经济增长之间的实证分析

本文以新疆地区1994年-2009年间税收收入与经济总量GDP的发展现状为例,探讨了税收增长与经济增长的相关性,并提出了通过调整产业结构和税收政策的方式促进经济与税收之间的协调发展。     

基于DEA方法的商业银行效率研究进展

商业银行效率是商业银行经营者追求的重要目标,也是当前银行理论研究的核心问题之一。本文按照时间顺序分别对国外和国内商业银行效率研究的进展情况进行了简要的梳理和回顾,介绍了在银行效率研究中广泛应用的前沿分析方法。特别是运用基于DEA的Malmquist指数分析商业银行效率的相关研究。     

财务软件操作中常见问题解析——以金蝶KIS标准版为例

结合教学实践，分析金蝶KIS标准版财务软件的主要功能模块——系统维护及系统初始化设置模块、账务处理模块以及工资管理、固定资产管理、出纳管理等存在的常见操作问题，便于广大初学者熟练掌握会计软件。     

Impact of Financial Development on the Environmental Quality in Iran

In recent decades, undesirable environmental changes, such as global warming and greenhouse gases emission, have raised worldwide concerns. In order to achieve higher growth rate, environmental problems emerged from economic activities have turned into a controversial issue. The aim of this study is to investigate the effect of financial development on environmental quality in Iran. For this purpose, the statistical data over the period from 1970 to 2011 were used. Also by using the Auto Regression Model Distributed Lag （ARDL）, short-term and long-term relationships among the variables of model were estimated and analyzed. The results show that financial development accelerates the degradation of the environment; however, the increase in trade openness reduces the damage to environment in Iran. Error correction coefficient shows that in each period, 53% of imbalances would be justified and will approach their long-run procedure. Structural stability tests show that the estimated coefficients were stable over the period.     

A neuro-fuzzy combination model based on singular spectrum analysis for air transport demand forecasting

Air transport demand forecasting is receiving increasing attention, especially because of intrinsic difficulties and practical applications. Total passengers are used as a proxy for air transport demand. However, the air passenger time series usually has a complex behavior due to their irregularity, high volatility and seasonality. This paper proposes a new hybrid approach, combining singular spectrum analysis (SSA), adaptive-network-based fuzzy inference system (ANFIS) and improved particle swarm optimization (IPSO), for short-term air passenger traffic prediction. The SSA is used for identifying and extracting the trend and seasonality of air transport demand and the artificial intelligence technologies, including ANFIS and IPSO, are utilized to deal with the irregularity and volatility of the demand. The HK air passenger data are collected to establish and validate the forecasting model. Empirical results clearly points to the enormous potential that the proposed approach possesses in air transport demand forecasting and can be considered as a viable alternative.