知识经济时代传统会计之变革

知识经济条件下会计面临着变革。知识经济对公允价值计量、会计目标、会计处理程序与方法、会计报告内容、无形资产和人力资源成本与价值的确认、会计电算化发展等方面产生巨大影响。     

知识经济与就业革命

知识经济的到来 ,对传统的就业方式提出了重大挑战 ,引起了就业领域中就业结构、就业机会、工作制等多方面的转变 ,一场有关就业的文明革命悄然兴起。中国应通过提高劳动者素质 ,转变劳动者就业观念 ,调整国家就业政策等多方面措施 ,改善就业环境 ,刺激就业增长 ,以缓解目前所面临的巨大就业压力 ,迎接知识经济的挑战     

知识经济时代高校图书馆人力资源的管理开发

本文分析了高校图书馆人力资源管理和开发的现状,提出了加强人力资源管理开发的 措施和加大人员培养力度,建立一支高素质、专业化人才队伍的办法。     

论知识与知识性劳动

本文针对知识经济来临时代一些人对价值源泉的模糊认识,结合新的实际,在马克思主义经济学理论框架内对知识、知识性劳动进行了分析,在新的经济条件下发展了商品二因素理论和劳动二重性理论.在知识经济时代,人类劳动的主体形式从体力劳动转向智力劳动,知识成为当代经济发展的重要因素,但价值的源泉仍旧是人类劳动.本文通过区分知识和知识性劳动,澄清了模糊认识,阐明是知识性劳动创造了价值,而不是知识创造了价值.知识性劳动就是人们不断探索的劳动,从而知识经济的本质是创新,只有坚持劳动价值论,我们才能在知识经济社会中建立一个以人为本的、不断创新的经济运行机制.     

Seemingly unrelated regression on the autoregressive (Ar(p)) singular equation system

This paper studies the estimation of seemingly unrelated regressions (SUR) of singular equation systems with an autoregressive error process (AR(p)) for each equation.Parameter estimates of the autoregressive singular equation system are not generally invariant to the equation deleted. Under the model specification restriction on the autoregressive parameters, the invariance property is preserved, and this paper shows that a single equation generalized least squares (GLS) estimation for a general autoregressive error process is equivalent to the SURGLS estimation of the AR(p) singular equation system.     

我国MIS的开发现状及发展趋势

为适应体制转换和市场经济的要求 ,建立管理信息系统 (MIS)对我国企业极具重要性和紧迫感 ,本文分析了我国MIS的开发现状及存在的问题 ,提出了相应的措施 ,并尝试性地指出管理信息系统的发展趋势是知识信息系统 (KIS) ,并随着知识经济向更高阶段———智能经济的发展进化 ,知识信息系统也将向智能信息系统 (IIS)进化。     

近现代中国人观念现代化的历史进程与启示

近现代中国,观念现代化经历了鸦片战争以后的三次思想解放和启蒙阶段,五四运动以后马克思主义广泛传播和新民主主义革命时期的深化阶段。它给我们留下了深刻的启示。     

基于BPR的组织学习

BPR是组织在适应快速变化环境中最常用且最具革命性的方法,它能很好地促进组织进行创新性学习。本文旨在聚焦于BPR活动中的项目组和指导委员会来研究BPR在项目初始、分析和再设计阶段中通过流程定位和确定顾客偏好来促进组织学习问题,从而提出并建立一种组织学习的BPR方法促进论。     

A spanning heuristic for the unordered and ordered matching identification problem

The matching identification problem (MIP) is a combinatoric search problem related to the fields of learning from examples, boolean functions, and knowledge acquisition. The MIP involves identifying a single “goal” item from a large set of items. Because there is commonly a cost associated with evaluating each guess, the goal item should be identified in as few guesses as possible. As in most search problems, the items have a similar structure, which allows an evaluation of each guessed item. In other words, each guessed item elicits partial information about the goal item, i.e. how similar the guess is to the goal. With this information the goal is more quickly identified.The unordered MIP has been studied by Mehrez and Steinberg (ORSA J. Comput. 7 (1995) 211) in which they proposed two different types of algorithms. The purpose of the present paper is to suggest an improved Spanning Heuristic algorithm. Its improvement increases as the problem size increases. Further results and comparisons are derived for the unordered and ordered cases.This research shows that when the search space is very large, it is better to inquire from items that are known not to be the goal (they have been ruled out by previous guesses), for the purpose of acquiring more information about the goal. As the search space is narrowed, it is better to guess items that have not been ruled out.     

Task partitioning in new product development teams: A knowledge and learning perspective

R&D alliances and outsourcing elements of the new product development process are now commonplace practices among many firms. However, little previous work has examined how these organizational choices influence project knowledge and learning. Based on a comparison of three new product development projects in the software industry, this paper examines how task partitioning in the project influences learning and knowledge development within the firm. The paper suggests that internal development projects encourage synthetic learning and development of architectural and tacit knowledge; in contrast, outsourcing and joint ventures encourage analytic learning and development of component and explicit knowledge.