基于商务智能平台的企业绩效管理框架研究

信息时代,越来越多的BPM框架引入数字仪表板、平衡计分卡、关键绩效指标等管理工具用以评估企业绩效,实时监测企业的运营状况,确保企业经营战略的成功实施,目的是使企业了解新一代BPM-BI的框架组成及其潜在的价值.首先介绍BPM产生的历史背景、BPM和BI之间的关系;其次,描述基于商务智能平台的企业绩效管理系统框架,讨论企业绩效管理系统中的BI技术工具和BPM的方法体系,主要从信息资源集成角度揭示企业绩效管理的管理效益和系统功能实施策略.     

企业知识管理中的案例推理思路与系统架构

在知识经济时代,有效实施知识管理(KM)成为企业重塑其核心竞争力的重要因素.增强对企业隐性知识的管理力度,在时空双维度内提升企业对案例知识的组织水平与应用效益,是有效实施知识管理的重要内容和难点所在,也是目前KM研究相时薄弱的领域.有鉴于此,详细分析了基于案例推理(CBR)技术的发展历程、核心技术思想以及系统工作流程,讨论了在企业知识管理中引入CBR的两条基本思路;在此基础上,设计了企业知识管理CBR系统架构,并对其要素组成、系统结构与工作机理进行了深入分析.     

企业知识管理中的知识集成方案与技术

针对当前企业知识管理对知识集成研究的不足,提出了对企业异构知识与系统的“间接整合”与“直接转化”相结合的集成策略,并对其中的公共知识模型、共同通信语言以及异构知识间的直接转化若干技术进行了深入探讨与分析,以指导企业KM的具体实施过程.     

商务智能解决方案比较研究——基于对五大主流供应商解决方案特点的分析

本文根据规模、市场关注度和发展势头选择了SAP、Oracle、IBM、Microsoft、SAS这五大型跨国商务智能供应商,并对它们提供的商务智能解决方案进行了分析,剖析了五家供应商解决方案的优缺点,指出各供应商商务智能解决方案的基本结构相似,但侧重点和长项各不相同。BI技术组件的性能和灵活性虽有差别,但并不是BI选型最重要的因素,按照企业的需求和现有条件选择BI解决方案才是正确的做法。     

浅析BI人才管理

商务智能能提高企业的核心竞争力,而BI人才是商务智能系统的建立的重要因素,本文介绍了BI人才的需求、技能要求、培养、能力中心以及企业的BI人才队伍建设,旨在读者对BI人才问题有一个较具体的了解.     

融人KM的企业神经系统的实现

本文通过对管理信息系统整合模型和知识管理(KM)相关理论的分析,提出了基于KM框架的企业神经系统模型及其实现过程.     

一种分布式动态知识基础设施的体系结构

分析了知识管理(KM)研究的现状和存在的问题,提出了一种基于应用到应用(A2A)模式、面向协同电子商务的知识基础设施(KI)的系统框架和体系结构模型,指出了该参考研究框架的关键问题和相关实现技术。     

复杂产品系统中KM活动及影响因素与研发绩效关系研究

从知识管理角度对CoPS进行了研究,提出了CoPS环境下KM影响因素、KM活动、研发绩效的关系模型。通过问卷调查,本研究收集了217个有效的样本数据,经过分析,得出以下主要研究结果:(1)复杂的知识特性是CoPS复杂性的根本;(2)CoPS环境下关键KM活动是知识创造和知识整合;(3)CoPS环境下KM活动对"KM影响因素-研发绩效"有着中介作用;(4)验证了CoPS环境下KM影响因素、KM活动、研发绩效的关系模型。     

知识管理与商务智能整合思考

在检索国内外相关文献基础上,通过比较知识管理和商务智能的异同点,对二者的关系进行了分析,并据此给出了二者进行整合的框架体系。文章提出在企业管理和决策实施过程中,知识管理和商务智能是既有差别、又相互关联的运作系统,二者必须有效整合,才能充分发挥各自的作用,提高决策质量和运作效率。     

大型工程有机共生集成优化系统体模型研究

论文结合特大型科技(工程)项目组织知识产生特点,从组织系统观、生态观两个视角对知识管理和学习型组织的耦合关系开展了研究,确立了特大型科技(工程)项目组织文化、组织战略、组织结构、组织学习与知识流动4个集成整合关键域,按着基于知识管理的学习型组织演化进程分为初始集成优化、发展集成优化、成熟集成优化、持续改进集成优化关键域,分析和研究了各个集成整合优化关键域的集成整合方法,构建了特大型科技(工程)项目组织知识管理与学习型组织有机共生集成优化系统体模型。     

基于知识管理与综合集成研讨厅融合的孵化器综合信息服务系统研究

针对孵化器不具备信息服务系统,或系统功能单一过于简单,或系统设计缺乏相应的科学理论而不能解决复杂问题的特点,提出构建基于知识管理与综合集成研讨厅融合的孵化器综合信息服务系统,并给出了系统框架和运作流程。     

组织文化、知识管理战略与绩效关系研究

摘要：以往关于组织文化和知识管理关系的研究,一般主张以文化的改造来适应知识管理,且偏重于质的分析。本文主张以不同的知识管理战略来适应既定的组织文化,并着重运用实证研究的方法,验证了知识管理战略与组织文化的适应性搭配对知识管理的有效性。     

Two forgotten elements of a knowledge management strategy

Knowledge Management Research & Practice - In reviewing the knowledge management (KM) literature, Guo & Sheffield (2008) show that KM research is part of the mainstream of information...     

商业智能提升企业信息化应用水平

企业信息化正在不断地向深度和广度双向推进，相应的信息技术也在不断地发展，商业智能作为一种新的信息技术在企业信息化中得到大量应用。本文就商业智能如何提升企业信息化以及在企业中应用模式进行探讨。     

Business intelligence impact on management accounting development given the role of mediation decision type and environment

Business Intelligence (BI) seeks to increase the profitability of the organization by making intelligent and accurate decisions. Management accounting (MA) reports are the score-card of an operation manager's efficiency. The operational; tactical, and strategic decision types make the road to achieving the goals of a company. Further, Environmental factors may affect the supply chain or increase the costs of materials. This study aims to investigate the impact of the BI on the development of MA in industrial companies. Samples are 200 Managers of these companies. The researcher-made questionnaire was employed to collect the required data. Factor analysis by reliability and item content technique verified by 0.896 Cronbach's alpha. Results revealed that the impact of BI on the development of MA is meaningful. For the β-values, the highest and the lowest effect of variables on success of BI is for decision type and flexibility variables, respectively. However, For the t-values, it is for data quality and integration with other systems (IOS) variables, respectively. Managers in industrial companies, should pay attention to decision type and data quality more than flexibility and IOS.     

Knowledge management technology-in-practice: a social constructionist analysis of the introduction and use of knowledge management systems

This paper argues that Knowledge Management Technology (KMT) is socially constructed in use based on the affordances and constraints of the technology artefact. Since many Knowledge Management (KM) systems are introduced with vague purposes (such as to improve knowledge sharing) it is therefore their affordances and constraints which strongly shape the socially constructed ‘KMT-in-practice’. The paper argues that knowledge is also socially constructed and that knowledge creation requires an element of surprise and challenge to routine. Using a case study of the British Council's KM programme between 1998 and 2003, the paper explores the social construction of a KMT as it is developed and used; describing how various features afforded by the technology influence its adoption and institutionalisation. The paper concludes by arguing that KMTs-in-practice, which are successful in supporting knowledge creation, must paradoxically remain in a state of neither stabilisation and acceptance, nor abandonment and disuse. Practical implications of how this might be achieved are provided.     

Machine learning models for evaluating the benefits of business intelligence systems

Due to the uncertainty of the market and the intensity of rivalry, business owners and managers are often compelled to experiment with a wide variety of strategies for enhancing their company's performance. By enhancing the timeliness and quality of inputs to the decision-making process, Business Intelligence (BI) is one such idea and tool that combines operational data with analytical tools to show complex and competitive information to planners and decision-makers. Business intelligence (BI) tools help companies rapidly generate insights that guide managers toward operational efficiencies, lead them to new opportunities, and set them apart from the competition. The literature study shows that there is a debate about whether BI tools have an effect on the quality of decisions and the development of businesses. The present research explores the varied empirical facets of BI application through ML models. This study concluded with a discussion of how Machine Learning models can be used to assess the value of BI tools. Machine learning models, fed with historical data and a wealth of input features, can foresee the effect of new systems on metrics like revenue development, customer behavior, and inventory management. Using these models, businesses will be able to better evaluate potential investments in new tools and systems.     

Knowledge-Based Risk Management framework for Information Technology project

The purpose of this paper is to explore the field of Risk Management (RM) in relation with Knowledge Management (KM). It attempts to present a conceptual framework, called Knowledge-Based Risk Management (KBRM) that employs KM processes to improve its effectiveness and increase the probability of success in innovative Information Technology (IT) projects. It addresses initiatives towards employing KM processes in RM processes by reviewing, interpreting the related and relevant literature and sheds light on integration with RM in the IT project.     

Knowledge,knowing, knower: what is to be managed and does it matter?

Knowledge Management Research & Practice - A knowledge management (KM) scope denotes our conception about what is relevant and useful, concerns what and how we are to manage, in KM. KM scopes...     

Creating the KM mindset: why is it so difficult?

Knowledge Management Research & Practice - The knowledge management (KM) mindset is a precursor to a knowledge-sharing culture. It is often assumed that developing a KM mindset is somewhat...