热电企业经营管理数据仓库建设

数据仓库技术是当前企业信息化应用领域的热点话题.本文对热电企业经营管理过程中如何构建数据仓库提出了新的解决方案,即将"自顶向下"和"自底向上"两种实施方式结合起来.首先分析了热电企业数据仓库体系化结构模型,然后具体介绍了热电企业数据仓库建设步骤,结合热力营销实例分析了数据仓库维度数据模型的设计方法.     

数据仓库与数据挖掘技术在客户关系管理（CRM）系统中的应用

利用数据仓库与数据挖掘技术实施企业CRM系统正逐渐成为企业管理中的热点。文章通过介绍数据仓库与数据挖掘技术的概念,对数据仓库与数据挖掘技术在企业CRM系统中应用的方式和技术进行了探讨。     

基于DW的金融信息管理系统研究与设计

本文主要探讨数据仓库技术和数据仓库在金融信息管理方面的应用,并设计出一种基于数据仓库的金融信息管理系统,该系统为金融机构和企业更好的管理和利用信息,在激烈的市场竞争中保持优势提供了一种新的技术途径。     

基于GIS技术的企业信息化系统研究

企业信息化系统集成了OA、ERP、CRM、DSS等模块,通过GIS的空间数据和地理位置信息服务,能够更好地发挥系统的功能,提高系统的效率。本文分析了企业信息化系统与GIS融合的可行性,设计了基于GIS技术的企业信息化系统的体系结构和网络结构,探讨了系统的功能,并对性能进行了研究。     

DSS的建设和业务流程重组

本文通过对建设DSS所遇到的主要问题分析,研究存在DSS支持下的组织结构和业务流程,并提出在DSS开发加入组织设计和业务流程重组过程的重要性.     

决策支持系统研究现状及发展趋势

DSS是当前信息系统研究的最新发展阶段,DSS的各类研究成果为各级各类决策提供了科学的方法和依据,因此DSS成为软科学中的一个重要分支.简要评述了近20年来DSS研究的理论成果与应用现状,分析了DSS研究存在的问题和不足,重点介绍了DSS研究发展趋势.     

企业实施数据仓库项目的技术经济分析

企业实施数据仓库项目,需要投入大量的物力财力,实施过程受到许多不确定因素的影响,项目投资具有一定的风险。而对数据仓库项目进行投资回报分析一直是让企业头疼的一个难题。本文结合项目具体实际,提出将技术经济的分析方法,引入数据仓库项目评估的设想,对数据仓库项目的投资回报作了定性和定量分析评价,推导出数据仓库项目实施的投资回报率(ROI)计算表达式。通过科学合理的分析方法对数据仓库项目进行分析评价,能保证项目实施的有效性,降低实施风险。     

医药流通企业供应链管理数据仓库模型设计

数据仓库技术以改进后的数据库技术进行数据存储和资源管理,弥补了传统数据库应用在决策支持方面能力的不足.本文根据医药流通企业供应链管理的特点和发展要求.构建医药流通企业供应链管理的数据仓库模型体系.该体系将数据仓库技术引入到医药流通企业供应链管理中,为建立企业的数据分析环境提供技术手段.     

证券公司经营管理数据仓库建设

本文分析了证券公司经营管理数据的特点,构建了证券公司数据仓库体系结构模型,具体介绍了证券公司数据仓库的建设步骤,从分析主题确定、维度逻辑模型设计、物理模型设计、ETL设计等几个方面详细阐述了该系统的设计过程。     

分布式数据仓库平台的应用研究

数据仓库可以为企业决策提供数据分析和信息预测,而传统的集中型数据仓库已经不能满足大型企业多层次的决策需求.本文根据实际应用,提出对于大型企业可采用分布式数据平台的构建模式,解决了多层次决策的问题,并对分布式数据仓库平台的实现技术、数据增量移植以及故障恢复等方面进行了研究.     

An Empirical Investigation of Information Search Strategies with Implications for Decision Support System Design

Understanding how people search through and combine information before making decisions is an important concern in the study of decision making and in the design of decision support systems (DSS). The purpose of this study is to examine DSS search strategies in relation to the body of empirical research on information load. Prior research is examined in relation to basic empirically-testable hypotheses and compared to the results of this study as a way of validating the procedures used here. The transfer of information load empirical research to a DSS scenario is confirmed statistically. Then, results of an analysis of information search patterns under DSS conditions are described. Finally, implications for DSS design are discussed in terms of possible search support mechanisms for specific search strategies.     

The Influences of User Characteristics on Performance in a Logistics DSS Application

Decision Support Systems (DSS) are widely used in logistics decision applications, and a large number and variety of systems are commercially available. We investigate the contributions of user characteristics including experiences, data preferences, intuition, and effort to decision performance in a logistics DSS context. The study includes a laboratory experiment in which decision makers with varied experiences used a DSS to make facility network design decisions for problems of varying complexity. Two variants of the DSS are utilized in order to examine the interactions of a DSS decision aid with user characteristics. We find that intuition and effort are associated with decision-making performance. High analytic ability is not related to intuition, however. Education and previous experience are associated with performance. Yet these characteristics are also unrelated to intuition. Decision makers who highly value disaggregated data provided by the DSS tend to perform poorly. Also, the results suggest that the effects of users' experiences and preferences on performance are influenced by an analytical decision aid.     

Complexity Factors and Intuition-based Methods for Facility Network Design

Logistics managers frequently utilize decision support systems (DSS) to make facility network design decisions. Many DSS do not provide optimization capabilities, but instead rely on scenario evaluation as a means for developing solutions. We experimentally assessed the performances of decision makers, including experienced managers, who used four variants of a scenario evaluation-based DSS to solve realistically sized network design problems of varying complexities. Complexity factors included DSS attributes, problem size, network types, and demand dispersion patterns. Decision makers' performances were assessed relative to optimal solutions. Overall, the decision makers generated relatively high-quality solutions using the DSS variants. The type of design problem solved did not significantly impact problem-solving performance. However, performance degraded and variability in solution quality escalated as problem size was increased. The availability of incremental solution cost improvement cues in the DSS significantly improved solution quality and reduced performance variability. Iconic graphic enhancements to the DSS did not consistently affect performance. However, significant interactions existed among the effects of DSS graphics capabilities, DSS information cues, and problem attributes.     

FINDING SYNERGY BETWEEN DECISION SUPPORT SYSTEMS AND EXPERT SYSTEMS RESEARCH

This article examines the potential for synergy between decision support systems (DSS) and expert systems research. Three predominant research traditions in DSS (applications, design, and technology) are examined and used as a basis to identify ways in which expert systems and DSS research interrelate. A range of emerging trends in DSS research that focus on these commonalities is discussed.     

Editorial Another milestone

A Master Production Scheduling Decision Support System within a multi-product medical supplies market has the dual task of providing good customer service levels while maintaining minimum reasonable levels of finished goods stock in the face of considerable internal manufacturing lead time and customer demand uncertainty. This paper examines the critical design parameters within an adaptive model highlighting how the total system orders in the internal pipeline are utilized in the decision-making process for assessing how much to load the internal manufacturing pipeline. Two different methods for tracking manufacturing lead times within the adaptive loop are also considered. Classical control concepts are applied within the Decision Support System (DSS) to avoid any long-term drift in finished stocks. Finally scenario analysis is performed via simulation for a set of design parameters and a range of stimuli typical of company operating situations. An effective decision support system design in terms of architecture and parameter settings is recommended based upon the ability of the model to maintain high customer service levels. The DSS readily interfaces between marketing and production functions to enhance company competitive advantage across a wide range of products.     

The Efficacy of a Decision Support System in Enhancing Risk Assessment Performance

A pervasive challenge for decision‐makers is evaluating data of varying form (e.g., quantitative vs. qualitative) and credibility in arriving at an overall risk assessment judgment. The current study tests the efficacy of a Decision Support System (DSS) for facilitating auditors’ evaluation and assimilation of financial and nonfinancial information in accurately assessing the risk of material misstatements (RMM) in financial information. Utilizing the proximity compatibility principle, the DSS manipulates the display of cues either in an integral (where pieces of information are displayed on one computer screen) or separable (where pieces of information are displayed on different computer screens) format. Based on cognitive fit theory, we expect that the integral (separable) display best supports financial (nonfinancial) information processing, leading to enhanced risk assessment performance. In addition, we predict that consistent DSS display of financial and nonfinancial information facilitates risk assessment performance. Further, this study accentuates the importance of auditors’ preference for presentation of financial and nonfinancial information and consistent presentation of all the information in strengthening the effect of DSS display format on risk assessment performance. We design a case which includes a seeded high fraud risk. A total of 112 audit seniors participated in the experiment where the DSS display format was manipulated and the auditors’ RMM assessments and display preferences were measured. The results support the hypotheses and highlight the value of the DSS in enhancing risk assessment performance.     

基于进程代数的DSS 模型系统建模与实现

把进程代数(process algebra , PA) 引入DSS 模型系统建模,提出一种新的DSS 模型建模理 论体系———DSS 模型代数,它可以描述模型之间激发、选择、重复、同步和并发等行为. 建立了 基于DSS 模型代数的模型系统与组件模型的对应关系,提出了基于组件技术的模型系统实现 方法,并通过一个实例给出实现方法的具体应用.     

The Design of a Knowledge-Based Decision Support System to Support the Information Analyst in Determining Requirements

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.     

User cognitive types for decision support systems

This paper describes and presents the results of an experiment that was used to investigate the relationships between cognitive types, information presentation and their effect on decision making performance within the context of an MIS/DSS. The experimental task required subjects to specify production levels for future periods given information on prior results. Ninety-six subjects performed the experiment, with 24 in each of the four Jungian cognitive type groups. All subjects received the same information for making decisions but different information presentation modes. The information presentation modes included raw and statistically summarized data and graphical and tabular layouts. The subjects were provided their results after each of their ten decision ‘runs’ via hard copy output. Decisions were entered at CRT terminals by the subjects. Experimental results demonstrated significant differences in performance by cognitive types. Decision performance rankings were partially supported by the results. Hypothesized pairings of cognitive types and information presentation modes were also partially supported. Implications of the results for MIS/DSS design are explored.     

CONTINUITY IN MIS/DSS LABORATORY RESEARCH: THE CASE FOR A COMMON GAMING SIMULATOR*

To date, case analyses and field studies have predominated in MIS/DSS research. Laboratory studies seem not to have been given the attention they deserve. This trend is partially due to: (1) the high costs associated with developing decision simulators and related software to support laboratory research and (2) difficult problems with external validity because of unrealistically simple simulated decision environments and DSS software. Since MIS/DSS laboratory research has been most successful when studies have occurred in an interrelated stream, the development of common, portable, and flexible simulators seems desirable. Common simulators would reduce the time and cost of developing experiments, provide for research continuity, comparability, and replication, and facilitate researcher-to-researcher communication. Sufficiently complex simulators and DSS software would reduce problems with external validity by providing more realistic laboratory models. This paper presents a software package that offers considerable potential as a common tool for DSS research.