Chapter 9 e-business Decision Support Learning Objectives




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《管理信息系统导论》双语教学

学生学习辅助资料

Chapter 9 E-Business Decision Support

Learning Objectives


  1. Identify the changes taking place in the form and use of decision support in e-business enterprises.

  2. Identify the role and reporting alternatives of management information systems.

  3. Describe how online analytical processing can meet key information needs of managers.

  4. Explain the decision support system concept and how it differs from traditional management information systems

  5. Explain how the following information systems can support the information needs of executives, managers, and business professionals;

    1. Executive information systems

    2. Enterprise information portals

    3. Enterprise knowledge portals

Chapter 9 Outline

Section I: Decision Support in e-Business


e-Business and Decision Support

Management Information Systems

Online Analytical Processing

Decision Support Systems

Using Decision Support Systems

Executive Information Systems

Enterprise Portals and Decision Support


Section2: Artificial Intelligence Technologies in Business


An Overview of Artificial Intelligence

Neural Networks

Fuzzy Logic Systems

Genetic Algorithms

Virtual Reality

Intelligent Agents

Expert Systems

Developing Expert Systems

The Value of Expert Systems

Chapter 9 Summary


  • e-Business Decision Support TrendsMajor changes are taking place in traditional MIS, DSS, and EIS tools for providing the information and modeling managers need to support their decision making. Decision support in business is changing, driven by rapid developments in end user computing and networking; Internet, Web browser, and related technologies; and the explosion of e-commerce activity. The growth of corporate intranets, extranets, as well as the Web, has accelerated the development of "executive class" interfaces like enterprise information portals, enterprise knowledge portals, and Web-enabled decision support software tools, and their use by lower levels of management and by individuals and teams of business professionals. In addition, the dramatic expansion of e-commerce has opened the door to the use of enterprise portals and DSS tools by the suppliers, customers, and other business stakeholders of a company for customer relationship and supply chain management and other e-business applications.

  • Information, Decisions, and Management.Information systems can support a variety of management decision-making levels and decisions. These include the three levels of management activity (strategic, tactical, and operational decision making) and three types of decision structures (structured, semistructured, and unstructured). Information systems provide a wide range of information products to support these types of decisions at all levels of the organization.

  • Management Information Systems:Management information systems provide prespecified reports and responses to managers on a periodic, exception, demand, or push reporting basis, to meet their need for information to support decision making.

  • OLAP and Data Mining: Online analytical processing interactively analyzes complex relationships among large amounts of data stored in multidimensional databases. Data mining analyzes the vast amounts of historical data that have been prepared for analysis in data warehouses. Both technologies discover patterns, trends, and exception conditions in a company's data that support their business analysis and decision making.

  • Decision Support Systems:Decision support systems are interactive, computer-based information systems that use DSS software and a model base and database to provide information tailored to support semistructured and unstructured decisions faced by individual managers. They are designed to use a decision maker's own insights and judgments in an ad hoc, interactive, analytical modeling process leading to a specific decision.

  • Executive Information Systems: Executive information systems are information systems originally designed to support the strategic information needs of top management. However, their use is spreading to lower levels of management and business professionals. EIS are easy to use and enable executives to retrieve information tailored to their needs and preferences. Thus, EIS can provide information about a company's critical success factors to executives to support their planning and control responsibilities.

  • Enterprise Information and Knowledge Portals:. Enterprise information portals provide a customized and personalized Web-based interface for corporate intranets to give their users easy access to a variety of internal and external business applications, databases, and information services that are tailored to their individual preferences and information needs. Thus, an EIP can supply personalized Web-enabled information, knowledge, and decision support to executives, managers, and business professionals, as well as customers, suppliers, and other business partners. An enterprise knowledge portal is a corporate intranet portal that extends the use of an EIP to include knowledge management functions and knowledge base resources so that it becomes a major form of knowledge management system for a company.

  • Artificial Intelligence:. The major application domains of artificial intelligence (AI) include a variety of applications in cognitive science, robotics, and natural interfaces. The goal of AI is the development of computer functions normally associated with human physical and mental capabilities, such as robots that see, hear, talk, feel, and move, and software capable of reasoning, learning, and problem solving. Thus, AI is being applied to many applications in business operations and managerial decision making, as well as in many other fields.

  • AI Technologies: The many application areas of AI are summarized in Figure 9.22, including neural networks, fuzzy logic, genetic algorithms, virtual reality, and intelligent agents. Neural nets are hardware or software systems based on simple models of the brain's neuron structure that can learn to recognize patterns in data. Fuzzy logic systems use rules of approximate reasoning to solve problems where data are incomplete or ambiguous. Genetic algorithms use selection, randomizing, and other mathematics functions to simulate an evolutionary process that can yield increasingly better solutions to problems. Virtual reality systems are multisensory systems that enable human users to experience computer-simulated environments as if they actually existed. Intelligent agents are knowledge-based software surrogates for a user or process in the accomplishment of selected tasks.

  • Expert Systems:Expert systems are knowledge-based information systems that use software and a knowledge base about a specific, complex application area to act as expert consultants to users in many business and technical applications. Software includes an inference engine program that makes inferences based on the facts and rules stored in the knowledge base. A knowledge base consists of facts about a specific subject area and heuristics (rules of thumb) that express the reasoning procedures of an expert. The benefits of expert systems (such as preservation and replication of expertise) must be balanced with their limited applicability in many problem situations.
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