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© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-1 Chapter 15 Integration, Impacts, and.

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Presentation on theme: "© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-1 Chapter 15 Integration, Impacts, and."— Presentation transcript:

1 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-1 Chapter 15 Integration, Impacts, and the Future of Management-Support Systems Turban, Aronson, and Liang Decision Support Systems and Intelligent Systems, Seventh Edition

2 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-2 Learning Objectives Learn the processes of systems integration for MSS. Understand the difficulties in integrating systems. Describe major models in integration. Define intelligent DSS. Understand concept of intelligent modelling. Know MSS integration with enterprise and Web systems. Describe impacts of MSS on organization. Learn the potential impact of MSS on individuals. Define societal impacts of MSS. Be cognizant of the ethical and legal issues of MSS. Understanding the digital divide. Describe Internet communities. Overview of future of MSS.

3 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-3 Systems Integration Functional integration –Different applications provided as single system Across differing MSS or within MSS –Solves repetitive problems Integration of MSS techniques to build specific MSS Physical integration –Hardware, software, and communications integration Applications integration –Data, applications, methods, and processes Develop level integration Integrate to increase capabilities Integrate to enhance intelligent tools

4 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-4 Models Integration of expert systems and DSS –Expert systems attached to DSS ES 1: Database intelligent component ES 2: Intelligent agent for model base and management ES 3: System for improving user interface ES 4: Consultant to DSS ES 5: Consultant to users –Usually, only one or two are attached –Expert system as separate components Expert systems output as input to DSS DSS output as input to expert system Feedback –Expert systems generation of alternatives to DSS –Unified approach

5 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-5

6 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-6 Models –Tight integration due to shared interfaces and resources –Shared decision-making Expandable to other intelligent systems –Can integrate EIS, DSS and expert systems Information from EIS is inputted into DSS DSS feedback to EIS Expert system used for interpretation, explanation

7 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-7 Intelligent DSS Active DSS –Intelligent component Symbiotic Understands domain and provides explanations Helps formulate problems Relates problems to solver Interprets results Explains results and decisions

8 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-8 Intelligent DSS Self-evolving DSS –Aware of how it is being used and adapts to needs of use Dynamic menus User interface Intelligent model-based management system Problem management –Automate processes by dividing into smaller steps –Specific architecture to support functional requirements

9 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-9 Intelligent Modeling Intelligence added to allow input of expertise Multiple models available Construction –Simplify real world situation Less complex version of reality Use of models –Some judgmental values –Expert systems supply sensitivity analysis –Expert systems provide result explanations, patterns, anomalies Most based on quantitative models

10 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Integration Increases functionality Makes enterprise systems more user friendly Provides greater flexibility Saves money by integration various systems Enables easier integration of functional systems

11 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Integration ERP –Integrates analytical capabilities Supply chain systems –Enhance capabilities –Optimize tools Knowledge management systems –Communication, collaboration, storage DSS integration Intelligent systems integration Data mining tools with manufacturing systems DSS and learning systems Data mining with business modeling

12 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Issues Cost-benefit justifications Feasibility Architecture choices –Infrastructure –Development process and tools –Connectivity –Web-based integration Data issues Legal issues and privacy New technology introduction, integration

13 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Impacts of MSS Organizational –Culture –Creation of new departments –Virtual teams –Business process reengineering Business simulation tools –Increased production –Increased customer satisfaction –Improvement in quality –Supply chain management improvements –Improved performance of managers and employees

14 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Impacts of MSS Individual –Increased job satisfaction –Negative effect on individuality Dehumanization –Job stress –Lack of cooperation by expert

15 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Impacts of MSS Societal –Positive effects Reduction or elimination of humans in hazardous positions Increased opportunities for disabled, home bound, and single parents Telecommuting Improved health care Improved quality of life –Negative effects Computer fraud and embezzlement Identity theft Neglect of family Increased power due to increased centralization of organizations

16 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Legal and Privacy Issues Antitrust Unfair competition Unreasonable personal intrusion –Collection of information about individuals Ethics –Personal values Intellectual property rights –Copyright –Trademarks –Domain names –Patents Computer abuse Electronic surveillance Use of proprietary databases Data integrity

17 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 15-17

18 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Impacts of Artificial Intelligence Increased employment through newly created MSS-related jobs Massive unemployment through automation of processes Social implications –Increased leisure time –Government intervention with employment levels –Increased wealth

19 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Internet Communities Groups of people with common interests Interact through Internet Types –Communities of transactions Facilitate buying and selling –Communities of interest Based on specific topic –Communities of relations Organized around life experiences –Communities of fantasy Based on imaginary environments Game playing

20 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Digital Divide Growing gap between those who have and those who do not have access to technology Exists within and between countries

21 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Future of MSS MSS is becoming a Web-based technology Combining and integration with business intelligence BI is being combined with a number of Web-based applications Intelligent systems are being employed in the war against terrorism Web-based advisory services are being developed More complex MSS applications are being developed Trend toward increasing intelligence of systems Pervasive computing MSS are being disseminated via ASPs Natural language based search engines Semantic web

22 © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang Future of MSS Voice technologies are being enriched through use of MSS CRM improvement Improvement along supply chain through integration with ERP Expertise availability on Internet Initiation of formal knowledge-management programs More intelligent agents on Internet and other networks Greater use of wireless technologies Intelligent agents will roam the Internet, intranets, and extranets to monitor information and assist in decision- making Increase in groupware technologies for collaboration and communication DSS for e-commerce Decision-support tools for e-commerce will be expanded


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