© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban,...

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

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Chapter 15Integration, Impacts, and the

Future of Management-Support Systems

Turban, Aronson, and Liang Decision Support Systems and Intelligent

Systems, Seventh Edition


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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.


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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


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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


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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


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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


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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


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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


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Integration

• Increases functionality

• Makes enterprise systems more user friendly

• Provides greater flexibility

• Saves money by integration various systems

• Enables easier integration of functional systems


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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


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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


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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


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Impacts of MSS

• Individual– Increased job satisfaction– Negative effect on individuality

• Dehumanization

– Job stress – Lack of cooperation by expert


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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


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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


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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


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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


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Digital Divide

• Growing gap between those who have and those who do not have access to technology

• Exists within and between countries


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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


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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

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban,...

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