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

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

3. Systems Integration Functional integration Physical 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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

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
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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
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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
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8. Intelligent DSS Self-evolving DSS Problem management
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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

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

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

11. Integration ERP Supply chain systems Knowledge management systems
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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

12. 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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

13. 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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

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

16. 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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18. 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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

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

21. 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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang

22. 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
© Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang