Turban, Aronson, and Liang
Decision Support Systems and Intelligent Systems,
Seventh Edition
Chapter 15
Integration, Impacts, and the Future
of Management-Support Systems
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
15-1
Learning Objectives
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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.
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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Models
• Integration of expert systems and DSS
– Expert systems attached to DSS
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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Integration
• ERP
– Integrates analytical capabilities
• Supply chain systems
– Enhance capabilities
– Optimize tools
• Knowledge management systems
– Communication, collaboration, storage
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DSS integration
Intelligent systems integration
Data mining tools with manufacturing systems
DSS and learning systems
Data mining with business modeling
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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Issues
• Cost-benefit justifications
• Feasibility
• Architecture choices
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Infrastructure
Development process and tools
Connectivity
Web-based integration
• Data issues
• Legal issues and privacy
• New technology introduction, integration
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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Impacts of MSS
• Organizational
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Culture
Creation of new departments
Virtual teams
Business process reengineering
• Business simulation tools
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Increased production
Increased customer satisfaction
Improvement in quality
Supply chain management improvements
Improved performance of managers and
employees
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Turban, Aronson, and Liang
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Impacts of MSS
• Individual
– Increased job satisfaction
– Negative effect on individuality
• Dehumanization
– Job stress
– Lack of cooperation by expert
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
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Computer fraud and embezzlement
Identity theft
Neglect of family
Increased power due to increased centralization of
organizations
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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
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Copyright
Trademarks
Domain names
Patents
Computer abuse
Electronic surveillance
Use of proprietary databases
Data integrity
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
15-16
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
15-17
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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Turban, Aronson, and Liang
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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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Turban, Aronson, and Liang
15-19
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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Turban, Aronson, and Liang
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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
© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition,
Turban, Aronson, and Liang
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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 decisionmaking
• 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, Aronson, and Liang
15-22