Decision Technologies in Management Track

Track Chair

Data Mining and Information Retrieval

Comprehensibility of data mining techniques, data visualization, task and model interaction, data quality assessment, interpretability, scalability, human factors and modeling, performance measurement and validation, acquisition of qualitative knowledge, feature selection, and the economics of decisions are some of the topics being sought. Examples of applications are point of sale data analysis for customized marketing, credit card as well as mobile telephone transaction data analysis for fraud detection, stock market prediction, book searching in electronic bookstores and auctions, and digital library catalogues among others. Models come from a variety of fields including statistical analysis, neural networks, fuzzy logic, intelligent agents, multidimensional analysis, data visualization, and decision trees, etc. Relevant software and economic issues will also be considered. . Also, major data mining research programs from both academic and industry groups are encouraged to submit results that address real world problems. Possible Topics may include, but are not limited to, the following areas:

• Measuring Model Performance
• Algorithms and Tools
• Task Characteristics
• Data Quality, Size, and Representation
• Web-based Data Mining
• Multimedia and Temporal Data
• Qualitative Knowledge
• Knowledge Reuse
• Active Learning
• Human Factors and Environmental Issues
• Mining Methodology Issues
• Scalability and Preprocessing
• Internet Interface with Information Retrieval
• Model Interpretation
• Sensitivity and Generalizability
• Economics and Cost of Errors
• Geographic Data
• Data Visualization
• Text Categorization and Summarization
• Cross Language Retrieval
• Speech and Broadcast Retrieval
• Application Case Studies
• Industry Projects

Minitrack Chairs

Decision Technologies for Supply Chain Management

• Strategic Management; design of the supply network, choice of partners, vertical integration and outsourcing, product design and lifecycles
• Tactical Management; purchasing, (vendor-managed) inventory, and production planning, collaborative forecasting and replenishment, distribution and transportation planning, design of information and work flows
• Operational Management; Available-to-Promise (ATP), Capable-to-Promise (CTP), scheduling of machines and staffs, routing of products and vehicles, organization of returns and services

• Simulation of entire supply chains enable managers to assess different design scenarios with respect to e.g. locations, planning algorithms, and cost structures
• Advanced Planning and Scheduling (APS) software systems which employ optimization and simulation algorithms in order to provide decision support for strategic network planning, demand planning, master planning, demand fulfillment and ATP/CTP, Production Planning and Scheduling and Distribution and Transport Planning
• Agent Technologies can assist with various activities in the supply chain. These include information gathering, filtering, and distribution throughout the supply chain, analysis and negotiation within marketplaces, triggering alerts and re-planning activities etc.
• Data Warehousing, OLAP, and Data Mining; these technologies assist managers in the gathering, reporting on, and analysis of information of the entire supply chain
• Descriptive models are an important tool for analyzing, benchmarking, and re-designing supply chains
• Forecasting models and algorithms are an integral part of all supply chain software systems. They are building blocks enabling real-time information sharing throughout the supply chain

Minitrack Chairs

Mark E. Nissen School of Business and Public Policy Naval Postgraduate School 555 Dyer Road, Code SM/Ni Monterey, CA 93943-5000 MNissen@nps.navy.mil Tel: 831-656-3570 Fax: 831-656-3407

Enterprise Architecture, Implementation, and Infrastructure Management

The mini track addresses such fundamental questions as:

• What are the different approaches to EA and what is their scope?
• How do we model EA?
• What are the enabling technologies for EA?
• How do we successfully implement and deploy EA in an organization?
• How do we manage information technology infrastructure in an organization?

While focusing on a holistic and integrated view of an organization, EA often can be subdivided into components such as business architecture, data architecture, application architecture, and technology architecture in order to contain the complexity of the design problem.

Possible Topics include the following:

• Enterprise architecture concepts and categorization
• Enterprise modeling techniques, implementation of processes, and policies.
• Software architecture and component-based development
• Interoperability and integration in large-scale systems
• Meta modeling
• Infrastructure support and enterprise services
• Mobility, scalability, security, and reliability issues
• Business model (in particular, e-business models) and organizational infrastructure
• Business process improvement support
• Information infrastructure
• Information system infrastructure
• Data architecture
• Application architecture and portfolio management
• Middle-ware management
• Interface management
• Quality of service management
• Web-based configuration management
• Network design and planning
• Security management
• IP Telephony and internet management
• Fault management
• Policy-based management
• Broadband impact and infrastructure
• Strategies and pricing of network management service
• Standards and regulations
• Network management protocols
• Intelligent mobile agent
• Distributed object technologies
• Broadband and multimedia network management
• Architectural element evaluation criteria
• Architecture repository structure and implementation
• Innovative tools in support of Enterprise Architecture
• Enterprise Architecture implementation cases

Minitrack Chairs

e-Services

1. Concepts, models, and methods for creating for e-services,
2. theory building or framework construction research through empirical, qualitative, or technical “proof of concept” system-design approaches, and
3. innovative applications and case studies highlighting challenges, issues and e-service solutions.

Relevant topics for this minitrack include (but are not limited to) the following:

1. e-services: Concepts, Modeling, Design, and Evaluation.
   • Concepts and methods for designing and delivering e-services
   • Theoretical frameworks and practical challenges, and research issues
   • Definition of XML-based e-services
   • Decision support mechanisms, methods, and tools for e-service design
   • Use of XML infrastructures for the design and delivery of e-services
   • Decision support for e-service delivery infrastructure design
   • Use of XML technologies for customization of e-services
   • Methods and concepts for one-to-many delivery and mass-customization
   • Experiences of using industry-standardized XML vocabularies for design and management of e-services
   • Knowledge management across families of related e-services
   • Design and process traceability for rapid design and delivery
   • Tools and mechanisms for redevelopment cycle time compression
   • Component-based architectures and modularity in e-service design
   • Relationships and comparison with information systems development (ISD) paradigms and theories
   • Usage and measurement mechanisms for pricing and charging for e-services
   • Scalability, integration, and maintenance considerations
   • Innovation management in the context of e-services
   • Decision support tools and coordination (collaborative, versioning, etc.) mechanisms for e-service design in temporally and spatially distributed virtual teams
   • Management of e-services
   • Theory building case studies of ISPs, e-commerce back office services, and ASPs
   • Integrating enterprise resource planning (ERP) and e-service platforms and tools
2. e-services: Applications.
   • Innovative implementations of e-service delivery systems
   • Single case studies and multi-case analyses of e-service implementation
   • Empirical research on the e-services
   • "Proof of concept" intelligent decision support tools for e-service design
   • Practioner reports on e-service implementation trials and tribulations

Minitrack Chairs

Intelligent Systems and Soft Computing

1. problem solving,
2. planning and
3. decision making, in contexts which range from
4. strategic management,
5. business process reengineering and
6. electronic commerce, to
7. production,
8. marketing and
9. financial management, and to
10. smarter IS applications for operational management.

Soft computing includes research on fuzzy logic, artificial neural nets, genetic algorithms and probabilistic modeling.

Intelligent systems include the following categories of systems:

• Knowledge based systems and expert systems
• Software agents
• Multiple criteria optimisation and support systems
• Genetic algorithms
• Artificial neural nets and self-organising maps
• Innovative and active DSS
• Smart MS Office & Windows designs

• Knowledge based systems
• Expert systems
• Software agents
• Multiple criteria optimisation and support systems
• Genetic algorithms
• Artificial neural nets and self-organising maps
• Innovative and active DSS
• Smart MS Office & Windows designs

Minitrack Chairs

Intelligent Systems in Traffic and Transportation

We seek research papers, case studies and practitioners reports relating to the design, the implementation and the use of Intelligent Systems built for particular problems in Traffic and Transportation. The papers need not to present fully developed complex systems. Conceptual papers, empirical papers and papers dealing with particular components of such a system, e.g. the Intelligent Techniques, are also welcome. Therefore, relevant topics for the Minitrack include (but are not limited to)

1. Modeling Intelligent Systems in Traffic and Transportation
   • Models for the estimation of future volume of traffic likely to be affected by planned projects or management policy
   • Models introducing changes in travel behavior
   • Agent-based modeling and simulation of traffic related problems
   • Transportation Network Design Problems including different modes of transportation and hubs
   • Vehicle Routing and Crew Scheduling Problems (e.g. in air transportation)
2. Intelligent Techniques applied to combinatorial optimization problems in traffic and transportation logistics
   • Tabu Search Metaheuristics
   • Population-based methods (Genetic and Evolutionary Algorithms)
   • Constraint programming
   • Multi-Agent Approaches

Minitrack Chairs

Mobile Commerce: Core Business Technology And Intelligent Support

• Research into finding and identifying potential customer groups for fast-growing value added mobile e-commerce. This issue points to the need for new or innovative e-commerce models and will require that both new methods for Internet research and good supporting technology will be developed.
• Research into the design, development and implementation of mobile e-commerce solutions for selected customer groups. If and when target groups for value-added services can be identified, this issue points to the need to develop/adapt new or innovative technologies for localized, personalized, ubiquitous, timely and convenient m-commerce service solutions.
• New and enhanced systems solutions for integrated production and distribution of m-commerce products and services. The elimination of bottlenecks and the modification and enhancement of service capacity will need (for instance) enhanced network architectures, intelligent information systems and agent technology. There will probably be a need to improve the network infrastructure for both producers and consumers of m-commerce products and services, as well as the process intermediaries.
• The design and development of value added user interfaces and user support systems for mobile e-commerce customers. This issue outlines the need to verify and validate the functionality of the new technologies and to prove that they are value adding. At the same time, we need better knowledge about the true functionality and substance of new m-commerce products and services.
• New methods for finding and evaluating value added services for customer groups. This issue points to the need for a proactive design of emerging m-commerce products and services ahead of the market (probably based on mobile new technology), interactive empirical tests with potential customer groups, feedback to the technology developers and testing of redesigns.
• New technologies for virtual community creation, portals and smartals will form new business models for m-commerce. We need to gain an understanding of which of these models are going to be commercially successful and why.

• Localization and personalization technology
• Location-based services
• Methods and design approaches for m-commerce products and services
• Knowledge based systems and soft computing
• Agent systems
• Technologies and solutions for m-commerce
• Data warehousing and intelligent front end solutions
• Consumer behavior and m-commerce
• Mass customization methods and technology

Minitrack Chairs

Modeling Knowledge-Intensive Processes: Concepts, Methods, and Applications

Relevant topics for this minitrack include (but are not limited to) the following:

1. Modeling Process Knowledge: Concepts and Methods
   • Concepts and methods for the capture and use of process knowledge in design tasks.
   • Capturing and retaining “embedded” or implicit knowledge.
   • Models and methods for linking process knowledge emerging from a particular design situation with the knowledgebase and memory of the larger organization.
   • Factors influencing (impeding and facilitating) comprehensive capture and use of process knowledge.
   • Frameworks for the evaluation of methods and tools.
   • Tangible and intangible costs and benefits of managing process knowledge.
2. Modeling Process Knowledge: Applications
   • Innovative implementations of "proof-of-concept" systems to support knowledge intensive processes.
   • Systems for supporting virtual design teams.
   • Case studies or experience reports on the capture and use of process knowledge in organizations.
   • Empirical research on the use and efficacy of process knowledge in design and maintenance of products/systems.
   • Systems to support rapid and evolutionary development.
   • Traceability of process knowledge across system components and phases.
   • Intelligent tools for management of process knowledge.
   • Systems to support concurrent development.
   • Process knowledge in formal software development.

Minitrack Chairs

Modeling and Simulation of Natural and Human Systems

Many natural and human-made systems can be described as complex. Such systems cannot meaningfully be reduced to straight cause-effect patterns. They typically escape the linear fashion of modeling and need a different treatment. Prominent approaches to modeling nonlinear dynamics are agent-based modeling and system dynamics. In agent-based modeling, for example, the power and intelligence of real life systems is mimicked in the laboratory populated by agents that act in the model space exactly as they are supposed to do in real life. Rather than trying to compute the solution to models, the agent-based model lets a solution emerge from the rule-based (inter) actions of its individual agents.

This modeling approach can be adapted to a very wide range of applications as has been shown in the work emerging from the Santa Fe Institute. A different approach to the same problem is provided by the modeling tradition of System Dynamics developed at MIT. SD modeling rests on the idea of feedback, or circular causality, inherent in nonlinear systems. The observer/SD modeler attempts to capture causal relationships between elements of a given system by describing its feedback structure with a multiplicity of positive and negative feedback loops. Carefully formulated models are able to simulate the behavior of a complex real system at an aggregate level. Identifying leverage points and applying structural changes in such SD models help pre-testing real system changes and implementing new policies.

Relevant topics for this minitrack include (but are not limited to):

• Cross-sectional Agent-Based and SD studies
• Business Applications and Case Studies
• Architectures and Environments
• Standards
• Experimental Studies
• Large Scale Simulations
• Web-Based Simulations
• Model Verification, Validation and Calibration
• Solution Comparisons
• Integration with Decision Models
• Constructive and Destructive Agents
• Artificial Organizations, Societies and Economies

Minitrack Chairs