FUBUTEC'2015, 11th Future Business Technology Conference, April 27-29, 2015, IST, Lisbon, Portugal, Themes

Conference Themes

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Statistical Analysis and Data Mining of Business Processes

Advanced statistical techniques for Business: dependency networks, influence diagrams, data envelopment analysis, data mining. Design of Methodological Studies. Machine Learning Techniques with applications in business. Data warehouses, OLAP, meta-data related issues and such. Neural Networks and Support-vector machines in Business. Genetic algorithms in Business. Decision/Classification/Regression Trees and rule-based systems in Business. K-Nearest Neighbours, case-based reasoning and other Methods. Fuzzy-related methodology in Business. Verification and/or validation techniques. Adaptive systems related to machine learning/data mining. Clustering methodologies with applications in business. Time-series methods/applications for Business. Other identification-methods applicable for Business.

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Applications using data mining and open source text information mining and analysis.

Data Mining or fuzzy-related Tools. Text-mining related to Business. Web Data mining and information retrieval. Fraud-detection, CRM, SRM, ERM, sensor information retrieval. Datamining in combination with change detection and forensic analysis for information retrieval and assimilation, text accumulation analysis using AI and natural language processing techniques, Metadata mining.

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Choice Modelling-Methods and Applications

Choice modelling attempts to model the decision process of an individual or segment in a particular context. Choice modelling may be used to estimate non-market environmental benefits and costs.
Choice modelling comprises a number of specific techniques that contribute to its power. Some or all of these may be used in the construction of a Choice Model. Orthogonality; Experimental design; Stated preference; Preferences as choice trade-offs; Sampling and block allocation and Model Generation.
Choice modelling is particularly useful for:
- Predicting uptake and refining New Product Development
- Estimating the implied willingness to pay (WTP) for goods and services
- Product or service viability testing
- Variations of product attributes
- Understanding brand value and preference
- Demand estimates and optimum pricing
- Brand value

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Simulation applied to Economics

Adaptive markets complex simulation based on cell biology, neuroeconomics and behavioural economics. Analytic Methods for Financial and Economic Protection. Macroeconomic models estimation and model development. Economic Analysis and Econometrics simulation using Stochastic General Equilibrium Model, State-space Methods, Bayesian estimation and Time Series analysis, Simulation and optimisation, Experimental design of simulation studies, Queuing networks and models, Embedded Heuristics in simulation and Rule-based optimization and simulation, Symbolic Regression Techniques, Financial Times Series Prediction, Weighted and Filtered Historical Simulation, Predictive Analytics in banking.

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Agents in Business Automation and Economics

Knowledge Management and Agent-based computational economics (ACE), Intelligent Business Agents, Human and Agent Interaction, Virtual-Agent Based Marketplaces, Automated Shopping and Trading Agents, Agents and E-Commerce, Legal Aspects of agents in e-commerce, performance measurement of e-commerce agents, rational information agents and electronic commerce, Agent-Based Trade and Mediating Services; Virtual Trading Institutions

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Agent-Based Interface for Business Automation. Agent-Based Data Retrieval for Business Automation. Agent-Based Automatic Demand/Supply Formation for Business Automation. Agent-Based Demand/Supply Matching for Business Automation. Agent-Based Transaction Formation for Business Automation. Agent-Based Transaction Implementation for Business Automation. Agent-Based Logistics and Workflow Management for Business Automation Modeling. System Design and Validation for Agent-Based Business Automation.

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Applications; Personal Agents, Virtual Agent-Based Office, E-Management and E-Control with Agents, E-Trade and E-Marketplace with Agents, E-Payment and E-Banking with Agents, Financial and Investment Agent-Based Applications, Agent-Based Supply Chain and B2B Systems, Agents for Games on the Internet, Wireless Agent-Based Systems, Semantic Web and Agents, Large Scale E-Business: Agent Based Systems

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Agent Methodology; Agent Learning, Agent Negotiation, Agent Trusts and Trust Based Action, Agent Cooperation Competition, AI Techniques: Neural Networks, Agent Coordination for Cooperative Systems, Agent Communication/Interaction, Agent Security and, Authentication, Agent Visualization, Agent and Multi-Agent Architecture, Distributed and Real-Time Techniques

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Simulation in Business and Economics

Business process engineering and simulation, Simulation in customer-oriented service processes, Decision support systems, Simulation in Finance and Risk Management, Simulation in workflow management, Process mapping and simulation, Simulation of production processes and equipment, Business Information Modeling Methods and Methodologies, UML and UP in Business Modelling, UML and UP for Enterprise Modeling.

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Simulation in Business Games

Enhancing strategic thinking and decision making capabilities using simulation games; Simulating Key Management and Strategic Issues; Customized Business Simulation Applications, Systems Thinking and System Dynamics; Visualizing, analyzing and solving challenges and opportunities; Using games to achieve strategic objectives; Simulation with "man in the loop"; Virtual Reality systems; Realistic presentation of simulation results; Simulation for training and education; Web-based simulation; Multi-site Group simulation; Simulation of Emergency procedures (Disaster gaming)

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Simulation in OR and Knowledge Management

The skill of the management scientist lies in the ability to balance the reality of the developed model with the effort that it will take to find an answer to the problem. Many decision support systems (DSS) use representational models to predict the impact of possible decisions. There are two major types of model: simulation and analytical. A more subjective approach to decision-making is needed. While information and some form of data processing are essential, the decision-maker should adopt a less structured approach to the way the data is used. The development of interactive software has given more flexibility to the way in which the decision-maker uses the data and the applied models. This is the essence of decision support systems. Simulation models as used in business, policy, conflict situations, and and crisis management through, in almost all cases, dynamic, discrete-event, and stochastic models. According to the application area, the researcher or designer should model the real-world situation very carefully. An incorrect, incomplete, or inconsistent model could result in a bad decision being made by the decision-maker possibly resulting in economic loss, physical damage or injury. The simulation models and their applications should take into account uncertainty and thus contain procedures for risk analysis. We are therefore interested in research presentations on the science of designing and developing simulation models to solve decisional problems in policy, management, conflict situations, and anti-disaster actions. In particular (but not exclusively), we welcome presentations and reports in the following areas:

  • new developments and sound practice in the use of interactive simulation in building decision support systems for conflict situations (including simulation games)
  • practice in the use of hybrid systems (artificial intelligence in simulation environments) as decision support in political, conflict and anti-disaster problems;
  • simulation based logistics decision support systems;
  • model based simulation in risk analysis for decision makers
  • application of simulation based pattern recognition in complex adaptive systems to identify and classify a situation to solve decision problems
  • Project Management
  • Project Intelligence
  • From Modelling to Management
  • Consumer Demand Behaviour
  • Modelling Future Demand
  • Data Modelling Tools
  • Sustainable Development Simulation
  • Business Process: Integration, Workflow and Process Management
  • Representation of Processes to Business Management
  • Achieving Flexibility
  • Encapsulating Processes the influence of the OO Revolution
  • From Business Model to Operational Performance Support
  • Models with the end users in mind
  • Best practice Processes
  • Business Process Modelling including information architecture and persuasive Web design
  • Creating and sharing knowledge

Submit your proposal on knowledge management here

Emergency Management and Risk Analysis Management

This part of the conference concerns itself more with the more "extreme" aspects of management, extreme managerial situations or management problem solving using numerical modelling, GIS, and information and Web 2.0 technologies.

This track covers

  • Risk identification, analysis and assessment
  • Risk assessment and horizon scanning
  • Risk sensoring
  • Risk scenario modelling, procedures formulation and planning: (Prevention, Preparedness, Mitigation, Response, Recovery)
  • Crisis management - extreme events or total disaster
  • Environment (forest fires, marine risk - tanker disaster, flood, earthquakes, drought, volcanic eruptions
  • Industrial (Hazards, Accidents (nuclear meltdown), Technology (asbestos)
  • Terrorist (Extreme events (September 11), Civil Protection, Conflicts risk management - security (Petersberg tasks - City Flood Vulnerability Index)
  • Project risk management (Investment decisions, Research projects risk management, Extremely risky projects risk management (space exploration), Software development risk management.
  • Enterprise risk management (Decision-making, Venture capital)
  • Financial risk management (Stocks, Portfolio selection, Options, Credit Risk Assessment, Insurance sector)
  • Crisis management (Extreme events, Total disaster)
  • Financial Modelling and simulation (Managing Intelligence Capital, Linking computer based financial models while limiting herd behavior, Black-Scholes Model, Real Options, Wiener process, Risk measures )
  • Business Process Reengineering (BPR)
  • Probabilistic Risk Assessment (PRA)
  • Fault Tree Analysis (Static and Dynamic FTA)
  • Event Tree Analysis (ETA)
  • HAZIP (Hazard identification) tools (HAZOP (Hazard and Operability Study), Judgement, FMEA (Failure Modes and Effects Analysis), SWIFT (Structured What-IF Checklist Technique)
  • Human Error Analysis (HEA)

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Policy Modelling and Simulation in E-Management, E-Government, E-Commerce and E-Trade

e-learning/ education management, knowledge management, knowledge economy, multimedia in manufacturing companies, maintenance of technical facilities and maintenance service management UML applications in Risk Management Modelling. E-democracy, electronic local government, the digital divide, e-governors, citizen centric services, GovMl Description Language, Government Portals, Shared contact centres, Costs and Risks, Customer relationship management, Models for automatic evaluation of public sector sites, the role of standards, knowledge management, community portal dynamics, diversity, creativity, Innovation and Knowledge Management in the Service Sector, Integrated Electronic Records, from e-government to e-regulation.
Knowledge Management and Dynamic Portals, Learning Networks: Policy making through portals, Portals with Purpose Case Studies, e-government portal design and Evolution, Risk Based Testing of E-government Portals

Submit your proposal on E-Business here

Political and Government Simulation

This track covers but is not limited to: Geopolitical Simulation, Domestic Policy Simulation, Political Campaign Simulation, Conflict Simulation, Crisis Simulation.

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Simulation Tools for Business Management and Business Intelligence Simulation

Management and Business simulation using PDSim, TreeAge Pro, StatFit, MyStrategy, Extend OR, Decision Pro, Decision Script, Crystal Ball, Analytica, AgenaRisk, @Risk, CBML, Cognos OlAP Datacubes in order to simulate a flexible system for setting up, tracking and communicating company performance against a set of management-defined Key Measurables within the Dashboard Module, Activity Based Intelligence.

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Geosimulation and Big Data

This theme covers topics such as:

  • Using Big Data to inform individual-based models of geographical systems
  • Hybrid modeling approaches (e.g. utilizing Spatial Interaction, Microsimulation, etc.)
  • Participatory behavioural modeling and simulation
  • Translating Big Data into agent rules while handling scale and space issues
  • Improving and Validating, verifying and calibrating agent-based models (ABM) and CA Models with Big Data
  • Visualization of agent-based models (along with their outputs)
  • Ways of representing behavior within models of geographical systems
  • Applications of geosimulation

Submit your proposal on geosimulation and big data here

Simulation and Analysis of Environmental effects of business

This theme covers topics such as:

  • Simulation of Costs and Effects of Business Policies for the Environment
  • Business Simulation for Environmental Feedback Analysis
  • Green Metrics for Business Simulation
  • Simulation of Customer Synchronous Reaction to Business Policies
  • Simulation of Social Feedback into Business Activity

Submit your proposal on environmental effects here

Predictive Simulation and Methodology for Futures Research

This track covers Futures Research, Methodology Evaluation, Environmental Scanning, The Delphi Method, Real-Time Delphi, The Futures Wheel and Polygoni,Trend Impact Analysis, Cross-Impact Analysis, Wild Cards Modelling, Structural Analysis, Systems Perspectives, Decision Modeling, Substitution Analysis, Statistical Modeling, Technology Sequence, Morphological Analysis, Relevance Trees, Scenarios and Interactive Scenarios (modelling software), Robust Decision making, Participatory Methods, Simulation and Games, Genius Forecasting and Intuition, Visioning for Strategic Planning, Normative Forecasting, TRIZ, S&T Road Mapping, Field Anomaly Relaxation (FAR), Text Mining for Technology Foresight, Global Event Mining (using f.ex.Culturomics 2.0), Agent Modeling (demo software), Prediction Markets, Forecasting By Artificial Neural Networks, SOFI Software Systems, Multiple Perspective Concept, Toolboxes for Scenario Planning, Heuristics Modeling, Causal Layered Analysis, Linking Methods, Integration, Comparisons, and Frontiers.

Submit your proposal on environmental effects here