Burstein / Brézillon / Zaslavsky Supporting Real Time Decision-Making

The Role of Context in Decision Support on the Move
1. Auflage 2010
ISBN: 978-1-4419-7406-8
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 13, 320 Seiten

Reihe: Annals of Information Systems

This volume of Annals of Information Systems will acknowledge the twentieth anniversary of the founding of the International Society for Decision Support Systems (ISDSS) by documenting some of the current best practices in teaching and research and envisioning the next twenty years in the decision support systems field. The volume is intended to complement existing DSS literature by offering an outlet for thoughts and research particularly suited to the theme of describing the next twenty years in the area of decision support. Several subthemes are planned for the volume. One subtheme draws on the assessments of internationally known DSS researchers to evaluate where the field has been and what has been accomplished. A second subtheme of the volume will be describing the current best practices of DSS research and teaching efforts. A third subtheme will be an assessment by top DSS scholars on where the DSS discipline needs to focus in the future. The tone of this volume is one of enthusiasm for the potential contributions to come in the area of DSS; contributions that must incorporate an understanding of what has been accomplished in the past, build on the best practices of today, and be integrated into future decision making practices.

Frada Burstein completed her PhD at the Institute of Cybernetics, Georgian Academy of Science (the Branch of USSR Academy of Sciences) in 1981. She has an extensive research record in the areas of decision theory and decision support systems. Since 1992 she has been working in the Department of Information Systems of the Faculty of Information Technology at Monash University, and is currently an Associate Professor, Associate Dean for Research Training, Founder and Director of the Knowledge Management Research Program and a virtual laboratory at the Caulfield School of IT. Dr. Burstein was co-editor of Handbook of Decision Support Systems (with Clyde Holsapple) published by Springer in 2008. She has been Program Co-Chair for the Australian Conference on Knowledge Management and Intelligent Decision Support, Steering Committee member and Doctoral Colloquium faculty for the IFIP TC8/WG8.3 Working Conference International Conference on Collaborative Decision Making, Executive Committee Member of the Australian Council of Professors & Heads of Information Systems, Chair for the Association of Information Systems Special Interest Group in DSS, and Secretary for the IFIP WG 8.3 Decision Support Systems. Dr. Burstein's many editorial board assignments include serving as Guest Co-Editor for the special issue of Decision Support Systems 'Decision Support in an Uncertain and Complex World' (with GeorgeWidmeyer), Guest Co-Editor for the special issues of the journal Information Systems and E-Business Management (with Clyde Holsapple), Area Editor for Decision Support Systems, Associate Editor for Journal of Decision Systems, Associate Editor for International Journal of Knowledge Management, and editorial board member for Journal of Knowledge Management Research and Practice and Journal of Information and Knowledge Management. In 2003, Dr. Burstein received the Monash University Postgraduate Association Supervisor of the Year award.Patrick Brezillon is a researcher at the National Center for Scientific Research in Paris where his work focuses on the study of intelligent assistant systems, particularly the modelling of context and the relationship between collaborative decision making and context. His papers have appeared in such journals as IEEE Intelligent Systems, Knowledge Engineering Review, Expert Systems with Applications, International Journal on Human-Computer Studies, and AI Magazine. Dr. Brezillon directs the SART project, which is developing a system to support subway traffic control decisions when incidents occur, and the PROTEUS program, which is developing an integrated platform for supporting e-maintenance strategy. He was co-editor of Creativity and Innovation in Decision Making and Decision Support, Volumes 1 and 2, Ludic Publishing Ltd.List of publications: http://www-poleia.lip6.fr/-brezil/Pages2/Publications/index.htmlArkady Zaslavsky is a Chaired Professor at the Luleå University of Technology, Sweden and Associate Professor at Monash University, Australia. He received MSc in Applied Mathematics majoring in Computer Science from Tbilisi State University (Georgia, USSR) and Ph.D. in Computer Science from the Moscow Institute for Control Sciences, USSR Academy of Sciences. His research interests include mobile and pervasive computing, context-awareness, distributed and mobile agents and objects, wireless networks, distributed computing and database systems, distributed object technology and mobile commerce. His research is published in such journals as Telecommunication Systems, Mobile Networks and Applications, Journal of Organizational Computing and Electronic Commerce, Electronic Commerce Research, and ACM SIGMOD Record, IEEE Transactions on Systems, Man, Cybernetics, Pervasive and Mobile Computing. He has edited four books of conference proceedings published in LNCS series. List of publications: http://www.ltu.se/forskning/1.16009?pureId=1161&l=en&pureFamily=dk.atira.pure.families.person.shared.model.Person&sortOrder=desc

Autoren/Hrsg.

Burstein, Frada

Brézillon, Patrick

Zaslavsky, Arkady

Inhaltsverzeichnis

1;Foreword;6
2;Preface;8
3;Acknowledgements;14
4;Contents;16
5;Contributors;18
6;Author Biographies;24
7;Part I Theories of Real-Time Decision Support;42
7.1;Chapter 1: Challenges of Real-Time Decision Support;43
7.1.1;1 Introduction;43
7.1.2;2 Defining Real-time Decision Support;44
7.1.3;3 Operational and Tactical Decision Support;45
7.1.4;4 Challenges;47
7.1.4.1;4.1 Technical Challenges;48
7.1.4.2;4.2 Organisational Challenges;48
7.1.4.3;4.3 Social/Psychological Challenges;48
7.1.5;5 Conclusions;49
7.1.6;References;50
7.2;Chapter 2: Improvisation as Model for Real-Time Decision Making;52
7.2.1;1 Introduction and Research Objectives;52
7.2.2;2 Real-Time Dynamic Decision Making Contexts and the Relationship with Improvisation;53
7.2.3;3 Towards a Shared Understanding of Improvisation;55
7.2.3.1;3.1 History of Interest in Improvisation;55
7.2.3.2;3.2 Defining Improvisation;56
7.2.3.3;3.3 A Typology of Improvisational Contexts;58
7.2.3.4;3.4 Antecedents of Improvisation;60
7.2.3.5;3.5 Degrees of Improvisation;61
7.2.3.6;3.6 Performance and the Episodic Nature of Improvisation;62
7.2.3.7;3.7 Elements Necessary for Individual and Team Improvisation;63
7.2.3.8;3.8 Improvising Effectively;63
7.2.4;4 Implications for Real-Time Dynamic Decision Support Systems (DSS);65
7.2.4.1;4.1 Pre-performance Support;66
7.2.4.2;4.2 Performance Support;67
7.2.4.3;4.3 Post-performance Support;67
7.2.4.4;4.4 Systems and Organisational Implications;68
7.2.5;5 Summary and Conclusions;69
7.2.6;References;70
8;Part II Tools and Technologies for Context-awareReal-Time Decision Support;72
8.1;Chapter 3: Context Prediction in Pervasive Computing Systems: Achievements and Challenges;73
8.1.1;1 Context and Context Prediction;73
8.1.2;2 Context Prediction Task;74
8.1.2.1;2.1 Context Prediction Task;74
8.1.2.2;2.2 From Task Definition to Evaluation Criteria;76
8.1.3;3 Context Prediction Methods;80
8.1.3.1;3.1 Sequence Prediction Approach;81
8.1.3.2;3.2 Markov Chains for Context Prediction;83
8.1.3.3;3.3 Neural Networks for Context Prediction;87
8.1.3.4;3.4 Bayesian Networks for Context Prediction;88
8.1.3.5;3.5 Branch Prediction Methods for Context Prediction;90
8.1.3.6;3.6 Trajectory Prolongation Approach for Context Prediction;91
8.1.3.7;3.7 Expert Systems for Context Prediction;91
8.1.3.8;3.8 Context Prediction Approaches Summary;93
8.1.4;4 General Approaches to Context Prediction;93
8.1.5;5 Research Challenges of Context Prediction;97
8.1.6;References;98
8.2;Chapter 4: A Contextual Methodology for Modelling Real-Time Decision-Making Support;102
8.2.1;1 Introduction;102
8.2.2;2 Background of the Contextual Methodology;104
8.2.2.1;2.1 Modelling of Procedure and Practice;104
8.2.2.2;2.2 A Context Representation by Contextual Elements;105
8.2.2.3;2.3 The Four-Level Representation of Human Reasoning;106
8.2.2.3.1;2.3.1 Policy Level;107
8.2.2.3.2;2.3.2 Strategic Level;108
8.2.2.3.3;2.3.3 Tactical Level;108
8.2.2.3.4;2.3.4 Operational Level;108
8.2.2.3.5;2.3.5 Summing Up;109
8.2.2.4;2.4 A Three-Layer Model;109
8.2.3;3 The Contextual Methodology;111
8.2.3.1;3.1 The 10 Steps;111
8.2.3.2;3.2 Application in the Modelling of Drivers’ Behaviour;114
8.2.4;4 Conclusion;123
8.2.5;References;124
8.3;Chapter 5: Towards Real-Time Context Awareness for Mobile Users: A Declarative Meta-Programming Approach;126
8.3.1;1 Introduction;126
8.3.2;2 A Brief Introduction to LogicCAP;128
8.3.2.1;2.1 LogicCAP Situation Programs;129
8.3.2.2;2.2 LogicCAP Prolog: Meta-Programming with Situation Programs;130
8.3.3;3 Prototype Implementation;132
8.3.3.1;3.1 Architecture of LogicCAP-S with the Context Toolkit;132
8.3.3.2;3.2 Extension 1: Extending the Vanila Metainterpreter in LogicCAP-S with Concurrent Event-Driven Behaviour;134
8.3.3.3;3.3 Extension 2: Levels of Abstraction, Dynamic Situation Program Binding, Dynamic Sensor Binding, and Goal Evaluations in the Mobile Environment;138
8.3.3.4;3.4 Extension 3: Control of Goal Evaluation – Persistent Queries, Forced Contraction, and Partially Complete Evaluations;141
8.3.4;4 Modes of Usage in Mobile Environments;142
8.3.4.1;4.1 Situation Programs As Mobile Context (and Sensor) Mashups;142
8.3.5;5 Related Work;145
8.3.6;6 Conclusion and Future Work;146
8.3.7;References;147
8.4;Chapter 6: The Role of Context for Crisis Management Cycle;150
8.4.1;1 Introduction;151
8.4.2;2 Need of Context for Crisis Management;152
8.4.3;3 Crisis Management;154
8.4.3.1;3.1 Crisis Characteristics;154
8.4.3.2;3.2 From Crisis Management Concept to Crisis Management Support;156
8.4.4;4 Contextualisation Use in the Three Phases of DICE Management;159
8.4.4.1;4.1 Contextualisation for Information Gathering;159
8.4.4.2;4.2 Contextualisation to Get a Meaningful Situation Awareness;162
8.4.4.3;4.3 Dual Impact of the Context on Decision Making;163
8.4.4.4;4.4 Contextualisation of the DICE Management Upgrade Process;165
8.4.5;5 Conclusion;166
8.4.6;References;167
8.5;Chapter 7: The Contextual and Collaborative Dimensions of Avatar in Real-Time Decision Making;170
8.5.1;1 Introduction;170
8.5.2;2 Background;172
8.5.2.1;2.1 Second Life;172
8.5.2.2;2.2 Second Life as an Environment for real-timeDecision Making;174
8.5.3;3 Research Model;177
8.5.4;4 Research Methodology;178
8.5.4.1;4.1 Subjects;179
8.5.5;5 Results;180
8.5.6;6 Discussion and Implications;181
8.5.6.1;6.1 Implications for Research;182
8.5.6.2;6.2 Implication for Practice;182
8.5.7;7 Conclusions and Future Work;183
8.5.7.1;7.1 Future Work;184
8.5.8;8 Appendix I: Example of Avatars;188
8.5.9;9 Appendix II: Survey Questions;189
8.5.10;10 Appendix III: General Linear Model;191
9;Part III Case Studies;194
9.1;Chapter 8: Beyond Rationality: Information Design for Supporting Emergent Groups in Emergency Response;195
9.1.1;1 Introduction;195
9.1.2;2 Emergency Assistance, Emergent Groups and Context-Based Decision Support;197
9.1.3;3 Theoretical Perspective on Information Requirements for Emergent Group Support;198
9.1.3.1;3.1 Template as Means of Information Support to Emergent Groups;200
9.1.3.2;3.2 Problem-Solving Approach;201
9.1.3.3;3.3 Action-Resource-Based Approach to Defining Information Needs;203
9.1.3.4;3.4 Control and Monitoring Approach to Managing Complex Organisations;204
9.1.3.5;3.5 Motivational Approach Based on the Altruistic Community Model;205
9.1.3.6;3.6 Sense Making and an Affective Approach to Deal with Disaster-Induced Stress;208
9.1.4;4 Conclusion;211
9.1.5;References;212
9.2;Chapter 9: Dynamic Emergency Response Management for Large Scale Decision Making in Extreme Hazardous Events;216
9.2.1;1 Introduction;216
9.2.2;2 The Nature of Emergencies;217
9.2.2.1;2.1 Large Groups and Subgroups of Decision-Analysis Teams;223
9.2.3;3 Formulating Group Viewpoints;223
9.2.4;4 Theory and Use of Emergency Management Systems;227
9.2.4.1;4.1 Groups as High Reliability Organisations;227
9.2.4.2;4.2 Building Knowledge, Experts Voting;228
9.2.5;5 Other Design Problems for Emergency Decision Support Systems;229
9.2.6;6 Threat Rigidity Syndrome;229
9.2.7;7 Information Overload in Emergency Management;231
9.2.8;8 High Reliability Organisations and Muddling Through;232
9.2.9;9 Observations and Conclusions;234
9.2.10;References;235
9.3;Chapter 10: Partially Distributed Emergency Teams: Considerations of Decision Support for Virtual Communities of Practice;238
9.3.1;1 Introduction;238
9.3.2;2 Partially Distributed Emergency Teams;239
9.3.2.1;2.1 Trust and PDETs;240
9.3.2.2;2.2 Role Management to Support PDETs;241
9.3.3;3 Training Members of PDETs;244
9.3.3.1;3.1 Wikis;244
9.3.3.2;3.2 Gaming;244
9.3.3.3;3.3 Collaborative Scenario and Exercise Generation;245
9.3.4;4 The Gold Mine: Citizen Participation;246
9.3.4.1;4.1 Warning System Development;246
9.3.4.2;4.2 Social Media and Citizen Participation;248
9.3.4.3;4.3 Global Community Participation;249
9.3.5;5 Conclusion;251
9.3.6;References;254
9.4;Chapter 11: Why Real-Time Transaction Processing Fails to Capture the Context Required for Decision Support;256
9.4.1;1 Introduction;256
9.4.2;2 A Context-based Representation of the Decision Maker;257
9.4.3;3 Research Methodology;258
9.4.4;4 The Case of the Deliver Process at SIT;260
9.4.4.1;4.1 Context and Justification in Selecting This Case Study;260
9.4.4.2;4.2 Information Systems Supporting the Process;262
9.4.5;5 Analysing the Case Study;262
9.4.5.1;5.1 Decision Making Remains Manual;262
9.4.5.2;5.2 Constraints Arising from the Physical Business Context;263
9.4.5.3;5.3 Constraints Arising from the Virtual Context (System Related);265
9.4.5.4;5.4 Decoupling the ERP System;267
9.4.6;6 Discussion;268
9.4.7;7 Conclusions and Guidelines for Technological Solutions;270
9.4.8;References;271
9.5;Chapter 12: Continuous Auditing as a Foundation for Real Time Decision Support: Implementation Challenges and Successes;272
9.5.1;1 Introduction;272
9.5.2;2 Definition;274
9.5.3;3 Architecture;274
9.5.3.1;3.1 Digitised Data Source;275
9.5.3.2;3.2 Data Validation Engine;276
9.5.4;4 Implementation Challenges;276
9.5.4.1;4.1 Formalising Business Processes;277
9.5.4.2;4.2 Cost;278
9.5.4.3;4.3 System Acceptance;279
9.5.4.4;4.4 Information Overload;280
9.5.4.5;4.5 System Performance;280
9.5.5;5 Successful Implementations;281
9.5.5.1;5.1 AT&T’s Paperless Billing System;281
9.5.5.2;5.2 Royal Canadian Mounted Police’s Accounts Payable Departments;281
9.5.5.3;5.3 Siemens’ SAP Security Settings;282
9.5.5.4;5.4 Summary (Table 1);283
9.5.6;6 Conclusion;283
9.5.7;References;285
9.6;Chapter 13: Towards a “Just-in-Time” Distributed Decision Support System in Health Care Research;288
9.6.1;1 Introduction;288
9.6.2;2 Literature Review;291
9.6.2.1;2.1 Health Research in Injury Prevention;291
9.6.2.2;2.2 Survey Approaches for Data Collection in Health Research;292
9.6.2.3;2.3 Decision Support Systems in Health Care;294
9.6.3;3 A Framework for a Decision-Making Process;294
9.6.4;4 Design and Development of the Just-in-Time AI-Based DSS;295
9.6.4.1;4.1 Just-in-Time Data Collection (JITDC) Module;296
9.6.4.1.1;4.1.1 Data Acquisition;296
9.6.4.1.2;4.1.2 Unified Survey Management System;297
9.6.4.1.2.1;4.1.2.1 Services Offered by the USMS;298
9.6.4.1.2.2;4.1.2.2 Architecture of the USMS;299
9.6.4.1.2.3;4.1.2.3 Data Analysis Unit;301
9.6.4.2;4.2 Artificial Intelligence (AI) Module;303
9.6.4.2.1;4.2.1 Data Definition;303
9.6.4.2.2;4.2.2 Knowledge Representation and Propagation;305
9.6.4.2.3;4.2.3 Agent Simulation;308
9.6.4.2.3.1;Simulation Set Up;308
9.6.4.2.3.2;Testing and Validation;310
9.6.4.2.3.3;Simulation Results;312
9.6.4.2.3.4;Effect of Social Network;312
9.6.4.2.3.5;Effect of Age Group;314
9.6.4.3;4.3 Persistent Storage;314
9.6.4.4;4.4 Business Logic and Decision Module;315
9.6.5;5 Conclusion;315
9.6.6;References;317
9.7;Chapter 14: Context Modelling in Time-Critical Decision Support for Medical Triage;321
9.7.1;1 Introduction;321
9.7.2;2 Context in Decision Making;322
9.7.3;3 Context Sensitive, Advisory Decision Support;324
9.7.4;4 Context in Time-Critical Decision Support;325
9.7.5;5 Context in Medical Triage;326
9.7.5.1;5.1 Modelling Context in Medical Triage;328
9.7.6;6 Implementation;330
9.7.7;7 System Evaluation and Discussion;331
9.7.8;8 Conclusions and Future Work;333
9.7.9;References;335
9.8;Chapter 15: Efficient Context Prediction for Decision Making in Pervasive Health Care Environments: A Case Study;337
9.8.1;1 Introduction;337
9.8.2;2 Motivating Application;338
9.8.3;3 The MUSIC Context Middleware;340
9.8.4;4 Learning Algorithms and Operators;343
9.8.5;5 Evaluation;345
9.8.5.1;5.1 Qualitative Evaluation;346
9.8.5.2;5.2 Quantitative Evaluation;347
9.8.6;6 Related Work;348
9.8.7;7 Conclusions;349
9.8.8;References;350
9.9;Chapter 16: On-demand Assistance in Handling Ammunition:Development of a Mobile Ammo DSS;352
9.9.1;1 Introduction;352
9.9.2;2 Background;353
9.9.2.1;2.1 Mobile Decision Support;353
9.9.2.2;2.2 Architectures of Mobile Decision Support;354
9.9.2.3;2.3 Mobile AME’s Context of Use;355
9.9.3;3 Mobile AME Design;356
9.9.3.1;3.1 Device Independence;357
9.9.3.2;3.2 Device usability;358
9.9.4;4 The Process of Decision Support for QASAS Personnel;358
9.9.5;5 Mobile AME System Architecture;359
9.9.5.1;5.1 Mobile AME Data Source;359
9.9.5.2;5.2 Server-Side Development;360
9.9.6;6 Mobile AME User Interface Design;360
9.9.6.1;6.1 Screen Design;361
9.9.6.2;6.2 Presentation of the Content;362
9.9.7;7 Application Navigation;362
9.9.8;8 Mobile AME Functionality;363
9.9.8.1;8.1 Ammunition, Inspection Points, Specification, Packaging and Shipping Information;364
9.9.8.2;8.2 Three-Dimensional Immersive Views;364
9.9.8.3;8.3 Inspection Point Video Clips;365
9.9.9;9 Exploratory Evaluation of Mobile AME;366
9.9.10;10 Discussion;366
9.9.11;11 Conclusion;367
9.9.12;References;368
9.10;Chapter 17: Development of a Mobile Situation Awareness Tool Supporting Disaster Recovery of Business Operations;370
9.10.1;1 Introduction;371
9.10.2;2 Related Work;373
9.10.3;3 Research Methodology;374
9.10.4;4 Situation Awareness (SA) Model;375
9.10.5;5 Situation Awareness (SA) Tool;376
9.10.6;6 Case Study;380
9.10.6.1;6.1 Definition;380
9.10.6.2;6.2 Preliminary Study;381
9.10.6.3;6.3 Requirements Elicitation;382
9.10.6.4;6.4 Theory/Tool Evaluation;384
9.10.6.5;6.5 Results from the Case Study;387
9.10.7;7 Discussion;388
9.10.8;8 Conclusions;389
9.10.9;References;390
10;Index;394