Schuff / Paradice / Burstein Decision Support

An Examination of the DSS Discipline
1. Auflage 2010
ISBN: 978-1-4419-6181-5
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 14, 224 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 be integrated into future decision making practices. The primary questions raised by this volume are: What will information systems-based decision support entail in twenty years? What research is needed to realize the envisioned future of information systems-based decision support? How will the teaching of information systems-based decision support change over the next twenty years? What are the best practices of teaching in the decision support area that can be leveraged to best disseminate DSS knowledge advances to students and practitioners?

Autoren/Hrsg.

Schuff, David

Paradice, David

Burstein, Frada

Sharda, Ramesh

Power, Daniel J.

Inhaltsverzeichnis

1;Preface;5
2;Contents;9
3;Contributors;11
4;About the Authors;13
5;1 GDSS Past, Present, and Future;21
5.1;1.1 Introduction;21
5.2;1.2 Overview of GDSS by Paul Gray;21
5.2.1;1.2.1 The Forerunner;22
5.2.2;1.2.2 The Churchill War Room;23
5.2.3;1.2.3 Engelbart's Decision Room at SRI (ca. 1967);24
5.2.4;1.2.4 University of Southern California (USC);25
5.2.5;1.2.5 Southern Methodist University (SMU);25
5.2.6;1.2.6 Claremont Graduate University;25
5.2.7;1.2.7 Other Rooms;26
5.3;1.3 The Role of Leaders in GDSS by Bob Johansen;27
5.4;1.4 Global Teams by Jay Nunamaker;30
5.4.1;1.4.1 Collaboration;30
5.4.2;1.4.2 Challenges Facing Global Virtual Teams;31
5.4.3;1.4.3 Trade-Offs;32
5.4.4;1.4.4 Effective Collaboration;33
5.4.5;1.4.5 Conclusions;33
5.5;1.5 The Entrepreneurial View by Gerald R. Wagner;34
5.5.1;1.5.1 The Planning Laboratory;35
5.5.2;1.5.2 Next Version;35
5.5.3;1.5.3 Vision Quest, Web IQ;36
5.5.4;1.5.4 Reincarnation of IFPS;37
5.5.5;1.5.5 Concluding Thoughts;37
5.6;1.6 Telepresence by Jeff Rodman;38
5.6.1;1.6.1 Definition;38
5.6.2;1.6.2 What Is in This Section;39
5.6.3;1.6.3 Telepresence Drivers, 2010--2030;39
5.6.4;1.6.4 The Telepresence Vision;40
5.6.5;1.6.5 Technical Enablers;42
5.6.6;1.6.6 Summary;44
6;2 Reflections on the Past and Future of Decision Support Systems: Perspective of Eleven Pioneers;45
6.1;2.1 Introduction;45
6.2;2.2 DSS Research and Development Timeline;46
6.3;2.3 Reflections on Decision Support Pioneers Research Project;49
6.4;2.4 Reflections of DSS Pioneers;50
6.4.1;2.4.1 Major Conclusions from Experiences with Computerized DSS;51
6.4.2;2.4.2 Continuing Issues Associated with Decision Support;54
6.5;2.5 Conclusions;62
6.6;Appendix: Brief Biographies of Interviewees ;64
6.7;References;66
6.8;Further Readings;68
7;3 The Intellectual Structure of Decision Support Systems Research (1991-2004);69
7.1;3.1 Introduction;69
7.2;3.2 Background;70
7.3;3.3 Data;71
7.4;3.4 Research Methodology;72
7.5;3.5 Results of Multivariate Analysis;73
7.6;3.6 Results of Multi-dimensional Scaling Analysis;80
7.7;3.7 Limitations;82
7.8;3.8 Conclusions;82
7.9;References;83
8;4 Ethical Decision-Making and Implications for Decision Support;89
8.1;4.1 Introduction;89
8.2;4.2 Background;89
8.2.1;4.2.1 The Ethical Decision-Making Process: A Jones Perspective;91
8.3;4.3 Measuring Ethical Decision-Making Components;94
8.3.1;4.3.1 Recognition of a Moral Issue;94
8.3.2;4.3.2 Make a Moral Judgment;95
8.3.3;4.3.3 Establish a Moral Intent;96
8.3.4;4.3.4 Engage in Moral Behavior;96
8.3.5;4.3.5 Moral Intensity and Other Factors;97
8.3.6;4.3.6 Measuring Ethical Decision Processes;97
8.4;4.4 Decision Support Considerations;99
8.5;References;100
9;5 Web and Mobile Spatial Decision Support as Innovations: Comparison of United States and Hong Kong, China;103
9.1;5.1 Introduction;103
9.1.1;5.1.1 Background;103
9.1.2;5.1.2 Issues, Controversies, Problems;105
9.2;5.2 Theories of Adoption and Diffusion;106
9.3;5.3 Research Propositions;109
9.3.1;5.3.1 There Are Significant Advantages to the Web and Mobile SDS over the Traditional SDS Approach;109
9.3.2;5.3.2 The WMSDS Innovation Helps the Organization Competitively;110
9.3.3;5.3.3 The Organization Can Adjust Well to the Innovation of WMSDS;110
9.3.4;5.3.4 The Innovation Is User-Friendly for Customers and Internal Users;110
9.3.5;5.3.5 In Development, the WMSDS Innovation Is Prototyped or Piloted in Small Segments;111
9.3.6;5.3.6 The WMSDS Innovation Is Visible Within and Outside the Organization;111
9.3.7;5.3.7 WMSDS Differs in Its Innovation Features Between the US and Hong Kong;111
9.4;5.4 Methodology;112
9.4.1;5.4.1 Case Studies;112
9.5;5.5 Findings;112
9.5.1;5.5.1 Decision Support;113
9.5.2;5.5.2 Findings on Differences Between US WMSDS and Hong Kong WMSDS for the Case Organizations;113
9.5.2.1;5.5.2.1 Difference in Systems Development of Web-Based SDS;121
9.5.2.2;5.5.2.2 Difference in WMSDS Application Areas;121
9.5.2.3;5.5.2.3 3-D Applications;122
9.6;5.6 Outcomes for the Research Propositions;123
9.6.1;5.6.1 There Are Significant Advantages to the Web and Mobile SDS Over the Old Approach?;123
9.6.2;5.6.2 WMSDS Innovation Helps the Organization Competitively;124
9.6.3;5.6.3 The Organization Can Adjust Well to the Innovation of WMSDS;124
9.6.4;5.6.4 The Innovation Is User-Friendly for Customers and Internal Users;124
9.6.5;5.6.5 In Development, the WMSDS Innovation Is Prototyped or Piloted in Small Segments;124
9.6.6;5.6.6 The WMSDS Innovation Is Visible Within and Outside the Organization?;125
9.6.7;5.6.7 WMSDS Differs in Its Innovation Features Between the US and Hong Kong;125
9.7;5.7 Case Findings and the Usefulness of the Research Models of Adoption and Use;126
9.8;5.8 Future Trends;127
9.8.1;5.8.1 Technology and Data;127
9.9;5.9 Conclusion;129
9.10;References;129
10;6 Knowledge Management Capability in Education;132
10.1;6.1 Introduction;132
10.2;6.2 Educational Background;133
10.3;6.3 Knowledge Management Capability Background;134
10.3.1;6.3.1 Defining Knowledge;134
10.3.2;6.3.2 Knowledge Processes;135
10.3.3;6.3.3 Knowledge Management Capability Constructs;136
10.3.4;6.3.4 Knowledge Management Capability Model;137
10.4;6.4 Expanding KMC into Educational Contexts;140
10.4.1;6.4.1 Department of Defense Field Study Results;141
10.5;6.5 Future Trends;143
10.5.1;6.5.1 Implementation Issues;143
10.5.2;6.5.2 Implications;145
10.6;6.6 Conclusion;145
10.7;References;146
11;7 Knowledge Warehouse for Decision SupportINTbreak; in Critical Business Processes: Conceptual ModelingINTbreak; and Requirements Elicitation;149
11.1;7.1 Introduction;149
11.2;7.2 Theoretical Background;150
11.2.1;7.2.1 Data Warehouse;151
11.2.2;7.2.2 Knowledge Management;152
11.2.3;7.2.3 Organizational Memory;152
11.2.4;7.2.4 Data Warehouses and Knowledge Management;153
11.3;7.3 Research Methodology;154
11.4;7.4 Knowledge Warehouse Conceptual Model;155
11.5;7.5 KW4DSCBP Architecture;158
11.6;7.6 KW4DSCBP Evaluation and Requirements Elicitation;159
11.7;7.7 Requirements Elicitation Tool;161
11.8;7.8 Conclusion and Future Work;163
11.9;References;164
12;8 Agent-Based Modeling and Simulation as a Tool for Decision Support for Managing Patient Falls in a Dynamic Hospital Setting;167
12.1;8.1 Introduction;167
12.2;8.2 Prior Research;169
12.3;8.3 Background;170
12.3.1;8.3.1 Description of the Hospital Floor Plan;170
12.4;8.4 Modeling and Simulation of Patient Falls Incident;173
12.4.1;8.4.1 Simulation Setup;174
12.5;8.5 Results;175
12.6;8.6 Conclusions and Future Work;177
12.7;References;178
13;9 Context-Aware Mobile Medical Emergency Management Decision Support System for Safe Transportation;181
13.1;9.1 Introduction;181
13.2;9.2 Challenges of Decision Support in Medical Emergency Transportation Management;183
13.2.1;9.2.1 Illustrative Scenario;184
13.3;9.3 The Need for Context-Awareness and Its Role in Decision Support;185
13.4;9.4 Importance of Applying Domain Ontology to DSS for Medical Emergency Transportation Management;186
13.5;9.5 The Architecture of a Context-Aware Decision Support Model for Safe Transportation in Medical Emergency Management;188
13.5.1;9.5.1 Knowledge Base;189
13.5.1.1;9.5.1.1 Context-Awareness;189
13.5.1.2;9.5.1.2 Domain Ontology;190
13.5.2;9.5.2 Decision Support Tools and User Interface;191
13.6;9.6 Implementation of the Proposed Architecture;193
13.6.1;9.6.1 An Overview of the Prototype of Context-Aware Agents for Healthcare Emergency Decision Support;193
13.7;9.7 Conclusions and Future Directions;195
13.8;References;197
14;10 General Motors Bailout Problem: A Teaching Case Using the Planners Lab Software;200
14.1;10.1 Introduction;200
14.2;10.2 The Assignment;200
14.2.1;10.2.1 Analysis of the GM Bailout Loan Agreement Using the Planners Lab;200
14.3;10.3 Instructions for Analyzing the Problem;201
14.4;10.4 The Model;205
14.4.1;10.4.1 Sales and Revenue;205
14.4.2;10.4.2 Costs and Expenses;206
14.4.3;10.4.3 Cash from Operating Activities;206
14.4.4;10.4.4 Cash from Investing Activities;207
14.4.5;10.4.5 Cash from Financing Activities;207
14.4.6;10.4.6 Net Cash Flow and Present Value;207
14.4.7;10.4.7 Bailout Activities;207
14.4.8;10.4.8 Market Capitalization;208
14.5;10.5 Appendix A: Introduction to the Planners Lab;208
15;11 Assessing Today: Determining the Decision ValueINTbreak; of Decision Support Systems;220
15.1;11.1 Introduction;220
15.2;11.2 Background on Decision-Making, DSS, and Evaluation;221
15.2.1;11.2.1 Decision Making Process;221
15.2.2;11.2.2 Decision Support Systems;223
15.2.3;11.2.3 Evaluation of DSS;225
15.3;11.3 Integrated Design and Evaluation Framework for DSS;227
15.4;11.4 Application;228
15.4.1;11.4.1 Analytic Hierarchy Process (AHP);228
15.4.2;11.4.2 Description of Application;228
15.4.3;11.4.3 Evaluation of Application;230
15.5;11.5 Future Trends;232
15.6;11.6 Conclusions;232
15.7;Appendix: Evaluation of DSS Compared to DSS with No AI Method The First Value Is Calculated for the DSS with IA and the Second for the DSS Without IA;234
15.8;References;235
16;Index;238