Design Science Research Methods and Patterns Innovating Information and Communication Technology, 2nd Edition

Presenting innovative research methods, this second edition of a bestseller describes a simple and practical methodology for conducting cutting-edge design science research (DSR). It provides comprehensive guidance on how to conduct such research andsupplies in-depth treatment of design science theory and the different types of theory that can be generated in design science research.Making novel use of the concept of patterns, it presents 84 research patterns for conducting effective DSR. It emphasizes design science theory throughout and is filled with practical examples of using patterns to conduct information and communication technology research (ICT).With a focus on reusing research activities to increase the effectiveness and efficiency of conducting design science research, the book relies on familiar patterns to provide the fundamentals of various research philosophies and techniques required to innovate ICT. It describes design science research in relation to other information systems research paradigms such as positivist and interpretivist research. New to this edition are relevant design science research patterns adapted from TRIZ, the widely regarded European engineering design and creativity method.This edition also provides greatly expanded treatment of theory building in design science research (DSR), a topic of rapidly growing interest in addition to a new chapter presenting a framework for theory development in DSR. The book provides an expanded examination of patterns in DSR presented using a new pattern classification mechanism to group patterns with like functionality.This book will be of value to those interested in learning to conduct design science research, particularly in the ICT disciplines the book focuses on.

IntroductionReferencesDESIGN SCIENCE RESEARCH METHODOLOGYIntroduction to Design Science Research in Information and Communication TechnologyOverview of Design Science ResearchDSR MethodologyOutputs of DSRTheory in DSRGeneral Guidance on Expected Outputs from DSRExample of Community-Determined OutputsPhilosophical Grounding of DSRAn Example of ICT DSRReferencesAppendix:A Design Science Research BibliographyAggregate Design Science Research Cycle as a Perspective on the Evolution of Computing Communities of InterestIntroductionDesign Science Research CycleAggregate DSRCExercising the ADSRC Framework: Concept Mapping 25 Years of Database ResearchUsing the ADSRC to Explain Coordination between Diverse GroupsConclusionReferencesA Framework for Theory Development in Design Science Research: Multiple PerspectivesIntroductionDesign Science Research in IS (DSR-IS) DefinedKnowledge Representation Perspective on the FrameworkExtending Knowledge Capture in DSR-IS: Alternative ApproachesStructure of the Remainder of the ChapterMid-Range Theory in DSR-ISTypological Perspective of the FrameworkEpistemological Perspective of the FrameworkTheory Construction in DSR-IS: Two Published ExamplesDiscussion and ConclusionsReferencesAppendix:Kernel Theory and DREPT Propositions for a DSR ProjectKaufmann’s Diagrammatic Representation of the Change in Modes of Mental Representation with Problem Novelty and Kasper’sInterpretation of Kaufmann’s Diagram in Terms of DSS AttributesTheory Building Techniques in Design Science ResearchOn Theory Development in Design Science Research: Anatomy of a Research ProjectIntroductionTheory in DSR-IS: What Does It Mean?ConclusionsReferencesAppendix:A Process Change Scenario Illustrating "Soft Context Information" (A True Story)System Quality RepresentationSample Process Graph "Slices" and Associated TextDescription and Micro-rationale as used in our Evaluation PrototypePATTERNSUsing Patterns to Illuminate Research PracticeIntroductionPatterns, Then, and NowUsing Patterns: The Design Science Research Cycle RevisitedMining of Design Science Research PatternsProblem-Solving Patterns in Engineering: The TRIZ ApproachPattern StructurePattern Usage in the Development of the Smart Object Paradigm Practice, Practice, PracticeReferencesAppendix:The TRIZ Inventive PrinciplesCreativity PatternsEnhancement Type PatternsUtilization Type PatternsReferencesProblem Selection and Development PatternsPreliminaries Type PatternsVisionary Type PatternExtrapolation Type PatternAnalysis Type PatternsGeneralization Type PatternExploration Type PatternSegmentation Type PatternCombination Type PatternReferencesLiterature Search PatternsPreliminaries Type PatternsAnalysis Type PatternModeling Type PatternReferencesSuggestion and Development PatternsTheory Type PatternsExpanding Design Theories (DTs) with Design and Measurement ModelsHermeneutical/Inductive (H/I) ApproachHypothetical/Deductive (H/D) ApproachIterative PrototypingPreliminaries Type PatternsVisionary Type PatternsExtrapolation Type PatternAnalysis Type PatternsExploration Type PatternsModeling Type PatternsGeneralization Type PatternsSegmentation Type PatternsCombination Type PatternsDevelopment Type PatternsCollaboration Type PatternsReferencesEvaluation and Validation PatternsBenchmarkingDemonstrationExperimentationLogical ReasoningMathematical ProofsSimulationUsing MetricsReferencesPublishing PatternsMAligning with a ParadigmConference and Journal SubmissionsNovelty and SignificanceMStyle ExemplarsUse of ExamplesWriting Conference PapersWriting Journal PapersReferencesKNOWLEDGE CONTRIBUTION & RESEAR CH PATTERNS USAGE ANALYSISKnowledge Contribution and Patterns Usage Analysis of Design Science Research ExemplarsIntroductionSmart Objects: A Data/Knowledge Paradigm for the Modeling andDesign of Operations Support SystemsCyberGate: A Design Framework and System for Text Analysis of Computer-Mediated CommunicationWorld Wide Web: Proposal for Hypertext Project.Entity-Relationship Model—Toward a Unified View of DataCase-Based Database Design Support SystemRelational Model of Data for Large Shared Data BanksAutomating the Discovery of AS-IS Business Process Models: Probabilistic and Algorithmic ApproachesWorking Set Model for Program BehaviorCommunicating Sequential ProcessesMultilevel Model for Measuring Fit between a Firm’s Competitive Strategies and ISs CapabilitiesImproving Analysis Pattern Reuse in Conceptual Design: AugmentingAutomated Processes with Supervised LearningOptimum Multiway Search TreesConclusionReferences

Vijay K. Vaishnavi is professor emeritus of computer information systems at Georgia State University. He holds a PhD from Indian Institute of Technology, Kanpur and has conducted postdoctoral work at McMaster University, Canada. His research covers several areas including design science research methods, information integration and web mining, software development, and data structures/algorithms.He has authored 150+ publications that include six books in these and related areas. His research has been funded by the National Science Foundation (NSF) as well as by the industry. He has served as consultant to various organizations such as IBM, AT&T, and Bell Northern Research. In 2007, he was awarded a Lifetime Achievement Award in Design Sciences (DESRIST 2007) for "making significant fundamental contributions in design science research through research, leadership, and mentorship."Bill Kuechler is a professor of information systems and former chair of the information systems discipline at the University of Nevada, Reno. He holds a BS in electrical engineering from Drexel University and a Ph.D. in computer information systems from Georgia State University. Bill’s academic career follows a successful 22-year industry career in information systems development and consulting. He has held positions as software engineer, software engineering manager, software systems product manager, consultant, and director of IT for a regional firm. His work experience brings insight to his teaching of both IS management and technical material and brings a wealth of practical background to his research. Bill’s two primary research themes are the cognitive bases of IS use, development and education, and design science research in IS. Dr. Kuechler is a member of AIS and ACM.