Design Science Perspectives on IT-Consulting

Transcription

1 Design Science Perspectives on IT-Consulting European Research Center for Information Systems (ERCIS) Department of Information Systems University of Münster, Germany

2 European Research Center for Information Systems (ERCIS) 2

3 WARNUNG! Die Autoren adressieren ein Problem, dass sich so in der Praxis des IT-Consulting nicht stellt. [aus den Reviews zu diesem Beitrag] 3

4 Rhetoriken Criteria Objectives Desired Output Consensual Mode Complexity Management Consulting Research Building theories Justified theories, truth (intersubjectively measurable) Dissent (critical-distant perspectice; practically uninvolved research) Imperative of sophisticated analyses, often resulting in increased complexity Consulting Practice Practical efficiency and effectiveness Best practices, pooling of experiences Consensus Imperative of reducing complexity (in deutscher Sprache: vgl. Kieser 1999, Mohe 2005) 4

5 Entsprechungen Criteria Objectives Desired Output Consensual Mode Information Systems Consulting Research Building theories Justified theories, truth (intersubjectively measurable) Dissent (critical-distant perspectice; practically uninvolved research) Information Systems Consulting Practice Practical efficiency and effectiveness Best practices, pooling of experiences Consensus Complexity Management Imperative of sophisticated analyses, often resulting in increased complexity Imperative of reducing complexity (vgl. Benbasat, Zmud 2003, Weber 2004, Walls et al etc.) 5

6 Versöhnungen Criteria Information Systems Consulting Research Information Systems Consulting Practice Objectives Desired Output Consensual Mode Building theories Justified theories, truth (intersubjectively measurable) Dissent (critical-distant perspectice; practically uninvolved research) Design Science Research Practical efficiency and effectiveness Best practices, pooling of experiences Consensus Complexity Management Imperative of sophisticated analyses, often resulting in increased complexity Imperative of reducing complexity (vgl. Walls et al. 1992, March & Smith 1995, Hevner et al. 2005, Markus et al. 2002, Rossi et al etc.) 6

7 Übertragungen Criteria Consulting Research Consulting Practice Objectives Desired Output Consensual Mode Building theories Justified theories, truth (intersubjectively measurable) Dissent (critical-distant perspectice; practically uninvolved research) Design Science Research Practical efficiency and effectiveness Best practices, pooling of experiences Consensus Complexity Management Imperative of sophisticated analyses, often resulting in increased complexity Imperative of reducing complexity -? - 7

8 Entwicklungen 8

9 Abgrenzungen origin Behavioural Science Research (BSR) natural science Design Science Research (DSR) engineering, sciences of the artificial approach problem understanding approach problem solving approach objective develop and justify theories which explain or predict organizational human phenomena surrounding the analysis, design, implementation, management, and use of information systems create innovations that define ideas, practices, technical capabilities, and product through the analysis, design, implementation, management, and use of information systems object human-computer-interaction IT artefact design (in Anlehnung an March & Smith 1995, Hevner et al. 2005) 9

10 IS Research Cycle Umdrehungen (in Anlehnung an March & Smith 1995, Hevner et al. 2005) 10

11 Design Research vs. Design Practice Environment Relevance IS Research Rigor Knowledge Base People Foundations Develop/Build Theories Theories Frameworks Artifacts Instruments Business Applicable Constructs Needs Organizations Assess Refine Knowledge Models Methods Instantiations Technology Justify/Evaluate Analytical CaseStudy Experimental Field Study Simulation Methodologies Data Analysis Techniques Formalisms Measures Validation Criteria Application in the Appropriate Environment Additions to the Knowledge Base (Quelle: Hevner et al. 2005) 11

12 Bewertungen Guideline Guideline 1: Design as an Artifact Guideline 2: Problem Relevance Guideline 3: Design Evaluation Guideline 4: Research Contributions Guideline 5: Research Rigor Guideline 6: Design as a Search Process Guideline 7: Communication of Research Description Design-science research must produce a viable artifact in the form of a construct, a model, a method, or an instantiation. The objective of design-science research is to develop technology-based solutions to important and relevant business problems. The utility, quality, and efficacy of a design artifact must be rigorously demonstrated via well-executed evaluation methods. Effective design-science research must provide clear and verifiable contributions in the areas of the design artifact, design foundations, and/or design methodologies. Design-science research relies upon the application of rigorous methods in both the construction and evaluation of the design artifact. The search for an effective artifact requires utilizing available means to reach desired ends while satisfying laws in the problem environment. Design-science research must be presented effectively both to technology-oriented as well as management-oriented audiences. (Quelle: Hevner et al. 2005) 12

13 Konzeptionalisierungen 13

14 Konzeptionalisierungen 14

15 Perspektiven Forschungsperspektive auf IT-Consulting (-Praxis) Auch: IT-Consulting als kontextueller Faktor Forschungsfokus (+) Publikationskultur international (+) Praxisperspektive auf IT-Consulting (-Forschung) Interesse an Publikation (?) Guidelines (Vorbereitung und Aufbereitung) 15

16 Q & A 16

17 Kontakt Experteninterview Designing IT-Consulting Processes Björn Niehaves, Dipl.-Kfm., M.A. European Research Center for Information Systems University of Münster Leonardo-Campus 3 Tel bjoern.niehaves@ercis.de 17