Designing Informing systems: What Research Tells Us - PowerPoint Presentation

1. Designing Informing systems: What Research Tells UsAlan R. HevnerUniversity of South Floridaahevner@usf.edu1

2. OutlineDesigning Informing SystemsDesign Science Research (DSR)Concepts, Models, and GuidelinesThree Cycles of Design ActivitiesPositioning and Presenting DSRThe Knowledge Contribution MatrixA Fitness/Utility Model of DSRDiscussion and Questions2

3. Informing SystemsDesign Science is a creative research paradigm that informs multiple audiences:Researchers: Design principles and mid-range design theoriesPractitioners: Artifact (product and process) instantiationsManagers: Work and application system controlsGovernment: Economic and social welfare3

4. Design Science ResearchSciences of the Artificial, 3rd Ed. – Simon 1996A Problem Solving ParadigmThe Creation of Innovative Artifacts to Solve Real ProblemsDesign in Other Fields – Long HistoriesEngineering, Architecture, ArtRole of Creativity in DesignDSR in Information SystemsA. Hevner, S. March, J. Park, and S. Ram, “Design Science Research in Information Systems,” Management Information Systems Quarterly, Vol. 28, No. 1, March 2004, pp. 75-105.S. Gregor and D. Jones, “The Anatomy of a Design Theory,” Journal of the Association of Information Systems, (8:5), 2007, pp. 312-335. 4

5. MISQ 2004 Research EssayA. Hevner, S. March, J. Park, and S. Ram, “Design Science Research in Information Systems,” Management Information Systems Quarterly, Vol. 28, No. 1, March 2004, pp. 75-105.Historically, the Informing Systems field has been confused about the role of design (technical) research.Technical researchers felt out of the mainstream of ICIS/MISQ community.Formation of Workshop on Information Technology and Systems (WITS) in 1991Initial Discussions and PapersIivari 1991 – Schools of IS DevelopmentNunamaker et al. 1991 – Electronic GDSSWalls, Widmeyer, and El Sawy 1992 – EIS Design TheoryMadnick from WITS 1991 KeynoteMarch and Smith 1995 from WITS 1992 KeynoteEncouragement from IS Leaders such as Gordon Davis, Ron Weber, and Bob ZmudAllen Lee, EIC of MISQ, invited authors to submit essay on Design Science Research in 1998Four Review Cycles with multiple reviewersPublished in 20045

6. Research in Information SystemsInformation Systems (IS) are complex, artificial, and purposefully designed.IS are composed of people, structures, technologies, and work systems.Two Basic IS Research ParadigmsBehavioral Research – Goal is TruthDesign Research – Goal is Utility (and Truth!)6

7. IS Research Cycle7

8. Design ThinkingDesign is an Artifact (Noun)ConstructsModelsMethodsInstantiationsDesign is a Process (Verb)BuildEvaluateDesign is a Wicked ProblemUnstable Requirements and ConstraintsComplex Interactions among Subcomponents of Problem and resulting Subcomponents of SolutionInherent Flexibility to Change Artifacts and ProcessesDependence on Human Cognitive Abilities - CreativityDependence on Human Social Abilities - Teamwork8

9. 9Additions to the Knowledge BaseEnvironmentIS ResearchKnowledge BasePeopleRolesCapabilitiesCharacteristicsExperienceOrganizationsStrategiesStructureCultureProcessesTechnologyInfrastructureApplicationsCommunications ArchitectureDevelopment CapabilitiesFoundationsTheoriesFrameworksExperimental InstrumentsConstructsModelsMethodsInstantiationsMethodologiesExperimentationData Analysis TechniquesFormalismsMeasuresValidation CriteriaOptimizationDevelop / BuildTheoriesArtifactsJustify / EvaluateAnalyticalCase StudyExperimentalField Study SimulationAssessRefineBusiness NeedsApplicable KnowledgeApplication in the Appropriate EnvironmentRelevanceRigor

10. Design Research Guidelines GuidelineDescriptionGuideline 1: Design as an ArtifactDesign-science research must produce a viable artifact in the form of a construct, a model, a method, or an instantiation.Guideline 2: Problem RelevanceThe objective of design-science research is to develop technology-based solutions to important and relevant business problems.Guideline 3: Design EvaluationThe utility, quality, and efficacy of a design artifact must be rigorously demonstrated via well-executed evaluation methods.Guideline 4: Research ContributionsEffective design-science research must provide clear and verifiable contributions in the areas of the design artifact, design foundations, and/or design methodologies.Guideline 5: Research RigorDesign-science research relies upon the application of rigorous methods in both the construction and evaluation of the design artifact. Guideline 6: Design as a Search ProcessThe search for an effective artifact requires utilizing available means to reach desired ends while satisfying laws in the problem environment.Guideline 7: Communication of ResearchDesign-science research must be presented effectively both to technology-oriented as well as management-oriented audiences. 10

11. Three Cycles of DSR11EnvironmentKnowledge BaseDesign ScienceBuild Design Artifacts & ProcessesEvaluate Design CycleApplication Domain People Organizational Systems Technical Systems Problems & OpportunitiesRelevance Cycle Requirements Field Testing Rigor Cycle Grounding Additions to KBFoundations Scientific Theories & Methods Experience & Expertise Meta-Artifacts (Design Products & Design Processes)Ref: A. Hevner, “A Three Cycle View of Design Science Research,” Scandinavian Journal of Information Systems, Vol. 19, No. 2, 2007, pp. 87-92.

12. The Relevance CycleThe Application Domain initiates Design Research with:Research requirements (e.g., opportunity, problem, potentiality)Acceptance criteria for evaluation of design artifact in application domainField Testing of Research ResultsDoes the design artifact improve the environment?How is the improvement measured?Field testing methods might include Action Research or Controlled Experiments in actual environments.Iterate Relevance Cycle as neededArtifact has deficiencies in behaviors or qualitiesRestatement of research requirementsFeedback into research from field testing evaluation12

13. The Rigor CycleDesign Research Knowledge BaseDesign TheoriesEngineering MethodsExperiences and ExpertiseExisting Design Artifacts and ProcessesResearch Rigor is predicated on the researcher’s skilled selection and application of appropriate theories and methods for constructing and evaluating the artifact.Additions to the Knowledge Base:Extensions to theories and methodsNew experiences and expertiseNew artifacts and design processes13

14. Design CycleRapid iteration of Build and Evaluate activitiesThe hard work of design research (1% inspiration and 99% perspiration - Edison) Build – Create and Refine artifact design as both product (noun) and process (verb)Evaluation – Rigorous, scientific study of artifact in laboratory or controlled environmentContinue Design Cycle until:Artifact ready for field test in Application EnvironmentNew knowledge appropriate for inclusion in Knowledge Base 14

15. Positioning and Presenting DSRS. Gregor and A. Hevner, “Positioning and Presenting Design Science Research for Maximum Impact,” June 2013, MISQ.DSR is stymied by lack of clear understanding of how knowledge is consumed, produced, and communicatedGoals of essay:appreciate the levels of artifact abstractions that may be DSR contributions to include design theoryidentify appropriate ways of consuming and producing knowledge when preparing journal articles or other scholarly worksunderstand and position the knowledge contributions of research projectsstructure a DSR article so that a significant contribution to the knowledge base is highlighted. 15

16. Useful KnowledgeΩ – Descriptive KnowledgeΛ – Prescriptive Knowledge Phenomena (Natural, Artificial, Human) Observations Classification Measurement Cataloging Sense-making Natural Laws Regularities Principles Patterns Theories Artifacts Constructs Concepts Symbols Models Representation Semantics/Syntax Methods Algorithms Techniques Instantiations Systems Products/Processes Design Theory16

17. The Artifact as Knowledge17 Contribution typeExamplesMore abstract, complete, and mature knowledge ↕ ↕ ↕ ↕ More specific, limited, and less mature knowledge Level 3. Well-developed design theory about embedded phenomenaDesign theories (mid-range and grand theories)Level 2. Nascent design theory – knowledge as operational principles/architectureConstructs, methods, models, design principles, technological rules.Level 1. Situated implementation of artifactInstantiations (software products or implemented methods)

18. Design Theory as KnowledgeTheory – set of statements of relationships among constructs that aims to describe, explain, enhance understanding, and, in some cases, allow predictions about the future (Gregor 2006)Design Theory (Gregor and Jones 2007) – prescriptions for design and actionBehaviors of individual artifacts (Level 1) lead to empirical generalizations or technical rulesExtending the boundaries of abstract design artifacts (Level 2) grows nascent design theoryMiddle-range design theory (Level 3) – understanding expands to partial theory (Goal of theory in applied fields – Merton 1968)Grand design theory – transitions to descriptive theory18

19. Ω KnowledgeΛ KnowledgeApplication Environment- Research Opportunities and Problems- Research QuestionsHuman Capabilities Cognitive Creativity Reasoning Analysis Synthesis Social Teamwork Collective IntelligenceKnowledge SourcesConstructsModelsMethodsInstantiationsInforming Ω KnowledgeThe DSR Process19Contribution to Ω KnowledgeDesign Theory

20. Ω1 KnowledgeΛ1 KnowledgeΩ2 KnowledgeΛ2 KnowledgeΩn KnowledgeΛn KnowledgeDesign Cycle 1Design Cycle 2Design Cycle n … … … …20Knowledge Growth in DSR Cycles

21. DSR Knowledge Contribution FrameworkA Guideline for Positioning DSR with respect to Knowledge ContributionTwo dimensions: Maturity of Application Domain (Opportunities/ Problems) Maturity of Solutions (Existing Artifacts)Difficulties: Subjectivity – where to draw the linesEverything builds on something else, nothing entirely new21

22. Solution MaturityApplication Domain (Problem) MaturityHighLowHighLowRoutine Design: Apply known solutions to known problemsExaptation: Extend known solutions to new problems (e.g. Adopt solutions from other fields) Research OpportunityImprovement: Develop new solutions for known problemsResearch OpportunityInvention: Invent new solutions for new problems Research Opportunity22

23. Invention QuadrantAn invention is a radical breakthrough; a departure from accepted ways of thinking and doingDSR projects in which little understanding of the problem context exists and no effective artifacts are available as solutionsResearch contributions are novel artifacts or inventionsLevel 1 artifactsThe newness of artifact makes this research difficult to publishInsufficiently grounded in theoryDesign is incomplete and not fully evaluatedUnderstanding is insufficient to provide new contribution to theory via the design23

24. Invention ExemplarsAgrawal, R., Imielinski, T. and Swami, A. (1993). “Mining Association Rules between Sets of Items in Large Databases”, Proceedings of the 1993 ACM SIGMOD Conference, Washington DC, May.Aim: produce an algorithm that generates all significant association rules between items in the databasePractical importance: Allows organizations to find interesting relationships (e.g. shopping patterns)Theoretical significance (newness): Shows (Sect 5) that no other work has done same thingDescription of new method: Shows requirements (Sect 1), new concepts (association rule, support, confidence), Formal Model (pseudocode) (Sects 2-3)Proof: Experiments (Sect 4)Scott-Morton (1967) – Decision Support Systems24

25. Improvement QuadrantAn improvement is a better artifact solution in the form of more efficient and effective products, processes, services, technologies, or ideasDSR projects in which the problem context is mature but there is a great need for more effective artifacts as solutionsImprovement DSR is judged by:Clearly grounding, representing, and communicating the new artifact designConvincing evaluation providing evidence of improvements over current solutionsAll levels of artifact knowledge contribution can be made25

26. Improvement ExemplarsMany DSR projects in IS are in the Improvement Quadrant, for example:Better data mining algorithms for knowledge discovery (extending the initial ideas invented by Agrawal et al. (1993)); for example, (Fayyad et al. 1996; Zhang et al. 2004; Witten et al. 2011)Improved recommendation systems for use in e-commerce; for example (Herlocker et al. 2004; Adomavicius and Tuzhilin 2005)Better technologies and use strategies for saving energy in IT applications; for example (Donnellan et al. 2011; Watson and Boudreau 2011)Improved routing algorithms for business supply chains; for example (van der Aalst and Hee 2004; Liu et al. 2005)26

27. Exaptation QuadrantAn exaptation is the expropriation of an artifact in one field to solve problems in another field DSR projects in which the problem context is not well understood but there exist mature artifacts in other fields that can be exapted as effective solutionsExaptation DSR is judged by:Clearly grounding, representing, and communicating the exapted artifact designConvincing evaluation providing evidence of how well the new artifact solves the given problemAll levels of artifact knowledge contribution can be made27

28. Exaptation ExemplarsExaptation DSR is employed when new technologies provide opportunities to solve new and/or different IS problems; for example:Codd’s exaptation of relational mathematics to the problem of database systems design leading to relational database concepts, models, methods, and instantiations (Codd, 1970; Codd, 1982)Berners-Lee original concept of the World Wide Web was one of simply sharing research documents in a hypertext form among multiple computers. In short time, however, many individuals saw the potential of this rapidly expanding interconnection environment to exapt applications from old platforms to the WWW platforms. These new Internet applications were very different from previous versions adding many new artifacts to Λ knowledgeResearch by Berndt et al. (2003) on the CATCH data warehouse for health care information. Well-known methods of data warehouse development (e.g. Inmon, 1992) were exapted to new and interesting areas of health care systems and decision-making applications28

29. Routine Design QuadrantProfessional design or system building to be distinguished from DSRHowever, evolving or best practices may be observed and documented in “extractive case study” work (Van Aken)Study of best practices in routine design may lead to empirical generalizationExample – Davenport’s observation of BPR (Davenport & Short SMR 1990)29

30. MISQ Papers mapped to Framework30Knowledge ContributionArticleKnowledge Contribution ClaimsImprovementA Multilevel Model for Measuring Fit Between a Firm’s Competitive Strategies and Information Systems Capabilities (McLaren et al., 2011)There is a need for a more fine-grained model for diagnosing the individual IS capabilities that contribute to the overall fit or misfit between a firm’s competitive strategies and IS capabilities (p.2) (See also Table 4).ImprovementGuidelines for Designing Visual Ontologies to Support Knowledge Identification (Bera et al., 2011) There could be several ways to address OWL’s inability to show state changes… We have taken a different path, taking the view that we can keep the existing OWL syntax and improve the extent to which it support s knowledge identification (pp. 885-886).ExaptationCo-creation in Virtual Worlds: The Design of the User Experience (Kohler et al., 2011) While Nambisan and his colleagues provide a useful framework for the online environment in general, little is known about designing co-creation experiences in virtual worlds (p. 774).ExaptationDesign Principles for Virtual Worlds(Chaturvedi et al., 2011)  ABVWs comprise a new class of information systems… Thus, they require an extension of the corresponding information system design principles (p. 675)ImprovementCorrelated Failures, Diversification, and Information Security Risk Management (Chen et al., 2011) While our model to estimate security loss due to unavailable (i.e., system downtime) is based on well-established queuing models, one innovation of our model is that the distribution from which the number of requests sent to the queue is drawn is endogeneous to system variables (p. 399).ExaptationThe Effects of Tree-View Based Presentation Adaptation on Mobile Web Browsing. (Adipat et al., 2011)  Presentation adaptation has been studied in the desktop environment and has been proven beneficial … However, research on adaptation of Web content presentation for mobile handheld devices is still rare (p. 100).ImprovementImproving Employees’ Compliance Through Information Systems Security Training: An Action Research Study. (Puhakainen and Sipponen 2010) There is a need for IS security training approaches that are theory-based and empirically evaluated. … (p. 757). To address this deficiency … this paper developed a theory-based training program … This paper then tested the practical workability through an action research intervention (p. 776).ImprovementDetecting Fake Websites: The Contribution of Statistical Learning Theory. (Abbasi et al., 2010) Systems grounded in SLT can more accurately detect various categories of fake web sites (p. 435).ImprovementThe Design Theory Nexus. ( Pries-Heje and Baskerville, 2008)The work suggests that the design theory nexus approach is more universal than previous approaches to contingency theory, because it can operate in both symmetrical and asymmetrical settings (p. 748).ImprovementProcess Grammar as a Tool for Business Process Design. (Lee et al., 2008)  The method improves on existing approaches by offering the generative power of grammar-based methods while addressing the principal challenge to using such approaches … (p. 757).ImprovementMaking Sense of Technology Trends in the Information Technology Landscape: A Design Science Approach. (Adomavicius, et al., 2008)Our approach may complement existing technology forecasting methods … by providing structured input and formal analysis of the past and current states of the IT landscape (p. 802).ImprovementCyberGate: A Design Framework and System for Text Analysis of Computer-Mediated Communication. (Abbasi and Chen 2008)The results revealed that the CyberGate system and its underlying design framework can dramatically improve CMC text analysis capabilities over those provided by existing systems (p. 811). ImprovementUsing Cognitive Principles to Guide Classification in Information Systems Modeling. ( Parsons and Wand 2008)Despite the importance of classification, no well-grounded methods exist .. (p. 840). We provide empirical evidence…that the rules can guide the construction of semantically clearer and more useful models (p. 858).

31. DSR Publication SchemaHow best to communicate DSR research contributions?A Publication Schema is proposed that highlights artifact build and evaluation activitiesThe knowledge contribution is a focus throughout the publication schema31

32. 32SectionContents1. IntroductionProblem definition, problem significance/motivation, introduction to key concepts, research questions/objectives, scope of study, overview of methods and findings, theoretical and practical significance, structure of remainder of paper. For DSR the contents are similar, but the problem definition and research objectives should specify the goals that are required of the artifact to be developed. The relevance of the research problem must be clearly stated.2. Literature ReviewPrior work that is relevant to the study, including theories, empirical research studies and findings/reports from practice.For DSR work, the prior literature surveyed should include any prior design theory/knowledge relating to the problem to be addressed, including artifacts that have already been developed to solve similar problems. An aim is to show the “gap” that is still to be filled.Reference should also be made to the justificatory theory that informed the design of the new artifact. A fuller explanation of the justificatory theory may be better placed in the Artifact Description section, matched with the specific artifact component to which it applies. However, it may help to signal what is to come by giving a brief description of the justificatory theory here. 3. MethodThe research approach that was employed. For DSR work the specific DSR approach adopted should be explained, with reference to existing authorities (for example, Hevner et al., 2004; Nunamaker et al., 1990-91; Peffers et al., 2008; Sein et al., 2011). Research rigor must be clearly demonstrated in selection of methods and techniques for the building and evaluating of the artifact.

33. 33SectionContents4. Artifact DescriptionThis section (or sections) should occupy the major part of the paper. The format is likely to be variable but should include at least the description of the design artifact and, perhaps, the design search process. If the aim is to show a design theory, this section could include meta-requirements, constructs, principles of form and function, artifact mutability, testable propositions and justificatory knowledge. Principles of implementation and any instantiation may also be provided.5. EvaluationThe artifact is evaluated to demonstrate its worth with evidence of validity, utility, quality, and efficacy. A rigorous design evaluation may draw from many potential techniques, such as analytics, case studies, experiments or simulations (see Hevner et al., (2004)). 6. Discussion Interpretation of the results: what the results mean and how they relate back to the objectives stated in the Introduction Section. Can include: summary of what was learned, comparison with prior work, limitations, theoretical significance, practical significance, areas requiring further work.Research contributions are highlighted and the broad implications of the paper’s results to research and practice are discussed. A summary of what has been learned could be provided by expressing the design theory (if any) produced in terms of the design theory components specified by Gregor and Jones (2007). Claims for novelty and utility should be expressed as well as claims for a contribution to design theory if appropriate.7. ConclusionConcluding paragraphs that restate the important findings of the work. States the main ideas in the contribution and why they are important.

34. DSR Publication Exemplar – McLaren et al. 2011 MISQ34SectionContentsIntroductionProblem definition: There is a need for a more fine-grained model for diagnosing the individual IS capabilities that contribute to the overall fit or misfit between a firm’s competitive strategies and IS capabilities. (p.2)Goal: to design and evaluate a new and more fine-grained measurement tool (p. 2).Relevance: Improving the strategic fit of a firm’s information system has been a primary goal of IS executives for at least two decades (p. 2). Literature ReviewReviews prior approaches and classifies them into three types. Shows the deficiencies in prior approaches. (pp. 2-4)MethodFollows Baskerville et al (2009) methodology, plus exploratory research methods for developing managerial guidelines from case study evidence (Eisenhardt 1989). (p. 4)Artifact DescriptionDescribes the seven steps of the multilevel strategic fit (MSF) measurement model in detail (p. 6-12). Justificatory theory for some steps is given; e.g., Conant, Mokwa and Varadarajan (1990). EvaluationThe model was evaluated for reliability, validity and utility (pp. 12-15).using data from the case studies that were used to inform the mode’s design. The reliability of the MSF model was evaluated by comparing outputs from the final version of the model with all the evidence gathered form the case studies (p. 13). Discussion The MSF measurement model is shown as an important contribution as a theory for design and action (prescriptive knowledge). Design knowledge is summarized in terms of Gregor and Jones (2007) framework for design theory, shown in an appendix.A contribution to supply chain management is argued in terms of clearer ways of conceptualizing supply chain management (descriptive knowledge). A contribution to research methodology is also argued and implications for practice are shown.The research itself is evaluated against Hevner et al (2004) guidelines for conducting design science research.ConclusionsAn overview of the work is given and contributions highlighted, as well as limitations and directions for further work.

35. Publishing Design ResearchCompetitive Workshops and ConferencesPresent ideas and receive feedback from reviews and live questions, Refine ideasACM, IEEE, AIS, INFORMS, AMIA ConferencesDESRIST ConferenceOpportunities to Fast-Track to JournalsJournal SubmissionKnow the Audience of the Journal (Technical, Managerial) and Focus Research ContributionsRead relevant papers from Journal and Cite themContact Senior Editors for guidanceAim High and Be Persistent35

36. A Fitness-Utility Model for DSRRethinking the Dependent Variable in DSRHow can we make the results of DSR (e.g., artifacts, design theories) more sustainable ?T.G. Gill and A. Hevner, “A Fitness-Utility Model for Design Science Research,” ACM Transactions on Management Information Systems, 2013.DESRIST 2011 Herbert Simon Best Paper Award36

37. The DSR Dependent VariableUsefulnessAligns with current MIS research paradigmsWell understood in academia and practiceMeasurable with current instrumentsWhy look elsewhere?Extend the search for DSR dependent variablesExplore ‘goodness’ ideas from other fieldsDesign Fitness (Biology)Design Utility (Economics)Goal is to complement and extend current DSR thinking37

38. Design Fitness LandscapeIn evolutionary biology, the term fitness landscape is used to describe a functional mapping between some abstract representation of an entity—such as a listing of attributes and traits or, even, as a DNA sequence—and its associated fitness that captures the entity’s ability to survive, reproduce, and evolve from generation to generation. This concept can be generalized to design situations, whereby a design is represented as a collection of traits and its fitness represents the likelihood that all or some pieces of the design (which we informally refer to as design DNA) will continue to exist and evolve from generation to generation.38

39. Design Process Elements39

40. Design FitnessDefinition 1 – The fitness of an organism describes its ability to survive as a high level of capacity over time.Definition 2 – The fitness of an organism describes its ability to replicate and evolve over successive generations.Two definitions are not correlatedEmpirical data refutes Malthus’ propositionFocus on Design Fitness as Definition 240

41. Design UtilityIS Artifact Utility typically means UsefulnessEfficacy to perform taskEase of Use, Ease of LearningCost-Benefit vis-à-vis other artifactsEconomic Utility involves a complex Utility Function used to rank alternatives in order to Maximize UtilityUtility = u(x1, x2, …, xN)Utility CharacteristicsIncome and consumptionExpectations and goalsSocial contextUtility Function will vary for different application contexts41

42. Evolutionary EconomicsEssentially, the human utility function is tuned to maximize evolutionary fitness on a fitness landscapeHigher fitness humans will crowd out lower fitness humans over timeSince fitness landscapes change over time, Evolutionary Stable Strategies (ESS) encourage traits that promote diversity and adaptationWhile Human Evolution is slow, ICT Evolution is rapid, made more so by good DSRWhat is a good design utility function to apply to a complex and evolving ICT fitness landscape?42

43. Fitness-Utility Model applied to DSRA design artifact has an associated fitness that designers estimate via design utility functionsArtifacts perform two roles in the design search process: They provide evidence that a particular design candidate is feasible, has value, can be effectively represented, and can be built. This serves to help us better estimate the shape of the design fitness landscapeThey provide a mechanism for communication between designers and for retaining information that might be imperfectly stored during the design processIntentionality – Creative guidance that differentiates ICT design/evolution from human evolutionSearch on the design space changes the design space by modifying the utility function of design fitness43

44. Re-Framing DSR with Fitness-UtilityThe goal of DSR is to impact the design space so as to ensure a continuous flow of high fitness design artifacts. This impact is accomplished in two ways: through the production of artifacts that demonstrate the feasibility of new designs and through improving the utility function that we use to assess the fitness of evaluation artifacts.44

45. DSR Evaluation with Fitness-UtilityAs opposed to just Usefulness, the evaluation would be based on a more extensive and detailed utility function that estimates the evolutionary fitness of the artifactUtility Function Attributes:Support the design’s ability to evolve incrementally;Encourage experimentation by users and other designers; andAre effective memes, meaning that they contain ideas of a form that propagate and replicate.45

46. Fitness Characteristics46Questions:How to measure the fitness characteristics?How to select appropriate characteristics for application environment?How to combine and weigh characteristics in utility function?How to evolve utility function as environment changes?

47. Designs That are Too Useful?Situations where a design artifact becomes so useful that it inhibits future design activityThe tendency of organizations to stick with designs that have proven useful is a well-documented phenomenon known as the Innovator’s Dilemma (Christensen, 1997)Disk DrivesPrintersMini-computers47

48. Decomposable DesignsSystems evolve from nearly decomposable subsystems (Simon, 1996)Decomposability supports:Independence of modulesInformation hidingMaintenance and evolution of modules separately from whole systemRobustnessExemplar – Open Source Software48

49. Malleable DesignsThe malleability of an artifact represents the degree to which it can be adapted by its users and respond to changing use/market environments Types of malleabilityCustomizationExaptationIntegrationExtension49

50. Open DesignsOpenness is the degree to which artifacts are open to inspection, modification, and reuseOpen designs—particularly when also imbued with decomposability and malleability—encourage further design evolution by making it easier both to see how an artifact is constructed and to modify existing components of the artifactExemplar – UNIX vs. LINUX50

51. Embedded in a Design SystemWe would expect design artifacts that are the product of a sustainable design system environment to evolve more rapidly than artifacts that are produced in a context where design is an unusual activityThe particular purpose that such systems play is encouraging communication within and throughout the design processA design system can also manifest itself as a community of users and designers, providing contributors with intrinsic motivation to contribute51

52. Design NoveltyA design may be considered novel if it originates from an unexplored region of the design fitness landscapeWhile a particular novel design may be less individually fit than existing counterparts, where the landscape is dynamic the fitness of the population as whole benefits from having a sub-population of designers seeking novelty for its own sake, thereby ensuring design diversity52

53. Interesting DesignsDesigns are interesting whenAn artifact may demonstrate unexpected emergent behaviors that are worthy of subsequent investigation and the creation of subsequent artifactsAn artifact may be constructed in an unexpected way that intrigues other designers or design researchersThe benefit of an interesting design is its propensity to diffuse—to be an effective meme53

54. Design EleganceThe Form of an artifact describes aesthetic elements such as appearance that do not necessarily serve a useful purpose, yet nevertheless increase the user’s utilityLike quality, elegance is hard to define in a rigorous manner and yet characteristics that might be associated with it—such as compactness, simplicity, transparency of use, transparency of behavior, clarity of representation—can all lead to designs that invite surprise, delight, imitation, and enhancement54

55. Fitness Characteristics and Outcomes55

56. Pros of Fitness-Utility ModelFitness-Utility Model complements current thinkingResearcher is an active participant in the design systemAlternative bases for evaluating DSR impactAligns better with dynamic design environmentsRecognizes limitations of intended usefulnessEncourages collaboration between researchers and designers in IS and other fields56

57. Cons of Fitness-Utility ModelExisting research standards do not reward design impacts based on new model – longitudinal studies needed to evaluate evolutionary impactsResearch is needed to understand how to evaluate design fitnessRigor in Fitness-Utility research requires alternative (new?) research methods57

58. ConclusionsThe Fitness-Utility Model of DSR provides a new approach for viewing the building and evaluating of design artifactsDesign characteristics beyond usefulness are important in rapidly changing application environmentsFuture ResearchEmpirical studies evaluating utility functions in context and for general applicationsCase studies of historical designs based on fitness-utilityAdapting Evolutionary Economics concepts to DSR58

59. Active DSR Research ProjectsInnovation and DSRS. Gregor and A. Hevner, “The Knowledge Innovation Matrix (KIM): A Clarifying Lens for Innovation,” Informing Science: The International Journal of an Emerging Transdiscipline, 17, 2014, pp. 217-239.S. Gregor and A. Hevner, “The Front End of Innovation: Perspectives on Creativity, Knowledge, and Design,” Proceedings of the Design Science Research in Information Systems and Technology (DESRIST 2015), Dublin, May 2015.Neuroscience and DSRA. Hevner, C. Davis, R.W. Collins, and T.G. Gill, “A NeuroDesign Model for IS Research,” Informing Science: The International Journal of an Emerging Transdiscipline, 17, 2014, pp. 103-132. C. Davis and A. Hevner, “Neurophysiological Analysis of Visual Syntax in Design,” Gmunden Retreat on NeuroIS, Gmunden, Austria, June 2015.Hermann Zemlicka Award for the most visionary paper.Cybersecurity and DSRJ. Sjostrom, P. Agerfalk, and A. Hevner, “The Design of a Multi-Layer Scrutiny Protocol to Support Online Privacy and Accountability,” Proceedings of the Design Science Research in Information Systems and Technology (DESRIST 2014), Miami, May 2014.Sociotechnical Systems and DSRA. Drechsler and A. Hevner, “Effectuation and its Implications for Socio-Technical Design Science Research in Information Systems,” Proceedings of the Design Science Research in Information Systems and Technology (DESRIST 2015), Dublin, May 2015.A. Drechsler, T.G. Gill, and A. Hevner, “Beyond Rigor and Relevance: Exploring Artifact Resonance,” submitted for publication, 2015.59

60. Discussion and Questions60