Designing Informing systems: What Research Tells Us

Designing Informing systems: What Research Tells Us
Alan R. Hevner University of South Florida

Outline Designing Informing Systems Design Science Research (DSR)
Concepts, Models, and Guidelines Three Cycles of Design Activities Positioning and Presenting DSR The Knowledge Contribution Matrix A Fitness/Utility Model of DSR Discussion and Questions

Informing Systems Design Science is a creative research paradigm that informs multiple audiences: Researchers: Design principles and mid-range design theories Practitioners: Artifact (product and process) instantiations Managers: Work and application system controls Government: Economic and social welfare

Design Science Research
Sciences of the Artificial, 3rd Ed. – Simon 1996 A Problem Solving Paradigm The Creation of Innovative Artifacts to Solve Real Problems Design in Other Fields – Long Histories Engineering, Architecture, Art Role of Creativity in Design DSR in Information Systems A. 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 S. Gregor and D. Jones, “The Anatomy of a Design Theory,” Journal of the Association of Information Systems, (8:5), 2007, pp

MISQ 2004 Research Essay A. 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 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 1991 Initial Discussions and Papers Iivari 1991 – Schools of IS Development Nunamaker et al – Electronic GDSS Walls, Widmeyer, and El Sawy 1992 – EIS Design Theory Madnick from WITS 1991 Keynote March and Smith 1995 from WITS 1992 Keynote Encouragement from IS Leaders such as Gordon Davis, Ron Weber, and Bob Zmud Allen Lee, EIC of MISQ, invited authors to submit essay on Design Science Research in 1998 Four Review Cycles with multiple reviewers Published in 2004

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

IS Research Cycle

Design Thinking Design is an Artifact (Noun)
Constructs Models Methods Instantiations Design is a Process (Verb) Build Evaluate Design is a Wicked Problem Unstable Requirements and Constraints Complex Interactions among Subcomponents of Problem and resulting Subcomponents of Solution Inherent Flexibility to Change Artifacts and Processes Dependence on Human Cognitive Abilities - Creativity Dependence on Human Social Abilities - Teamwork

Environment IS Research Knowledge Base
Additions to the Knowledge Base Environment IS Research Knowledge Base People Roles Capabilities Characteristics Experience Organizations Strategies Structure Culture Processes Technology Infrastructure Applications Communications Architecture Development Capabilities Foundations Theories Frameworks Experimental Instruments Constructs Models Methods Instantiations Methodologies Experimentation Data Analysis Techniques Formalisms Measures Validation Criteria Optimization Develop / Build Artifacts Justify / Evaluate Analytical Case Study Experimental Field Study Simulation Assess Refine Business Needs Applicable Knowledge Application in the Appropriate Environment Relevance Rigor

Design Research Guidelines
Description Guideline 1: Design as an Artifact Design-science research must produce a viable artifact in the form of a construct, a model, a method, or an instantiation. Guideline 2: Problem Relevance The objective of design-science research is to develop technology-based solutions to important and relevant business problems. Guideline 3: Design Evaluation The utility, quality, and efficacy of a design artifact must be rigorously demonstrated via well-executed evaluation methods. Guideline 4: Research Contributions Effective 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 Rigor Design-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 Process The search for an effective artifact requires utilizing available means to reach desired ends while satisfying laws in the problem environment. Guideline 7: Communication of Research Design-science research must be presented effectively both to technology-oriented as well as management-oriented audiences.

Three Cycles of DSR Ref: A. Hevner, “A Three Cycle View of Design Science Research,” Scandinavian Journal of Information Systems, Vol. 19, No. 2, 2007, pp Design Science Knowledge Base Environment Foundations Scientific Theories & Methods Application Domain People Organizational Systems Technical Systems Problems & Opportunities Build Design Artifacts & Processes Experience & Expertise Rigor Cycle Grounding Additions to KB Relevance Cycle Requirements Field Testing Design Cycle Evaluate Meta-Artifacts (Design Products & Design Processes)

The Relevance Cycle The Application Domain initiates Design Research with: Research requirements (e.g., opportunity, problem, potentiality) Acceptance criteria for evaluation of design artifact in application domain Field Testing of Research Results Does 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 needed Artifact has deficiencies in behaviors or qualities Restatement of research requirements Feedback into research from field testing evaluation

The Rigor Cycle Design Research Knowledge Base
Design Theories Engineering Methods Experiences and Expertise Existing Design Artifacts and Processes Research 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 methods New experiences and expertise New artifacts and design processes

Design Cycle Rapid iteration of Build and Evaluate activities
The 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 environment Continue Design Cycle until: Artifact ready for field test in Application Environment New knowledge appropriate for inclusion in Knowledge Base

Positioning and Presenting DSR
S. 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 communicated Goals of essay: appreciate the levels of artifact abstractions that may be DSR contributions to include design theory identify appropriate ways of consuming and producing knowledge when preparing journal articles or other scholarly works understand and position the knowledge contributions of research projects structure a DSR article so that a significant contribution to the knowledge base is highlighted.

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

The Artifact as Knowledge
Contribution type Examples More abstract, complete, and mature knowledge ↕ ↕ ↕ ↕ More specific, limited, and less mature knowledge Level 3. Well-developed design theory about embedded phenomena Design theories (mid- range and grand theories) Level 2. Nascent design theory – knowledge as operational principles/architecture Constructs, methods, models, design principles, technological rules. Level 1. Situated implementation of artifact Instantiations (software products or implemented methods)

Design Theory as Knowledge
Theory – 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 action Behaviors of individual artifacts (Level 1) lead to empirical generalizations or technical rules Extending the boundaries of abstract design artifacts (Level 2) grows nascent design theory Middle-range design theory (Level 3) – understanding expands to partial theory (Goal of theory in applied fields – Merton 1968) Grand design theory – transitions to descriptive theory

The DSR Process Human Capabilities Application Environment Ω Knowledge
Cognitive Creativity Reasoning Analysis Synthesis Social Teamwork Collective Intelligence Knowledge Sources - Research Opportunities and Problems - Research Questions Contribution to Ω Knowledge Informing Ω Knowledge Constructs Models Methods Instantiations Design Theory Λ Knowledge

Knowledge Growth in DSR Cycles
Ωn Knowledge Λn Knowledge Design Cycle 1 Design Cycle 2 Design Cycle n … … … …

DSR Knowledge Contribution Framework
A Guideline for Positioning DSR with respect to Knowledge Contribution Two dimensions: Maturity of Application Domain (Opportunities/ Problems) Maturity of Solutions (Existing Artifacts) Difficulties: Subjectivity – where to draw the lines Everything builds on something else, nothing entirely new

Invention: Invent new solutions for new problems Research Opportunity
Improvement: Develop new solutions for known problems Research Opportunity Low Solution Maturity Exaptation: Extend known solutions to new problems (e.g. Adopt solutions from other fields) Research Opportunity Routine Design: Apply known solutions to known problems High High Low Application Domain (Problem) Maturity

Invention Quadrant An invention is a radical breakthrough; a departure from accepted ways of thinking and doing DSR projects in which little understanding of the problem context exists and no effective artifacts are available as solutions Research contributions are novel artifacts or inventions Level 1 artifacts The newness of artifact makes this research difficult to publish Insufficiently grounded in theory Design is incomplete and not fully evaluated Understanding is insufficient to provide new contribution to theory via the design

Invention Exemplars Agrawal, 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 database Practical importance: Allows organizations to find interesting relationships (e.g. shopping patterns) Theoretical significance (newness): Shows (Sect 5) that no other work has done same thing Description 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 Systems

Improvement Quadrant An improvement is a better artifact solution in the form of more efficient and effective products, processes, services, technologies, or ideas DSR projects in which the problem context is mature but there is a great need for more effective artifacts as solutions Improvement DSR is judged by: Clearly grounding, representing, and communicating the new artifact design Convincing evaluation providing evidence of improvements over current solutions All levels of artifact knowledge contribution can be made

Improvement Exemplars
Many 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)

Exaptation Quadrant An 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 solutions Exaptation DSR is judged by: Clearly grounding, representing, and communicating the exapted artifact design Convincing evaluation providing evidence of how well the new artifact solves the given problem All levels of artifact knowledge contribution can be made

Exaptation Exemplars Exaptation 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 knowledge Research 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 applications

Routine Design Quadrant
Professional design or system building to be distinguished from DSR However, 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 generalization Example – Davenport’s observation of BPR (Davenport & Short SMR 1990)

MISQ Papers mapped to Framework
Knowledge Contribution Article Knowledge Contribution Claims Improvement A 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). Guidelines for Designing Visual Ontologies to Support Knowledge Identification (Bera et al., ) 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 ). Exaptation Co-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). Design 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) Correlated Failures, Diversification, and Information Security Risk Management (Chen et al., ) 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). The 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). Improving 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). Detecting 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). The 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). Process 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). Making 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). CyberGate: 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). Using 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).

DSR Publication Schema
How best to communicate DSR research contributions? A Publication Schema is proposed that highlights artifact build and evaluation activities The knowledge contribution is a focus throughout the publication schema

Section Contents 1. Introduction Problem 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 Review Prior 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. Method The 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., ; 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.

Section Contents 4. Artifact Description This 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. Evaluation The 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. Conclusion Concluding paragraphs that restate the important findings of the work. States the main ideas in the contribution and why they are important.

DSR Publication Exemplar – McLaren et al. 2011 MISQ
Section Contents Introduction Problem 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 Review Reviews prior approaches and classifies them into three types. Shows the deficiencies in prior approaches. (pp. 2-4) Method Follows Baskerville et al (2009) methodology, plus exploratory research methods for developing managerial guidelines from case study evidence (Eisenhardt 1989). (p. 4) Artifact Description Describes 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). Evaluation The model was evaluated for reliability, validity and utility (pp ).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. Conclusions An overview of the work is given and contributions highlighted, as well as limitations and directions for further work.

Publishing Design Research
Competitive Workshops and Conferences Present ideas and receive feedback from reviews and live questions, Refine ideas ACM, IEEE, AIS, INFORMS, AMIA Conferences DESRIST Conference Opportunities to Fast-Track to Journals Journal Submission Know the Audience of the Journal (Technical, Managerial) and Focus Research Contributions Read relevant papers from Journal and Cite them Contact Senior Editors for guidance Aim High and Be Persistent

A Fitness-Utility Model for DSR
Rethinking the Dependent Variable in DSR How 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 Award

The DSR Dependent Variable
Usefulness Aligns with current MIS research paradigms Well understood in academia and practice Measurable with current instruments Why look elsewhere? Extend the search for DSR dependent variables Explore ‘goodness’ ideas from other fields Design Fitness (Biology) Design Utility (Economics) Goal is to complement and extend current DSR thinking

Design Fitness Landscape
In 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.

Design Process Elements

Design Fitness Definition 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 correlated Empirical data refutes Malthus’ proposition Focus on Design Fitness as Definition 2

Design Utility IS Artifact Utility typically means Usefulness
Efficacy to perform task Ease of Use, Ease of Learning Cost-Benefit vis-à-vis other artifacts Economic Utility involves a complex Utility Function used to rank alternatives in order to Maximize Utility Utility = u(x1, x2, …, xN) Utility Characteristics Income and consumption Expectations and goals Social context Utility Function will vary for different application contexts

Evolutionary Economics
Essentially, the human utility function is tuned to maximize evolutionary fitness on a fitness landscape Higher fitness humans will crowd out lower fitness humans over time Since fitness landscapes change over time, Evolutionary Stable Strategies (ESS) encourage traits that promote diversity and adaptation While Human Evolution is slow, ICT Evolution is rapid, made more so by good DSR What is a good design utility function to apply to a complex and evolving ICT fitness landscape?

Fitness-Utility Model applied to DSR
A design artifact has an associated fitness that designers estimate via design utility functions Artifacts 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 landscape They provide a mechanism for communication between designers and for retaining information that might be imperfectly stored during the design process Intentionality – Creative guidance that differentiates ICT design/evolution from human evolution Search on the design space changes the design space by modifying the utility function of design fitness

Re-Framing DSR with Fitness-Utility
The 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.

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

Fitness Characteristics
Questions: 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?

Designs That are Too Useful?
Situations where a design artifact becomes so useful that it inhibits future design activity The 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 Drives Printers Mini-computers

Decomposable Designs Systems evolve from nearly decomposable subsystems (Simon, 1996) Decomposability supports: Independence of modules Information hiding Maintenance and evolution of modules separately from whole system Robustness Exemplar – Open Source Software

Malleable Designs The 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 malleability Customization Exaptation Integration Extension

Open Designs Openness is the degree to which artifacts are open to inspection, modification, and reuse Open 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 artifact Exemplar – UNIX vs. LINUX

Embedded in a Design System
We 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 activity The particular purpose that such systems play is encouraging communication within and throughout the design process A design system can also manifest itself as a community of users and designers, providing contributors with intrinsic motivation to contribute

Design Novelty A design may be considered novel if it originates from an unexplored region of the design fitness landscape While 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 diversity

Interesting Designs Designs are interesting when
An artifact may demonstrate unexpected emergent behaviors that are worthy of subsequent investigation and the creation of subsequent artifacts An artifact may be constructed in an unexpected way that intrigues other designers or design researchers The benefit of an interesting design is its propensity to diffuse—to be an effective meme

Design Elegance The Form of an artifact describes aesthetic elements such as appearance that do not necessarily serve a useful purpose, yet nevertheless increase the user’s utility Like 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 enhancement

Fitness Characteristics and Outcomes

Pros of Fitness-Utility Model
Fitness-Utility Model complements current thinking Researcher is an active participant in the design system Alternative bases for evaluating DSR impact Aligns better with dynamic design environments Recognizes limitations of intended usefulness Encourages collaboration between researchers and designers in IS and other fields

Cons of Fitness-Utility Model
Existing research standards do not reward design impacts based on new model – longitudinal studies needed to evaluate evolutionary impacts Research is needed to understand how to evaluate design fitness Rigor in Fitness-Utility research requires alternative (new?) research methods

Conclusions The Fitness-Utility Model of DSR provides a new approach for viewing the building and evaluating of design artifacts Design characteristics beyond usefulness are important in rapidly changing application environments Future Research Empirical studies evaluating utility functions in context and for general applications Case studies of historical designs based on fitness-utility Adapting Evolutionary Economics concepts to DSR

Active DSR Research Projects
Innovation and DSR S. 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 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 DSR A. 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 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 DSR J. 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 DSR A. 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.

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