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Reconciling Theories with Design Choices in Design Science Research

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Design Science at the Intersection of Physical and Virtual Design (DESRIST 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7939))

Abstract

Despite increased acceptance of design science research, concerns about rigor and relevance permeate the research community. One way to increase rigor is by codifying design knowledge into design theories. While this idea is gaining popularity, it is unclear how to approach design theorizing in a scientifically rigorous, yet practically relevant, way. In this paper, we address one particularly murky issue in design science research: reconciling theoretical abstractness with practicality. Since many design theories are moderately abstract, a gap exists between theoretical propositions and concrete issues faced in practice. We present a case study of real information system (IS) development where these issues become evident. Based on the identified issues we provide four theory-driven recommendations including specification of transformational rules, developing or imagining a real IS artifact, specification of boundary conditions and over-specification of the theoretical core. The consequences of these recommendations for design science theorizing are discussed.

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References

  1. Gregor, S., Hevner, A.R.: Introduction to the Special Issue on Design Science. Information Systems & e-Business Management 9, 1–9 (2011)

    Article  Google Scholar 

  2. Lee, A., Chasson, M., Alter, S., Kremar, H.: Long Live Design Science Research! .... and Remind Me again about Whether it is a New Research Paradigm Or a Rationale of Last Resort for Worthwhile Research that Doesn’t Fit Under any Other Umbrella. In: ICIS 2012 (2012)

    Google Scholar 

  3. Hevner, A., March, S., Park, J., Ram, S.: Design Science in Information Systems Research. MIS Quarterly 28, 75–105 (2004)

    Google Scholar 

  4. March, S.T., Smith, G.F.: Design and Natural Science Research on Information Technology. Decision Support Systems 15, 251–266 (1995)

    Article  Google Scholar 

  5. Gregor, S., Jones, D.: The Anatomy of Design Theory. Journal of the Association for Information Systems 8, 312–335 (2007)

    Google Scholar 

  6. Gregor, S.: The Nature of Theory in Information Systems. MIS Quarterly 30, 611–642 (2006)

    Google Scholar 

  7. Walls, J.G., Widmeyer, G.R., El Sawy, O.A.: Building an Information System Design Theory for Vigilant EIS. Information Systems Research 3, 36–59 (1992)

    Article  Google Scholar 

  8. Iivari, J.: A Paradigmatic Analysis of Information Systems as a Design Science. Scandinavian Journal of Information Systems, 39–64 (2007)

    Google Scholar 

  9. Gleasure, B., Feller, J., O’Flaherty, B.: Procedurally Transparent Design Science Research: A Design Process Model. In: ICIS 2012, pp. 1–19 (2012)

    Google Scholar 

  10. Piirainen, K.A., Briggs, R.O.: Design Theory in Practice – Making Design Science Research More Transparent. In: Jain, H., Sinha, A.P., Vitharana, P. (eds.) DESRIST 2011. LNCS, vol. 6629, pp. 47–61. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  11. Hovorka, D., Gregor, S.: Untangling Causality in Design Science Theorizing. In: 5th Biennial ANU Workshop on Information Systems Foundations: Theory Building in Information Systems (2010)

    Google Scholar 

  12. Gregor, S., Hovorka, D.S.: Causality: The Elephant in the Room in Information Systems Epistemology. In: ECIS 2011 (2011)

    Google Scholar 

  13. Venable, J.: The Role of Theory and Theorising in Design Science Research. In: DESRIST 2006, pp. 1–18 (2006)

    Google Scholar 

  14. Kuechler, W., Vaishnavi, V.: A Framework for Theory Development in Design Science Research: Multiple Perspectives. Journal of the Association for Information Systems 13, 395–423 (2012)

    Google Scholar 

  15. Weber, R.: Evaluating and Developing Theories in the Information Systems Discipline. Journal of the Association for Information Systems 13, 2 (2012)

    Google Scholar 

  16. Moody, D.L., Iacob, M., Amrit, C. In: Search of Paradigms: Identifying the Theoretical Foundations of the Information System Field. In: ECIS 2010, pp. 1–15 (2010)

    Google Scholar 

  17. Kuechler, B., Vaishnavi, V.: On Theory Development in Design Science Research: Anatomy of a Research Project. European Journal of Information Systems 17, 489–504 (2008)

    Article  Google Scholar 

  18. Merton, R.: On Sociological Theories of the Middle Range. In: Merton, R. (ed.) Social Theory and Social Structure, pp. 39–53. Simon & Schuster, New York (1949)

    Google Scholar 

  19. Venable, J.: Incorporating Design Science Research and Critical Research into an Intro-ductory Business Research Methods Course. Electronic Journal of Business Research Methods 9 (2011)

    Google Scholar 

  20. Peffers, K., Tuunanen, T., Gengler, C.E., Rossi, M., Hui, W., Virtanen, V., Bragge, J.: The Design Science Research Process: A Model for Producing and Presenting Information Systems Research. In: DESRIST 2006, pp. 83–106 (2006)

    Google Scholar 

  21. Iivari, J.: Nothing is as Clear as Unclear. Scandinavian Journal of Information Systems 19, 111–117 (2007)

    Google Scholar 

  22. Sutton, R.I., Staw, B.M.: What Theory is Not. Administrative Science Quarterly, 371–384 (1995)

    Google Scholar 

  23. Weick, K.E.: Theory Construction as Disciplined Reflexivity: Tradeoffs in the 90s. Academy of Management Review 24, 797–806 (1999)

    Google Scholar 

  24. Arazy, O., Kumar, N., Shapira, B.: A Theory-Driven Design Framework for Social Re-commender Systems. Journal of the Association for Information Systems 11, 455–490 (2010)

    Google Scholar 

  25. Benbasat, I., Weber, R.: Research Commentary: Rethinking “diversity” in Information Systems Research. Information Systems Research 7, 389–399 (1996)

    Article  Google Scholar 

  26. Hirschheim, R.A., Klein, H.K.: Crisis in the IS Field? A Critical Reflection on the State of the Discipline. Journal of the Association for Information Systems 4, 237–293 (2003)

    Google Scholar 

  27. Silvertown, J.: A New Dawn for Citizen Science. Trends in Ecology & Evolution 24, 467–471 (2009)

    Article  Google Scholar 

  28. Hand, E.: People Power. Nature 466, 685–687 (2010)

    Article  Google Scholar 

  29. Lukyanenko, R., Parsons, J., Wiersma, Y.: Citizen Science 2.0: Data Management Principles to Harness the Power of the Crowd. In: Jain, H., Sinha, A.P., Vitharana, P. (eds.) DESRIST 2011. LNCS, vol. 6629, pp. 465–473. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  30. Fortson, L., Masters, K., Nichol, R., Borne, K., Edmondson, E., Lintott, C., Raddick, J., Schawinski, K., Wallin, J.: Galaxy Zoo: Morphological Classification and Citizen Science. In: Advances in Machine Learning and Data Mining for Astronomy, pp. 1–11 (2011)

    Google Scholar 

  31. Prestopnik, N.R., Crowston, K.: Gaming for (Citizen) Science: Exploring Motivation and Data Quality in the Context of Crowdsourced Science through the Design and Evaluation of a Social-Computational System. In: “Computing for Citizen Science” Workshop at the IEEE eScience Conference, pp. 1–28 (2011)

    Google Scholar 

  32. Antelio, M., Esteves, M.G.P., Schneider, D., de Souza, J.M.: Qualitocracy: A Data Qual-ity Collaborative Framework Applied to Citizen Science. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics, pp. 931–936 (2012)

    Google Scholar 

  33. Parsons, J., Lukyanenko, R., Wiersma, Y.: Easier Citizen Science is Better. Nature 471, 37–37 (2011)

    Article  Google Scholar 

  34. Rowland, K.: Citizen Science Goes ‘Extreme’. Nature (2012)

    Google Scholar 

  35. Chen, P.: The Entity-Relationship Model - Toward a Unified View of Data. ACM Transactions on Database Systems 1, 9–36 (1976)

    Article  Google Scholar 

  36. Teorey, T.J., Yang, D., Fry, J.P.: A Logical Design Methodology for Relational Data-bases using the Extended Entity-Relationship Model. ACM Computing Surveys 18, 197–222 (1986)

    Article  MATH  Google Scholar 

  37. Codd, E.F.: Relational Database: A Practical Foundation for Productivity. Communications of the ACM 25, 109–117 (1982)

    Article  Google Scholar 

  38. Hochachka, W.M., Fink, D., Hutchinson, R.A., Sheldon, D., Wong, W., Kelling, S.: Data-Intensive Science Applied to Broad-Scale Citizen Science. Trends in Ecology & Evolution 27, 130–137 (2012)

    Article  Google Scholar 

  39. Silvertown, J.: Taxonomy: Include Social Networking. Nature 467, 788–788 (2010)

    Article  Google Scholar 

  40. Lukyanenko, R., Parsons, J.: Conceptual Modeling Principles for Crowdsourcing. In: Proceedings of the 1st International Workshop on Multimodal Crowd Sensing, pp. 3–6 (2012)

    Google Scholar 

  41. Lukyanenko, R., Parsons, J.: Rethinking Data Quality as an Outcome of Conceptual Modeling Choices. In: 16th International Conference on Information Quality, pp. 1–16 (2011)

    Google Scholar 

  42. Parsons, J., Wand, Y.: Emancipating Instances from the Tyranny of Classes in Information Modeling. ACM Transactions on Database Systems 25, 228–268 (2000)

    Article  Google Scholar 

  43. Wand, Y., Weber, R.: On the Deep Structure of Information Systems. Information Systems Journal 5, 203–223 (2008)

    Article  Google Scholar 

  44. Ghose, A., Goldfarb, A., Han, S.: How is the Mobile Internet Different? Search Costs and Local Activities. Information Systems Research, pp. 1–19 (forthcoming)

    Google Scholar 

  45. Gredler, M., Shields, C.: Does no One Read Vygotsky’s Words? Commentary on Glassman. Educational Researcher 33, 21–25 (2004)

    Article  Google Scholar 

  46. Chomsky, N.: The minimalist program. MIT Press (1995)

    Google Scholar 

  47. Chiang, R.H.L., Barron, T.M., Storey, V.C.: Reverse Engineering of Relational Data-bases: Extraction of an EER Model from a Relational Database. Data & Knowledge Engineering 12, 107–142 (1994)

    Article  Google Scholar 

  48. Sein, M.K., Rossi, M., Purao, S.: Exploring the Limits of the Possible. Scandinavian Journal of Information Systems 19, 105–110 (2007)

    Google Scholar 

  49. Cole, R., Purao, S., Rossi, M., Sein, M.: Being Rigorously Relevant: Design Research and Action Research in Information Systems. In: ICIS 2005, pp. 325–336 (2005)

    Google Scholar 

  50. Figueiredo, A., Cunha, P.: Action Research and design in Information Systems. In: Kock, N. (ed.) Information Systems Action Research, pp. 61–96. Springer (2007)

    Google Scholar 

  51. Järvinen, P.: Mapping Research Questions to Research Methods. In: Avison, D., Kasper, G.M., Pernici, B., Ramos, I., Roode, D. (eds.) Advances in Information Systems Research, Education and Practice. IFIP, vol. 274, pp. 29–41. Springer, Boston (2008)

    Chapter  Google Scholar 

  52. Sein, M., Henfridsson, O., Purao, S., Rossi, M., Lindgren, R.: Action Design Research. MIS Quarterly 35, 37 (2011)

    Google Scholar 

  53. Bamberger, P.: From the Editors Beyond Contextualization: Using Context Theories to Narrow the Micro-Macro Gap in Management Research. Academy of Management Journal 51, 839–846 (2008)

    Article  Google Scholar 

  54. Weick, K.E.: Theory Construction as Disciplined Imagination. Academy of Management Review, 516–531 (1989)

    Google Scholar 

  55. Weick, K.E.: What Theory is Not, Theorizing is. Administrative Science Quarterly 40, 385–390 (1995)

    Article  Google Scholar 

  56. Lee, A.S.: A Scientific Methodology for MIS Case Studies. MIS Quarterly, 33–50 (1989)

    Google Scholar 

  57. Tversky, A.: Features of Similarity. Psychological Review 84, 327–352 (1977)

    Article  Google Scholar 

  58. Evermann, J.: Applying Cognitive Principles of Similarity to Data Integration–the Case of SIAM. In: AMCIS 2012 (2012)

    Google Scholar 

  59. Te’eni, D.: Designs That Fit: An Overview of Fit Conceptualizations in HCI. In: Zhang, P., Galletta, D. (eds.) Human-Computer Interaction and Management Information Systems: Foundations, pp. 205–223. M.E. Sharpe (2006)

    Google Scholar 

  60. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 425–478 (2003)

    Google Scholar 

  61. Gefen, D., Karahanna, E., Straub, D.W.: Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly 27, 51–90 (2003)

    Google Scholar 

  62. Parsons, J., Wand, Y.: Using Cognitive Principles to Guide Classification in Information Systems Modeling. MIS Quarterly 32, 839–868 (2008)

    Google Scholar 

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Lukyanenko, R., Parsons, J. (2013). Reconciling Theories with Design Choices in Design Science Research. In: vom Brocke, J., Hekkala, R., Ram, S., Rossi, M. (eds) Design Science at the Intersection of Physical and Virtual Design. DESRIST 2013. Lecture Notes in Computer Science, vol 7939. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38827-9_12

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  • DOI: https://doi.org/10.1007/978-3-642-38827-9_12

  • Publisher Name: Springer, Berlin, Heidelberg

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