Technological knowledge has been characterized as having a scope that is specific to a particular problem. However, the information systems community is exploring forms of design science research that provide a promising avenue to technological knowledge with broader scope: design theories. Because design science research is materially prescriptive, it requires a different perspective in developing the breadth of applications of design theories. In this paper we propose different concepts that embody forms of general technological knowledge The concept of projectability, developed originally as a means of distinguishing realized generalizations from unrealized generalizations, helps explain how design theories, being prescriptive, possess a different form of applicability. The concept of entrenchment describes the use of a theory in many projections. Together these concepts provide a means for comparative discussions of the importance of design theories. Projectable design theories guide designers in the design of artifacts similar in principle, but different in context. These can also help design researchers understand interrelationships between design theories.


design science research design theory technological knowledge generalizability research methodology 


  1. 1.
    Pries-Heje, J., Pries-Heje, L.: Designing a Framework for Virtual Management and Team Building. In: Peffers, K., Rothenberger, M., Kuechler, B. (eds.) DESRIST 2012. LNCS, vol. 7286, pp. 256–270. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  2. 2.
    Gregor, S., Jones, D.: The Anatomy of a Design Theory. Journal of the Association for Information Systems 8(5), 312–335 (2007)Google Scholar
  3. 3.
    Hevner, A.R., March, S.T., Park, J., Ram, S.: Design Science in Information Systems Research. MIS Quarterly 28(1), 75–105 (2004)Google Scholar
  4. 4.
    March, S.T., Smith, G.: Design and Natural Science Research on Information Technology. Decision Support Systems 15(4), 251–266 (1995)CrossRefGoogle Scholar
  5. 5.
    Walls, J.G., Widmeyer, G.R., El Sawy, O.A.: Building an Information System Design Theory for Vigilant EIS. Information Systems Research 3(1), 36–59 (1992)CrossRefGoogle Scholar
  6. 6.
    Baskerville, R., Lyytinen, K., Sambamurthy, V., Straub, D.: A Response to the Design-Oriented Information Systems Research Memorandum. European Journal Information Systems 20(1), 11–15 (2011)CrossRefGoogle Scholar
  7. 7.
    Junglas, I., Niehaves, B., Spiekermann, S., Stahl, B.C., Weitzel, T., Winter, R., Baskerville, R.: The Case for Design Science Research in Europe. European Journal Information Systems 20(1), 1–6 (2011)CrossRefGoogle Scholar
  8. 8.
    Österle, H., Becker, J., Frank, U., Hess, T., Karagiannis, D., Krcmar, H., Loos, P., Mertens, P., Oberweis, A., Sinz, E.J.: Memorandum on Design-Oriented Information Systems Research. European Journal Information Systems 20(1), 7–10 (2011)CrossRefGoogle Scholar
  9. 9.
    Lee, A.S., Baskerville, R.L.: Generalizing Generalizability In Information Systems Research. Information Systems Research 14(3), 221–243 (2003)CrossRefGoogle Scholar
  10. 10.
    Goodman, N.: Fact, Fiction, & Forecast. Harvard University Press, Cambridge (1955)Google Scholar
  11. 11.
    Nagel, E.: The Structure of Science: Problems in Scientific Explanation. Routledge and Kegan Paul, London (1961)Google Scholar
  12. 12.
    Shadish, W.R., Cook, T.D., Campbell, D.T.: Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin, Boston (2002)Google Scholar
  13. 13.
    Simon, H.A.: The Science of the Artificial, 3rd edn. MIT Press, Cambridge (1996)Google Scholar
  14. 14.
    Williams, R., Pollock, N.: Moving Beyond the Single Site Implementation Study: How (and Why) We Should Study the Biography of Packaged Enterprise Solutions. Information Systems Research 23(1), 1–22 (2012)CrossRefGoogle Scholar
  15. 15.
    Baskerville, R., Pries-Heje, J.: Explanatory Design Theory. Business & Information Systems Engineering 2(5), 271–282 (2010)CrossRefGoogle Scholar
  16. 16.
    Walls, J.G., Widmeyer, G.R., El Sawy, O.A.: Assessing Information System Design Theory in Perspective: How Useful Was Our 1992 Initial Rendition? Journal of Information Technology Theory and Application 6(2), 43–58 (2004)Google Scholar
  17. 17.
    Guba, E.G., Lincoln, Y.S.: Epistemological and Methodological Bases of Naturalistic Inquiry. Educational Communications and Technology Journal 30(4), 233–252 (1982)Google Scholar
  18. 18.
    Lincoln, Y.S., Guba, E.G.: Naturalistic Inquiry. Sage, Newbury Park (1985)Google Scholar
  19. 19.
    Walmsley, J.: The Development of Lockean Abstraction. British Journal for the History of Philosophy 8(3), 395–418 (2000)CrossRefGoogle Scholar
  20. 20.
    Priest, S.: Abstraction. In: Honderich, T. (ed.) The Oxford Companion to Philosophy, p. 3. Oxford University Press, Oxford (2005)Google Scholar
  21. 21.
    Walmsley, J.: Locke on Abstraction: A Response to M.R. Ayers. British Journal for the History of Philosophy 7(1), 123 (1999)CrossRefGoogle Scholar
  22. 22.
    Kasper, G.M.: A Theory of Decision Support System Design for User Calibration. Information Systems Research 7(2), 215–232 (1996)CrossRefGoogle Scholar
  23. 23.
    Markus, M.L., Majchrzak, A., Gasser, A.: A Design Theory for Systems That Support Emergent Knowledge Processes. MIS Quarterly 26(3), 179–212 (2002)Google Scholar
  24. 24.
    Bunge, M.: Scientific Research I: The Search for System. Springer, New York (1967)zbMATHGoogle Scholar
  25. 25.
    Bunge, M.: Scientific Research II: The Search for Truth. Springer, New York (1967)zbMATHGoogle Scholar
  26. 26.
    van Aken, J.E.: Management Research Based on the Paradigm of the Design Sciences: The Quest for Field-Tested and Grounded Technological Rules. Journal of Management Studies 41(2), 219–246 (2004)CrossRefGoogle Scholar
  27. 27.
    Davenport, T.H., Barth, P., Bean, R.: How Big Data Is Different. MIT Sloan Management Review 54(1), 43–46 (2012)Google Scholar
  28. 28.
    Argyris, C.: The Discipline of Managment and Academic Defensive Routines. In: Mansfield, R. (ed.) Frontiers of Management, pp. 8–21. Routledge, London (1989)Google Scholar
  29. 29.
    Pries-Heje, J., Baskerville, R.: The Design Theory Nexus. MIS Quarterly 32(4), 731–755 (2008)Google Scholar
  30. 30.
    Ritchey, T.: Wicked Problems: Structuring Social Messes with Morphological Analysis (2011),
  31. 31.
    Rittel, H., Webber, M.W.: Dilemmas in a General Theory of Planning. Policy Sciences 4, 155–169 (1973)CrossRefGoogle Scholar
  32. 32.
    Vaishnavi, V.K., Kuechler, W.: Design Science Research Methods and Patterns: Innovating Information and Communication Technology. Auerbach Publications, Boca Raton (2008)Google Scholar
  33. 33.
    Alexander, C.: Notes on the Synthesis of Form. Harvard University Press, Cambridge (1964)Google Scholar
  34. 34.
    Alexander, C., Ishikawa, S., Silverstein, M.: A Pattern Language: Towns, Buildings, Construction. Oxford University Press, New York (1977)Google Scholar
  35. 35.
    Gamma, E., Helm, R., Johnson, R., Vlissides, J.: Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley, Reading (1995)Google Scholar
  36. 36.
    Donaldson, L.: The Contingency Theory of Organizations. Sage Publications, Thousand Oaks (2001)CrossRefGoogle Scholar
  37. 37.
    Galegher, J., Kraut, R.E.: Computer-Mediated Communication for Intellectual Teamwork: An Experiment in Group Writing. Information Systems Research 5(2), 110 (1994)CrossRefGoogle Scholar
  38. 38.
    Hersey, P., Blanchard, K.H.: Life Cycle Theory Of Leadership. Training and Development Journal 23(5), 26–34 (1969)Google Scholar
  39. 39.
    Hersey, P., Blanchard, K.H.: So You Want to Know Your Leadership Style? Training and Development Journal 35(6), 34–54 (1981)Google Scholar
  40. 40.
    Lawrence, P.R., Lorsch, J.W.: Organization and Environment: Managing Differentiation and Integration. Harvard University, Graduate School of Business Administration, Division of Research, Boston (1967)Google Scholar
  41. 41.
    Zigurs, I., Buckland, B.: A Theory of Task/Technology Fit and Group Support System Effectiveness. MIS Quarterly 22(3), 313–334 (1998)CrossRefGoogle Scholar
  42. 42.
    Zigurs, I., Buckland, B.K., Connolly, J.R., Wilson, E.V.: A Test of Task/Technology Fit Theory for Group Support Systems. Database for Advances in Information Systems 30(3/4), 34–50 (1999)CrossRefGoogle Scholar
  43. 43.
    Van de Ven, A.H., Drazin, R.: The Concept of Fit in Contingency Theory. Research in Organizational Behaviour 7, 333–365 (1985)Google Scholar
  44. 44.
    van Aken, J.E.: Management Research as a Design Science: Articulating the Research Products of Mode 2 Knowledge Production in Management. British Journal of Management 16(1), 19–36 (2005)CrossRefGoogle Scholar
  45. 45.
    van Aken, J.E., Romme, G.: Reinventing the Future: Adding Design Science to the Repertoire of Organization and Management Studies. Organization Management Journal 6, 5–12 (2009)CrossRefGoogle Scholar
  46. 46.
    Lee, A.S., Baskerville, R.L.: Conceptualizing Generalizability: New Contributions and a Reply. MIS Quarterly 36(3), 749–761 (2012)Google Scholar
  47. 47.
    Tsang, E.W.K., Williams, J.N.: Generalization and Hume’s Problem of Induction: Misconceptions and Clarifications. MIS Quarterly 36(3), 729–748 (2012)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Richard Baskerville
    • 1
    • 2
  • Jan Pries-Heje
    • 3
  1. 1.Georgia State UniversityAtlantaUSA
  2. 2.Curtin University of TechnologyPerthAustralia
  3. 3.Roskilde UniversityRoskildeDenmark

Personalised recommendations