Advertisement

Class of Problems and Artifacts

  • Aline DreschEmail author
  • Daniel Pacheco Lacerda
  • José Antônio Valle AntunesJr
Chapter
  • 3.8k Downloads

Abstract

This chapter is organized into three sections. In Sect. 5.1, the definitions and concepts related to the Class of Problems will be presented. In addition, examples of some Classes of Problems that are common to management will be provided. Section 5.2 addresses the concept and typification of the artifacts generated from the Design Science Research. Additionally, the definitions of each type of artifact, as well as the main characteristics that distinguish them, will be presented. Section 5.3 presents a logic that relates the artifacts generated from Design Science Research and the concept of the Class of Problems. Furthermore, the formalization of a possible research trajectory that is grounded on Design Science will be performed.

Keywords

Traditional Science Artifact Designing Construction Heuristic Design Science Research Outer Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. Allora, F. (1985). Engenharia de Custos Técnicos [Engineering of Technical Costs]. Blumenau: FURB.Google Scholar
  2. Alturki, A., Gable, G. G., & Bandara, W. (2011). A Design Science Research RoadmapDESRIST. Milwakee: Springer.Google Scholar
  3. Andrade, L. A., et al. (2006). Pensamento Sistêmico: Caderno de Campo [Systems Thinking: Fieldbook]. Porto Alegre: Bookman.Google Scholar
  4. Beer, M., & Eisenstat, R. (1996). Developing an organization capable of implementing strategy and learning. Human Relations, 49(5), 597.CrossRefGoogle Scholar
  5. Cole, R. et al. (2005). Being proactive: Where action research meets design research. In Proceedings of the Twenty-Sixth International Conference on Information Systems, Anais…Las Vegas.Google Scholar
  6. Cooper, R., & Kaplan, R. S. (1988). Measure costs right: Make the right decisions. Harvard Business Review, n. September–October, pp. 96–104.Google Scholar
  7. Cox III J. F., & Schleier Jr., J. G. (2010). Theory of constraints handbook. New York: The McGraw-Hill Companies.Google Scholar
  8. Gill, T. G., & Hevner, A. R. (2011). A fitness-utility model for design science research service-oriented perspectives in design science research. 6th International Conference, DESRIST 2011. Anais…Milwakee: Springer.Google Scholar
  9. Goldratt, E. M. (2006). The Haystack Syndrome: Digging information in an ocean of data. USA: The North River Press.Google Scholar
  10. Goldratt, E. M. (1997). Critical chain. USA: The North River Press.Google Scholar
  11. Goldratt, E. M. (1994). It’s not luck. USA: The North River Press.Google Scholar
  12. Goldratt, E. M., & Cox, J. (1984). The goal: A process of ongoing improvement. USA: The North River Press.Google Scholar
  13. Gregor, S. (2009). Building theory in the sciences of the artificial. In: DESRIST, v. May 7–8, 2009.Google Scholar
  14. Gregor, S., & Jones, D. (2007). The anatomy of a design theory. Journal of the Association for Information Systems, 8(5), 312–335.Google Scholar
  15. Hambrick, D., & Cannella Jr, A. A. (1989). Strategy implementation as substance and selling. Academy of Management Executive, 3(4), 278–285.Google Scholar
  16. Holmström, J., Ketokivi, M., & Hameri, A.-P. (2009). Bridging practice and theory: A design science approach. Decision Sciences, 40(1), 65–88.CrossRefGoogle Scholar
  17. Huff, A., Tranfield, D., & van Aken, J. E. (2006). Management as a design science. Journal of Management Inquiry, 15, 413–424.CrossRefGoogle Scholar
  18. Kaplan, R., & Norton, D. P. (1992). The balanced scorecard: Measures that drive performance. Harvard Business Review, 70(1), 71–86.Google Scholar
  19. Kepner, C. H., & Tregoe, B. B. (1980). O Administrador Racional: Uma abordagem sistemática à solução de problemas e tomada de decisão [The Rational Manager: A Systematic Approach to Problem Solving and Decision-Making] (2nd ed.). São Paulo: Atlas.Google Scholar
  20. Koen, B. V. (2003). Discussion of the method: Conducting the engineer’s approach to problem solving. New York: Oxford University Press.Google Scholar
  21. Labovitz, G., & Rosansky, V. (1997). The power of alignment: how great companies stay centered and accomplish extraordinary things. EUA: John Wiley and Sons.Google Scholar
  22. Lacerda, D. P., et al. (2013). Design Science Research: A research method to production engineering. Gestão & Produção, 20(4), 741–761.CrossRefGoogle Scholar
  23. March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems, 15, 251–266.CrossRefGoogle Scholar
  24. Nunamaker, J. F., Chen, M., & Purdin, T. D. M. (1991). Systems Development in Information Systems Research. Journal of Management Information Systems, 7(3), 89–106.Google Scholar
  25. Ohno, T. (1988). Toyota production system: beyond large-scale production. USA: Productivity Press.Google Scholar
  26. Purao, S. (2002). Design research in the technology of information systems: Truth or Dare: Atlanta.Google Scholar
  27. Rother, M., & Shook, J. (1999). Aprendendo a enxergar [Learning to see]. São Paulo: Lean Institute Brasil.Google Scholar
  28. Scheer, A. (2005) Methods Aris 7.0. Saarbrücken: IDS Scheer AG.Google Scholar
  29. Sein, M. K., et al. (2011). Action design research. MIS Quaterly, 35(1), 37–56.Google Scholar
  30. Shingo, S. (1989). A study of the Toyota production system from an industrial engineering viewpoint. USA: Productivity Press.Google Scholar
  31. Simon, H. A. (1996). The sciences of the artificial (3rd ed.). USA: MIT Press.Google Scholar
  32. Spearman, M. L., Woodruff, D. L., & Hopp, W. J. (1990). CONWIP—a pull alternative to KANBAN. International Journal of Production Research, 28(5), 879–894.CrossRefGoogle Scholar
  33. van Aken, J. E. (2004). 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.CrossRefGoogle Scholar
  34. van Aken, J. E. (2011) The research design for design science research in management. Eindhoven.Google Scholar
  35. van Aken, J. E., Berends, H., & van der Bij, H. (2012). Problem solving in organizations (2nd ed., p. 235). United Kingdom, Cambridge: University Press Cambridge.CrossRefGoogle Scholar
  36. Venable, J. R. (2006). The role of theory and theorising in design science research. In: DESRIST, pp. 1–18, v. Feb. 24–25, 2006.Google Scholar
  37. Walls, J. G., Wyidmeyer, G. R., & Sawy, O. A. E. (1992). Building an information system design theory for vigilant EIS. Information Systems Research, 3, 36–60.Google Scholar

Suggested Reading

  1. Holmström, J., Ketokivi, M., & Hameri, A. P. (2009). Bridging practice and theory: A design science approach. Decision Sciences, 40(1), 65–88.CrossRefGoogle Scholar
  2. Koen, B. V. (2003). Discussion of the method: Conducting the engineer’s approach to problem solving. New York: Oxford University Press.Google Scholar
  3. Lacerda, D. P., Dresch, A., Proença, A., & Antunes Jr., J. (2013). Design science research: A research method to production engineering. Gestão & Produção, 20(4), 741–761.Google Scholar
  4. March, S. T., & Smith, G. F. (1995). Design and natural science research on information technology. Decision Support Systems, 15, 251–266.CrossRefGoogle Scholar
  5. Simon, H. A. (1996). The sciences of the artificial (3rd ed.). USA: MIT Press.Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Aline Dresch
    • 1
    Email author
  • Daniel Pacheco Lacerda
    • 1
  • José Antônio Valle AntunesJr
    • 1
  1. 1.GMAP|UNISINOSPorto AlegreBrazil

Personalised recommendations