Establishing a Decision Tool for Business Process Crowdsourcing

  • Nguyen Hoang ThuanEmail author
  • Pedro Antunes
  • David Johnstone
  • Nguyen Huynh Anh Duy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9446)


The integration of crowdsourcing in organisations fosters new managerial and business capabilities, especially regarding flexibility and agility of external human resources. However, a crowdsourcing project involves considering multiple contextual factors and choices and dealing with the novelty of the strategy, which makes managerial decisions difficult. This research addresses the problem by proposing a tool supporting business decision-makers in the establishment of crowdsourcing projects. The proposed tool is based on an extensive review of prior research in crowdsourcing and an ontology that standardises the fundamental crowdsourcing concepts, processes, dependencies, constraints, and managerial decisions. In particular, we discuss the architecture of the proposed tool and present two prototypes, one supporting what-if analysis and the other supporting detailed establishment of crowdsourcing processes.


Business process crowdsourcing Crowdsourcing Decision support system Design science Ontology 


  1. 1.
    Zhao, Y., Zhu, Q.: Evaluation on crowdsourcing research: current status and future direction. Inf. Syst. Front. 16(3), 417–434 (2014)CrossRefGoogle Scholar
  2. 2.
    Howe, J.: The rise of crowdsourcing. In: Wired Magazine 2006, pp. 1–4. Dorsey Press, Homewood (2006)Google Scholar
  3. 3.
    Rosen, P.A.: Crowdsourcing lessons for organizations. J. Decis. Syst. 20(3), 309–324 (2011)CrossRefGoogle Scholar
  4. 4.
    Massolution: The Crowd in the Cloud: Exploring the Future of Outsourcing. Massolution (2013)Google Scholar
  5. 5.
    Zogaj, S., Bretschneider, U., Leimeister, J.M.: Managing crowdsourced software testing: a case study based insight on the challenges of a crowdsourcing intermediary. J. Bus. Econ. 84(3), 375–405 (2014)CrossRefGoogle Scholar
  6. 6.
    Whitla, P.: Crowdsourcing and its application in marketing activities. Contemp. Manage. Res. 5(1), 15–28 (2009)CrossRefGoogle Scholar
  7. 7.
    Brabham, D.C., et al.: Crowdsourcing applications for public health. Am. J. Prev. Med. 46(2), 179–187 (2014)CrossRefGoogle Scholar
  8. 8.
    La Vecchia, G., Cisternino, A.: Collaborative workforce, business process crowdsourcing as an alternative of BPO. In: Daniel, F., Facca, F.M. (eds.) ICWE 2010. LNCS, vol. 6385, pp. 425–430. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Thuan, N.H., Antunes, P., Johnstone, D.: Toward a nexus model supporting the establishment of business process crowdsourcing. In: Dang, T.K., Wagner, R., Neuhold, E., Takizawa, M., Küng, J., Thoai, N. (eds.) FDSE 2014. LNCS, vol. 8860, pp. 136–150. Springer, Heidelberg (2014)Google Scholar
  10. 10.
    Tranquillini, S., et al.: Modeling, enacting, and integrating custom crowdsourcing processes. ACM Trans. Web (TWEB) 9(2), 7 (2015)Google Scholar
  11. 11.
    Thuan, N.H., et al.: Building an enterprise ontology of business process crowdsourcing: a design science approach. In: PACIS 2015 Proceedings, Paper 112 (2015)Google Scholar
  12. 12.
    Khazankin, R., Satzger, B., Dustdar, S.: Optimized execution of business processes on crowdsourcing platforms. In: IEEE 8th International Conference on Collaborative Computing: Networking, Applications and Worksharing, Pittsburgh, PA (2012)Google Scholar
  13. 13.
    Thuan, N.H., Antunes, P., Johnstone, D.: Factors influencing the decision to crowdsource: a systematic literature review. Inf. Syst. Front. 1–22 (2015)Google Scholar
  14. 14.
    Arnott, D., Pervan, G.: A critical analysis of decision support systems research revisited: the rise of design science. J. Inf. Technol. 29(4), 269–293 (2014)CrossRefGoogle Scholar
  15. 15.
    Hosack, B., et al.: A look toward the future: decision support systems research is alive and well. J. Assoc. Inf. Syst. 13(5), 315–340 (2012)Google Scholar
  16. 16.
    Hevner, A., Chatterjee, S.: In: Sharda, R., Voß, S. (eds.) Design Research in Information Systems: Theory and Practice. Integrated Series in Information Systems, vol. 22. Springer, Heidelberg (2010)Google Scholar
  17. 17.
    Hevner, A., et al.: Design science in information systems research. MIS Q. 28(1), 75–105 (2004)CrossRefGoogle Scholar
  18. 18.
    Hetmank, L., Developing an ontology for enterprise crowdsourcing. In: Multikonferenz Wirtschaftsinformatik, Paderborn, pp. 1089–1100 (2014)Google Scholar
  19. 19.
    Estellés-Arolas, E., González-Ladrón-de-Guevara, F.: Towards an integrated crowdsourcing definition. J. Inf. Sci. 38(2), 189–200 (2012)CrossRefGoogle Scholar
  20. 20.
    Geiger, D., Schader, M.: Personalized task recommendation in crowdsourcing information systems—current state of the art. Decis. Support Syst. 65, 3–16 (2014)CrossRefGoogle Scholar
  21. 21.
    Leimeister, J.M., et al.: Leveraging crowdsourcing: activation-supporting components for IT-based ideas competition. J. Manage. Inf. Syst. 26(1), 197–224 (2009)CrossRefGoogle Scholar
  22. 22.
    Djelassi, S., Decoopman, I.: Customers’ participation in product development through crowdsourcing: issues and implications. Ind. Mark. Manage. 42(5), 683–692 (2013)CrossRefGoogle Scholar
  23. 23.
    Chiu, C.-M., Liang, T.-P., Turban, E.: What can crowdsourcing do for decision support? Decis. Support Syst. 64, 40–49 (2014)CrossRefGoogle Scholar
  24. 24.
    McCormack, K., et al.: A global investigation of key turning points in business process maturity. Bus. Process Manage. J. 15(5), 792–815 (2009)CrossRefGoogle Scholar
  25. 25.
    Van Looy, A., et al.: Choosing the right business process maturity model. Inf. Manage. 50(7), 466–488 (2013)CrossRefGoogle Scholar
  26. 26.
    Prokesch, T., Wohlenberg, H.: Results from a group wisdom supporting system. In: Proceedings of the European Conference on Information Systems (ECIS) 2014, Paper 7 (2014)Google Scholar
  27. 27.
    Miah, S., Kerr, D., von Hellens, L.: A collective artefact design of decision support systems: design science research perspective. Inf. Technol. People 27(3), 259–279 (2014)CrossRefGoogle Scholar
  28. 28.
    Power, D.J.: Decision support systems: a historical overview. In: Handbook on Decision Support Systems 1, pp. 121–140. Springer, Heidelberg (2008)Google Scholar
  29. 29.
    Arnott, D., Pervan, G.: Eight key issues for the decision support systems discipline. Decis. Support Syst. 44(3), 657–672 (2008)CrossRefGoogle Scholar
  30. 30.
    Holsapple, C.W.: DSS architecture and types. In: Handbook on Decision Support Systems 1, pp. p. 163–189. Springer, Heidelberg (2008)Google Scholar
  31. 31.
    Şeref, M.M., Ahuja, R.K.: Spreadsheet-based decision support systems. In: Handbook on Decision Support Systems 1, pp. 277–298. Springer, Heidelberg (2008)Google Scholar
  32. 32.
    Arnott, D., Pervan, G.: Design science in decision support systems research: an assessment using the Hevner, March, Park, and Ram guidelines. J. Assoc. Inf. Syst. 13(11), 923–949 (2012)Google Scholar
  33. 33.
    Pries-Heje, J., Baskerville, R.: The design theory nexus. MIS Q. 32(4), 731–755 (2008)CrossRefGoogle Scholar
  34. 34.
    Osterwalder, A.: The business model ontology: a proposition in a design science approach. Institut d’Informatique et Organisation. Lausanne, Switzerland, University of Lausanne, Ecole des Hautes Etudes Commerciales HEC (2004)Google Scholar
  35. 35.
    Ostrowski, L., Helfert, M., Gama, N.: Ontology engineering step in design science research methodology: a technique to gather and reuse knowledge. Behav. Inf. Technol. 33(5), 443–451 (2014)CrossRefGoogle Scholar
  36. 36.
    Guarino, N., Oberle, D., Staab, S.: What is an ontology? In: Staab, S., Studer, R. (eds.) Handbook on ontologies, pp. 1–17. Springer, Heidelberg (2009)Google Scholar
  37. 37.
    Valaski, J., Malucelli, A., Reinehr, S.: Ontologies application in organizational learning: a literature review. Expert Syst. Appl. 39(8), 7555–7561 (2012)CrossRefGoogle Scholar
  38. 38.
    Lim, Y.-K., Stolterman, E., Tenenberg, J.: The anatomy of prototypes: prototypes as filters, prototypes as manifestations of design ideas. ACM Trans. Comput. Hum. Interact. (TOCHI) 15(2) (2008)Google Scholar
  39. 39.
    Kordon, F.: An introduction to rapid system prototyping. IEEE Trans. Softw. Eng. 28(9), 817–821 (2002)MathSciNetCrossRefGoogle Scholar
  40. 40.
    Miah, S.J., Kerr, D.V., Gammack, J.G.: A methodology to allow rural extension professionals to build target-specific expert systems for Australian rural business operators. Expert Syst. Appl. 36(1), 735–744 (2009)CrossRefGoogle Scholar
  41. 41.
    Antunes, P., et al.: Integrating decision-making support in geocollaboration tools. Group Decis. Negot. 23(2), 211–233 (2014)CrossRefGoogle Scholar
  42. 42.
    Vukovic, M.: Crowdsourcing for enterprises. In: 2009 World Conference on Services-I. IEEE, Los Angeles, CA (2009)Google Scholar
  43. 43.
    Peffers, K., Rothenberger, M., Tuunanen, T., Vaezi, R.: Design science research evaluation. In: Peffers, K., Rothenberger, M., Kuechler, B. (eds.) DESRIST 2012. LNCS, vol. 7286, pp. 398–410. Springer, Heidelberg (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nguyen Hoang Thuan
    • 1
    • 2
    Email author
  • Pedro Antunes
    • 1
  • David Johnstone
    • 1
  • Nguyen Huynh Anh Duy
    • 2
  1. 1.School of Information ManagementVictoria University of WellingtonWellingtonNew Zealand
  2. 2.Can Tho University of TechnologyCan ThoVietnam

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