Human Resource Allocation in Process Simulations Based on Competency Vectors

  • Štěpán Kuchař
  • Jan Martinovič
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 188)


This paper specifies a method to describe human resources’ skills and competencies for the use in automatic simulations of operative business processes to enhance the precision of such simulations. A way to convert this description into the vector space model is also provided and used to find and evaluate adequate resources for performing process activities based on their competency requirements. Two different competency vector representations are introduced and experimentally compared on the software process of a local software development company using the F-measure.


Human Resource Allocation Business Process Simulation Competency Model Vector Space Model 


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  1. 1.
    van der Aalst, W.M.P.: The application of Petri nets to workflow management. The Journal of Circuits, Systems and Computers 8(1), 21–66 (1998)CrossRefGoogle Scholar
  2. 2.
    van der Aalst, W.M.P., Nakatumba, J., Rozinat, A., Russell, N.: Business process simulation: How to get it right. BPM Center Report BPM-08-07, (2008)Google Scholar
  3. 3.
    Aiolli, F., De Filippo, M., Sperduti, A.: Application of the preference learning model to a human resources selection task. In: IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009, pp. 203–210 (April 2009)Google Scholar
  4. 4.
    Andre, M., Baldoquin, M.G., Acuna, S.T.: Formal model for assigning human resources to teams in software projects. Inf. Softw. Technol. 53(3), 259–275 (2011)CrossRefGoogle Scholar
  5. 5.
    Berry, M.W.: Survey of text mining: clustering, classification, and retrieval, vol. 1. Springer-Verlag New York Inc. (2004)Google Scholar
  6. 6.
    Chang, W.A., Huang, T.C.: Relationship between strategic human resource management and firm performance: A contingency perspective. International Journal of Manpower 26(5), 434–449 (2005)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Crow, D., DeSanto, J.: A hybrid approach to concept extraction and recognition-based matching in the domain of human resources. In: 16th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2004, pp. 535–541 (November 2004)Google Scholar
  8. 8.
    Dreyfus, S.E., Dreyfus, H.L.: A five-stage model of the mental activities involved in directed skill acquisition. Technical report, DTIC Document (1980)Google Scholar
  9. 9.
    Ennis, M.R.: Competency models: a review of the literature and the role of the employment and training administration (ETA). US Department of Labor (2008)Google Scholar
  10. 10.
    Gómez-Pérez, A., Ramírez, J., Villazón-Terrazas, B.: An Ontology for Modelling Human Resources Management Based on Standards. In: Apolloni, B., Howlett, R.J., Jain, L. (eds.) KES 2007, Part I. LNCS (LNAI), vol. 4692, pp. 534–541. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Hanne, T., Neu, H.: Simulating human resources in software development processes. Berichte des Fraunhofer ITWM 64(64), 83–87 (2003)Google Scholar
  12. 12.
    Hatch, N.W., Dyer, J.H.: Human capital and learning as a source of sustainable competitive advantage. Strategic Management Journal 25(12), 1155–1178 (2004)CrossRefGoogle Scholar
  13. 13.
    Jensen, K.: Coloured Petri Nets: Basic Concepts, Analysis Methods, and Practical Use. Springer (1996)Google Scholar
  14. 14.
    Kessler, R., Béchet, N., Roche, M., El-Bèze, M., Torres-Moreno, J.-M.: Automatic Profiling System for Ranking Candidates Answers in Human Resources. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM-WS 2008. LNCS, vol. 5333, pp. 625–634. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  15. 15.
    Kessler, R., Béchet, N., Torres-Moreno, J.-M., Roche, M., El-Bèze, M.: Job Offer Management: How Improve the Ranking of Candidates. In: Rauch, J., Raś, Z.W., Berka, P., Elomaa, T. (eds.) ISMIS 2009. LNCS, vol. 5722, pp. 431–441. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  16. 16.
    Malinowski, J., Keim, T., Wendt, O., Weitzel, T.: Matching people and jobs: A bilateral recommendation approach. In: Hawaii International Conference on System Sciences, vol. 6, p. 137c. IEEE Computer Society, Los Alamitos (2006)Google Scholar
  17. 17.
    Pesic, M., van der Aalst, W.M.P.: Modelling work distribution mechanisms using colored petri nets. Int. J. Softw. Tools Technol. Transf. 9(3), 327–352 (2007)CrossRefGoogle Scholar
  18. 18.
    Radevski, V., Trichet, F.: Ontology-Based Systems Dedicated to Human Resources Management: An Application in e-Recruitment. In: Meersman, R., Tari, Z., Herrero, P. (eds.) OTM 2006 Workshops. LNCS, vol. 4278, pp. 1068–1077. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  19. 19.
    van Rijsbergen, C.J.: Information Retrieval. Butterworth (1979)Google Scholar
  20. 20.
    Rozinat, A., Wynn, M.T., van der Aalst, W.M.P., ter Hofstede, A.H.M., Fidge, C.J.: Workflow simulation for operational decision support. Data Knowl. Eng. 68(9), 834–850 (2009)CrossRefGoogle Scholar
  21. 21.
    Russell, N., van der Aalst, W.M.P., ter Hofstede, A.H.M., Edmond, D.: Workflow Resource Patterns: Identification, Representation and Tool Support. In: Pastor, Ó., Falcão e Cunha, J. (eds.) CAiSE 2005. LNCS, vol. 3520, pp. 216–232. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  22. 22.
    SFIA Foundation. Framework reference SFIA version 4G (2010)Google Scholar
  23. 23.
    Sinnott, G., Madison, G., Pataki, G.: Competencies: Report of the competencies workgroup, workforce and succession planning work groups (September 2002)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.IT4InnovationsVŠB Technical University in OstravaOstravaCzech Republic

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