Improving Work Allocation Practices in Business Processes Supported by BPMS

  • Robbie Uahi
  • José Luís Pereira
  • João Varajão
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)


BPMS (Business Process Management Systems) are responsible for the execution of business process models, by delivering work activities to suitable agents (human or automatisms) that execute them. During the design-time, modelers have to specify the potential performers of a work activity according to their organizational position or role. Once several workers may share the same role, during run-time all of them can be assigned by BPMS to execute a work activity. However, distinct persons have different personality traits and, in a specific piece of work (for instance, requiring special teamwork skills), some of them can perform better than others. Addressing a gap in theory and practice of BPMS, in this paper we present a new approach that enables BPMS to assign (in run-time) the most suitable workers to perform specific work activities, grounded on the concept of psychological profile and taking into account technical, human and social aspects.


Human resources BPMS Task allocation Personality Assessment Frameworks 



This work has been supported by FCT - Fundação para a Ciência e Tecnologia, within the Strategic Project plan PEst2015-2020, UID/CEC/00319/2013.


  1. 1.
    Hernaus, T.: Process-based organization design model: theoretical review and model conceptualization. EFZG Working Paper Series, vol. 6, pp. 1–17 (2008)Google Scholar
  2. 2.
    Hammer, M.: What is business process management? In: vom Brocke, J., Rosemann, M. (eds.) Handbook on Business Process Management, pp. 3–16. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  3. 3.
    Vanderfeesten, I.T.P., Grefen, P.W.P.J.: Advanced dynamic role resolution in business processes. In: Persson, A., Stirna, J. (eds.) Lecture Notes in Business Information Processing. vol. 215, pp. 87–93. Springer, Heidelberg (2015)Google Scholar
  4. 4.
    Weske, M.: Business Process Management: Concepts, Languages Architectures. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  5. 5.
    Pereira, J.L.: Process-based information systems: a component-based systems development infrastructure. In: Proceedings of the 3rd International Conference on Virtual and Networked Organizations, Emergent Technologies and Tools, ViNOrg 2014. Póvoa de Varzim, Portugal (2014)Google Scholar
  6. 6.
    Cabanillas, C., Resinas, M., Ruiz-Cortés, A.: Designing business processes with history-aware resource assignments. In: La Rosa, M., Soffer, P. (eds.) Business Process Management Workshops. Lecture Notes in Business Information Processing. vol. 132, pp. 101–112. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  7. 7.
    Armstrong, M., Taylor, S.: Armstrong’s handbook of human resource management practice. Kogan Page Publishers, London (2014)Google Scholar
  8. 8.
    Uahi, R., Pereira, J.L.: Work allocation in organizations: the contribution of the personality assessment frameworks in the selection of human resources. In: Proceedings of the 28th International Business Information Management Association Conference, Seville, Spain (2016)Google Scholar
  9. 9.
    Uahi, R., Pereira, J.L.: Human resources selection in business processes supported by bpms: optimizing work performance. In: Proceedings of the 5th International Conference on Management, Leadership and Governance - ICMLG 2017, Johannesburg, South Africa (2017)Google Scholar
  10. 10.
    Stefansen, C., Rajamani, S., Seshan, P.: A work allocation language with soft constraints. In: CEUR Workshop Proceedings, vol. 344, pp. 85–88 (2008)Google Scholar
  11. 11.
    Fretwell, C.E., Lewis, C.C., Hannay, M.: Myers-Briggs type Indicator, A/B personality types, and locus of control: where do they intersect? Am. J. Manag. 13(3), 57–66 (2013)Google Scholar
  12. 12.
    Costa, P.T., McCrae, R.R.: Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) Manual. Psychological Assessment Resources (1992)Google Scholar
  13. 13.
    Robbins, S., Judge, T.A., Millett, B., Boyle, M.: Organizational Behaviour. Pearson Higher Education, Sydney (2013)Google Scholar
  14. 14.
    Scullard, M., Baum, D.: Everything DiSC Manual. Wiley, Minneapolis (2015)Google Scholar
  15. 15.
    UNECE: The generic statistical business process model (2013). Accessed 15 Aug 2017
  16. 16.
    Van der Aalst, W., Van Hee, K.M.: Workflow Management: Models, Methods, and Systems. MIT Press, Cambridge (2004)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Robbie Uahi
    • 1
  • José Luís Pereira
    • 2
  • João Varajão
    • 2
  1. 1.National Statistics Institute of MozambiqueMaputoMozambique
  2. 2.Universidade do Minho, DSI and Centro ALGORITMIGuimarãesPortugal

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