Devising a project risk management method under scrum conditions based on cognitive approach

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.313050

Keywords:

project, risks, Scrum, fuzzy cognitive map, factor, decision-making, information

Abstract

Any project implemented using Scrum is characterized by the impact of risks, including negative changes in the environment and crisis circumstances. Therefore, the processes related to risk management, which is the object of this paper, become important. The problem solved in this study is to improve the efficiency of projects through the construction of a long-term strategy for reducing the level of risk and avoiding negative consequences for projects in the context of Scrum. The proposed method of risk management has been developed on the basis of the application of the synthesis of management of intelligent decision-making technologies and formalized methods. Difficult external circumstances are characterized by a high degree of uncertainty and do not always contribute to the successful implementation of the project. Therefore, this method of project risk management under Scrum conditions based on a cognitive approach is characterized by a combined combination of cognitive analysis, mathematical modeling, and expert methods. As part of the method, a model of project risk management under Scrum conditions has been built in the form of a fuzzy cognitive map, which could ensure determining the optimal strategic decision in dynamics, taking into account the effects of various factors. The result of applying this method is compliance with time limits, reduction of overspending of resources and losses in the project, as well as adaptation to rapidly changing circumstances and adequate response.

The method of project risk management is characterized by solving the problem of formalizing management decision-making procedures and their information support, taking into account the availability of both quantitative and qualitative data. Within the framework of this method, a project risk management procedure under Scrum conditions has been proposed, which contributes to the systematization, monitoring, and control of risks under the conditions of complex, rapidly changing crisis circumstances

Author Biographies

Tetiana Prokopenko, Cherkasy State Technological University

Doctor of Technical Sciences, Professor

Department of Information Technology Design

Oleg Grygor, Cherkasy State Technological University

Doctor of Political Sciences, Professor

Department of Economics and Management

Valentyn Prokopenko, Cherkasy State Technological University

PhD Student

Department of Information Technology Design

Olha Lavdanska, Cherkasy State Technological University

PhD, Associate Professor

Department of Information Technology Design

References

  1. Hong, B., Ly, M., Lin, H. (2023). Robotic Process Automation Risk Management: Points to Consider. Journal of Emerging Technologies in Accounting, 20 (1), 125–145. https://doi.org/10.2308/jeta-2022-004
  2. Practice Standard for Project Risk Management (2009). Project Management Institute, 116.
  3. Verma, K. K., Ospanova, A. (2022). Risk Management. International Journal of Innovative Research in Science Engineering and Technology, 11 (12), 14315.
  4. A Guide to the Project Management Body of Knowledge (2013). Project Management Institute, 589.
  5. Benov, D. M. (2016). The Manhattan Project, the first electronic computer and the Monte Carlo method. Monte Carlo Methods and Applications, 22 (1), 73–79. https://doi.org/10.1515/mcma-2016-0102
  6. Freedman, D. (2009). Statistical Models: Theory and Practice. Cambridge University Press. https://doi.org/10.1017/cbo9781139165495
  7. Stulp, F., Sigaud, O. (2015). Many regression algorithms, one unified model: A review. Neural Networks, 69, 60–79. https://doi.org/10.1016/j.neunet.2015.05.005
  8. Leha, Yu. H., Prokopenko, T. O., Danchenko, O. B. (2010). Ekspertni protsedury ta metody pryiniattia rishen v investytsiynykh proektakh. Visnyk ChDTU, 2, 69–73.
  9. Prokopenko, T., Lavdanska, O., Povolotskyi, Y., Obodovskyi, B., Tarasenko, Y. (2021). Devising an integrated method for evaluating the efficiency of scrum-based projects in the field of information technology. Eastern-European Journal of Enterprise Technologies, 5 (3 (113)), 46–53. https://doi.org/10.15587/1729-4061.2021.242744
  10. Prokopenko, T., Lanskykh, Y., Prokopenko, V., Pidkuiko, O., Tarasenko, Y. (2023). Development of the comprehensive method of situation management of project risks based on big data technology. Eastern-European Journal of Enterprise Technologies, 1 (3 (121)), 38–45. https://doi.org/10.15587/1729-4061.2023.274473
  11. Glowka, G., Hule, R., Zehrer, A. (2024). Risk perception of SMEs: strategic risks, family-related risks, external risks. Risk Management, 26 (4). https://doi.org/10.1057/s41283-024-00148-2
  12. Abbas, D. S., Ismail, T., Taqi, M., Yazid, H. (2021). Determinants of enterprise risk management disclosures: Evidence from insurance industry. Accounting, 7 (6), 1331–1338. https://doi.org/10.5267/j.ac.2021.4.005
  13. Willumsen, P. L., Oehmen, J., Selim, H. M. R. (2024). Project risk management in practice: the actuality of project risk management in organizations. International Journal of Managing Projects in Business, 17 (4/5), 593–617. https://doi.org/10.1108/ijmpb-09-2023-0214
  14. Tak, A., Sunil Chahal, S. C. (2024). Risk Management in Agile Al/Ml Projects: Identifying and Mitigating Data and Model Risks. Journal of Technology and Systems, 6 (3), 1–18. https://doi.org/10.47941/jts.1824
  15. Prokopenko, T., Grigor, O. (2018). Development of the comprehensive method to manage risks in projects related to information technologies. Eastern-European Journal of Enterprise Technologies, 2 (3 (92)), 37–43. https://doi.org/10.15587/1729-4061.2018.128140
  16. Taber, W. R. (1994). Fuzzy Cognitive Maps Model Social Systems. Artificial Intelligence Expert, 9, 18–23.
  17. Liu, Z.-Q., Zhang, J. Y. (2003). Interrogating the structure of fuzzy cognitive maps. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 7 (3), 148–153. https://doi.org/10.1007/s00500-002-0202-x
  18. Kosko, B. (1986). Fuzzy cognitive maps. International Journal of Man-Machine Studies, 24 (1), 65–75. https://doi.org/10.1016/s0020-7373(86)80040-2
  19. Prokopenko, T. O., Ladaniuk, A. P. (2015). Informatsiyni tekhnolohiyi upravlinnia orhanizatsiyno-tekhnolohichnymy systemamy. Cherkasy: Vertykal, vydavets Kandych S.H., 224.
  20. Sawaragi, T., Iwai, S., Katai, O. (1986). An integration of qualitative causal knowledge for user-oriented decision support. Control Theory and Advanced Technology, 2, 451–482.
  21. Fedyk, O., Fedyk, S. (2024). Project Risk Management: modern trends and effective practices. Visegrad Journal on Human Rights, 6, 45–50. https://doi.org/10.61345/1339-7915.2023.6.8
Devising a project risk management method under scrum conditions based on cognitive approach

Downloads

Published

2024-10-30

How to Cite

Prokopenko, T., Grygor, O., Prokopenko, V., & Lavdanska, O. (2024). Devising a project risk management method under scrum conditions based on cognitive approach. Eastern-European Journal of Enterprise Technologies, 5(3 (131), 18–26. https://doi.org/10.15587/1729-4061.2024.313050

Issue

Vol. 5 No. 3 (131) (2024): Control processes

Section

Control processes

License

Copyright (c) 2024 Tetiana Prokopenko, Oleg Grygor, Valentyn Prokopenko, Olha Lavdanska

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.

A license agreement is a document in which the author warrants that he/she owns all copyright for the work (manuscript, article, etc.).
The authors, signing the License Agreement with TECHNOLOGY CENTER PC, have all rights to the further use of their work, provided that they link to our edition in which the work was published.
According to the terms of the License Agreement, the Publisher TECHNOLOGY CENTER PC does not take away your copyrights and receives permission from the authors to use and dissemination of the publication through the world's scientific resources (own electronic resources, scientometric databases, repositories, libraries, etc.).
In the absence of a signed License Agreement or in the absence of this agreement of identifiers allowing to identify the identity of the author, the editors have no right to work with the manuscript.
It is important to remember that there is another type of agreement between authors and publishers – when copyright is transferred from the authors to the publisher. In this case, the authors lose ownership of their work and may not use it in any way.