Published September 22, 2020 | Version 1
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Information support of dynamic management of business processes with collective expert evaluation

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Information support of dynamic business process management with collective expert evaluation.

The principles of information support of business process dynamic management by collective assessment by a team of insider experts in the conditions of dynamic changes and information uncertainty are developed. Information support of dynamic management is based on the formation of a team of expert insiders who are employees of the enterprise, who know and understand the problems of the enterprise from within and are interested in solving problems of the enterprise. The main stages of collective expert evaluation and its features in the implementation of the concept of "collective intelligence" are considered. The main advantages of collective expert evaluation with the involvement of insider experts are shown. Approbation of the proposed concept showed its effectiveness.

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References

  • 1. Big problems of small business: System report. (2020). Rada biznes-ombudsmena: website. 64 p. Retrived from https://boi.org.ua/media/uploads/system_bigproblemssmalbusiness/3_2020_syste m_ua.pdf [in Ukrainian].
  • 2. Nesterenko, O.V. & Savenkov, O.I. & Falovskyi, O.O. (2016) Intelligent decision support systems: a textbook / Ed. P.I. Bidiuk. Kyiv: Natsionalna akademiia upravlinnia. 188 p. Retrived from https://www.nam.kiev.ua/files/publications/978-966-8406-94-2-pos.pdf [in Ukrainian].
  • 3. Popov, O.O. & Yatsyshyn, A.V. & Artemchuk, V.O. (2016). Possibilities of using expert methods and systems to solve environmental safety problems in NPP impact zones. Zbirnyk naukovykh prats instytutu heokhimii navkolyshnoho seredovyshcha. Is, 25, 5-16 [in Ukrainian].
  • 4. Kuvaieva, V.I. & Lipianina, Kh.V. & Boltonkov, V.O. (2018). Processing of expert information in the collective assessment of tourist infrastructure. Suchasnyi stan naukovykh doslidzhen ta tekhnolohii v promyslovosti. 3, 35-43 [in Ukrainian].
  • 5. Lysetskyi, Yu.M. (2017). The technology for analyzing the consistency and reliability of expert estimates. Matematychne ta kompiuterne modeliuvannia. Seriia: Tekhnichni nauky. Is. 16, 72-79 [in Russian].
  • 6. Venedyktov, A.A. (2018). On the indicator of consistency of expert assessments. Vooruzheniye i ekonomika. 3 (45), P. 52-66 [in Russian].
  • 7. Weiss, A. (2005). The Power of Collective Intelligence. Collective Intelligence, 9, 17-23 [in English].
  • 8. Malone, T.W. & Laubacher, R. & Dellarocas C. (2009). Harnessing crowds: mapping the genome of collective intelligence. Cambridge, MA: MIT Center for Collective Intelligence Massachusetts Institute of Technology. 21 p. DOI: 10.2139/ssrn.1381502 [in English].
  • 9. Filippov, V.Yu. (2020). System-integrated management of business development according to the imperatives of sustainable development in information and innovation economics. Schweinfurt: Time Realities Scientific Group UG (haftungsbeschränkt) [in Ukrainian].
  • 10. Woolley, A. & Aggarwa, I. & Malone, T. (2015). Collective Intelligence and Group Performance. Current Directions in Psychological Science, 24/6, 420-424 [in English].
  • 11. Slavyn, B.B. (2016). Collective intelligence technologies. Problemy upravleniya, 5, 2-9 [in Ukrainian].
  • 12. Gonzalo, N.R. & Zoumpolia, D. & Elpiniki, P. & Rafael, B. & Koen V. (2015). Aggregation of Partial Rankings – An Approach Based on the Kemeny Ranking Problem. Advances in computational intelligence, 2, 343-355 [in English].
  • 13. Boltenkov, V. & Kuvaieva, V. & Galchonkov, O. & Ishchenko, O. (2018). The research of possibilities for fast calculation of median consensus rankings. Eastern-European Journal of Enterprise Technologies, 4/4 (94), 28-35 [in English].
  • 14. Triantaphyllou, E. & Hou, F. & Yanase, J. (2020). Analysis of the Final Ranking Decisions Made by Experts After a Consensus has Been Reached in Group Decision Making. Group Decision and Negotiation. 29, 271-291. DOI: 10.1007/s10726-020-09655-5 [in English].
  • 15. Bonnini, S. & Corain, L. & Marozzi, M. & Salmaso S. (2014). Nonparametric Hypothesis Testing – Rank and Permutation Methods with Applications in R. N.Y.: John Wiley & Sons [in English].