Advertisement

Managing Business Process Based on the Tonality of the Output Information

  • Raissa Uskenbayeva
  • Rakhmetulayeva SabinaEmail author
  • Bolshibayeva Aigerim
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 991)

Abstract

Algorithms that perform separate processing of absolute and relative evaluation (of feedbacks) of the quality of activity and output of a business process for the purpose of obtaining general conclusions about quality are described. Then, based on the results of processing by separate algorithms of absolute and relative evaluation, a total score i.e. a generalized assessment of the quality of activities and products (products and resources) of the business process is formed. Based on the results of the assessment, the weighting factors of the products are adjusted to production plan of the business process.

Keywords

Business process Formation Tonality Absolute tonality Relative tonality 

Notes

Acknowledgments

This work was supported by Ministry of Education and Science Republic of Kazakhstan (Grant No. 0118PК01084, Digital transformation platform of National economy business processes BR05236517).

References

  1. 1.
    Anderson, D.J.: Kanban: Successful Evolutionary Change for Your Technology Business. Published by Blue Hole Press (2010)Google Scholar
  2. 2.
    Duisebekova, K., Serbin, V., Ukubasova, G., Kebekpayeva, Z., Skakova, A., Rakhmetulayeva, S., Shaikhanova, A., Duisebekov, T., Kozhamzharova, D.: Design and development of automation system of business processes in educational activity. J. Eng. Appl. Sci. 8:4702–4714 Medwell Journals, ISSN:86-949X (2017)Google Scholar
  3. 3.
    Rakhmetulaeva, S.: Using inverse information as a method for assessing and analyzing reputational risk. J. Vestn. EKSTU 2, 129–133 (2015)Google Scholar
  4. 4.
    Kuandykov, A., Rakhmetulayeva, S., Baiburin, Y., Nugumanova, A.: Usage of singular value decomposition matrix for search latent semantic structures in natural language texts. In: The 34th Chinese Control Conference and SICE Annual Conference 2015 (CCC&SICE2015), pp. 286–291. Hangzhou, China (2015). https://ieeexplore.ieee.org/document/7285567. Last accessed 21 Feb 2019
  5. 5.
    Nugumanova, A., Mansurova, M., Alimzhanov, E., Zyryanov, D., Apayev, K.: An automatic construction of concet mas based on statistical text mining. In: International Conference on Data Management Technologies and Applications, pp. 29–38 (2015)Google Scholar
  6. 6.
    Bessmertny, I.: Knowledge visualization based on semantic networks. Program. Comput. Softw. 36(4), 197–204 (2010)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Raissa Uskenbayeva
    • 1
  • Rakhmetulayeva Sabina
    • 1
    Email author
  • Bolshibayeva Aigerim
    • 1
  1. 1.International Information Technology UniversityAlmatyKazakhstan

Personalised recommendations