• Home
  • Historical notes
  • Articles & Issues
    • Current
    • All Issues
  • About
    • Aims and Scope
    • Editorial Board
    • Indexing
    • Sources of Financing
  • For Authors
    • Submission
    • Terms of Publication
    • Formatting Guidelines
    • Peer Review Process
    • Article Processing Charges
    • License Agreement
  • Ethics & Policies
    • Publication Ethics
    • Conflict of Interest
    • Open Access Policy
    • Archiving
    • Complaints Policy
    • Privacy Statement
    • Corrections and Retractions
    • Anti-plagiarism Policy
    • Generative AI Policy
  • Contacts
en English
  • Українська Українська

UkrainianProfessional Education

  • Submit an article
  • Home
  • Articles & Issues
    • Current
    • All Issues
  • About
    • Aims and Scope
    • Editorial Board
    • Indexing
    • Sources of Financing
  • For Authors
    • Submission
    • Terms of Publication
    • Formatting Guidelines
    • Peer Review Process
    • Article Processing Charges
    • License Agreement
  • Ethics & Policies
    • Publication Ethics
    • Conflict of Interest
    • Open Access Policy
    • Archiving
    • Complaints Policy
    • Privacy Statement
    • Corrections and Retractions
    • Anti-plagiarism Policy
    • Generative AI Policy
  • Search
  • Contacts

Article

  • Read article
  • Download article

Received 12.11.2024

Revised 26.02.2025

Accepted 29.03.2025

Retrieved from Iss. 117, P. 1, 2025

Pages 293 -305

  • 185 Views

Suggested citation

Vorkut, T., & Volynets, L. (2025). MODEL FOR ASSESSMENT OF THE STATUS OF FUNCTIONING OF A LOGISTICS PROVIDER ORGANIZATION IN THE PROCESSES OF ORGANIZATIONAL STRATEGIC MANAGEMENT. Automobile Roads and Road Construction, (117.1), 293-305. https://doi.org/10.33744/0365-8171-2025-117.1-293-305

MODEL FOR ASSESSMENT OF THE STATUS OF FUNCTIONING OF A LOGISTICS PROVIDER ORGANIZATION IN THE PROCESSES OF ORGANIZATIONAL STRATEGIC MANAGEMENT

Tetyana Vorkut Lyudmyla Volynets

Abstract

The relevance of the research topic is due to the need to develop a model for assessing the state of functioning of the organization of the logistics provider in the processes of organizational strategic management. The purpose of the research is to develop a comprehensive model for assessing the state of the organization's functioning in the context of effective and efficient implementation of the monitoring and control stage of strategic management in the logistics provider's organization. The object of research is the process of organizational strategic management. The subject of the study is methods, models and mechanisms for assessing the state of the organization's functioning for the purposes of strategic management. The article substantiates that today in strategic management methods and models of organization evaluation usually consider the conceptual issues of the formation of appropriate evaluation systems, but leave aside the issue of the implementation of appropriate systems, in particular, in terms of information support. In terms of solving the problem of developing complex models that take into account both the methodological aspects of the actual strategic management process and the information support of this process, it is relevant to conduct an analysis of the mathematical apparatus, which is based on the use of the theory of artificial intelligence. Develops a comprehensive model based on strategic management and information technology approaches for assessing the state of the organization's functioning in the context of effective and efficient implementation of the monitoring and control stage of strategic management in the organization of a logistics provider

Keywords:

logistics provider organization, strategic management, information technologies, monitoring, control

References

  1. Mintzberg, H., Lampel, J., & Ahlstrand, B. (2001). Strategy safari: A guided tour through the wilds of strategic management. Toronto: Free Press.
  2. Vorkut, T.A., Lushchai, Yu.V., Sevostianova, A.V., Sribna, N.V., & Kharuta, V.S. (2022). Strategically oriented management of logistics outsourcing projects in a dynamic external environment. Bulletin of the National Transport University. Series “Technical Sciences”, 1(51), 55-73. doi: 10.33744/2308-6645-2022-1-51-055-073.
  3. Niven, P.R. (2006). Balanced scorecard step-by-step: Maximizing performance and maintaining results (2nd ed.). Hoboken: Wiley.
  4. Kaplan, R.S., & Norton, D.P. (2000). The strategy-focused organization: How balanced scorecard companies thrive in the new business environment. Boston: Harvard Business School Press.
  5. Kaplan, R.S., & Norton, D.P. (2006). Alignment: Using the balanced scorecard to create corporate synergies. Boston: Harvard Business School Press.
  6. Neave, G.W. (2011). Organization as system: Principles for building a sustainable business by Edwards Deming (2nd ed.). Moscow: Alpina Publisher.
  7. Obruch, H., Derbentsev, V., Babenko, V., Khrustalev, K., & Khrustalova, S. (2021). Comparative performance of machine learning ensemble algorithms for forecasting cryptocurrency prices. International Journal of Engineering, 34(1), 140-148. doi: 10.5829/ije.2021.34.01a.16.
  8. Ko, Y.-C., & Fujita, H. (2019). An evidential analytics for buried information in big data samples: Case study of semiconductor manufacturing. Information Sciences, 486, 190-203. doi: 10.1016/j.ins.2019.01.079.
  9. Gödri, I., Kardos, C., Pfeiffer, A., & Váncza, J. (2019). Data analytics-based decision support workflow for high-mix low-volume production systems. CIRP Annals, 68(1), 471-474. doi: 10.1016/j.cirp.2019.04.001.
  10. Harding, J.L. (2013). Data quality in the integration and analysis of data from multiple sources: Some research challenges. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XL-2/W1, 59-63. doi: 10.5194/isprsarchives-XL-2-W1-59-2013.
  11. Chen, H. (2018). Evaluation of personalized service level for library information management based on fuzzy analytic hierarchy process. Procedia Computer Science, 131, 952-958. doi: 10.1016/j.procs.2018.04.233.
  12. Osman, A.M.S. (2019). Novel big data analytics framework for smart cities. Future Generation Computer Systems, 91, 620-633. doi: 10.1016/j.future.2018.06.046.
  13. Maccarone, A.D., Brzorad, J.N., & Stone, H.M. (2008). Characteristics and energetics of great egret and snowy egret foraging flights. Waterbirds, 31(4), 541-549. doi: 10.1675/1524-4695-31.4.541.
  14. Pérez-González, C.J., Colebrook, M., Roda-García, J.L., & Rosa-Remedios, C.B. (2019). Developing a data analytics platform to support decision making in emergency and security management. Expert Systems with Applications, 120, 167-184. doi: 10.1016/j.eswa.2018.11.023.
  15. Chan, H.K., Sun, X., & Chung, S.-H. (2019). When should fuzzy analytic hierarchy process be used instead of analytic hierarchy process? Decision Support Systems, advance online publication. doi:10.1016/j.dss.2019.113114.
  16. Vorkut, T., & Volynets, L. (2024). Devising a method for assessing the efficiency in managing logistics operations of motor transport enterprises. Eastern-European Journal of Enterprise Technologies, 6(3(132)), 17-24. doi: 10.15587/1729-4061.2024.317567.
Share
Facebook
Twitter
LinkedIn
Email
Telegram
Viber
WhatsApp

https://doi.org/10.33744/0365-8171-2025-117.1-293-305

Address
01010, Ukraine, Kyiv,
1, M. Omelianovycha-Pavlenka Str.


Email
ntu@arrcjournal.org

Main information
  • Aims and Scope
  • Indexing
  • Terms of Publication
  • Editorial Board
  • Publication Ethics
Additional information
  • Complaints Policy
  • Peer Review Process
  • Open Access Policy
  • Anti-plagiarism Policy
  • Generative AI Policy
  • Archiving