IDEAS home Printed from https://ideas.repec.org/a/ags/areint/364302.html

Modelling the efficiency of technological management of agricultural enterprises in economic security

Author

Listed:
  • Vovk, Mykola
  • Zubro, Tetyana
  • Omarov, Elvin
  • Kolomiiets, Bohdan
  • Hnydiuk, Volodymyr

Abstract

Purpose. The purpose of this study is to develop a model for assessing the efficiency of technological management of agricultural enterprises in the context of ensuring economic security. The study also focuses on the analysis of key factors affecting the efficiency of technological processes, and on the development of tools for improving management technologies in the context of modern economic challenges and risks. Methodology / approach. The study applied a comprehensive approach to modelling the efficiency of technological management at agricultural enterprises. The main tool of analysis was quantitative methods, in particular economic and mathematical modelling, which allowed to assess the impact of various factors on the efficiency of management decisions. Data on financial, economic, technological and production activities of agricultural enterprises were used to build the models. The approach, based on the integration of the methods used, allows not only to assess the current state of technological management, but also to predict possible development scenarios in conditions of economic instability. Results. Modelling of the state of efficiency of technological management in the system of economic security of agricultural enterprises of Poltava, Kyiv and Sumy regions for 2014–2023 was carried out. It was established that agricultural enterprises of Poltava region show consistently high scores, which indicates a strong technical-and-technological potential and the implementation of innovative solutions. Agricultural enterprises of Kyiv region demonstrate a gradual increase in the efficiency of technological management, although their indicators still remain lower than those of enterprises of the Poltava region. Agricultural enterprises of Sumy region have the lowest scores, which indicates serious problems in technical-and-technological development, probably due to an insufficient level of investment. In general, it is necessary to improve the technological management of agricultural enterprises, especially in Kyiv and Sumy regions, in order to ensure stable development of enterprises in the long term. Originality / scientific novelty. The novelty lies in the original authors’ comprehensive modelling of the efficiency of technological management of agricultural enterprises through an integrated assessment, which includes technical and technological, production, innovation and management indicators. The originality of the methodology lies in the application of the principal component method to determine weighting factors, which allows identifying key factors that affect technological management and economic security. Taking into account stimulators and destimulators when analysing the development of enterprises allows for accurate diagnostics and developing effective strategies for improving management. Practical value / implications. The results can be used in the activities of agricultural enterprises to optimise the processes of making management decisions. The proposed methodology also facilitates the analysis of large volumes of data and increases the accuracy of forecasts, which has a direct impact on strategic planning and competitiveness of the enterprise.

Suggested Citation

  • Vovk, Mykola & Zubro, Tetyana & Omarov, Elvin & Kolomiiets, Bohdan & Hnydiuk, Volodymyr, . "Modelling the efficiency of technological management of agricultural enterprises in economic security," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 11(1).
    • Handle: RePEc:ags:areint:364302
    DOI: 10.22004/ag.econ.364302
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/364302/files/10_Vovk_article.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.364302?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Markina, Iryna & Somych, Nikolai & Taran-Lala, Olena & Varaksina, Elena & Potapiuk, Iryna & Vovk, Mykola, 2022. "Managerial Aspects of Forming Enterprises’ Competitive Advantages: The Case of Agri-food Sector," International Journal on Food System Dynamics, International Center for Management, Communication, and Research, vol. 13(01), January.
    2. Guoqing Zhao & Shaofeng Liu & Carmen Lopez & Huilan Chen & Haiyan Lu & Sachin Kumar Mangla & Sebastian Elgueta, 2020. "Risk analysis of the agri-food supply chain: A multi-method approach," International Journal of Production Research, Taylor & Francis Journals, vol. 58(16), pages 4851-4876, July.
    3. Assunta Di Vaio & Flavio Boccia & Loris Landriani & Rosa Palladino, 2020. "Artificial Intelligence in the Agri-Food System: Rethinking Sustainable Business Models in the COVID-19 Scenario," Sustainability, MDPI, vol. 12(12), pages 1-12, June.
    4. Iryna Markina & Dmytro Diachkov & Tetiana Bodnarchuk & Polina Paschenko & Nataliia Chernikova, 2022. "Management of Resource-Saving and Energy-Saving Technologies as an Innovative Direction of Agri-Food Enterprise Restructuring," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 19(02), pages 1-24, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Iva Gregurec & Martina Tomičić Furjan & Katarina Tomičić-Pupek, 2021. "The Impact of COVID-19 on Sustainable Business Models in SMEs," Sustainability, MDPI, vol. 13(3), pages 1-24, January.
    2. Mohammad Nabipour & M. Ali Ülkü, 2021. "On Deploying Blockchain Technologies in Supply Chain Strategies and the COVID-19 Pandemic: A Systematic Literature Review and Research Outlook," Sustainability, MDPI, vol. 13(19), pages 1-32, September.
    3. Michael Rennings & Philipp Baaden & Carolin Block & Marcus John & Stefanie Bröring, 2024. "Assessing emerging sustainability-oriented technologies: the case of precision agriculture," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(6), pages 2969-2998, June.
    4. Stéphanie Camaréna, 2021. "Engaging with Artificial Intelligence (AI) with a Bottom-Up Approach for the Purpose of Sustainability: Victorian Farmers Market Association, Melbourne Australia," Sustainability, MDPI, vol. 13(16), pages 1-28, August.
    5. Nurul Najihah Azalanzazllay & Sarina Abdul Halim Lim & Ungku Fatimah Ungku Zainal Abidin & Cherrafi Anass, 2022. "Uncovering Readiness Factors Influencing the Lean Six Sigma Pre-Implementation Phase in the Food Industry," Sustainability, MDPI, vol. 14(14), pages 1-20, July.
    6. Ancín, María & Pindado, Emilio & Sánchez, Mercedes, 2022. "New trends in the global digital transformation process of the agri-food sector: An exploratory study based on Twitter," Agricultural Systems, Elsevier, vol. 203(C).
    7. Subhodeep Mukherjee & Venkataiah Chittipaka, 2022. "Analysing the Adoption of Intelligent Agent Technology in Food Supply Chain Management: An Empirical Evidence," FIIB Business Review, , vol. 11(4), pages 438-454, December.
    8. Nazym Akhmetzhanova & Assel Tapalova & Zhumakyz Gabbassova & Aigul Shadiyeva & Gulistan Akhmetova & Yerlan Onlassynov & Marat Saparbaev & Zhanar Yerzhanova, 2024. "Development of a methodology for assessing the efficiency of an agribusiness enterprise in using digital technologies," Eastern-European Journal of Enterprise Technologies, PC TECHNOLOGY CENTER, vol. 5(13 (131)), pages 48-57, October.
    9. Fahmida Akhter & Mohammad Rokibul Hossain & Amina Omrane & Mohammad Rokibul Kabir, 2022. "Impact of Corporate Attributes on Human Resource Disclosure Practices, Evidences from Commercial Banks of Bangladesh," FIIB Business Review, , vol. 11(3), pages 303-314, September.
    10. López, C. & Morales-Contreras, M.F. & Langella, I.M. & Alonso-Monge, J., 2025. "Modeling supply chain disruptions due to geopolitical Reasons: A systematic literature review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
    11. Lina Baranauskaitė & Daiva Jurevičienė, 2021. "Import Risks of Agricultural Products in Foreign Trade," Economies, MDPI, vol. 9(3), pages 1-15, July.
    12. Anna M. Hansson & Eja Pedersen & Niklas P. E. Karlsson & Stefan E. B. Weisner, 2023. "Barriers and drivers for sustainable business model innovation based on a radical farmland change scenario," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(8), pages 8083-8106, August.
    13. Abderahman Rejeb & Karim Rejeb & Andrea Appolloni & Mohammad Iranmanesh & Horst Treiblmaier & Sandeep Jagtap, 2022. "Exploring Food Supply Chain Trends in the COVID-19 Era: A Bibliometric Review," Sustainability, MDPI, vol. 14(19), pages 1-33, September.
    14. Garima, & Olaru, Doina & Smith, Brett & Siddique, Kadambot H.M., 2026. "Farm-level adaptations to harvest logistics constraints in export-oriented grain systems," Agricultural Systems, Elsevier, vol. 231(C).
    15. Laith T. Khrais, 2020. "Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce," Future Internet, MDPI, vol. 12(12), pages 1-14, December.
    16. Zhao, Guoqing & Xie, Xiaotian & Wang, Yi & Liu, Shaofeng & Jones, Paul & Lopez, Carmen, 2024. "Barrier analysis to improve big data analytics capability of the maritime industry: A mixed-method approach," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    17. Adiqa Kausar Kiani & Wasim Ullah Khan & Muhammad Asif Zahoor Raja & Yigang He & Zulqurnain Sabir & Muhammad Shoaib, 2021. "Intelligent Backpropagation Networks with Bayesian Regularization for Mathematical Models of Environmental Economic Systems," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    18. Jaya Priyadarshini & Rajesh Kr Singh & Ruchi Mishra & Surajit Bag, 2022. "Investigating the interaction of factors for implementing additive manufacturing to build an antifragile supply chain: TISM-MICMAC approach," Operations Management Research, Springer, vol. 15(1), pages 567-588, June.
    19. Juan Carlos Pérez-Mesa & Laura Piedra-Muñoz & Emilio Galdeano-Gómez & Cynthia Giagnocavo, 2021. "Management Strategies and Collaborative Relationships for Sustainability in the Agrifood Supply Chain," Sustainability, MDPI, vol. 13(2), pages 1-16, January.
    20. Masouda A. Gurban & Abeer S. Almogren, 2022. "Students’ Actual Use of E-Learning in Higher Education During the COVID-19 Pandemic," SAGE Open, , vol. 12(2), pages 21582440221, May.

    More about this item

    Keywords

    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:areint:364302. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: http://are-journal.com/are .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.