IDEAS home Printed from https://ideas.repec.org/a/cuc/eforum/v13y2023i3p87-96.html

Analysis of the influence of value-forming components on machine-building enterprises market capitalization dynamics

Author

Listed:
  • Oleksandr Burban

Abstract

The article determines the importance of the impact of value-forming components on the dynamics of the market capitalization of Ukrainian machine-building enterprises. The main objective of the conducted research is to implement a scientific and methodological approach to realization of factor analysis of the influence of value-forming components on the dynamics of market capitalization of enterprises. A critical analysis of the content of scientific publications on the researched topic determines expediency of using factor analysis and sensitivity analysis in determining the influence of value-forming components on machine-building enterprises market capitalization dynamics. The relevance of solving the specified problem is due to the importance of determining the set of value components that are considered by the market as the most most valuable for machine-building enterprises from the standpoint of impact on market capitalization in order to identify potential reserves for its increase. The methodological basis is a system of methods used to obtain research results: theoretical generalization – to clarify the content of scientific publications with the aim of forming a scientific and methodological approach to the implementation of a factor analysis of an enterprise market capitalization; factor analysis – to reveal the influence of changes in the value-forming components of the representative machine-building enterprises on the target indicator of their market capitalization; sensitivity analysis – to determine the degree of responsiveness of the market capitalization to changes in the discount rate and the terminal growth rate; logical generalization – to summarize conclusions based on research results. The object of research is the market capitalization of enterprises, formed under the influence of changes in the main components of their value. The article presents the results of evaluating the impact of the value-forming components on the market capitalization dynamics of Ukrainian machine-building enterprises. The results were obtained through the proposed author’s scientific-methodological approach. The analysis and logical generalization of the research results served as the basis for determining the impact of value components on market capitalization dynamics, including the identification of those components that have the most significant impact, such as discount rate and terminal growth rate. The results of the study have practical value for the further development of a system of management solutions for increasing the market capitalization of the enterprise

Suggested Citation

  • Oleksandr Burban, 2023. "Analysis of the influence of value-forming components on machine-building enterprises market capitalization dynamics," E-Forum Working Papers, Economic Forum, vol. 13(3), pages 87-96, September.
  • Handle: RePEc:cuc:eforum:v:13:y:2023:i:3:p:87-96
    DOI: https://doi.org/10.36910/6775-2308-8559-2023-3-12
    as

    Download full text from publisher

    File URL: https://e-forum.com.ua/web/uploads/pdf/EF_N3_2023_Burban.pdf
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.36910/6775-2308-8559-2023-3-12?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. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    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. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    2. Makam, Vaishno Devi & Millossovich, Pietro & Tsanakas, Andreas, 2021. "Sensitivity analysis with χ2-divergences," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 372-383.
    3. Plischke, Elmar & Borgonovo, Emanuele, 2019. "Copula theory and probabilistic sensitivity analysis: Is there a connection?," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1046-1059.
    4. Wen Shi & Xi Chen & Jennifer Shang, 2019. "An Efficient Morris Method-Based Framework for Simulation Factor Screening," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 745-770, October.
    5. F. Wang & G. H. Huang & Y. Fan & Y. P. Li, 2020. "Robust Subsampling ANOVA Methods for Sensitivity Analysis of Water Resource and Environmental Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3199-3217, August.
    6. Daniel Harenberg & Stefano Marelli & Bruno Sudret & Viktor Winschel, 2019. "Uncertainty quantification and global sensitivity analysis for economic models," Quantitative Economics, Econometric Society, vol. 10(1), pages 1-41, January.
    7. Tobias Fissler & Silvana M. Pesenti, 2022. "Sensitivity Measures Based on Scoring Functions," Papers 2203.00460, arXiv.org, revised Jul 2022.
    8. Shang, Xiaobing & Su, Li & Fang, Hai & Zeng, Bowen & Zhang, Zhi, 2023. "An efficient multi-fidelity Kriging surrogate model-based method for global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    9. Magni, Carlo Alberto, 2016. "Capital depreciation and the underdetermination of rate of return: A unifying perspective," Journal of Mathematical Economics, Elsevier, vol. 67(C), pages 54-79.
    10. Lu, Xuefei & Borgonovo, Emanuele, 2023. "Global sensitivity analysis in epidemiological modeling," European Journal of Operational Research, Elsevier, vol. 304(1), pages 9-24.
    11. Matteo Fontana & Massimo Tavoni & Simone Vantini, 2020. "Global Sensitivity and Domain-Selective Testing for Functional-Valued Responses: An Application to Climate Economy Models," Papers 2006.13850, arXiv.org, revised Apr 2024.
    12. Stefano Cucurachi & Carlos Felipe Blanco & Bernhard Steubing & Reinout Heijungs, 2022. "Implementation of uncertainty analysis and moment‐independent global sensitivity analysis for full‐scale life cycle assessment models," Journal of Industrial Ecology, Yale University, vol. 26(2), pages 374-391, April.
    13. Yun, Wanying & Lu, Zhenzhou & Feng, Kaixuan & Li, Luyi, 2019. "An elaborate algorithm for analyzing the Borgonovo moment-independent sensitivity by replacing the probability density function estimation with the probability estimation," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 99-108.
    14. Puppo, L. & Pedroni, N. & Maio, F. Di & Bersano, A. & Bertani, C. & Zio, E., 2021. "A Framework based on Finite Mixture Models and Adaptive Kriging for Characterizing Non-Smooth and Multimodal Failure Regions in a Nuclear Passive Safety System," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    15. Ziemele, Jelena & Gravelsins, Armands & Blumberga, Andra & Blumberga, Dagnija, 2017. "Sustainability of heat energy tariff in district heating system: Statistic and dynamic methodologies," Energy, Elsevier, vol. 137(C), pages 834-845.
    16. Thomas H. Jørgensen, 2023. "Sensitivity to Calibrated Parameters," The Review of Economics and Statistics, MIT Press, vol. 105(2), pages 474-481, March.
    17. Tiwari, Saurabh & Kumar, Akshay & Tiwari, Gaurav & Sharma, Pratibha, 2025. "An efficient uncertainty analysis of performance of hydrogen storage systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 209(C).
    18. Marchioni, Andrea & Magni, Carlo Alberto, 2018. "Investment decisions and sensitivity analysis: NPV-consistency of rates of return," European Journal of Operational Research, Elsevier, vol. 268(1), pages 361-372.
    19. Magni, Carlo Alberto & Marchioni, Andrea, 2020. "Average rates of return, working capital, and NPV-consistency in project appraisal: A sensitivity analysis approach," International Journal of Production Economics, Elsevier, vol. 229(C).
    20. Aigner, Philipp & Schlütter, Sebastian, 2023. "Enhancing gradient capital allocation with orthogonal convexity scenarios," ICIR Working Paper Series 47/23, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).

    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:cuc:eforum:v:13:y:2023:i:3:p:87-96. 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: Economic Forum (email available below). General contact details of provider: https://e-forum.com.ua/ .

    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.