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Методологія Оцінювання Інноваційного Потенціалу Підприємств

Author

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  • Yepifanova, Iryna
  • Dzhedzhula, Viacheslav

Abstract

Purpose. The purpose of this article is to form a methodology for assessing the innovative potential of agricultural engineering enterprises using the Harrington’s desirability function. Methodology / approach. The general scientific and special methods of economic theory and management theory are methodological basis of the work. The paper uses an abstract-logical method – for the logical formation of the main aspects and conclusions of the study; methods of mathematical modeling, including expert ones and Harrington’s method – to assess the level of innovation potential of agricultural engineering enterprises. Results. Approaches to defining the essence and components of innovation potential are generalized. Indicators to determine the innovation potential are systematized. The scientific-and-methodological approach to assessing the level of innovation potential based on the generalized Harrington`s criterion is proposed, which allows generalizing various criteria and factors that determine the innovation potential of the enterprise, transfer them into a dimensionless scale and calculate the criterion of desirability – the level of innovation potential. The gradation of values of the desirability function depending on the values of the function is proposed. The innovative potential of agricultural engineering enterprises of Vinnytsia and Khmelnytsky regions was assessed according to the proposed method. Originality / scientific novelty. The scientific novelty of the work is in improving the scientific-and-methodological approach to assessing the level of innovation potential, which, unlike existing approaches, involves the definition of innovation potential as a generalized coefficient of desirability, which depends on human, financial, economic, scientific-and-technical potential, taking into account their mutual influence. Practical value / implications. The results of the study allow a more comprehensive assessment of the level of innovation potential of the enterprise and identifying areas of its growth in the formation of sources of financial support for innovation.

Suggested Citation

  • Yepifanova, Iryna & Dzhedzhula, Viacheslav, 2020. "Методологія Оцінювання Інноваційного Потенціалу Підприємств," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 6(3), September.
  • Handle: RePEc:ags:areint:305559
    DOI: 10.22004/ag.econ.305559
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    References listed on IDEAS

    as
    1. Dziallas, Marisa & Blind, Knut, 2019. "Innovation indicators throughout the innovation process: An extensive literature analysis," Technovation, Elsevier, vol. 80, pages 3-29.
    2. Arne Isaksen & Michaela Trippl, 2017. "Innovation in space: the mosaic of regional innovation patterns," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 33(1), pages 122-140.
    3. Parrilli, Mario Davide & Balavac, Merima & Radicic, Dragana, 2020. "Business innovation modes and their impact on innovation outputs: Regional variations and the nature of innovation across EU regions," Research Policy, Elsevier, vol. 49(8).
    4. Stojčić, Nebojša & Srhoj, Stjepan & Coad, Alex, 2020. "Innovation procurement as capability-building: Evaluating innovation policies in eight Central and Eastern European countries," European Economic Review, Elsevier, vol. 121(C).
    5. G. M.P. Swann, 2009. "The Economics of Innovation," Books, Edward Elgar Publishing, number 13211.
    6. Khedhaouria, Anis & Thurik, Roy, 2017. "Configurational conditions of national innovation capability: A fuzzy set analysis approach," Technological Forecasting and Social Change, Elsevier, vol. 120(C), pages 48-58.
    7. Sam Tavassoli & Charlie Karlsson, 2018. "The role of regional context on innovation persistency of firms," Papers in Regional Science, Wiley Blackwell, vol. 97(4), pages 931-955, November.
    8. Noh, Heeyong & Lee, Sungjoo, 2020. "What constitutes a promising technology in the era of open innovation? An investigation of patent potential from multiple perspectives," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    9. Vyacheslav Dzhedzhula & Iryna Yepifanova, 2018. "Methodological Bases Of Concept Formation And Choice Of Innovative Business Strategies," Baltic Journal of Economic Studies, Publishing house "Baltija Publishing", vol. 4(3).
    10. Freeman, Christopher & Soete, Luc, 2009. "Developing science, technology and innovation indicators: What we can learn from the past," Research Policy, Elsevier, vol. 38(4), pages 583-589, May.
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