AN INNOVATIVE COMPONENT IN GENERATING EFFICIENCY OF SUNFLOWER PRODUCTION

##plugins.themes.bootstrap3.article.main##

##plugins.themes.bootstrap3.article.sidebar##

Published: Aug 27, 2021

  Dmytro Shyian

  Nataliia Ulianchenko

  Kateryna Honcharova

Abstract

The introductory part emphasizes that since 2004, Ukrainian agriculture has gradually begun to crank up production. This is largely associated with the growth of crop production, including sunflower. During 2004–2020, gross sunflower yield increased by 3.1 times, and yield capacity – more than double. Research methods involve grouping a complex of agricultural enterprises following the cost value per 1 ha of the sown area and sunflower yield. To classify the enterprises according to the level of innovative production, the authors have put forward a method for determining the coefficient of innovation. The object of the study comprises the agricultural enterprises of Kharkiv region. The results of grouping following yield rate have made it possible to establish a direct dependence between the cost value and sunflower yield. In a group of enterprises with an average yield of up to 15 centners/ha, costs amounted to 9653 UAH / ha; in a group with a yield of 25.1–30 centners/ha – 14860 UAH/ha; with a yield of more than 45 centners/ha – 27518 UAH/ha. It has also been found that an increase in the rate of sunflower yield by 1 centner leads to an average profit increase of 307.9 UAH/ha. The grouping of enterprises by the level of costs per 1 sown area of sunflower has made it possible to assume that the nature of the relationship of a grouping indicator with profit margin is characterized by a nonlinear function. It has been determined that this function has a maximum when the cost increases by 16960 UAH/ha and the amount of profit – by 6199 UAH/ha. The paper has also marked that under such cost value, the value of sunflower yield should be equal to 29.8 centners/ha. The practical approval of the methodological approach to determining the coefficient of innovative development of sunflower production has shown that this indicator objectively conveys the rate of use of innovations in the manufacturing process. Enterprises that had a coefficient of innovative development above 1 were characterized by a much higher level of yield, profitability, and production intensity.

How to Cite

Shyian, D., Ulianchenko, N., & Honcharova, K. (2021). AN INNOVATIVE COMPONENT IN GENERATING EFFICIENCY OF SUNFLOWER PRODUCTION . Economics & Education, 6(2), 23-28. https://doi.org/10.30525/2500-946X/2021-2-4
Article views: 288 | PDF Downloads: 147

##plugins.themes.bootstrap3.article.details##

Keywords

production efficiency, sunflower yield, production intensity, maximum of function, coefficient of innovative development

References

Kondratiuk, N. V. (2013). Suchasni tendentsii vyrobnytstva nasinnia soniashnyku v silskohospodarskykh pidpryiemstvakh Kharkivskoi oblasti [Current trends in sunflower seed production in agricultural enterprises of Kharkiv region]. Visnyk KhNAU. Seriia: Ekonomichni nauky, 3, 157–162. (in Ukrainian)

Kondratiuk, N. V. (2014). Kontsentratsiia yak chynnyk formuvannia efektyvnosti vyrobnytstva soniashnyku [Concentration as a factor in shaping the efficiency of sunflower production]. Visnyk KhNAU. Seriia: Ekonomichni nauky, 6, 243–250. (in Ukrainian)

Kontseba, S. M. (2014). Shliakhy pidvyshchennia efektyvnosti vyrobnytstva nasinnia soniashnyku v rehioni [Ways to increase the efficiency of sunflower seed production in the region]. Visnyk KhNAU. Seriia: Ekonomichni nauky, 4, 313–323. (in Ukrainian)

Perebyinis, V. I. (2014). Stratehichni napriamy udoskonalennia lohistyky i marketynhu nasinnia soniashnyku [Strategic directions for improving the logistics and marketing of sunflower seeds]. Visnyk KhNAU. Seriia: Ekonomichni nauky, 5, 48–54. (in Ukrainian)

Milan R. Milanović & Simo Stevanović (2012). Models of Regression of the Scope of Sown Areas and Purchase Prices of Oil Crops in Serbia, Economic Research-Ekonomska Istraživanja, 25:4, 1017–1032. DOI: https://doi.org/10.1080/1331677X.2012.11517545

Demirhan, Haydar (2020). dLagM: An R package for distributed lag models and ARDL bounds testing. PLOS ONE. 15. e0228812. DOI: https://doi.org/10.1371/journal.pone.0228812.

Strapchuk, S. (2016). Pattern formation of business conditions in domestic market of crop production. Baltic Journal of Economic Studies, 2(4). DOI: https://doi.org/10.30525/2256-0742/2016-2-4-79-83