Abstract:The paper deals with an economic assessment of impacts of precision agriculture (PA) on crop production economy. Based on a questionnaire survey and a FADN agricultural product expense-to-revenue ratio survey, it analyses a set of agricultural businesses the structure of which essentially copies the composition of business forms in the Czech Republic's agricultural sector. The economic assessment applies economic analysis methods based on cost calculations and a calculation formula that considers the commodity… Show more
“…It creates significant advantages over traditional farming along with a reduction in human labour and resource efficiency, as outlined in the results of this paper. Thus, the conventional approach is associated with increased costs, production's economic intensity and environmental pollution risk [10]. The main ecological problem is the excessive application of agrochemicals and poorer traceability of records of soil operations.…”
Modern technologies are penetrating all fields of human activity, including agriculture, where they significantly affect the quantity and quality of agricultural production. Precision agriculture can be characterised as an effort to improve the results of practical farming, achieving higher profits by exploiting the existing spatial unevenness of soil properties. We aim to evaluate precision agriculture technologies’ practical use in agricultural enterprises in the Czech Republic. The research was based on a questionnaire survey in which 131 farms participated. We validated the hypothesis through a Chi-squared test on the frequency of occurrence of end-use technology. The results showed that precision farming technologies are used more in crop than livestock production. In particular, 58.02% of enterprises use intelligent weather stations, 89.31% use uncrewed vehicles, and 61.83% use navigation and optimisation systems for optimising journeys. These technologies are the most used and closely related to autonomous driving and robotics in agriculture. The results indicate how willing are agricultural enterprises to adopt new technologies. For policy makers, these findings show which precision farming technologies are already implemented. This can make it easier to direct funding towards grants and projects.
“…It creates significant advantages over traditional farming along with a reduction in human labour and resource efficiency, as outlined in the results of this paper. Thus, the conventional approach is associated with increased costs, production's economic intensity and environmental pollution risk [10]. The main ecological problem is the excessive application of agrochemicals and poorer traceability of records of soil operations.…”
Modern technologies are penetrating all fields of human activity, including agriculture, where they significantly affect the quantity and quality of agricultural production. Precision agriculture can be characterised as an effort to improve the results of practical farming, achieving higher profits by exploiting the existing spatial unevenness of soil properties. We aim to evaluate precision agriculture technologies’ practical use in agricultural enterprises in the Czech Republic. The research was based on a questionnaire survey in which 131 farms participated. We validated the hypothesis through a Chi-squared test on the frequency of occurrence of end-use technology. The results showed that precision farming technologies are used more in crop than livestock production. In particular, 58.02% of enterprises use intelligent weather stations, 89.31% use uncrewed vehicles, and 61.83% use navigation and optimisation systems for optimising journeys. These technologies are the most used and closely related to autonomous driving and robotics in agriculture. The results indicate how willing are agricultural enterprises to adopt new technologies. For policy makers, these findings show which precision farming technologies are already implemented. This can make it easier to direct funding towards grants and projects.
“…The changes in agricultural prices impact farmers' decisions on production scale and scope. The major sources of price changes are shifts in supply and demand that may occur due to natural factors (e.g., weather conditions), policy measures (e.g., support payments and taxes) or economic situation (e.g., shifts in the demand due to introduction of new technologies for bioenergy) (Pánková et al, 2020;Oláh et al, 2020). Climate change has been noticed as a factor of increased volatility in agricultural output (and, hence, prices), but agricultural support policies can be adapted to combat it (Searchinger et al, 2020).…”
This paper analyses the trends and sources of change in agricultural revenue for the new European Union (EU) member states, namely Latvia, Lithuania, and Poland. These countries still lag behind the old EU member states in terms of profitability, productivity, and farm size. Thus, assessment of the patterns in agricultural revenue changes in these countries may provide evidence for reasonable policy making. The period covered is 2011-2019. The analysis is carried out for selected agricultural products (wheat, milk, poultry, potatoes). The logarithmic mean Divisia index is applied for the decomposition. The results indicate that the effects of scale, productivity, and price change varied across the countries and products. Therefore, dedicated policy measures and pathways are needed for each particular context.
In business valuation, alternative cost of equity plays an important role considering the risk related to investment. Even a slight change in cost of equity can significantly affect the resulting business value. However, in the Czech Republic, risk premium has not been adequately addressed in terms of methodology. The objective of the paper is to explore the application of selected methods in calculating risk premium, and to select or modify existing methodology for the calculation of risk premium used in agricultural companies. For the purposes of determining the alternative cost of equity, three methods are selected: build up model, CAPM, and Fama and French Three Factor model; internal data of a family farm XY are used. Beta coefficient is calculated on the basis of the input data, and the results of the individual methods are compared. Based on the data of companies operating in the Czech market, the performed analysis suggests that the Build Up model is suitable for expressing alternative cost of equity. The agriculture sector is very specific, as agricultural companies are the first to be affected by the climate change. A follow-up study could be focused on the analysis and prediction of the impacts of climate change, with possible emphasis on the importance of weather derivatives for agriculture companies.
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