No 3/2021, September

Forecasting Grain Production and Static Capacity of Warehouses Using the Natural Neighbor and Multiquadric Equations


The strategic logistics of agricultural production and storage aggregates information related to production and storage. In this sense, time, location, and distance from producer and consumer markets are considered, emphasizing the importance of grain storage and production logistics. The natural neighbor and multiquadric equation are spatial interpolation methods used to predict these variables value at non-sampled locations, for asymmetric and categorical data, respectively. This study investigated the spatial prediction of grain production (tons) (soybean, first crop corn, and second-crop corn, and wheat) in the 2016/2017 growing season and qualitative data on the static capacity of warehouses in the 2017/2018 growing season. The result obtained through the spatial interpolation using the natural neighbor method was coherent, as it showed the high variability of grain production relative to the different meso-regions. Therefore, the method was appropriate because it allowed predicting the behavior of grain production in the 2016/2017 growing season in the state of Paraná-Brazil, making it possible to identify regions of higher or lower production. The result of the spatial interpolation using the multiquadric equations allowed identifying a higher predominance of storage units with a low static capacity of warehouses, but also enabled the detection of regions with a static capacity of warehouses that varied from the medium to the high category in the state of Paraná, Brazil.

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Productivity and Efficiency of Precision Farming: The Case of Czech Cereal Production


The paper deals with the sources of competitiveness of Czech cereal production by considering precision farming technology and employing micro-level data collected in the FADN database for the period 2005–2018. The analysis is based on the stochastic frontier modelling of an input distance function in the specification of the four-component model, which currently represents the most advanced approach to technical efficiency analysis. To provide a robust estimate of the model, the paper employs methods which control for the potential endogeneity of netputs in the four-step estimation procedure. Furthermore, the total factor productivity change is calculated using the Törnqvist-Theil index. The results reveal that Czech cereal producers took great advantage of their production possibilities and experienced technological progress, which contributed considerably to productivity dynamics and consequently to an increase in their competitiveness. Precision farming, which is associated with a large number of innovations reflected in technological change and optimal resource use, contributed to higher technical efficiency connected with cost savings in Czech cereal production.

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Assessment of Consumers Acceptance of E-Commerce to Purchase Geographical Indication Based Crop Using Technology Acceptance Model (TAM)


Diffusion of Information and Communication Technology (ICT) in every aspect of life has made the applications of e-commerce a fundamental part of marketing. Hence using e-commerce to market Geographical Indication (GI) based crops is quite essential for the survival of the growers associated with such crops. Due to this significance, it is critical to assess consumers acceptance of e-commerce to purchase geographical indication-based crop. The study uses Technology Acceptance Model (TAM) to validate consumers’ willingness of using e-commerce to purchase GI crops with specific reference to Udupi jasmine. To analyse the relationships between TAM variables, Structural Equation Modelling (SEM) technique was adopted. The analysis suggests that behavioural intentions of consumers will influence them into actual e-commerce use. Behavioural intention exerts a significant positive influence on the actual e-commerce use suggests that, if provided with an e-commerce application to purchase the product online, consumers are likely to accept and use it.

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Time-Varying Integration of Ukrainian Sunflower Oil Market with the EU Market


Ukraine (UA) is one of the world-leading countries in sunflower oil production and sunflower oil exports. Due to the increasing demand caused by biofuel regulations, the European Union (EU) remains the key importer of Ukrainian sunflower oil. Therefore, the aim of the proposed research is to provide an evaluation of the time-varying integration of the UA sunflower oil market with the EU market. To fulfill this goal, first, the trends in sunflower oil production and exports in Ukraine as well as trade regulations are presented. The market integration was assessed using the ARDL-ECM approach that was applied to weekly sunflower oil prices in the period from 2000 to 2020. The analytical study was supplemented with the Toda-Yamamoto (T-Y) Granger causality test, the Bai-Perron multiple structural breakpoint test (B-P) as well as impulse response functions (IRF). This study and the obtained results for the whole sample confirm the presence of a long-run relationship between EU and UA prices. The EU prices are the Granger cause for UA prices, as it is shown in the T-Y test. The Bai-Perron test indicates the existence of multiple structural breaks that can be justified by the market condition and policy modifications. Both the long- and the short-run response of UA prices to changes in EU prices vary significantly in different sub-periods.

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Influence of Key Performance Indicators in Marketing on the Financial Situation of Wine Producers Using ICT


Marketing is one of the key elements of the success of all companies, including the wine sector. Given the importance of wine producers for agriculture, it is important to define and monitor key performance indicators in marketing (KPIs) for a successful stay in the market and a competitive position at home and abroad. Today, the increase in competitive advantage includes mainly marketing, innovation and information and communication technologies. New digital tools and innovations have changed the way we approached data and decisions. A modernly adapted and effective strategic marketing strategy represents for wine companies an understanding mainly of their possibilities as well as the possibilities to influence the customer. This article evaluates the key performance indicators in marketing (KPI) and its relationship and impact on the financial situation of wine producers in Slovakia. The research sample includes 80 respondents. We obtained the primary data through a questionnaire, which was filled in by the leaders of wine companies. We verified the accuracy by means of descriptive statistics and multiple linear regression and Kruskall-Wallis test. We have verified the reliability of the data with the Cronbach alpha test. We have formulated scientific assumptions for in-depth analysis: hypothesis 1 – assumes that key performance indicators have a significant influence on financial situation of selected companies, hypothesis 2 – the use of ICT in marketing is statistically related to the key performance indicators. The results showed a statistically significant impact of KPIs on the financial situation of companies. We have identified significance in customer satisfaction and loyalty, brand awareness and return of investment. However, we were unable to statistically confirm the impact of other indicators (sales growth, market share, gaining new customers). We also identified significant differences in the use of ICT in marketing with key performance indicators in hiring new customers and return on investment. This research contributes positively to the importance of brand building in the eyes of customers as well as customer service, building loyalty and satisfaction, which returns to the loyal approach of customers to the repurchase of wine products and provides advice for professionals. Return on investment helps in more accurate business decisions that can be used when purchasing new equipment (technology), hiring employees, or properly assessing the profitability of marketing strategies.

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Possibilities of Using Social Networks as Tools for Integration of Czech Rural Areas - Survey 2021


This paper deals with the use of social networks in agricultural enterprises and focuses mainly on their role and share in increasing the competitiveness of agricultural enterprises in the market. Primary data were obtained from an extensive survey of the development of information and communication technologies in agricultural enterprises, which was conducted in the first quarter of 2021 throughout the Czech Republic (“Survey 2021”). The research was primarily focused on capturing current trends in the use of ICT with emphasis on selected key areas (broadband, social networks, communication tools, regional Internet portals, used hardware categories, used software, mobile communications, Internet of Things, data storage and security, social networks, etc.). This survey builds on previous extensive surveys conducted by the Department of Information Technologies, Faculty of Electrical Engineering, CULS in Prague in several phases since 1999, with the last stage being conducted in 2017. Some surveys were conducted in cooperation with the Ministry of Agriculture of Czech Republic. Compared to recent years, the survey includes new domains, such as the use of the Internet of Things in plant and animal production, data storage and security, the impact of the Covid-19 pandemic on the company's core operations, etc. The survey was prepared, conducted and administered by the Department of Information Technology, Faculty of Economics and Management, University of Life Sciences Prague.

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Asymmetry in Price Transmission: Evidence from the Wheat-Flour Supply Chain in Russia


Price volatility has serious implications for economic welfare of various agents in the grain supply chain. The paper examines asymmetric price transmission along the wheat producer-processor supply chain in Russia using log-transformed monthly prices during the period of 2000-2019. Having specified linear asymmetric vector error correction model, we exposed the long-term cumulative asymmetry in price transmission, however, the hypothesis of short-term symmetry presence failed to reject. The analysis revealed dominant position for wheat producers and wholesalers over the wheat processors. Imperfect competition and their resulting market power, as well as the existence of a huge number of illegal processors are the main causes for asymmetric price transmission on the Russian wheat market.

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Price Forecasting Accuracy of the OECD-FAO's Agricultural Outlook and the European Commission DG AGRI's Medium-Term Agricultural Outlook Report


The OECD-FAO's Agricultural Outlook and the European Commission DG AGRI's Medium-term agricultural outlook report provide price forecasts. Users of these forecasts may be interested in their accuracy. This paper measures the accuracy for values forecast for the following year. These are very accurate as regards the AO EU price of poultry, the EC outlook price of common wheat and feed barley, but not so accurate as regards the EC outlookon beef prices. In some cases, discrepancies between the forecasts follow a systematic pattern. The paper also discovers how the OECD-FAO's outlook projections for a common wheat world representative price are changing from year to year. Usually they are positively correlated, but there are certain exceptions where their correlation is significantly negative. This means that the price projections of some commodities may vary dramatically.

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World´s 24 Biggest Agricultural Producers` Eco-Efficiency Considering Undesirable Outputs


There is still a lack of studies, which are comparing the eco-efficiency of the world`s biggest agricultural producers, which affect the development of agricultural policy the most, not just EU countries. Therefore, the main goal of this article is to evaluate and compare the eco-efficiency of the world`s 24 biggest agricultural producers in time and space and verifying the hypothesis that all the biggest agriculture producers are eco-efficient. Due to the improvement of technologies, we expect a positive development of agricultural eco-efficiency during the time. Eco-efficiency of the world’s 24 biggest agricultural producers is computed for the years 2007 and 2017, using an output-oriented DEA model with two undesirable outputs. Data are obtained from FAOSTAT for the years 2007 and 2017. 15 countries have an eco-effective agricultural sector in both years 2007 and 2017 and could be considered as sustainable efficient countries. On average the agricultural eco-efficiency is decreasing over time. Based on the eco-efficiency values, the biggest agricultural producers are divided into three eco-efficiency agricultural groups – eco-efficiency leaders, eco-efficiency followers, and eco-efficiency laggards. According to the results, the research hypothesis that all the biggest agriculture producers are eco-efficient is not confirmed. Likewise, in general, technology improvement during time does not lead to a positive development of agricultural eco-efficiency.

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An Analysis of Technical Efficiency of Vegetables’ Household Production in Mongolia


Vegetable production is one important agricultural product in crop production after wheat and potatoes production in Mongolia. Currently, household production dominates in total vegetable production (approximately 80 percent). Thus, the purposes of this paper were to measure technical efficiency and to determine influencing factors inefficiency on vegetable household production in Mongolia by using Stochastic production frontier analysis (SFA). Primary data was collected from randomly selected 260 vegetable households of Mongolia in 2019. The empirical result indicated that the average technical efficiency of the sampled vegetable household was 64.6 % (range between 43.2% and 99.9%) or they lost about 35.4% of the potential output due to technical inefficiency. We found that land and labor are the main influencing input factors of the household’s vegetable production. Also, the result of the technical inefficiency model, variables of age, sex, experience, and credit use obtained a negative relationship with inefficiency. The other variables are family size, education level, land fragmentation index was positively affected by technical inefficiency.

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