Economic planning at agricultural enterprises: Ukrainian experience of increasing the availability of data in the context of food security
DOI:
https://doi.org/10.51599/are.2023.09.04.08Keywords:
data availability, planning, food security, agricultural enterprises, consulting in agriculture.Abstract
Purpose. The purpose of the research is a comparative assessment of the state of data availability for planning the economic activity of agricultural enterprises, as well as the development of a model for increasing data availability based on the established correlation between socio-economic factors of internal and external influence of agricultural enterprises and readiness to disclose information when receiving consulting services.
Methodology / approach. The study is based on the results of a survey of agricultural enterprises’ (farms’) managers, collected based on a random sampling, the volume of which satisfies the requirements of representativeness. The results of the research made it possible to conduct a correlation analysis of the dependence model for increasing data availability based on the established correlation between socio-economic factors of internal and external influence of agricultural enterprises and readiness to disclose information when receiving consulting services. The obtained results of the analysis made it possible to confirm the research hypotheses and obtain answers to several research questions.
Results. The study reveals several dependencies and trends in the formation of openness and availability of data at agricultural enterprises (farms) for the implementation of economic activity planning by third-party consultants/experts. A strong direct connection was established between the unwillingness of enterprises to share management accounting data with third-party experts precisely because of the lack of practice of collecting such data, and not because of privacy concerns or negative past experiences. It was established that at enterprises characterized by a low level of openness to the dissemination of management accounting data, planning work is conducted directly by managers without qualified support of experts or planning is not conducted at all. The results suggest a number of solutions to ensure better access to the data needed for effective planning.
Originality / scientific novelty. The study concerns the problems of data availability at agricultural enterprises (farms) for the implementation of planning of economic activities by external consultants/experts and uses the method of correlation analysis to establish relationships between variables of the model. The data collection paradigm of agricultural enterprises for planning their activities has been developed. For the first time, the relationship between a number of socio-economic factors and the openness of agricultural enterprises and farms to management consulting was established.
Practical value / implications. The study formulates a number of proposals for improving the data availability at agricultural enterprises (farms) for the implementation of economic activity planning by third-party consultants/experts, which can be used by regional and state development agencies; state and private scientific institutions; governmental and non-governmental organizations; product manufacturers; legislators, etc., when developing support programs for agricultural producers to motivate them to use more effective planning tools, as well as when determining areas of activity for the regional advisory centers, taking into account the priority tasks in the sphere of planning data collection and analysis at agricultural enterprises and farms. Further studies of the data availability for planning the economic activity of agricultural enterprises are possible on the basis of the current study.
References
Bozga, I., Borga, A., Cristea, A., Nijloveanu, D., Tita, V., Cruceru, C., & Gheorghe, N. (2016). Study on the degree of satisfaction of Romanian farmers who accessed agricultural consulting services. Agriculture and Agricultural Science Procedia, 10, 525–531. https://doi.org/10.1016/j.aaspro.2016.09.029.
Andreopoulou, Z., Tsekouropoulos, G., Theodoridis, A., Samathrakis, V., & Batzios, Ch. (2014). Consulting for sustainable development, information technologies adoption, marketing and entrepreneurship issues in livestock farms. Procedia Economics and Finance, 9, 302–309. https://doi.org/10.1016/S2212-5671(14)00031-8.
Cretu, D., & Iova, R. (2015). The consultant role, in identifying and solving socio-economic aspects, specific to agriculture and rural area. Case study. Agriculture and Agricultural Science Procedia, 6, 654–660. https://doi.org/10.1016/j.aaspro.2015.08.115.
Far, S., & Rezaei-Moghaddam, K. (2017). Determinants of Iranian agricultural consultants’ intentions toward precision agriculture: integrating innovativeness to the technology acceptance model. Journal of the Saudi Society of Agricultural Sciences, 16(3), 280–286. https://doi.org/10.1016/j.jssas.2015.09.003.
Guosheng, Y., Chengxin, N., & Wenshun, C. (1998). Study & application of agricultural production decision-making consulting system (APDCS). IFAC Proceeding Volumes, 31(5), 199–203. https://doi.org/10.1016/S1474-6670(17)42122-7.
Wacher, M., & Wytrzens, H. (2022). Barn or building lot? A cross-case comparison viewing the role of agricultural interests in Austria’s local spatial planning processes. Land Use Policy, 122, 106437. https://doi.org/10.1016/j.landusepol.2022.106347.
Raddad, S. (2022). Strategic planning to integrate urban agriculture in Palestinian urban development under conditions of political instability. Urban Forestry & Urban Greening, 76, 127734. https://doi.org/10.1016/j.ufug.2022.127734.
Benini, M., Blasi, E., Detti, P., & Fosci, L. (2023). Solving crop planning and rotation problem in a sustainable agriculture perspective. Computers & Operation Research, 159, 106316. https://doi.org/10.1016/j.cor.2023.106316.
Zhang, Ch., Yang, G., Wang, Ch., & Huo, Z. (2023). Linking agricultural water-food-environment nexus with crop area planning: a fuzzy credibility-based multi-objective linear fractional programming approach. Agricultural Water Management, 277, 108135. https://doi.org/10.1016/j.agwat.2022.108135.
Jansma, J., & Wertheim-Heck, S. (2022). Feeding the city: a social practice perspective on planning for agriculture in peri-urban Oosterwold, Almere, the Netherlands. Land Use Policy, 117, 106104. https://doi.org/10.1016/j.landusepol.2022.106104.
Redhead, J., Berkmar, R., Brown, M., & Pywell, R. (2022). E-Planner: a web-based tool for planning environmental enhancement on British agricultural land. Environmental Modelling & Software, 155, 105437. https://doi.org/10.1016/j.envsoft.2022.105437.
Sallustio, L., Pettenella, D., Merlini, P., Romano, R., Salvati, L., Marchetti, M., & Corona, P. (2018). Assessing the economic marginality of agricultural lands in Italy to support land use planning. Land Use Policy, 76, 526–534. https://doi.org/10.1016/j.landusepol.2018.02.033.
Freytag, J., Britz, W., & Kuhn, T. (2023). The economic potential of organic production for stockless arable farms importing biogas digestate: a case study analysis for western Germany. Agricultural Systems, 209, 103682. https://doi.org/10.1016/j.agsy.2023.103682.
McDowell, R., & Kaye-Blake, W. (2023). Viewpoint: act local, effect global: integrating farm plans to solve water quality and climate change problems. Land Use Policy, 129, 106670. https://doi.org/10.1016/j.landusepol.2023.106670.
Pavlyk, V. (2020). Improvement of planning of economic activity of agricultural enterprises. Ekonomika APK, 3, 89–99. https://doi.org/10.32317/2221-1055.202003089.
Burkovska, A., Shebanina, O., Lunkina, T., & Burkovska, A. (2022). Socio-psychological determinants of food security in Ukraine: causal aspect. Ikonomicheski Izsledvania, 31(5), 145–162. https://www.iki.bas.bg/Journals/EconomicStudies/2022/2022-5/09_Anna-Burkovska.pdf.
Shebanina, O., Golubeva, O., Burkovska, A., & Radzevicius, G. (2018). The investment in the meat sector in the context of food security in Ukraine. Management Theory and Studies for Rural Business and Infrastructure Development, 40(3), 393–402. https://ejournals.vdu.lt/index.php/mtsrbid/article/view/121.
Burkovska, A., Ciccullo, F., Shebanina, O., Lunkina, T., & Burkovska, A. (2019). Modeling the system of social stability through the food safety paradigm. Management Theory and Studies for Rural Business and Infrastructure Development, 41(4), 474–486. https://doi.org/10.15544/mts.2019.38.
Poltorak, A., Khrystenko, O., Sukhorukova, A., Moroz, T., & Sharin, O. (2022). Development of an integrated approach to assessing the impact of innovative development on the level of financial security of households. Eastern-European of Enterprise Technologies, 1(13–115), 103–112. https://doi.org/10.15587/1729-4061.2022.253062.
Yekimov, S., Prodius, O., Chelombitko, T., Poltorak, A., Sirenko, N., Dudnyk, A., & Chernyak, V. (2022). Reengineering of agricultural production based on digital technologies. IOP Conference Series: Earth and Environmental Science, 981(3). https://doi.org/10.1088/1755-1315/981/3/032005.
Poltorak, A., Potryvaieva, N., Kuzoma, V., Volosyuk, Yu., & Bobrovska, N. (2021). Development of doctrinal model for state financial security management and forecasting its level. Eastern-European Journal of Enterprise Technologies, 5(13), 26–33. https://doi.org/10.15587/1729-4061.2021.243056.
Kolaj, R., Borisov, P., Arabska, E., & Radev, T. (2023). Food safety among and beyond: the power of market actors, institutions and researchers in the new era of food safety from farm-to-table. Agricultural and Resource Economics, 9(2), 276–294. https://doi.org/10.51599/are.2023.09.02.12.
Elzaki, R. M. (2023). Challenges of food security in the gulf cooperation council countries: an empirical analysis of fixed and random effects. Agricultural and Resource Economics, 9(1), 44–68. https://doi.org/10.51599/are.2023.09.01.03.
Irz, X., Leroy, P., Réquillart, V., & Solerb, L. G. (2015). Farmers’ markets and farm shops in Germany: is the motivation to buy there the same? 143rd Joint EAAE/AAEA Seminar (March 25–27, 2015). Naples, Italy. https://doi.org/10.22004/ag.econ.202721.
Skrynkovskyy, R., Pavlenchyk, N., Tsyuh, S., Zanevskyy, I., & Pavlenchyk, A. (2022). Economic-mathematical model of enterprise profit maximization in the system of sustainable development values. Agricultural and Resource Economics, 8(4), 188–214. https://doi.org/10.51599/are.2022.08.04.09.
Jiang, L., Li, Y., & Cai, L.-P. (2018). Evaluation of enterprise economic performance based on principal component analysis. Journal of Interdisciplinary Mathematics, 21(5), 1309–1314. https://doi.org/10.1080/09720502.2018.1498004.
Vu, Q., & Nga, N. T. T. (2022). Does the implementation of internal controls promote firm profitability? Evidence from private Vietnamese small- and medium-sized enterprises (SMEs). Finance Research Letters, 45, 102178. https://doi.org/10.1016/j.frl.2021.102178.
Fedicheva, K., Kochetkov, O., Honcharenko, S., Levkina, R., & Bichevin, M. (2021). Controlling, monitoring and diagnostics in identifying effective management practices of agricultural enterprises. Agricultural and Resource Economics, 7(2), 200–218. https://doi.org/10.51599/are.2021.07.02.11.
Prylipko, S., Shevchenko, N., & Hryshchenko, O. (2016). Efficiency of small farms functioning in Ukraine. Economic Annals–XXI, 158(3–4), 17–21. https://doi.org/10.21003/ea.V158-04.
Zomchak, L., & Umrysh, H. (2017). Modeling and forecasting of meat and egg production in Ukraine using the seasonal ARIMA model. Agricultural and Resource Economics, 3(3), 16–27. https://doi.org/10.51599/are.2017.03.03.02.
Zielińska-Sitkiewicz, M., & Chrzanowska, M. (2021). Prediction of pork meat prices by selected methods as an element supporting the decision-making process. Operations Research and Decisions, 31(3), 137–152. https://doi.org/10.37190/ord210307.
Shebanina, O., Klyuchnik, A., Burkovska, A., Caruso, D., & Burkovska, A. (2018). Providing labor income as a supporting factor of the food security. Management Theory and Studies for Rural Business and Infrastructure Development, 40(4), 597–608. http://doi.org/10.15544/mts.2018.51.
Kucher, L., Knіaz, S., Pavlenko, O., Holovina, O., Shayda, O., Franiv, I. & Dzvonyk, V. (2021). Development of entrepreneurial initiatives in agricultural business: a methodological approach. European Journal of Sustainable Development, 10(2), 321–335. https://doi.org/10.14207/ejsd.2021.v10n2p321.
Sumets, A., Kniaz, S., Heorhiadi, N., Skrynkovskyy, R., & Matsuk, V. (2022). Methodological toolkit for assessing the level of stability of agricultural enterprises. Agricultural and Resource Economics, 8(1), 235–255. https://doi.org/10.51599/are.2022.08.01.12.
Claassen, R., Langpap, C., & Wu, J. J. (2017). Impacts of federal crop insurance on land use and environmental quality. American Journal of Agricultural Economics, 99(3), 592–613. https://doi.org/10.1093/ajae/aaw075.
Rezaei, R., Mianaji, S., & Ganjloo, A. (2018). Factors affecting farmers’ intention to engage in on-farm food safety practices in Iran: extending the theory of planned behavior. Journal of Rural Studies, 60, 152–166. https://doi.org/10.1016/j.jrurstud.2018.04.005.
Daxini, A., O’Donoghue, C., Ryan, M., Buckley, C., Barnes, A., & Daly, K. (2018). Which factors influence farmers’ intentions to adopt nutrient management planning? Journal of Environmental Management, 224, 350–360. https://doi.org/10.1016/j.jenvman.2018.07.059.
Yu, X., Schweikert, K., Li, Y., Ma, J., & Doluschitz, R. (2023). Farm size, farmers’ perceptions and chemical fertilizer overuse in grain production: evidence from maize farmers in northern China. Journal of Environmental Management, 325, 116347. https://doi.org/10.1016/j.jenvman.2022.116347.
Gorge, H., Dittrich, I., Kemper, N., & Krieter, J. (2023). Solutions and prospects for digital documentation of treatment data on-farm. Smart Agricultural Technology, 6, 100299. https://doi.org/10.1016/j.atech.2023.100299.
Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. (2017). Big data in smart farming – a review. Agricultural Systems, 253, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023.
Wangen, S., Zhang, F., Fadul-Pacheco, L., Silva, T., & Cabrera, V. (2021). Improving farm decisions: the application of data engineering techniques to manage data streams from contemporary dairy operations. Livestock Science, 250, 104602. https://doi.org/10.1016/j.livsci.2021.104602.
Harnisch, R., Schlauderer, R., Prochnow, A., & Jessel, B. (2003). Financing nature conservation of former military training areas – economic problems in preservation of important open soil habitats. Naturschutz und Landschaftsplanung, 35(9), 272–278.
Ackermann, I., Schlauderer, R., Vegricht, J., Kovararova, M., & Abrham, Z. (2001). Modernisation and restructuring of agricultural enterprises depending on hired labour – a crooss-border comparison. Berichte uber Landwirtschaft, 79(3), 399–414.
Robling, H., Hatab, A., Sall, S., & Hansson, H. (2023). Measuring sustainability at farm level – a critical view on data and indicators. Environmental and Sustainability Indicators, 18, 100258. https://doi.org/10.1016/j.indic.2023.100258.
Kotykova, O., Pohorielova, O., Babych, M., & Shkilnyak, M. (2023). Information provision, accounting and analysis of food losses and waste: EU experience for Ukraine. Agricultural and Resource Economics, 9(3), 103–123. https://doi.org/10.51599/are.2023.09.03.05.
Kotykova, O., Babych, M., & Pohorielova, O. (2020). Food losses and waste along the value chain of food products in Ukraine. Agricultural and Resource Economics, 6(3), 191–220. https://doi.org/10.51599/ARE.2020.06.03.11.
Karnaushenko, A., Tanklevska, N., Povod, Т., Kononenko, L., & Savchenko, V. (2023). Implementation of blockchain technology in agriculture: fashionable trends or requirements of the modern economy. Agricultural and Resource Economics, 9(3), 124–149. https://doi.org/10.51599/are.2023.09.03.06.
Horoneskul, M. (2009). Tables of functions and critical points of distributions. University of Civil Defense of Ukraine. Available at: http://repositsc.nuczu.edu.ua/bitstream/123456789/1530/1/Tablici.pdf.
State Statistics Service of Ukraine (2022). Agriculture of Ukraine. Available at: https://www.ukrstat.gov.ua.
Farms of Ukraine (2023). Reference information portal. Available at: https://tripoli.land.
