Impact of the Remoteness of Farms on the Use of Robotics in Regional Agriculture
DOI:
https://doi.org/10.17059/ekon.reg.2023-1-12Abstract
Spatial aspects, including remoteness as one of the most important characteristics, significantly affect the socio-economic development of regions, in particular, the introduction of innovations by business. The present study aims to analyse the impact of distance to large cities and regional centres on the use of robotics in agriculture. At the first stage, the Google Maps application was used to determine the distances between robot farms and district and regional centres; at the second stage, a cluster analysis of the obtained data was performed. The study involved 81 farms located in 32 Russian regions, which use 371 robot units (85.2 % of their total number in the country). The greatest distance from the robot farm to the regional centre is 470 km, to the district centre — 73 km. The cluster analysis revealed an inverse correlation between distances to regional centres and the average number of robots on farms. On average, there are 32.5 robots in a cluster with an average distance of 35.0 km between a farm and a regional centre, 3.6 robots in a cluster with a distance of 114.7 km, and 3.0 robots in a cluster of extremely remote farms with a distance of 227.5 km. Farms with the largest number of robots are located near major urban agglomerations. Accordingly, the introduction of robotics in remote areas will be slower due to underdeveloped transport and other infrastructure. At the same time, rural population commuting to large cities additionally stimulates the robotisation of agriculture. To reduce the technological backwardness of remote rural areas, it is proposed to implement measures of innovation stimulation, including agricultural growth corridors, agriculture clusters, agro-industrial parks, special economic zones and agribusiness incubators.
References
Bandman, M. K. (1980). Territorialno-proizvodstvennye kompleksy: teoriya i praktika predplanovykh issledovaniy [Territorial-industrial complexes: theory and practice of preplanned research]. Novosibirsk: Nauka. Sib. department, 254. (In Russ.)
Bowland, C. & Otto, L. (2012). Implementing Development Corridors. Lessons from the Maputo Corridor. SAIIA Policy Briefing, 54. South African Institute of International Affairs. August. DOI: http://dx.doi.org/10.13140/RG.2.2.26673.43366.
Brezzi, M., Dijkstra, L. & Ruiz, V. (2011). OECD Extended Regional Typology: The Economic Performance of Remote Rural Regions. OECD Regional Development Working Papers, 2011/06, OECD Publishing. DOI: http://dx.doi.org/10.1787/5kg6z83tw7f4-en.
Bugromenko, V. I. (1981). Economic assessment of transport-geographical position of economic objects. Izvestiya AN SSSR [Bulletin of the Academy of Sciences of the USSR], 5, 66-79. (In Russ.)
Cooper, K. & Parsons, D. (1999). An economic analysis of automatic milking using a simulation model. Journal of Agricultural Engineering Research, 73(3), 311-321. DOI: 10.1006/JAER.1999.0422.
Demircan, V., Binici, T., Koknaroglu, H. & Aktas, A. (2006). Economic analysis of different dairy farm sizes in Burdur province in Turkey. Czech Journal of Animal Science, 51(1), 8-17. DOI: 10.17221/3903-CJAS.
El-Osta, H. S. & Morehart, M. J. (2000). Technology Adoption and Its Impact on Production Performance of Dairy Operations. Review of Agricultural Economics, 22(2), 477-498. DOI: http://dx.doi. org/10.1111/1058-7195.00034.
Emmi, L., Gonzalez-de-Soto, M., Pajares, G. & Gonzalez-de-Santos, P. (2014). New trends in robotics for agriculture: integration and assessment of a real fleet of robots. The Scientific World Journal, 1-21. DOI: https://doi.org/10.1155/2014/404059.
Gálvez-Nogales, E. (2010). Agro-based clusters in developing countries: staying competitive in a globalized economy. Rome, Italy: Food and Agriculture Organization of the United Nations.
Geetha, K. & Lavanya, V. (2013). Economic analysis of dairy farming in Vellalore village in Coimbatore district. Journal of Economic & Social Development, 9(1), 25-37.
Gokhberg, L., Kuzminov, I. & Khabirova, E. (2021). Technological Landscape of the Agriculture and Food Sector: A Long-Term Vision. In: E. Koukios, A. Sacio-Szymańska (Eds.), Bio#Futures. Foreseeing and Exploring the Bioeconomy (pp. 2053-227). Cham: Springer. DOI: https://doi.org/10.1007/978-3-030-64969-2_10.
Grabowska, S., Saniuk, S. & Gajdzik, B. (2022). Industry 5.0: improving humanization and sustainability of Industry 4.0. Scientometrics, 127, 3117-3144. DOI: https://doi.org/10.1007/s11192-022-04370-1.
Hyde, J. & Engel, P. (2002). Investing in a robotic milking system: A Monte Carlo simulation analysis. Journal of Dairy Science, 85, 2207-2214.
Jiang, H., Wang, W., Li, C. & Wang, W. (2017). Innovation, practical benefits and prospects for the future development of automatic milking systems. Frontiers of Agricultural Science and Engineering, 4, 37-47. DOI: 10.15302/J-FASE-2016117.
Kalugina, Z. I. & Fadeeva, O. P. (2009). New Paradigm of the Rural Development. Mir Rossii [Universe of Russia], 2, 34–49. (In Russ.)
Kapeliushnikov, R. I. (2013). Informality in the Russian Labor Market: What Do Alternative Definitions Tell Us? Zhurnal novoy ekonomicheskoy assotsiatsii [Journal of the new economic association], 4, 52-84. (In Russ.)
Klerkx, L., Aarts, N. & Leeuwis, C. (2010). Adaptive management in agricultural innovation systems: The interactions between innovation networks and their environment. Agricultural systems, 103(6), 390-400.
Kolosovsky, N. N. (1958). Osnovy ekonomicheskogo rayonirovaniya [Fundamentals of economic zoning]. Moscow: Gospolitizdat, 200. (In Russ.)
Krugman, P. (2010). The New Economic Geography, Now Middle-Aged. Paper presented to Association of American Geographers. 16. Retrieved from: http://www. princeton.edu/~pkrugman/aag.pdf.
Kuznetsova, L. V. & Mazurov, V. N. (2022). The effectiveness of the implementation of the Departmental Target Program «Creation of 100 robotic dairy farms in the Kaluga region». Agrarnyy vestnik Urala [Agrarian Bulletin of the Urals], 07(222), 79–90. DOI: 10.32417/1997-4868-2022-222-07-79-90. (In Russ.)
Lesh, A. (2007). Prostranstvennaya organizatsiya khozyaystva [Spatial organization of the economy]. M.: Nauka, 663. (In Russ.)
Melnikov, Y. B., Skvortsov, E., Ziablitckaia, N. & Kurdyumov, A. (2022). Modeling of Territorial and Managerial Aspects of Robotization of Agriculture in Russia. Mathematics, 10, 2540. DOI: https://doi.org/10.3390/math10142540.
Monnat, S. M. & Beeler Pickett, M. (2011). Rural / Urban differences in self-rated health: Examining the roles of county size and metropolitan adjacency. Health Place, 17(1), 311-319. DOI: https://doi.org/10.1016/j.healthplace.2010.11.008.
Nabokov, V. I. & Skvortsov, E. A. (2020). The impact of infrastructure provision and the level of subsidies on agricultural robotization. Ekonomika selskogo khozyaystva Rossii [Economics of agriculture in Russia], 12, 42-49. (In Russ.)
Nabokov, V. I., Skvortsov, E. A. & Kukhar, V. S. (2021). Robotization of agricultural production and wages in the industry. Ekonomika selskogo khozyaystva Rossii [Economics of agriculture in Russia], 9, 47-52. (In Russ.)
Nabokov, V. I., Skvortsov, E. A. & Pryadilina, N. K. (2020). Indicators of economic development of regions and robotization of agriculture. Russian Journal of Management, 8(4), 161-165. (In Russ.)
Nahavandi, N. (2019). Industry 5.0 A Human-Centric Solution. Sustainability, 11(16), 4371. DOI: https://doi.org/10.3390/su11164371.
Örs, A. & Oğuz, C. (2018). Comparison of the Economic Performance of Robotic Milking System and Conventional Milking System. Manas Journal of Agriculture Veterinary and Life Sciences, 8(2), 35-51.
Ozdogan B., Gacar, A. & Aktas, H. (2017). Digital Agriculture Practices in The Context of Agriculture 4.0. Journal of Economics, Finance and Accounting, 4, 184-191.
Panov, M. M. (2015). Intra-regional typology of rural areas (the case study of the Vologda Oblast). Problemy razvitiya territorii [Problems of territory’s development], 2(76), 159-173. (In Russ.)
Pedersen, S. M., Fountas, S., Have, H. & Blackmore, B. S. (2006). Agricultural robots — system analysis and economic feasibility. Precision agriculture, 7(4), 295-308.
Sanz-Cañada, J. & Muchnik, J. (2016). Geographies of origin and proximity: Approaches to local agro-food systems. Culture and History, 5(1), e002. DOI: http://dx.doi.org/10.3989/chdj.2016.002.
Semin, A. N., Drokin, V. V. & Zhuravlev, A. S. (2021). On the use of the results of positive experience in the digital economy of agricultural production. Ekonomika selskokhozyaystvennykh i pererabatyvayushchikh predpriyatiy [Economy of agricultural and processing enterprises], 9, 2-8. (In Russ.)
Simões Filho, L. M., Lopes, M. A., Brito, S. C., Rossi, G., Conti, L. & Barbari, M. (2020). Robotic milking of dairy cows: a review. Semina: Ciencias Agrarias, 41, 2833-2850. DOI: 10.5433/1679-0359.2020v41n6p2833
Skvortsov, E. A. & Nabokov, V. I. (2020). On the issue of regional trends in agricultural robotization. Ekonomika selskogo khozyaystva Rossii [Economics of agriculture in Russia],8, 30-38. DOI: https://doi.org/10.32651/208-30. (In Russ.)
Surovtsev, V. N., Nikulina, Yu. N. & Payurova, E. N. (2019). Achieving milk threshold of food security doctrine: forecast, factors and risks. APK: ekonomika, upravlenie [AIC: Economics, Management], 12, 38-50. DOI: https://doi.org/10.33305/1912-38. (In Russ.)
Thunen, I. (1926). The isolated state [Izolirovannoe gosudarstvo]. Trans. M.: Economic life, 326. (In Russ.)
Torres-Salcido, G. & Sanz-Cañada, J. (2018). Territorial Governance. A Comparative Research of Local Agro-Food Systems in Mexico. Agriculture, 8(2), 18. DOI: https://doi.org/10.3390/agriculture8020018.
Veysset, P., Wallet, P. & Prugnard, E. (2001). Automatic milking systems: Characterising the farms equipped with AMS, impact and economic simulations. ICAR Technical Series, 7, 141-150.
Weber A. (1926). Theory of industrial location [Teoriya razmeshcheniya promyshlennosti]. Trans. L.-M.: Book, 119. (In Russ.)
Yener Ögür, A. (2021). Factors Affecting the Adoption of Technology in Dairy Farms in the Konya Region of Turkey. New Medit, 20(3), 145-157. DOI: https://doi.org/10.30682/nm2103j.
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