Diffusion of technologies: a longitudinal analysis of the Brazilian agricultural machinery sector
DOI:
https://doi.org/10.33448/rsd-v11i8.29185Keywords:
Technology diffusion; Innovation; Agriculture mechanization; Agriculture change; Agribusiness.Abstract
The importance of adopting technology innovations, mainly in food production contributing to food safety, is significant. This study aims to analyze the diffusion of agricultural production technologies in Brazil, mainly the use of wheel tractors, grain and sugarcane harvesters by producers. A quantitative approach is used to understand the market-level factors that influence the adoption of technologies. A supply response is estimated based on the Bass diffusion model. Data were collected from the National Association of Vehicle Manufacturers (Anfavea), which includes Brazilian monthly sales information for wheel tractors, grain and sugarcane harvesters. For each agricultural machine, 700 months of sales records were collected. The imitator’s coefficients were higher than innovators for all types of machines studied. The data showed that, for wheel tractors and grain harvesters, the diffusion curve presented S format (S-curves). However, sugarcane harvesters had a different pattern of diffusion. The distribution of the investigated technologies in Brazil was an imitation process; the market saturation was observed for wheel tractors and grain harvesters. This study helps to comprehend the supply response of agricultural machinery and presents suggestions for the diffusion of agricultural production technologies in Brazil. The experience has shown that several factors can constrain technology adoption, such as lack of credit, limited access to information and inputs, and inadequate infrastructure.
References
Aryal, J. P., Rahut, D. B., Thapa, G., & Simtowe, F. (2021). Mechanisation of small-scale farms in South Asia: Empirical evidence derived from farm households survey. Technology in Society, 65, 101591. https://doi:10.1016/j.techsoc.2021.10159
Baer, W. (1965). A industrialização e o desenvolvimento econômico do Brasil. Rio de Janeiro: FGV.
Barth, H., Ulvenblad, P., Ulvenblad, P.-O., & Hoveskog, M. (2021). Unpacking sustainable business models in the Swedish agricultural sector– the challenges of technological, social and organisational innovation. Journal of Cleaner Production, 304, 127004. https://doi:10.1016/j.jclepro.2021.127004
Bass, F. M. (1969). A new product growth for model consumer durables. Management Science, 15(5), 215–227. Recuperado de: http://www.jstor.org/stable/2628128
Bass, F. M. (2004). Comments on “A new product growth for model consumer durables the Bass model”. Management Science, 50(12), 1833–1840. https://doi.org/10.1287/mnsc.1040.0300
Betarelli Junior, A. A., Faria, W. R., Montenegro, R. L. G., Bahia, D. S., & Gonçalves, E. (2020). Research and development, productive structure and economic effects: Assessing the role of public financing in Brazil. Economic Modelling, 90, 235–253. https://doi:10.1016/j.econmod.2020.04.017
Brazilian Institute of Geography and Statistics (IBGE). (2010). Censo 2010. Recuperado de: http://www.censo2010.ibge.gov.br/
Camara, S., Martins, S., Silva, A., Andreatta, T., & Azevedo, J. (2020). Contribuições do Pronaf Mais Alimentos. Revista de Política Agrícola, 29(1), 73–81. Recuperado de: https://seer.sede.embrapa.br/index.php/RPA/article/view/1487/pdf
Casarotto, E. L. (2019). Proposta de framework com utilização de big data baseado em inteligência competitiva para a geração de vantagem competitiva. Tese (Doutorado em Administração) – Programa de Pós-graduação em Administração, Universidade Federal de Mato Grosso do Sul, Brasil.
Delgado, G. C. (1985). Capital financeiro e agricultura no Brasil: 1965-1985. São Paulo: Icone, Unicamp.
Duval, Y., & Biere, A. (2002). Product diffusion and the demand for new food products. Agribusiness, 18(1), 23–36. https://doi:10.1002/agr.10005.
Faostat. (2017). Food and agriculture data. Recuperado de: http://faostat.fao.org
Feder, G., & Umali, D. L. (1993). The adoption of agricultural innovations: A review. Technological Forecasting and Social Change, 43(3), 215–239. https://doi:10.1016/0040-1625(93)90053-A
Ferneda, R. (2018). Adoção de tecnologias da indústria 4.0 por firmas do agronegócio do Rio Grande do Sul. Mestrado (Mestrado em Economia) – Programa de Pós-graduação em Economia, Universidade do Vale do Rio dos Sinos, Brasil.
Ferreira, J. L., Ruffoni, J., & Carvalho, A. M. (2018). Dinâmica da difusão de inovações no contexto brasileiro. Revista Brasileira de Inovação, 17(1), 175–200. https://doi.org/10.20396/rbi.v16i4.8650852
Gaffney, J., Bing, J., Byrne, P. F., Cassman, K. G., Ciampitti, I., Delmer, D., & Warner, D. (2019). Science-based intensive agriculture: Sustainability, food security, and the role of technology. Global Food Security, 23, 236–244. https://doi:10.1016/j.gfs.2019.08.003
Jankowska, B., Maria, E. D., & Cygler, J. (2021). Do clusters matter for foreign subsidiaries in the era of industry 4.0? The case of the aviation valley in Poland. European Research on Management and Business Economics, 27(2), 100150. https://doi:10.1016/j.iedeen.2021.100150
Lima, V., Santos, I., & Amato Neto, J. (2017). A indústria de máquinas agrícolas no Brasil: Análise evolucionária no período de 1985-2015; uma revisão. Recuperado de: https://www.researchgate.net/publication/321149791_a_industria_de_maquinas_agricolas_no_brasil_analise_evolucionaria_no_periodo_de_1985-2015_uma_revisao
Meade, N., & Islam, T. (2006). Modelling and forecasting the diffusion of innovation – A 25-year review. International Journal of Forecasting, 22(3), 519–545. https://doi:10.1016/j.ijforecast.2006.01.005
Metcalfe, J. S. (1981). Impulse and diffusion in the study of technical change. Futures, 13(5), 347–359. https://doi:10.1016/0016-3287(81)90120-8
National Association of Vehicle Manufacturers (Anfavea). (2017). Estatísticas. Recuperado de: http://www.anfavea.com.br/estatisticas.html
OECD/FAO. (2018). OECD-FAO Agricultural Outlook 2018-2027. Rome, Paris: OECD, FAO. https://doi.org/10.1787/agr_outlook-2018-en.
Pingali, P. L. (2007). Chapter 54 Agricultural mechanization: Adoption Patterns and Economic Impact. Recuperado de: https://www.researchgate.net/publication/222232011_Chapter_54_Agricultural_Mechanization_Adoption_Patterns_and_Economic_Impact
Ribeiro, A., Amaral, A., & Barros, T. (2021). Project manager competencies in the context of the industry 4.0. Procedia Computer Science, 181, 803–810. https://doi:10.1016/j.procs.2021.01.233
Rodrigues, L. F., Jesus, R. A., & Schützer, K. (2016). Industrie 4.0: Uma revisão da literatura. Revista de Ciência & Tecnologia, 19(38), 33–45. https://doi:10.15600/2238-1252/rct.v19n38p33-45
Ryan, B., & Gross, N. C. (1943). The diffusion of hybrid seed corn in two Iowa communities. Rural Sociology, 8(1), 15–24.
Schultz, T. W. (1964). Transforming traditional agriculture. New Haven: Yale University Press.
Sunding, D., & Zilberman, D. (2001). The agricultural innovation process: research and technology adoption in a changing agricultural sector. Handbook of Agricultural Economics, 1, 207–261. https://doi.org/10.1016/S1574-0072(01)10007-1
The World Bank. (2017). World Bank open data. Recuperado de: https://data.worldbank.org/
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Copyright (c) 2022 Debin Zhang; Dieisson Pivoto; Carlos Alberto Oliveira de Oliveira; Caroline Pauletto Spanhol Finocchio; Leila Dal Moro; Lucas Bucior; Giana de Vargas Mores
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