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A theoretical framework on network's dynamics for precision agriculture technologies adoption
2021
Deborah Bentivoglio | Giorgia Bucci | Matteo Belletti | Adele Finco
Abstract: Recently, the agricultural sector has had to face several challenges related to the innovation process, the most significant of which seems to be that of its digital transformation. As a consequence, the issue of digital technology adoption is becoming of important scientific interest due to its potential impact on products, services, processes, and new business models. In general, the adoption behavior can be indirectly explained by studying factors that lead a firm to innovate; among these factors, the literature emphasizes the function of networks. The objective of the paper is to investigate the role of networks as key drivers of precision agriculture technologies adoption. To achieve this goal, qualitative research was developed by using 8 case studies recollected among that few Italian farms which can be defined as innovative for having already experienced precision agriculture. Results show that only a few farms can develop and manage innovations internally; success often requires cooperation between individual actors and organizations. Finally, the paper provides some practical advice and a set of propositions for those farms that are trying to achieve digital technological innovations.
اظهر المزيد [+] اقل [-]Inovação na indústria sucroalcooleira paulista: os determinantes da adoção das tecnologias de agricultura de precisão
2010
Claudia Brito Silva Cirani | Márcia Azanha Ferraz Dias de Moraes
As tecnologias de Agricultura de Precisão (AP) já são adotadas nas lavouras do Brasil, com técnicas cada vez mais produtivas, indispensáveis para garantir a liderança do País na produção agrícola. No entanto, ainda não existem estudos sobre a intensidade do uso das tecnologias de AP no País e dos condicionantes de sua adoção. O desafio central deste trabalho foi, então, investigar o processo de adoção e uso das tecnologias de AP alcançado pela indústria sucroalcooleira no estado de São Paulo. Para tanto, foram utilizados dados primários, a partir de encaminhamento de questionário a todas as empresas do setor sucroalcooleiro paulista, com o objetivo de conhecer não só o grau de adoção e uso das tecnologias de AP, mas também de verificar a influência das variáveis estudadas na probabilidade de adoção dessas tecnologias. As conclusões deste trabalho sugerem não apenas que o percentual de adoção das tecnologias de AP é elevado na indústria sucroalcooleira paulista, mas também que a probabilidade de adotar tais tecnologias é maior em ordem decrescente de importância, em usinas/destilarias de capital nacional, que fazem parte de um grupo empresarial, de orientação exportadora, de gestão profissional, e que utilizam maior percentual de recursos próprios para investimentos na empresa.<br>Technologies of Precision Agriculture (PA) are already a reality in crops throughout Brazil, using more and more productive techniques, crucial to ensure the country as the world leader in agriculture. However, studies on the intensity of the use of PA technologies in Brazil and the determiners of their adoption do not exist yet. The main focus of this study was, therefore, to investigate the adoption process and the use of PA technologies in the sugarcane industry in São Paulo state. For that purpose, it used primary data based upon a questionnaire submitted to all enterprises of the sugarcane sector in the state, aiming to figure out not only the adoption level and use of PA technologies in the sugarcane industry, but also to verify the influence of the variables studied on the probability for the adoption of the PA technologies. The conclusions of this study suggest that the percentage for the PA adoption is high in the sugarcane industry of São Paulo and also that the probability to adopt PA technologies is higher in decrescent order of importance in mills/distilleries of national capital, which are part of an export-driven group, of professional management and that use higher percentage of their own resources.
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