Modelo de aceitação para tecnologias digitais na agricultura: aplicação à sistemas de informação de gestão agrícola

• Ano de defesa: 2023
• Autor(a) principal: Lima, Anderson Rodolfo
• Orientador(a): Batalha, Mário Otávio
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia de Produção - PPGEP
• Palavras-chave em Português: Adoção; Aceitabilidade; Modelos comportamentais
• Palavras-chave em Inglês: Smart farm
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA DE PRODUCAO::GERENCIA DE PRODUCAO
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/20267

Farmers who are able to take advantage of the benefits arising from the use of Agriculture 4.0 technologies will gain a competitive advantage through cost reduction, resource savings and increased productivity. Despite this situation, many farmers are reluctant or face obstacles to the adoption of digital technologies. It is in this context that the identification and analysis of acceptance factors and use of digital technologies by Brazilian rural producers assumes all its relevance and contemporaneity. Therefore, this thesis proposes an adaptation of the Unified Theory of Acceptance and Use of Technology (UTAUT), incorporating the effect of new variables arising from the phenomenon of digital agriculture, for the study of the acceptability of Agricultural Management Information Systems (Farm Management Information Systems (FMIS)) by Brazilian farmers. Thus, this thesis envisaged the creation and validation of an analytical model via a survey research, in which respondents were invited to participate in an online electronic format. The collected data were treated using descriptive and multivariate statistics. Structural equation modeling (SEM) using the partial least squares approach (PLS- SEM) with a global adequacy adjustment was used for model analysis. The results confirmed three of the ten proposed hypotheses. Effort expectancy and external pressure positively influence farmers' behavioral intention to use FMIS. On the other hand, perceived cost negatively influences farmers' intention to use FMIS. This study provides valuable contributions to studies of behavioral models and the role of different factors in FMIS acceptability. The findings could be useful to both farmers and other stakeholders, including extension agents, the government, contractors, agronomists and farm workers