Proposal of a Model of Irrigation Operations Management for Exploring the Factors That Can Affect the Adoption of Precision Agriculture in the Context of Agriculture 4.0
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Published:2024-01-16
Issue:1
Volume:14
Page:134
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ISSN:2077-0472
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Container-title:Agriculture
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language:en
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Short-container-title:Agriculture
Author:
Monteleone Sergio1, Alves de Moraes Edmilson1, Protil Roberto Max2ORCID, Faria Brenno Tondato de3ORCID, Maia Rodrigo Filev4ORCID
Affiliation:
1. School of Business Administration, Centro Universitário FEI, São Paulo 01525-000, SP, Brazil 2. Department of Agricultural Economics, Universidade Federal de Viçosa (UFV), Viçosa 36570-900, MG, Brazil 3. School of Electrical Engineering, Centro Universitário FEI, São Bernardo do Campo 09850-901, SP, Brazil 4. Centre of Regional and Rural Futures, Deakin University, Hanwood 2680, Australia
Abstract
Agriculture is undergoing a profound change related to Agriculture 4.0 development and Precision Agriculture adoption, which is occurring at a slower pace than expected despite the abundant literature on the factors explaining this adoption. This work explores the factors related to agricultural Operations Management, farmer behavior, and the farmer mental model, topics little explored in the literature, by applying the Theory of Planned Behavior. Considering the exploratory nature of this work, an exploratory multi-method is applied, consisting of expert interviews, case studies, and modeling. This study’s contributions are a list of factors that can affect this adoption, which complements previous studies, theoretical propositions on the relationships between these factors and this adoption, and a model of irrigation Operations Management built based on these factors and these propositions. This model provides a theoretical framework to study the identified factors, the relationships between them, the theoretical propositions, and the adoption of Precision Agriculture. Furthermore, the results of case studies allow us to explore the relationships between adoption, educational level, and training. The identified factors and the model contribute to broadening the understanding of Precision Agriculture adoption, adding Operations Management and the farmer mental model to previous studies. A future research agenda is formulated to direct future studies.
Funder
European Commission in Europe MCTIC/RNP in Brazil
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