In this review, we identify the key drivers that affect the intention to adopt Precision Agriculture technologies. We collected research articles about the adoption of precision agriculture and we split them in two groups: (1) ex-post assessment that make use of utility-based models, and (2) ex-ante assessments that make use of predictive models, and especially the Technology Acceptance Model. We identified the main classes of constructs that were used to interpret what led the farmer to use technology. Dealing with both ex-ante and ex-post drivers, we offer an accurate representation of all the drivers that influence PA adoption. We depict three classes: financial, sociodemographic, and competitive-contingent factors. Furthermore, this review shows that the design of a proper adoption process needs to contemplate all the three classes of drivers and that farmers can be more easily attracted by disruptive innovation, rather than by sustaining innovation.

Drivers of Precision Agriculture technologies adoption: a literature review / Pierpaoli E.; Carli G.; Pignatti E.; Canavari M.. - In: PROCEDIA TECHNOLOGY. - ISSN 2212-0173. - ELETTRONICO. - 8:(2013), pp. 61-69. (Intervento presentato al convegno 6th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2013) tenutosi a Corfu Island, Greece nel September 19-22, 2013) [10.1016/j.protcy.2013.11.010].

Drivers of Precision Agriculture technologies adoption: a literature review

PIERPAOLI, EMANUELE;CARLI, GIACOMO;PIGNATTI, ERIKA;CANAVARI, MAURIZIO
2013

Abstract

In this review, we identify the key drivers that affect the intention to adopt Precision Agriculture technologies. We collected research articles about the adoption of precision agriculture and we split them in two groups: (1) ex-post assessment that make use of utility-based models, and (2) ex-ante assessments that make use of predictive models, and especially the Technology Acceptance Model. We identified the main classes of constructs that were used to interpret what led the farmer to use technology. Dealing with both ex-ante and ex-post drivers, we offer an accurate representation of all the drivers that influence PA adoption. We depict three classes: financial, sociodemographic, and competitive-contingent factors. Furthermore, this review shows that the design of a proper adoption process needs to contemplate all the three classes of drivers and that farmers can be more easily attracted by disruptive innovation, rather than by sustaining innovation.
2013
HAICTA 2013
61
69
Drivers of Precision Agriculture technologies adoption: a literature review / Pierpaoli E.; Carli G.; Pignatti E.; Canavari M.. - In: PROCEDIA TECHNOLOGY. - ISSN 2212-0173. - ELETTRONICO. - 8:(2013), pp. 61-69. (Intervento presentato al convegno 6th International Conference on Information and Communication Technologies in Agriculture, Food and Environment (HAICTA 2013) tenutosi a Corfu Island, Greece nel September 19-22, 2013) [10.1016/j.protcy.2013.11.010].
Pierpaoli E.; Carli G.; Pignatti E.; Canavari M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/214704
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