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Tesi etd-07052021-134036


Tipo di tesi
Tesi di dottorato di ricerca
Autore
APICELLA, ANDREA
URN
etd-07052021-134036
Titolo
Precision agriculture in Italy, awareness rate and adoption by farmers. The future prospects of agriculture at the time of Covid19.
Settore scientifico disciplinare
SECS-P/13
Corso di studi
ECONOMIA AZIENDALE E MANAGEMENT
Relatori
tutor Prof.ssa Tarabella, Angela
Parole chiave
  • farm management
  • technologies
  • precision agriculture
  • willingness to invest
Data inizio appello
21/07/2021
Consultabilità
Non consultabile
Data di rilascio
21/07/2061
Riassunto
The agriculture of our century is facing rapidly changes of economic, social and environmental scenarios due to the evolution of the global context. There is the pressing need to improve the yield of agricultural crops to meet future food needs given by the expected increase of the world population, while on the other side, there is the need to frame the entire agricultural management system from an environmental sustainability perspective. To cope with such dichotomous needs, modern Precision Agriculture (PA) techniques can be the strategic instrument for agricultural activity in order to preserve the environment without neglecting the economic impact for companies. Therefore, technological innovation related to the sublimation of the Industry 4.0 paradigm within the agricultural context become necessary to meet the rising needs of companies which, growing in size and structure, build their growth strategy on implementation of technologies integrated in the agricultural production and transformation of agricultural products. The present research aimed to identify the spreading of knowledge and adoption of Precision Agriculture with the methodology of an online survey carried out on a sample of 755 Italian farmers. Farmers were required to respond to socio-demographic questions and to provide information about the composition of the farm, and their knowledge, possible adoption and opinion on Precision Agriculture. The sample was divided into different groups of farmers as follows: Informed Farmers, Uninformed farmers, Informed and Adopters Farmers, Informed and Non-Adopters Farmers, Farmers willing to invest in PA. In order to detect knowledge and adoption drivers for PA, regression analyses were performed on collected data. Overall, results showed that Italian farmers seemed to be not well-informed about the Precision Agriculture techniques. Results revealed that the age of the farmers, the size of the company, the gender and the turnover for the previous year are mostly the drivers of adoption. The present research can be considered a starting point for future research. Future interventions should develop formation programs about such techniques. This would help the detection of more accurate drivers of PA.
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