Drivers of farmers' adoption and continuation of climate-smart agricultural practices. A study from northeastern Italy

Pagliacci, Francesco; Defrancesco, Edi; Mozzato, Daniele; Bortolini, Lucia; Pezzuolo, Andrea; Pirotti, Francesco; Pisani, Elena; Gatto, Paola

doi:10.1016/j.scitotenv.2019.136345

Cited by 68 publications

(47 citation statements)

References 89 publications

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“…Although the strong correlation, adequately tested, prevents the logit model from identifying all variables as significant, the descriptive results showed important different characteristics between adopters and non-adopters. As already demonstrated in recent scientific literature, young farmers with a high level of education, well-oriented to gathering information on PFTs, and with large farm sizes, are more likely to adopt or to continue to embrace PFTs [107][108][109][110].…”

Section: Logit Regression Resultsmentioning

confidence: 99%

Adoption of Precision Farming Tools: The Case of Italian Farmers

Vecchio

Agnusdei

Miglietta

et al. 2020

IJERPH

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The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions. Preliminary results found high levels of adoption among younger farmers, those that had a high level of education, those with high intensity of information, with large farm sizes, and high labor intensity. A logit model was used to understand the role played by labor intensity and perceived in the adoption process. In light of the Common Agricultural Policy Reform post 2020, the findings suggest relevant policy implications, such as the need to increase awareness of PF tools and foster dissemination of information aimed at reducing the degree of perceived complexity.

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Section: Logit Regression Resultsmentioning

confidence: 99%

Adoption of Precision Farming Tools: The Case of Italian Farmers

Vecchio

Agnusdei

Miglietta

et al. 2020

IJERPH

View full text Add to dashboard Cite

show abstract

“…Research on farmers' adoption and sustainability of farmers' choice to adopt was influenced by factors that were related to farmers' characteristics, such as the activity of an extension institution and the farmers' managerial capacity (Adekambi et al, 2020;Bavorová et al, 2020;Kurnia, 2014;Wadsworth, 1995), individual behavior to choose technological use independently (Frank, 1995(Frank, , 1997, human behavior based on behavioral precursor (Alemayehu et al, 2020), the influence of socio-culture environment (Heffernan et al, 2008), technology (Pagliacci et al, 2020;Serah, 2013), attitude and motivation as well as the farmers' socio-economy characteristics (Deng et al, 2016;Luo et al, 2016;Page & Bellotti, 2015;Pagliacci et al, 2020;Sasongko, 2016;Trischler et al, 2020). These factors have been widely studied by considering the farmers' adoption.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Innovation Attributes in The Innovation Adoption of Agricultural Mechanization Technology in Farmers

Gandasari

2021

Jurnal KMP

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In the last 4-6 years, the government has provided an agricultural mechanization assistance through the Ministry of Agriculture to Gapoktan, Poktan or the Agricultural Equipment and Machinery Service Business (UPJA). Assistance is provided in order to support increased production and productivity of superior commodities. It is suspected that the use of alsintan has not been optimally utilized. In order to optimize the utilization of this government innovation, the optimization is carried out by analyzing the adoption and the use of alsintan and implementing the optimization of machinery. This study is limited to character analysis of the innovation that affects the speed of adoption of alsintan innovation in farmers in Bogor, Sukabumi and Cianjur districts. The unit of research analysis was individual alsintan user farmers. The samples were determined purposively. There were 158 selected respondents. The descriptive statistical analysis used was Microsoft Excel 2016. The results showed there were some influences of innovation attributes on the adoption of two-wheeled hand tractor and water pump innovations. Farmers can make use of innovation because it reduces production costs, makes work easier, and increases production. Besides, it is easy to use and easy to test; and the results are easy to see. Further research is needed to analyze the environment, organizations and individuals as the driving factors for innovation adoption.

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“…The integration of precision farming systems and digital technology has become the most prevalent trend in agricultural development, contributing to fewer inputs, higher yields, and less damage in agricultural production. Digitized agriculture has become a mainstream trend in numerous countries [ 7 , 8 , 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Farmers’ Knowledge, Attitude, and Adoption of Smart Agriculture Technology in Taiwan

Chuang

Wang

Liou

2020

IJERPH

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Climate change and food security are critical topics in sustainable agricultural development. The climate-smart agriculture initiative proposed by the Food and Agriculture Organization of the United Nations has attracted international attention. Smart agriculture (SA) has since been recognized as an influential trend contributing to agricultural development. Therefore, encouraging farmers to adopt digital technologies and mobile devices in farming practices has become a policy priority worldwide. However, the literature on the psychological factors driving farmers’ intentions to adopt SA technologies remains limited. This study investigated how farmers’ knowledge and attitudes regarding SA affect their adoption of smart technologies in Taiwan. A total of 321 farmers participated in a survey in 2017 and 2018, and the data were used to construct an ordinary least squares regression model of SA adoption. This study provides a preliminary understanding of the relationship between psychological factors and innovation adoption of SA technologies in a small-scale farming economic context. The findings suggest that policymakers and research and development institutes should concentrate on improving market access to established and critical SA technologies.

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Drivers of farmers' adoption and continuation of climate-smart agricultural practices. A study from northeastern Italy

Cited by 68 publications

References 89 publications

Adoption of Precision Farming Tools: The Case of Italian Farmers

Adoption of Precision Farming Tools: The Case of Italian Farmers

Analysis of Innovation Attributes in The Innovation Adoption of Agricultural Mechanization Technology in Farmers

Farmers’ Knowledge, Attitude, and Adoption of Smart Agriculture Technology in Taiwan

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