Awareness and Attitudes towards Biotechnology Innovations among Farmers and Rural Population in the European Union

LUIZA TOMA1, LÍVIA MARIA COSTA MADUREIRA2, CLARE HALL1, ANDREW BARNES1, ALAN RENWICK1

Paper prepared for presentation at the 131st EAAE Seminar ‘Innovation for Agricultural Competitiveness and Sustainability of Rural Areas’, Prague, Czech Republic, September 18-19, 2012

*SEM may consist of two components, namely the measurement model (which states the relationships between the latent variables and their constituent indicators), and the structural model (which designates the causal relationships between the latent variables). The measurement model resembles factor analysis, where latent variables represent ‘shared’ variance, or the degree to which indicators ‘move’ together. The structural model is similar to a system of simultaneous regressions, with the difference that in SEM some variables can be dependent in some equations and independent in others.*

A Structural Equation Model of Farmers Operating within Nitrate Vulnerable Zones (NVZ) in Scotland

Toma, L.1, Barnes, A.1, Willock, J.2, Hall, C.1

12th Congress of the European Association of Agricultural Economists – EAAE 2008

To identify the factors determining farmers’ nitrate reducing behaviour, we follow the attitude-behaviour framework as used in most literature on agri- environmental issues. To statistically test the relationships within this framework, we use structural equation modelling (SEM) with latent (unobserved) variables. We first identify the latent variables structuring the model and their constituent indicators. Then, we validate the construction of the latent variables by means of factor analysis and finally, we build and test the structural equation model by assigning the relevant relationships between the different latent variables.

To identify the factors determining farmers’ nitrate reducing behaviour, we follow the attitude-behaviour framework as used in most literature on agri- environmental issues. To statistically test the relationships within this framework, we use structural equation modelling (SEM) with latent (unobserved) variables. We first identify the latent variables structuring the model and their constituent indicators. Then, we validate the construction of the latent variables by means of factor analysis and finally, we build and test the structural equation model by assigning the relevant relationships between the different latent variables.

See also:

PLoS One. 2014; 9(1): e86174.

Published online Jan 29, 2014. doi: 10.1371/journal.pone.0086174

PMCID: PMC3906022

**Determinants of Public Attitudes to Genetically Modified Salmon**

Latifah Amin,1,* Md. Abul Kalam Azad,1,2 Mohd Hanafy Gausmian,3 and Faizah Zulkifli1

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