摘要：The paper analyses the impact that European Union (EU) farmers’ and rural population’s awareness of biotechnology innovations and access to/trust in information on these issues (amongst other a priori determinants) have on their perceptions of risks and benefits of the applications of biotechnology innovations, and attitudes towards their implementation in practice. We employ structural equation models (SEM) with observed and latent variables. SEM is a statistical technique for testing and estimating relationships amongst variables, using a combination of statistical data and qualitative causal assumptions. We use an Eurobarometer dataset (2010) about awareness/acceptance of biotechnology innovations and run SEM models for ten EU countries, which include older and newer Member States. The variables included are sociodemographics, access to biotechnology information, trust in information sources on biotechnology innovations, attitudes towards the importance and impact of science and technology on society, perceptions of the risks and benefits of the applications of biotechnology innovations and attitudes towards their implementation in practice. Results between the different EU countries are comparable and, alongside other determinants, trust in information sources will significantly impact perceptions of risks and benefits of the applications of biotechnology innovations, and attitudes towards their implementation in practice. This underlines the importance of information and knowledge to acceptance of biotechnology innovations, which should be a key point on policy-makers’ agenda of developing the economic and environmental efficiency in the agricultural sector and rural sustainability in Europe. Increasing awareness of biotechnology innovations that safeguard people and the environment in order to enable informed debate and decisions will help enhance sustainability of rural areas.
关键词：biotechnology innovations;farmers and rural population;European Union;information and knowledge;biotechnology attitudes;structural equation models
