An assessment of the barriers to the consumers' uptake of genetically modified foods: a neural network analysis.

Journal: Journal of the science of food and agriculture
Published Date:

Abstract

BACKGROUND: This paper studies which of the attitudinal, cognitive and socio-economic factors determine the willingness to purchase genetically modified (GM) food, enabling the forecasting of consumers' behaviour in Andalusia, southern Spain. This classification has been made by a standard multilayer perceptron neural network trained with extreme learning machine. Later, an ordered logistic regression was applied to determine whether the neural network can outperform this traditional econometric approach.

Authors

  • Macario Rodríguez-Entrena
    Institute of Agricultural Research and Training (IFAPA), Department of Agricultural Economics and Rural Studies, Avda. Menéndez Pidal, 14080, - Córdoba, Spain.
  • Melania Salazar-Ordóñez
    Universidad Loyola Andalucía, Department of Economics, C/ Escritor Castilla Aguayo n° 4, 14004 -, Córdoba, Spain.
  • David Becerra-Alonso
    Universidad Loyola Andalucía, Department of Management and Quantitative Methods, C/Energía solar, 41014 -, Sevilla, Spain.