Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks

Findings about consumer decision-making process regarding GM food purchase remain mixed and are inconclusive. This paper offers a model which classifies willingness to purchase GM food, using data from 399 surveys in Southern Spain. Willingness to purchase has been measured using three dichotomous questions and classification, based on attitudinal, cognitive and socio-demographic factors, has been made by an artificial neural network model. The results show 74% accuracy to forecast the willingness to purchase. The highest relative contributions lie in the variables related to beliefs, especially those link to perceived risks; while the variables with the least relative contribution are age and knowledge on GMO.


Issue Date:
2014-08
Publication Type:
Conference Paper/ Presentation
PURL Identifier:
http://purl.umn.edu/182940
Total Pages:
6




 Record created 2017-04-01, last modified 2017-08-27

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