Purpose The purpose of this paper is to explore a hybrid model of the consumption of organic foods, combining the use of exploratory factor analysis (EFA) and an artificial neural network (ANN). Design/methodology/approach The study has three phases. In the first phase, the Delphi method is employed, and 15 motives for the consumption of organic food are identified; these motives are used to develop the model in the second phase. Finally, in the last phase, an ANN is used to rank the motives to determine their priority. Findings The EFA model explored includes four factors that have a positive effect on the level of organic food consumption. These are naturalness, trust, sanitariness and marketing. Results from the use of an ANN indicate that the main variables in organic food consumption are claims, psychological variables and doubt. From the results of the EFA model it is clear these three variables are components of the factor of trust. Practical implications Marketers can use the model developed in this paper to satisfy the needs of their customers and hence enhance their market share and profitability. This study shows that improvements in truth in the claims made for organic products, perceived security from using these products and doubts about the safety of other foods can lead marketers to their goal. Informative advertisements can inculcate trust and naturalness among consumers as main factors. Originality/value The main contribution of this study is the light it sheds on how consumers think about organic foods. It develops a model incorporating motives for consuming organic food and determining the priorities held by consumers of organic foods.

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This study aims to extract, model, and rank reference groups on green consumer behavior to achieve environmentally sustainable development. This research was conducted in Iran in four stages. In the first stage, thematic factors were extracted through the research literature. These factors were expressed in 26 factors using expert opinions. A questionnaire containing 26 factors affecting the subject was

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Purpose This paper explores a triplex model of the political messages consumer behavior in social networks, combining the use of Delphi method, exploratory factor analysis (EFA), and an artificial neural network (ANN). Design/methodology/approach The study has 3 phases. In the first phase, the Delphi method is employed, and 24 motivations for the forwarding a political message with a social media are identified; these motivations are used to develop the model in the second phase. Finally, in the last phase, an ANN is used to rank the motivations to determine their priority. Findings The EFA model explored includes 5 factors that have a positive effect on the level of political messages forwarding with a social network. These are Public view, Performance of Party, Disclosure, Interests and Destruction. Results from the use of an ANN indicate that the main variables in political messages forwarding are showing the relative candidate commitment to ethics (Commitment to ethics) and showing the appropriate scientific level of the relative candidate (Appropriate scientific level). From the results of the EFA model, it is clear these 2 variables are components of the factor of the Public view. Practical implications Political marketer, politicians, and political analyst can use our findings and model to satisfy their political messages consumer' needs and enhance their vote market and electoral success. The public view in the political message gets a very important role in its forwarding. They should show in their political messages that the relative candidate has commitment to ethics and has appropriate scientific level. They must create more message with this studies priorities and avoid produce the low priority characteristics of message of this study. Originality/value For the first time, the main contribution of this study is to shed light on how political messages in social network is forwarded and how political messages consumers think about political messages in the social network?