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Description of the research project:
- The idea of the Project and state of the art: Previous research has demonstrated the potential relevance of nutritional and health claims on consumer behavior. Additionally it is possible to find a direct and positive relationship between nutritional labels and quality diet of the consumers (Teisl et al., 2001; Kim et al., 2001 among others). This information is relevant specially to health benefits (Annunziata et al., 2016, Bernabeu y Diaz, 2016, Erraach et al., 2017, Gracia et al., 2009, Likoudis et al., 2016, Talati et al., 2016, van Rompay et al., 2016 (among others)). The olive oil sector will be study specially because is a good example to nutrititional and health aspects combined with others as geographical origin or environmental aspects.
- Objectives: a) The study of the different valorization opportunities to agrifood product (olive oil, vegetables and others) by health and nutritional aspects, b) The analysis of food quality aspects (intrinsic-extrinsic; experience-search and credence) evaluated by consumers (with hierarchical options), c) To define different food consumer models combined product characteristics with personal (socio-demographic and psychological aspects) profiles and d) To determine the food innovation consumer acceptance by different risk perception measures (neophobia scale, emotion scale, ethnocentrism scale, food health interest (basically)). Methodologies: The different methodologies combines declared and revealed consumer preferences as: Classical interview, Depth Interview (Means end Chain), commercial experiments and some of the actual neuromarketing options. Initially it could be relevant to collaborate with another research group expert on food sensorial analysis (from IsFood Research Institute in Public University of Navarra, or another research group of the Campus Iberus). In statistical terms the econometric models selected are basically: Factorial Confirmatory Analysis, Structural Equation Models, Multilevel Regression models and different options to cluster food consumers. The neuromarketing models and big data analysis will be employed with individual consumers or social networks massive information (Twitter basically).
- The research project is linkage with Nutriberus Project (Campus Iberus Consortium) entitled: Incorporation of the Health Claim for olive oil polyphenols, in relation to the Prevention of Cardiovascular Disease, on olive oils of the Ebro Valley. First concept testing for the creation of the brand Nutriberus. Additionally the objectives of the project are linkage with the Bioeconomy Spanish Strategy (Fecyt, 2017) and Agriculture and Food 2030 (European Commission, 2016) to analyse the future of diet and nutrition. At local level the objectives are aligned with the ISFOOD Research Institute objectives (Dr Mercedes Sánchez is member of this Institute).
On the other hand, the both supervisors (Dr Marian García- University of Kent-Reino Unido and Dr Mercedes Sánchez-Public University of Navarra-Spain) have a continuous research collaboration the last ten years with excellent results in terms of international publications in agricultural economic topic
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Supervisor short biography:
Associated Professor at Public University of Navarre (UPNA) (Agricultural Economics, Business Department). Degree in Business and Economics, Basque Country University (1989) and Ph. D. in Business by Public University of Navarre (1995). Research topics: Food Consumer Behavior, Food Quality Labels, Agri-food Marketing Decisions, Food Chain Innovation, Environmental Economic Valuation. Principal researcher in 12 projects (4 international) and project member in 10 projects (2 international).
More than 90 scientific papers, some recent international Journals in JCR Base: Agribusiness, Journal of Agricultural Economics, Food Quality and Preferences, Food Policy, European Review of Agricultural Economics, Land Use Policy, Technovation, Trends in Food Science and Technology. First quartile papers (WOS-JCR): 22. Five PhD students supervised in the last ten years. H- Index (WOS): 13, H-Index (Scopus): 17; H-Index Google Scholar: 28
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