FoodSMART · Shaping Smarter Consumer Behaviour and Food Choice
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2015-01-01 → 2018-12-31
- EU contribution
- €499,500
- Participants
- 6
- Scheme
- MSCA-RISE
Lines connect the coordinator with its partners.
Results in brief
Shaping Smarter Consumer Behaviour and Food Choice
Summary The aim of FoodSMART is to develop an innovative technical (ICT) menu solution that enables informed consumer choice that takes into account individual characteristics (such as culture, dietary requirements and age group) as well as product (specification). This aim will be achieved through the evaluation of consumer orientated intelligence (what information consumers require/trust i.e. information quality); the assessment of industry orientated intelligence (impact of customisation) and the subsequent development of data analytics and Quick Recognition (QR) coding for personalised food recommendation. Results will be gathered and modelled to provide strategic intelligence for menu design and better population health. The FoodSMART project will be achieved by pursuing the following specific objectives within three overlapping research and partnership programme areas of ICT development, foodservice operation and consumer behaviour: 01 Identification of key criteria required by consumers to enable informed choice when eating out (across key stages and countries). (D2) 02 Mapping of the relationship between criteria to provide personalised dish recommendation enabling the trigger for optimum practice. 03 Provision of predictive capacity to foodservice operators (e.g. data analytics).(D3) 04 Production of a flexible customisable and accessible interface (e.g. smartphone app and QR coding) for personalised food recommendation and facilitating the consumption of healthy and appropriate dishes. (D4) 05 Proof of concept. (D5) 06 Interpreting and evaluating consumer food choice through data mining and related measurement/analytical approaches across countries (Denmark, France, Greece, UK), key stages and public sector settings (universities and workplaces). (D6) 07 Synthesising and benchmarking the attributes of a successful human-app interface in preparation for commercialisation. (D7) 08 Providing a platform to promote, inform and educate the general public and industry competiveness within the European business climate. Developing methods for wider applicability and aiding design of potentially more effective measures to improve, enhance efficacy and cost effectiveness of healthy dish selection within the out-of-home market. (D8) Increasing the pace and scale of innovation within out-of-home eating is fundamental to this project.
Data: CORDIS, © European Union
Project objective
Compared to meals prepared at home, meals eaten out tend to contain more calories, total fat and saturated fat and it is here where the consumer has very little control or knowledge of the nutrient profile of the food they are eating (Bohm and Quartuccio, 2008). The positive association between the rise in consumption of food prepared outside the home and the increasing prevalence of obesity has been described as a major health and wellbeing societal challenge. Attempts to increase public awareness of appropriate ways to eat more healthily unfortunately do not seem to have led to significant changes in patterns of food purchase and consumption especially from an eating ‘out-of-home’ situation. It has become obvious that the development of effective measures for improvement requires further systematic research and a radical approach. The aim of FoodSMART is to develop an innovative technical (ICT) menu solution that enables informed consumer choice when eating out that takes into account individual characteristics (such as culture, dietary requirements and age group) as well as product (specification) and environmental cues (choice architecture and consumption setting). This aim will be achieved through the evaluation of consumer orientated intelligence (what information consumers require/trust i.e. information quality); the assessment of industry orientated intelligence (impact of customisation) and the subsequent development of data analytics and Quick Recognition (QR) coding for personalised food recommendation; thereby, facilitating the consumption of healthy and appropriate dishes. Results will be gathered and modelled to provide strategic intelligence for menu design and decision-making (by Industry) and for policy purposes (by the EU); further, this translational research will be disseminated both at scientific and consumer levels. Increasing the pace and scale of innovation within out-of-home eating is fundamental to this proposal.
Original text from CORDIS.
Participants
Links
- View on CORDIS
- DOI: 10.3030/643999
- https://arquivo.pt/wayback/20160525010112/http://www.foodsmartproject.net/
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5a62c0154&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5a67033dd&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5a99a37ef&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5afbcf315&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5b59bad02&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5bc7bd333&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5bc7bd695&appId=PPGMS
- https://www.ec.europa.eu/research/participants/documents/downloadPublic?documentIds=080166e5bfcd8280&appId=PPGMS
Data: CORDIS, © European Union
