Colour Me In – an empirical study on consumer responses to the traffic light signposting system in nutrition labelling

Public Health Nutrition

Petra Wilczynski¹  Sophie Hieke¹ 

关键词: Nutrition labelling;    Traffic light signposting;    Conjoint analysis;   

DOI  :  10.1017/S1368980011002874

学科分类：卫生学

来源: Cambridge University Press

【 摘 要 】

ObjectiveAs a means of empowering consumers, nutrition labelling has become a widely discussed topic. Simplicity and uniformity of labelling systems are regarded as the prevailing demands from the consumer side. In the present study, we analyse the effects of the traffic light signposting scheme on consumers’ food choices.DesignIn an online survey, respondents first rated the understandability of the traffic light signposting scheme. In a following conjoint experiment, they indicated which products they would select as the healthiest of the presented products, based on the nutritive information provided by the traffic light signposting scheme.SettingA major German university.SubjectsIn total 2002 undergraduate students participated in the survey. Two-thirds (69 %) of the respondents were female and the majority of the respondents (70 %) were between 18 and 24 years old. Seventy-seven per cent of the participants indicated that they had a higher level of education.ResultsOverall, the participants rated the understandability of the traffic light nutrition signposting scheme fairly high (5·9 out of 7). Sugar and fat were found to be the most important attributes of the scheme. Participants placed greater emphases on a change in a product's nutrient characteristic from ‘amber to ‘red’ compared with a change from ‘green’ to ‘amber’.ConclusionsOur results confirm the signalling effect of colour coding as it helps reduce the complexity of decision making. Our findings shed new light on the ongoing discussion concerning appropriate and efficient nutrition labelling and provide interesting insights for further research as well as implications for public policy making.

【 授权许可】

Unknown