4.7 Article

Assessing Consumer Willingness to Pay for Nutritional Information Using a Dietary App

期刊

NUTRIENTS
卷 14, 期 23, 页码 -

出版社

MDPI
DOI: 10.3390/nu14235023

关键词

choice experiment; food information; nutrition label; mixed multinomial logit; latent class

资金

  1. University of Sari Agricultural Sciences and Natural Resources
  2. Ministry of Science, Research and Technology of Iran
  3. UNIVPM-D3A

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Promoting healthy nutrition is crucial for a healthy society. Providing nutritional information plays a significant role in consumers' preferences.
A healthy society is the foundation of development in every country, and one way to achieve a healthy society is to promote healthy nutrition. An unbalanced diet is one of the leading causes of noncommunicable diseases globally. If food was correctly selected and correctly consumed, both the problems of overeating and lack of nutrition could be largely solved while also decreasing public health costs. Interventions such as presenting necessary information and warning labels would help consumers make better food choices. Hence, providing nutritional information to consumers becomes essential. The present study investigates the importance of nutrition information labels on consumers' preferences by estimating their willingness to pay for features and information provided by a dietary software program (app). An application can easily display the information to the consumers and help them make informed food choices. A discrete choice experiment investigated consumers' preferences and willingness to pay to receive nutritional information. Mixed multinomial logit and latent class analysis were applied. The results showed the existence of heterogeneity in consumer preferences for different nutritional information provided by the application. Consumers are willing to pay more for salt and fat alerts. The results of this study allow for the analysis of consumers' interest in nutritional information. Such results are essential for the industry for future investments in similar applications that potentially could help consumers make better informed choices.

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