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Consumers' Preferences and Willingness to Pay for Personalised Nutrition

Author

Listed:
  • Daniel Pérez-Troncoso

    (University of Granada)

  • David M. Epstein

    (University of Granada)

  • José A. Castañeda-García

    (University of Granada)

Abstract

Introduction Personalised nutrition (PN) has great potential for disease prevention, particularly if coupled with the power and accessibility of mobile technology. However, success of PN interventions will depend on the willingness of users to subscribe. This study investigates the factors associated with potential users' perceived value of PN and heterogeneity in these values. Methods A discrete choice experiment was carried out in a representative sample (N = 429 valid responses) from the adult population in Spain. The results were analysed in line with McFadden's Random Utility Theory, using conditional and mixed logit models in addition to a latent class logit model. Results The conditional and mixed logit models revealed the existence of a significant preference and willingness to pay for personalised nutrition, but the effect on average was not large for the highest level of personalisation. The latent class logit revealed four classes of respondent: those who would be likely to pay for a high level of personalised nutrition service, those who would use it if it were heavily subsidised, those who would use only a basic nutrition service, and those who would not be willing to engage. These results could be useful for the design and targeting of effective personalised nutrition services. Conclusions Over half of adults currently perceive some individual benefit in a high level of PN, which may justify some degree of public subsidy in investment and delivery of such a service.

Suggested Citation

  • Daniel Pérez-Troncoso & David M. Epstein & José A. Castañeda-García, 2021. "Consumers' Preferences and Willingness to Pay for Personalised Nutrition," Applied Health Economics and Health Policy, Springer, vol. 19(5), pages 757-767, September.
    • Handle: RePEc:spr:aphecp:v:19:y:2021:i:5:d:10.1007_s40258-021-00647-3
    DOI: 10.1007/s40258-021-00647-3
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    References listed on IDEAS

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    1. Pérez-Troncoso, Daniel, 2022. "Optimal sequential strategy to improve the precision of the estimators in a discrete choice experiment: A simulation study," Journal of choice modelling, Elsevier, vol. 43(C).

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