Country of origin or EU/non-EU labelling of beef? Comparing structural reliability and validity of discrete choice experiments for measurement of consumer preferences for origin and extrinsic quality cues

Lagerkvist Carl-Johan, Berthelsen Thomas, Kristian Sundström, Helena Johansson

Research output: Contribution to journalArticlepeer-review

34 Citations (SciVal)

Abstract

The use of food labels and packaging information on place of origin and credence quality has increased, but it is still unclear how such information relates to consumer decisions and choices concerning the relative valuation of attributes. Valid measurement methods are needed to assess the importance attributed by the public to such information, but also to inform the industry about market demand. Discrete choice experiments (CEs) are frequently used to assess consumer preferences for food attributes. However, suitable methods are needed to reveal the probabilistic nature of preference data, so that heterogeneity can be explicitly accounted for. An R-index measure was modelled to account for choice probabilities in this study. Two surveys of Swedish residents, without (n=506) and with (n=278) a price vector, compared attribute importance for origin and extrinsic quality labelling of beef in CEs. Problems of structural reliability owing to unstable associations in attribute importance between formats were supported, but on levels rather than orderings. The R-index analysis of CE data revealed violations of attribute transitivity and dominance. Extending CE analysis to include choice probabilities may be useful for consumer profiling and for optimisation of product information. Labels with specific country-of-origin information instead of a wider EU/non-EU designation were the most determining attribute in this study.
Original languageEnglish
Pages (from-to)50-61
JournalFood Quality and Preference
Volume34
DOIs
Publication statusPublished - 2014

Subject classification (UKÄ)

  • Economics and Business

Keywords

  • Beef
  • Food quality
  • Food labelling
  • Choice experiments
  • Hierarchical Bayesian estimation
  • R-index

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