Investigating heterogeneity in food risk perceptions using best-worst scaling

Abstract

The psychometric paradigm has dominated the field of empirical work analysing risk perceptions. In this paper, we use an alternative method, Best-Worst Scaling (BWS), to elicit relative risk perceptions concerning potentially unsafe domestic food behaviours. We analyse heterogeneity in those risk perceptions via estimation of latent class models. We identify 6 latent segments of differing risk perception profiles with the probability of membership of those segments differing between experts and the lay public. The BWS method provides a practical approach to assessing relative risks as the choices made by the participants and subsequent analysis have a strong theoretical basis. It does so without the influence of scale bias, the cognitive burden of ranking a large number of items or issues of aggregation of data, often associated with the more commonly used psychometric paradigm. We contend that BWS, in conjunction with latent class modelling, provides a powerful method for eliciting risk rankings and identifying differences in these rankings in the population.

Keywords:

• Risk perception
• domestic food safety
• Best-Worst Scaling
• expert-lay differences
• psychometric paradigm
• heterogeneity

Acknowledgements

The authors thank all those who participated in and circulated the study.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was undertaken as part of a studentship (ES/G030782/1) funded by the Economics Social Research Council, linked to the RELU project ‘Reducing E. coli O157 Risk in Rural Communities’ (RES-229-31-0003) funded under the UK Research Councils’ Rural Economy and Land Use Programme.