Author
Listed:
- Peter Tait
- Caroline Saunders
- Paul Dalziel
- Paul Rutherford
- Timothy Driver
- Meike Guenther
Abstract
Price discounting strategies for suboptimal food perform an essential part in reducing food waste. This study provides new information empirically estimating discounts for levels of apple injury and deformity consistent with United States Department of Agriculture definitions using a Discrete Choice Experiment with Californian consumers. Latent Class Modelling identifies consumer segments with differing preferences for injury and deformity, alongside social responsibility and environmental claims. While discounts range substantially across segments, levels of deformity negatively influence choices more than equivalent levels of injury. Required discounts can be reduced by the presence of beneficial credence attributes, particularly an organic claim. We find a segment of respondents indifferent to suboptimal characteristics and requiring no discount to select suboptimal apples. These consumers have stronger preferences for environmental and social attributes, are more likely to be female, more educated, younger and concerned about genetic engineering. Preferences for social responsibility claims vary over the targeted beneficiaries, with programmes focused on workers preferred more overall. Willingness-to-pay for greenhouse gas reductions are relatively diminutive; however, 83% of the respondents support at least moderate reductions. This study contributes to understanding behaviours towards suboptimal food and is beneficial to forming food waste reduction strategies by identifying discount levels across consumer types.
Suggested Citation
Peter Tait & Caroline Saunders & Paul Dalziel & Paul Rutherford & Timothy Driver & Meike Guenther, 2024.
"How much less? Estimating price discounts for suboptimal food with environmental and social credence attributes,"
Applied Economics, Taylor & Francis Journals, vol. 56(13), pages 1581-1594, March.
Handle:
RePEc:taf:applec:v:56:y:2024:i:13:p:1581-1594
DOI: 10.1080/00036846.2023.2176460
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