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Meta-analysis of consumers' willingness to pay for sustainable food products
Open accessAbstract
There is a continuous increase in the number of studies dealing with consumers' willingness to pay (WTP) price premiums for sustainable food products. This research focused on a broad area of sustainable food products, including different sustainable attributes using a meta-analysis of 80 worldwide studies. The publication bias was verified using the funnel plot and Egger's test. In addition, the subgroup analysis and meta-regression were applied to classify the source of heterogeneity. The results suggest that the overall WTP premium for sustainability (in percentage terms) is 29.5% on average. Furthermore, gender, region, sustainable attributes and food categories influence the average WTP estimates and their heterogeneity. Results also indicate that the WTP estimate conducted by hypothetical approach (choice experiment and contingent valuation method) is higher than non-hypothetical one due to hypothetical bias. In addition, the WTP estimate from the CVM is higher than that from the CE. Additionally, the WTP value of organic attribute is higher than the other sustainable attributes. The subgroup analysis indicates that the fruit &vegetable category has the highest WTP estimate while the seafood receives the lowest one. Results also highlight that Asian WTP estimates, in percentage terms, are higher than those obtained in North America and similar to those from Europe. In addition, positive WTP estimates are shown independent of the food categories, region or methods, denoting the presence of great market potential for sustainable products worldwide. The findings of this research can be used as a guide by food producers, marketers and policymakers when making decisions related to the sustainability of food products.
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Metadata
- Authors
- Li, S., & Kallas, Z.
- Affiliations
- Institute of Agrifood Research and Technology (ES)
- Corresponding author
- Li, Shanshan
- Kallas, Zein
- Venue
- Appetite
- Publisher
- Elsevier BV
- Published
- 2021-08
- Volume
- 163
- Pages
- 105239
- ISSN
- 0195-6663 (ISSN-L)
- OpenAlex
- W3140641139
- Cited by
- 359
- References
- 118
- Citations by year
- 2026: 82 · 2025: 93 · 2024: 82 · 2023: 54 · 2022: 39 · 2021: 9
- FWCI
- 8.99
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Appetite (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by-nc-nd)
- AgEcon Search (University of Minnesota, USA) (submittedVersion, cc-by-nc-nd)
- AgEcon Search (University of Minnesota, USA)
- Topics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic and Environmental Valuation
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Organic Food and Agriculture
- Social Sciences › Business, Management and Accounting › Marketing › Environmental Sustainability in Business
- Keywords
- willingness to pay, sustainable food products, price premium, organic food, discrete choice experiment, contingent valuation, hypothetical bias, food categories, gender differences, regional variation, publication bias
- MeSH terms
- Consumer Behavior, Europe, Fruit, Humans
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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