IDEAS home Printed from https://ideas.repec.org/a/bla/canjag/v71y2023i2p203-230.html
   My bibliography  Save this article

Covid‐19‐tested food labels

Author

Listed:
  • Longzhong Shi
  • Xuan Chen
  • Bo Chen

Abstract

While the transmission of virus SARS‐CoV‐2 via food is rare, some Chinese food retailers are considering a Covid‐19‐tested food label. However, how consumers may support such a label is unknown. We quantify Chinese consumers’ willingness to pay (WTP) for food carrying a Covid‐19‐tested label using an online choice experiment. We find that the WTPs for such a label are always positive for all food products considered. The amount of WTP depends on the entities authenticating the labels, country of origin of the food, and consumers’ socio‐demographic status. Contrary to expectation, the knowledge on Covid‐19 does not affect consumer preferences for the Covid‐19‐tested food labels. Our benefit and cost analysis suggests a possible large benefit of creating and administering a Covid‐19‐tested food label. This study provides insights for policymakers, global food manufacturers, and retailers to create marketing strategies to alleviate consumer food safety concerns associated with Covid‐19. Alors que la transmission du virus SARS‐CoV‐2 via les aliments est rare, certains détaillants alimentaires chinois envisagent une étiquette alimentaire « Testée Covid‐19 ». Cependant, la façon dont les consommateurs peuvent soutenir une telle étiquette est inconnue. Nous quantifions la capacité à payer (CAP) des consommateurs chinois pour les aliments portant une étiquette « Testée Covid‐19 » à l'aide d'une expérience de choix réalisée en ligne. Nous constatons que les CAP pour un tel label sont toujours positifs pour tous les produits alimentaires considérés. Le montant du CAP dépend des entités authentifiant les étiquettes, du pays d'origine de l'aliment et du statut sociodémographique des consommateurs. Contrairement aux attentes, les connaissances sur le Covid‐19 n'affectent pas les préférences des consommateurs pour les étiquettes alimentaires « Testée Covid‐19 ». Notre analyse des avantages et des coûts suggère un potentiel avantage important pour la création et de l'administration d'une étiquette alimentaire « Testée Covid‐19 ». Cette étude fournit des informations aux décideurs politiques, aux fabricants mondiaux de produits alimentaires et aux détaillants pour créer des stratégies de marketing visant à atténuer les problèmes de sécurité alimentaire des consommateurs associés à la Covid‐19.

Suggested Citation

  • Longzhong Shi & Xuan Chen & Bo Chen, 2023. "Covid‐19‐tested food labels," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 71(2), pages 203-230, June.
    • Handle: RePEc:bla:canjag:v:71:y:2023:i:2:p:203-230
    DOI: 10.1111/cjag.12327
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/cjag.12327
    Download Restriction: no
    File URL: https://libkey.io/10.1111/cjag.12327?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jerrod M Penn & Wuyang Hu, 2018. "Understanding Hypothetical Bias: An Enhanced Meta-Analysis," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(4), pages 1186-1206.
    2. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    3. David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
    4. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    5. Eng, Teck-Yong & Ozdemir, Sena & Michelson, Grant, 2016. "Brand origin and country of production congruity: Evidence from the UK and China," Journal of Business Research, Elsevier, vol. 69(12), pages 5703-5711.
    6. Linhai Wu & Hongsha Wang & Dian Zhu & Wuyang Hu & Shuxian Wang, 2016. "Chinese consumers’ willingness to pay for pork traceability information—the case of Wuxi," Agricultural Economics, International Association of Agricultural Economists, vol. 47(1), pages 71-79, January.
    7. David Revelt & Kenneth Train, 1998. "Mixed Logit With Repeated Choices: Households' Choices Of Appliance Efficiency Level," The Review of Economics and Statistics, MIT Press, vol. 80(4), pages 647-657, November.
    8. Liu, Ruifeng & Gao, Zhifeng & Nayga, Rodolfo M. & Snell, Heather Arielle & Ma, Hengyun, 2019. "Consumers’ valuation for food traceability in China: Does trust matter?," Food Policy, Elsevier, vol. 88(C).
    9. Muhammad Zeeshan Zafar & Adnan Maqbool & Lucian-Ionel Cioca & Syed Ghulam Meran Shah & Shahjahan Masud, 2021. "Accentuating the Interrelation between Consumer Intention and Healthy Packaged Food Selection during COVID-19: A Case Study of Pakistan," IJERPH, MDPI, vol. 18(6), pages 1-14, March.
    10. Jayson L. Lusk & Ted C. Schroeder & Glynn T. Tonsor, 2014. "Editor's choice Distinguishing beliefs from preferences in food choice," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(4), pages 627-655.
    11. Xiang Wu & Bin Hu & Jie Xiong, 2020. "Understanding Heterogeneous Consumer Preferences in Chinese Milk Markets: A Latent Class Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(1), pages 184-198, February.
    12. Liu, Peng & Ma, Liang, 2016. "Food scandals, media exposure, and citizens’ safety concerns: A multilevel analysis across Chinese cities," Food Policy, Elsevier, vol. 63(C), pages 102-111.
    13. Xiang Wu & Bin Hu & Jie Xiong, 2020. "Understanding Heterogeneous Consumer Preferences in Chinese Milk Markets: A Latent Class Approach," Post-Print hal-02489646, HAL.
    14. Ekin Birol & Bhushana Karandikar & Devesh Roy & Maximo Torero, 2015. "Information, Certification and Demand for Food Safety: Evidence from an In-store Experiment in Mumbai," Journal of Agricultural Economics, Wiley Blackwell, vol. 66(2), pages 470-491, June.
    15. Annika Tienhaara & Heini Ahtiainen & Eija Pouta & Mikołaj Czajkowski, 2022. "Information Use and Its Effects on the Valuation of Agricultural Genetic Resources," Land Economics, University of Wisconsin Press, vol. 98(2), pages 337-354.
    16. Wongprawmas, Rungsaran & Canavari, Maurizio, 2017. "Consumers’ willingness-to-pay for food safety labels in an emerging market: The case of fresh produce in Thailand," Food Policy, Elsevier, vol. 69(C), pages 25-34.
    17. Jill J. McCluskey & Kristine M. Grimsrud & Hiromi Ouchi & Thomas I. Wahl, 2005. "Bovine spongiform encephalopathy in Japan: consumers' food safety perceptions and willingness to pay for tested beef," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 49(2), pages 197-209, June.
    18. Malone, Trey & Lusk, Jayson L., 2017. "Taste Trumps Health And Safety: Incorporating Consumer Perceptions Into A Discrete Choice Experiment For Meat," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 49(1), pages 139-157, February.
    19. Yang, Yang & Hobbs, Jill E. & Natcher, David C., 2020. "Assessing consumer willingness to pay for Arctic food products," Food Policy, Elsevier, vol. 92(C).
    20. Satoru Shimokawa & Dezhuang Hu & Dandan Li & Hong Cheng, 2021. "The urban–rural gap in the demand for food safety in China: The role of food label knowledge," Agricultural Economics, International Association of Agricultural Economists, vol. 52(2), pages 175-193, March.
    21. Soley, Graham & Hu, Wuyang & Vassalos, Michael, 2019. "Willingness to Pay for Shrimp with Homegrown by Heroes, Community-Supported Fishery, Best Aquaculture Practices, or Local Attributes," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 51(4), pages 606-621, November.
    22. Wu, Linhai & Wang, Shuxian & Zhu, Dian & Hu, Wuyang & Wang, Hongsha, 2015. "Chinese consumers’ preferences and willingness to pay for traceable food quality and safety attributes: The case of pork," China Economic Review, Elsevier, vol. 35(C), pages 121-136.
    23. Neill, Clinton L. & Williams, Ryan B., 2016. "Consumer Preference For Alternative Milk Packaging: The Case Of An Inferred Environmental Attribute," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 48(3), pages 241-256, August.
    24. Kelvin J. Lancaster, 1966. "A New Approach to Consumer Theory," Journal of Political Economy, University of Chicago Press, vol. 74(2), pages 132-132.
    25. Roe, Brian & Teisl, Mario F., 2007. "Genetically modified food labeling: The impacts of message and messenger on consumer perceptions of labels and products," Food Policy, Elsevier, vol. 32(1), pages 49-66, February.
    26. Tatiana Drugova & Kynda R. Curtis & Sherzod B. Akhundjanov, 2020. "Are multiple labels on food products beneficial or simply ignored?," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(4), pages 411-427, December.
    27. David F. Layton & Gardner Brown, 2000. "Heterogeneous Preferences Regarding Global Climate Change," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 616-624, November.
    28. Wuyang Hu & Shan Sun & Jerrod Penn & Ping Qing, 2022. "Dummy and effects coding variables in discrete choice analysis," American Journal of Agricultural Economics, John Wiley & Sons, vol. 104(5), pages 1770-1788, October.
    29. Andrew A. Goett & Kathleen Hudson & Kenneth E. Train, 2000. "Customers' Choice Among Retail Energy Suppliers: The Willingness-to-Pay for Service Attributes," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-28.
    30. Loomis, John B., 2014. "2013 WAEA Keynote Address: Strategies for Overcoming Hypothetical Bias in Stated Preference Surveys," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 39(1), pages 1-13, April.
    31. Junfei Bai & Caiping Zhang & Jing Jiang, 2013. "The role of certificate issuer on consumers’ willingness-to-pay for milk traceability in China," Agricultural Economics, International Association of Agricultural Economists, vol. 44(4-5), pages 537-544, July.
    32. Peterson, Hikaru H. & Bernard, John C. & Fox, John A. (Sean) & Peterson, Jeffrey M., 2013. "Japanese Consumers' Valuation of Rice and Pork from Domestic, U.S., and Other Origins," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), pages 1-14, April.
    33. John List & Craig Gallet, 2001. "What Experimental Protocol Influence Disparities Between Actual and Hypothetical Stated Values?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 20(3), pages 241-254, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shi, Longzhong & Chen, Xuan & Chen, Bo & Qiu, Jingran & Li, Li, 2021. "Assessing Consumers’ Willingness to Pay for Covid-19-tested Food Labels," 2021 ASAE 10th International Conference (Virtual), January 11-13, Beijing, China 329403, Asian Society of Agricultural Economists (ASAE).
    2. Chloe S McCallum & Simone Cerroni & Daniel Derbyshire & W George Hutchinson & Rodolfo M Nayga, 2022. "Consumers’ responses to food fraud risks: an economic experiment," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(4), pages 942-969.
    3. Lin Bai & Zhanguo Zhu & Tong Zhang, 2021. "How to Improve Food Quality in the Domestic Market: The Role of “Same Line Same Standard Same Quality”—Evidence from a Consumer Choice Experiment in China," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    4. Zhang, Tong & Hu, Wuyang & Zhu, Zhanguo & Penn, Jerrod, 2023. "Consumer preference for food products addressing multiple dimensions of poverty: Evidence from China," Food Policy, Elsevier, vol. 115(C).
    5. Liu, Ruifeng & ,, 2021. "What We Can Learn from the Interactions of Food Traceable Attributes? a Case Study of Fuji Apple in China," 2021 Conference, August 17-31, 2021, Virtual 315916, International Association of Agricultural Economists.
    6. West, Grant H. & Snell, Heather & Kovacs, Kent & Nayga, Rodolfo M., 2020. "Estimation of the preferences for the intertemporal services from groundwater," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304220, Agricultural and Applied Economics Association.
    7. Gillespie Rob & Kragt Marit E., 2012. "Accounting for Nonmarket Impacts in a Benefit-Cost Analysis of Underground Coal Mining in New South Wales, Australia," Journal of Benefit-Cost Analysis, De Gruyter, vol. 3(2), pages 1-29, May.
    8. Robert Gillespie & Jeff Bennett, 2011. "Willingness to pay for kerbside recycling the Brisbane Region," Environmental Economics Research Hub Research Reports 1097, Environmental Economics Research Hub, Crawford School of Public Policy, The Australian National University.
    9. Hoyos, David, 2010. "The state of the art of environmental valuation with discrete choice experiments," Ecological Economics, Elsevier, vol. 69(8), pages 1595-1603, June.
    10. Campbell, Danny & Hutchinson, W. George & Scarpa, Riccardo, 2006. "Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates," Sustainability Indicators and Environmental Valuation Working Papers 12224, Fondazione Eni Enrico Mattei (FEEM).
    11. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    12. Bliemer, Michiel C.J. & Rose, John M., 2013. "Confidence intervals of willingness-to-pay for random coefficient logit models," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 199-214.
    13. Gutsche, Gunnar & Ziegler, Andreas, 2019. "Which private investors are willing to pay for sustainable investments? Empirical evidence from stated choice experiments," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 193-214.
    14. Campbell, Danny, 2007. "Combining mixed logit models and random effects models to identify the determinants of willingness to pay for rural landscape improvements," 81st Annual Conference, April 2-4, 2007, Reading University, UK 7975, Agricultural Economics Society.
    15. Faustin, Vidogbèna & Adégbidi, Anselme A. & Garnett, Stephen T. & Koudandé, Delphin O. & Agbo, Valentin & Zander, Kerstin K., 2010. "Peace, health or fortune?: Preferences for chicken traits in rural Benin," Ecological Economics, Elsevier, vol. 69(9), pages 1848-1857, July.
    16. Mohammed H. Alemu & Søren B. Olsen, 2017. "Can a Repeated Opt-Out Reminder remove hypothetical bias in discrete choice experiments? An application to consumer valuation of novel food products," IFRO Working Paper 2017/05, University of Copenhagen, Department of Food and Resource Economics.
    17. Kipperberg, Gorm & Bond, Craig A. & Hoag, Dana L., 2008. "An Application of Mixed Logit Estimation in the Analysis of Producers’ Stated Preferences," Working Papers 108719, Colorado State University, Department of Agricultural and Resource Economics.
    18. Daan Hulshof & Machiel Mulder, 2020. "Willingness to Pay for $$\hbox {CO}_2$$CO2 Emission Reductions in Passenger Car Transport," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(4), pages 899-929, April.
    19. Lea Skræp Svenningsen, 2017. "Distributive outcomes matter: Measuring social preferences for climate policy," IFRO Working Paper 2017/11, University of Copenhagen, Department of Food and Resource Economics.
    20. Wu, Linhai & Wang, Shuxian & Zhu, Dian & Hu, Wuyang & Wang, Hongsha, 2015. "Chinese consumers’ preferences and willingness to pay for traceable food quality and safety attributes: The case of pork," China Economic Review, Elsevier, vol. 35(C), pages 121-136.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:canjag:v:71:y:2023:i:2:p:203-230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/caefmea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.