Vol. 10 No. 2 (2021)
Original Research Article

Consumer preferences for certified wines in France: A comparison of sustainable labels

Adeline Alonso Ugaglia
Bordeaux Sciences Agro, French National Institute for Agriculture, Food and Environment, Umr Save ISVV, Gradignan
Britta Niklas
Ruhr-Universität Bochum, Institute of Development Research and Development Policy, Bochum
Wolfram Rinke
Fachhochschule Burgenland GmbH, Eisenstadt
Dan Moscovici
School of Natural Sciences & Mathematics, Stockton University
Jeff Gow
University of Southern Queensland, Toowoomba, Australia
Lionel Valenzuela
Universidad Técnica Federico, Santa Maria
Radu Mihailescu
Stenden Hotel Management School, Leeuwarden

Published 2021-07-14

Keywords

  • Consumer preferences,
  • stated preferences,
  • wine,
  • certified wines

How to Cite

Alonso Ugaglia, A., Niklas, B., Rinke, W., Moscovici, D., Gow, J., Valenzuela, L., & Mihailescu, R. (2021). Consumer preferences for certified wines in France: A comparison of sustainable labels. Wine Economics and Policy, 10(2), 75–86. https://doi.org/10.36253/wep-10382

Abstract

The wine industry has faced various environmental and social challenges. On the demand side, consumer demand for sustainable wines has been increasing but, to date, it is unknown whether consumers perceive wine companies’ efforts to obtain sustainable development (SD) certifications and labels as being valuable or how they differentiate them. On the supply side, sustainable wine production is increasing but producers report a lack of information to engage and select their SD strategy. This article uses a logistic regression and an artificial neural network model to show how French consumers differentiate and value different SD labels (Organic, Biodynamic, Sustainable, Fairtrade, Natural). Results show that consumers’ willingness to buy and willingness to pay are influenced by the importance each consumer gives to the certification. For all other drivers, consumers differentiate between labels, highlighting the importance of comparison between and knowledge about each of them, thereby aiding producers in choosing an appropriate marketing strategy.

References

Alonso Ugaglia, A., Cardebat, J.M., Dupuy, L., Sloop, S. (2017). Sustainability certifications in the wine industry: what are the drivers for adoption? INFER conference, Wine sustainability 1-2 September, Pescara, Italy.
Ashton, R.H. (2014). Wine as an experience good: price versus enjoyment in blind tastings of expensive and inexpensive wines, Journal of wine economics, 9(2), 171-182.
Baker, R., Ruting, B. (2014). Environmental Policy Analysis: A Guide to Non-Market Valuation, Productivity, Commission Staff Working Paper, Canberra.
Bazoche, P., Deola, C., Soler, L.G. (2008). An experimental study of wine consumers’ willingness to pay for environmental characteristics, European Association of Agricultural Economists (EAAE) 2008 International Congress, August 26-29, 2008, Ghent, Belgium, DOI: 10.22004/ag.econ.4365.
Carson, R.T., Louviere, J.J. (2011). A Common Nomenclature for Stated Preference Approaches, Environmental and Resource Economics, 49(4): 539 – 59.
Christ, K., Burritt, R. (2013). Critical environmental concerns in wine production: an integrative review, Journal of Cleaner Production, 53, 232-242.
Di Vita, G., Pappalardo, G., Chinnici, G., La Via, G., D’Amico, M. (2019). Not everything has been still explored: Further thoughts on additional price for organic wine. Journal of Cleaner Production, 231, 520-528.
IWSR (2019). Organic Wine report, 2019.
Forbes, S.L., Cohen, D.A., Cullen, R., Wratten, S.D., Fountain, J. (2009). Consumer attitudes regarding environmentally sustainable wine: an exploratory study of the New Zealand marketplace, Journal of Cleaner Production 17, 1195-1199.
Freeman I.I.I., A.M., Herriges, J.A., Kling, C.L. (2014). The Measurement of Environmental and Resource Values: Theory and Methods, RFF Press: Routledge.
Gabrielyan, G., Marsh, T.L., McCluskey, J.J., Ross, C.F. (2018). Hoppiness is Happiness? Under-fertilized Hop Treatments and Consumers’ Willingness to Pay for Beer, Journal of Wine Economics, 13(2), 160-181.
Galati, A.G., Schifani, M. Crescimanno, G., Migliore, G. (2019). “Natural Wine” consumers and interest in label information: An Analysis of Willingness to Pay in a New Italian Wine Market Segment, Journal of Cleaner Production, 227(1), 405-413.
Hanemann, W.M., (1984). Welfare evaluations in contingent valuation experiments with discrete responses, American Journal of Agricultural Economics, 66: 332-341.
Hornik, K., Stichcombe, M., White, H. (1990). Universal approximation of an unknown mapping and its derivatives using multilayer feedforward networks, Neural Networks, 3, 551-560.
Horowitz, J.L., Savin, N.E. (2001). Binary Response Models: Logits, Probits and Semiparametrics, Journal of Economic Perspectives, 15(4), 43-56.
Kealy, M.J., Turner, R.W. (1993). A test of the equality of closed-ended and open-ended contingent valuations, American Journal of Agricultural Economics, 75, 321-331.
Lee, D., Derrible, S., Pereira, F.C. (2018). Comparison of Four Types of Artificial Neural Network and a Multinomial Logit Model for Travel Mode Choice Modeling, Transportation Research Record, 2672(49), 101–112. doi: 10.1177/0361198118796971.
Louviere, J.J., Hensher, D.A., Swait, J.D. (2000). Stated Choice Methods. Analysis and Application, Cambridge: Cambridge University Press.
Manderson, A.K. (2006). A systems-based framework to examine the multi- contextual application of the sustainability concept, Environment, Development and Sustainability, 8 (1), 85-97.
Mihailescu, R., Hecht, K. (2015). Is there a scope for Organic wine tourism development? A focus on South African wine industry, Revista Di Scienze Del Turismo, 6(1-2), 1-11.
Mitchell, R.C., Carson, R.T. (1989). Using Surveys to Value Public Goods: The Contingent Valuation Method, Washington, D.C.: Resources for the Future.
Mogas, J., Riera, P., Bennett, J. (2002). A Comparison of Contingent Valuation and Choice Modelling: estimating the environmental values of Catalonian Forests. Occasional Paper No. 1, National Centre for Development Studies, Australian National University, Canberra, Australia.
Moscovici, D., Mihailescu R., Valenzuela, L., Alonso Ugaglia, A., Gow, J. (2018). Can Consumers Distinguish between Environmental Wine Certifications? Choosing between Biodynamic, Fair Trade, Natural, Organic and Sustainable, 12th Annual AAWE Conference, 10-14 June, Ithaca, NY, USA.
Moscovici, D., Reed, A. (2018). Comparing Wine Sustainability Certifications around the World: History, Status, and Opportunity, Journal of Wine Research, 29(1), 1-25.
Niklas, B., Storchmann, K., Vink, N. (2017). Fairtrade Wine Price Dispersion in the United Kingdom, Journal of Wine Economics, 12(4), 446-456.
Niklas, B., Rinke, W. (2020). Pricing Models for German Wine: Hedonic Regression vs. Machine Learning, Journal of Wine Economics, 15(3), 284-311. doi:10.1017/jwe.2020.16
OIV, 2017. Prospective filière française des vins biologiques, Les Etudes FranceAgriMer, FranceAgriMer Vin, April 2017, 199p.
Owen, G.W. (2012). Applying point elasticity of demand principles to optimal pricing in management accounting, International Journal of Applied Economics and Finance, 6, 89–99.
Paloviita, A. (2010). Consumers' Sustainability Perceptions of the Supply Chain of Locally Produced Food, Sustainability, 2, 1492-1509.
Poelmans, E., Rousseau, S. (2017). Beer and Organic Labels: Do Belgian Consumers Care?, Sustainability, 9(9), 1509-1523.
Pullman, M., Maloni, M., Carter, C. (2009). Food for thought: Social versus environmental sustainability practices and performance outcomes, Journal of Supply Chain Management, 45 (4), 38-54.
Remaud, H., Mueller, S., Chvyl, P., Lockshin, L. (2008). Do Australian Wine Consumers Value Organic Wine?, International Conference of the Academy of Wine Business Research. Refereed paper, Siena, Italy.
Rinke, W. (2015). Calculating the dependency of components of observable nonlinear systems using artificial neural networks, MakeLearn & TIIM conference proceedings, 367-374. Available from: https://EconPapers.repec.org/RePEc:tkp:mklp15:367-374.
Rumelhart, D.E., Hinton, G.E., Williams, R.J. (1986). Learning representations by backpropagating errors, Nature, 323, 533-536.
Sellers-Rubio, R., Nicolau-Gonzalbez, J.L. (2016). Estimating the willingness to pay for a sustainable wine using a Heckit model, Wine Economics and Policy, 5(2), 96-104.
Shavlik, J.W., Diettrich, T.G. (eds.) (1990). Reading in Machine Learning, San Mateo, CA: Morgan Kaufmann.
Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., Leyton-Brown, K., Parkes, D., Press, W., Saxenian, A., Shah, J., Tambe, M., Teller, A. (2016). Artificial intelligence and life in 2030. One hundred years study on artificial intelligence: Report of the 2015-2016, Study Panel, 8. Available from:
https://ai100.stanford.edu/sites/default/files/ai100report10032016fnl_singles.pdf.
Szolnoki, G. (2013). A cross-national comparison of sustainability in the wine industry, Journal of Cleaner Production, 53, 243-251.
Tozer, P.R., Galinato, S.P., Ross, C.F., Miles, C.A., McCluskey, J.J. (2015). Sensory Analysis and Willingness to Pay for Craft Cider, Journal of Wine Economics, 10(3), 314-328.
Tran V.H., Takumi A., Mikiharu A. (2019). Determination of the influence factors on household vehicle ownershippatterns in Phnom Penh using statistical and machine learning methods, Journal of Transport Geography, 78(2019), 70-86.
https://doi.org/10.1016/j.jtrangeo.2019.05.015
Trienekens, J.H., Wognum, P.M., Beulens, A.J.M., Van der Vorst, J.G.A.J. (2012). Transparency in complex dynamic food supply chains, Advanced Engineering Informatics, 26, 55-65.
Valenzuela, L., Moscovici, D., Mihailescu R., Alonso Ugaglia, A., Gow, J., Rinaldi, A. (2019). Wine consumers market sustainability: an international study, 13th Annual AAWE Conference, 14-18 July, Vienna, Austria.
Varian, H.R. (2010). Intermediate Microeconomics. A Modern Approach , 78th Edition. New York, USA, W.W. Norton & Company, 73-89.
Vecchio, R. (2013). Determinants of Willingness-to-Pay for Sustainable Wine: Evidence from Experimental Auctions, Wine Economics and Policy, 2(2), 85-92.
Witten, I., Eibe F., Hall, M. (2017). Data mining – practical machine learning tools and techniques, 4th Edition. New York, USA, Morgan Kaufmann, 261-269.
Yeh, I.C., Cheng, W.L. (2010). First and second order sensitivity analysis of ML, Neurocomputing, 73, 2225–2233.