Analysis of heterogeneity in the preferences of wine consumption

  1. María Carolina Rodríguez Donate 1
  2. Margarita Esther Romero Rodríguez 1
  3. Víctor Javier Cano Fernández 1
  4. Ginés Guirao Pérez 1
  1. 1 Universidad de La Laguna
    info

    Universidad de La Laguna

    San Cristobal de La Laguna, España

    ROR https://ror.org/01r9z8p25

Journal:
Wine Economics and Policy

ISSN: 2212-9774

Year of publication: 2019

Volume: 8

Issue: 1

Pages: 69-80

Type: Article

DOI: 10.1016/J.WEP.2019.02.006 DIALNET GOOGLE SCHOLAR

Abstract

The general decline in per capita consumption of wine worldwide over recent decades reveals the need to apply effective marketing strategiesto capture segments of the population, such as young people or women, who tend to consume wine sporadically and in small amounts, evenamong traditional wine-producing countries. However, until now these strategies have been designed considering these segments ashomogeneous groups, when in fact they are not. In this paper, several discrete choice models are used to incorporate the unobservedheterogeneity present in individuals’decisions, such as mixed or latent class models, with the aim of identify the socio-demographics profiles ofindividuals who consume a certain amount of wine per week. The results highlights the superiority of these models and the variability individuals'characteristics due to heterogeneity.

Bibliographic References

  • Aitchison, J., Silvey, S., The generalization of probit analysis to the case of multiple responses. Biometrika 44 (1957), 131–140.
  • Albisu, L.M., Zeballos, G., 2014. Consumo de vino en España. Tendencias y comportamiento del consumidor, en La economía del vino en España y en el mundo, Cajamar Caja Rural (Ed.), Capítulo 3, 99-14.
  • Algers, S., Bergstrom, P., Dahlberg, M., Dillén, J.L., 1998. Mixed logit estimation of the value of travel time. Scandinavian Working Papers in Economics, 15.
  • Andrews, R., Ainslie, A., Currim, I., An empirical comparison of logit choice models with discrete vs. continuous representations of heterogeneity. J. Mark. Res. 39:4 (2002), 479–487.
  • Atkin, T., Thach, L., Millennial wine consumers: risk perception and information research. Wine Econ. Policy 1 (2012), 54–62.
  • Ben-Akiva, M.E., Bolduc, D., 1996. Multinomial probit with a logit kernel and a general parametric specification of the covariance structure. Department of Civil Engineerign, MIT, Working Paper.
  • Ben-Akiva, M.E., Swait, J.D., The Akaike likelihood ratio index. Transp. Sci. 20 (1986), 133–136.
  • Bhat, C.R., An analysis of travel mode and departure time choice for urban shopping trips. Transp. Res. Part B 32 (1998), 361–371.
  • Bhat, C.R., Incorporating observed and unobserved heterogeneity in urban work travel mode choice modeling. Transp. Sci. 34:2 (2000), 228–238.
  • Bhat, C.R., Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences. Transp. Res. Part B 37:9 (2003), 837–855.
  • Bruwer, J., Saliba, A., Miller, B., Consumer behaviour and sensory preference differences: implications for wine product marketing. J. Consum. Mark. 28 (2011), 5–18.
  • Cameron, A.C., Trivedi, P.K., Microeconometrics: Methods and Applications. 2005, Cambridge University Press.
  • De Magistris, T., Groot, E., Gracia, A., Albisu, L.M., Do millennial generation׳s wine preferences of the “New World” differ from the “Old World”?. Int. J. Wine Bus. Res. 23:2 (2011), 145–160.
  • Escobar, C., Kallas, Z., Gil, J.M., Consumers´ wine preferences in a changing scenario. Br. Food J. 120:1 (2017), 18–32, 10.1108/BFJ-02-2017-0070.
  • Gázquez, J.C., Sánchez, M., La heterogeneidad del consumidor en los modelos de elección: evidencias empíricas utilizando modelos logit. Rev. Eur. De. Dir. Y. Econ. De. La. Empresa 16:4 (2007), 163–186.
  • Glasgow, G., Mixed logit models for multiparty elections. Political Anal. 9:2 (2001), 116–136.
  • Greene, W.H., Hensher, D., Modeling ordered Choices. 2010, Cambridge University Press, Cambridge, UK.
  • Halton, J., On the efficiency of evaluating certain quasi-random sequences of points in evaluating multi-dimensional integrals. Numer. Math. 2 (1960), 84–90.
  • Hensher, D., Greene, W.H., The mixed logit model: the state of practice. Transportation 30:2 (2003), 133–176.
  • Hynes, S., Hanley, N., Scarpa, R., Effects on welfare measures of alternative means of accounting for preference heterogeneity in recreational demand models. Am. J. Agric. Econ. 90:4 (2008), 1011–1027.
  • Jarvis, W., Mueller, S., Chiong, K., A latent analysis of images and words in wine choice. Australas. Mark. J. 18 (2010), 138–144.
  • Kallas, Z., Escobar, C., Gil, J.M., Assessing the impact of a Christmas advertisement campaign on Catalan wine preference using Choice Experiments. Appetite 58 (2012), 285–298.
  • Kallas, Z., Escobar, C., Gil, J.M., Analysis of consumers׳ preferences for a special-occasion red wine: a dual response choice experiment approach. Food Qual. Prefer. 30 (2013), 156–168.
  • Kamakura, W., Russell, G., A probabilistic choice model for market segmentation and elasticity structure. J. Mark. Res. 26 (1989), 379–390.
  • Lai, M.B., Del Giudice, T., Pomarici, E., 2008. Unobserved heterogeneity in the wine market: an analysis of sardinian wine using mixed logit. American Association of Wine Economists, Working Paper, 28.
  • Lockshin, L., Mueller, S., Louviere, J., Francis, L., Osidacz, P., Development of a new method to measure how consumers choose wine. Aust. N. Z. Wine Ind. J. 24:2 (2009), 35–40.
  • Macías, A., El paisaje vitícola de Canarias. Cinco siglos de historia. Ería 68 (2005), 351–364.
  • Marinelli, N., Fabbrizzi, S., Sottini, V.A., Sacchelli, S., Bernetti, I., Menghini, S., Generation Y, wine and alcohol. A semantic differential approach to consumption analysis in Tuscany. Appetite 75 (2014), 117–127.
  • Martínez-Carrión, J.M., Medina-Albadalejo, F.J., Change and development in the Spanish Wine Sector, 1950–2009. J. Wine Res. 21:1 (2010), 77–95, 10.1080/09571264.2010.495856.
  • Mccullagh, P., Regression models for ordinal data. J. R. Stat. Soc., Ser. B (Methodol.) 42 (1980), 109–142.
  • McFadden, D., Train, K., Mixed mnl models of discrete response. J. Appl. Econ. 15 (2000), 447–470.
  • Mckelvey, R.D., Zavoina, W., A statistical model for the analysis of ordinal level dependent variables. J. Math. Sociol. 4 (1975), 103–120.
  • MERCASA, 2014. Ministerio de Agricultura, Alimentación y Medio Ambiente. Alimentación en España 2014. Producción, Industria, Distribución, Consumo.
  • Molina, A., Gómez, M., González-Díaz, B., Esteban, A., Market segmentation in wine tourism: strategies for wineries and destinations in Spain. J. Wine Res. 26:3 (2015), 192–224.
  • Mora, M., Urdaneta, E., Chaya, C., Emotional response to wine: sensory properties, age and gender as drivers of consumers´ preferences. Food Qual. Prefer. 66 (2018), 19–28.
  • Mueller, S., Sxolnoki, G., The relative influence of packaging, labelling, branding and sensory attributes on liking and purchase intent: consumers differ in their responsiveness. Food Qual. Prefer. 21 (2010), 774–783.
  • Mueller, S., Lockshin, L., Saltman, Y., Blanford, J., Message on a bottle: the relative influence of wine back label information on wine choice”. Food Qual. Prefer. 21 (2010), 22–32.
  • Munizaga, M.A., Álvarez, R., 2002. Evaluation of mixed logit as a practical modelling alternative. In: Proceedings European Transport Conference, Cambridge, UK.
  • Pomarici, E., Vecchio, R., Millennial generation attitudes to sustainable wine: an exploratory study on Italian consumers. J. Clean. Prod. 66 (2014), 537–545.
  • Rémaud, H., Mueller, S., Chvyl, P., Lockshin, L., 2008. Do Australian wine consumers value organic wine? In: Proceedings of 4th International Conference of the Academy of Wine Business Research, Siena, 17–19, July 2008.
  • Revelt, D., Three Discrete Choice Random Coefficients Papers and One Police Crime Study (PhD. Thesis). 1999, University of California, Berkeley.
  • Revelt, D., Train, K., Mixed logit with repeated choices: households´choices of appliance efficiency level. Rev. Econ. Stat. 80 (1998), 647–657.
  • Revelt, D., Train, K., 2000. Customer-specific taste parameters and mixed logit. University of California, Department of Economics, Working Paper.
  • Rodríguez-Donate, M.C., Romero-Rodríguez, M.E., Cano-Fernández, V.J., Guirao-Pérez, G., Sociodemographic determinants of the probability of wine consumption in Tenerife (Canary Islands). Int. J. Wine Bus. Res. 29:3 (2017), 316–334, 10.1108/IJWBR-06-2016-0017.
  • Scarpa, R., Thiene, M., Galletto, L., 2006. Consumers WTP for wine with certified origin: latent classes based on attitudinal responses. In: Proceedings of 10th Joint conference on food, agriculture and the environment, Duluth, Minnesota, Ausust, 27–30, 2006.
  • Scherrer, P., Alonso, A., Sheridan, L., Expanding the destination image: wine tourism in the Canary Islands. Int. J. Tour. Res. 11 (2009), 451–463.
  • Seller-Rubio, R., Nicolau-Gonzalbez, J.L., Estimating the willingness to pay for a sustainable wine using a Heckit model. Wine Econ. Policy 5 (2016), 96–104.
  • Snell, E.J., A scaling procedure for ordered categorical data. Biometrics 20 (1964), 592–607.
  • Stasi, A., Bimbo, F., Viscecchia, R., Seccia, A., Italian consumers´ preferences regarding dealcoholized wine, information and price. Wine Econ. Policy 3 (2014), 54–61.
  • Train, K., 2001. A comparison of hierarchical Bayes and maximum simulated likelihood for mixed logit. University of California, Department of Economics, Working Paper.
  • Train, K., Discrete Choice Methods with Simulation. 2003, Cambridge University Press, Cambridge, UK.
  • Vecchio, R., Decordi, G., Grésillon, L., Gugenberber, C., Mahéo, M., Jourjon, F., European consumers׳ perception of moderate wine consumption on health. Wine Econ. Policy 6 (2017), 14–22.
  • Vermunt, J.K., Magidson, J., Technical Guide for Latent GOLD 4.0: Basic and Advanced. 2005, Statistical Innovations Inc, Belmont, Massachusetts.
  • Wedel, M., Kamakura, W., Market Segmentation: Conceptual and Methodological Foundations, 2nd ed., 2000, Kluwer Academic Publishers, Boston, MA.