Research Article Open Access

Drinking Wine at Home: Hedonic Analysis of Sicilian Wines Using Quantile Regression

Giuseppe Di Vita1, Francesco Caracciolo2, Luigi Cembalo2, Eugenio Pomarici2 and Mario D’Amico1
  • 1 Department of Agri-Food and Environmental Systems Management, University of Catania, Catania, Italy
  • 2 Department of Agriculture, Agricultural Economics and Policy Group, University of Naples Federico II, Naples, Italy

Abstract

In recent decades, the Sicilian wine industry has experienced a booming expansion because of the growing preferences of Italian consumers for Sicilian wines, especially in extra-regional markets. These consumers have been paying closer attention to Sicilian premium wines. For this reason, the objective of this study is to inform professional investors and wine managers about the consumer preferences with respect to the most important segment categories of domestically consumed Sicilian wines. Using the quantile regression technique, we analyzed the role of wine attributes and prices as an information tool in order to value for each wine segment the implicit price of the attributes affecting wine consumers’ choices. The results indicate that Protected Designation of Origin (PDO) and Geographical Indication (PGI) certification is the main determinant in the wine price mechanisms and certified wines achieve premium prices that are progressively higher as the price level of the wine increases. Furthermore the effect of the brand on price formation seems to have a significant impact for low-end wines, whereas it has no specific impact on the price mechanism for high-end wines.

American Journal of Applied Sciences
Volume 12 No. 10, 2015, 679-688

DOI: https://doi.org/10.3844/ajassp.2015.679.688

Submitted On: 27 September 2014 Published On: 14 October 2015

How to Cite: Vita, G. D., Caracciolo, F., Cembalo, L., Pomarici, E. & D’Amico, M. (2015). Drinking Wine at Home: Hedonic Analysis of Sicilian Wines Using Quantile Regression. American Journal of Applied Sciences, 12(10), 679-688. https://doi.org/10.3844/ajassp.2015.679.688

  • 2,544 Views
  • 2,223 Downloads
  • 27 Citations

Download

Keywords

  • Consumer Scan Dataset
  • Geographic Origin
  • Hedonic Price
  • Robust Regression
  • Wine Consumption