The Price of Ros\ue9 Wines in Italian Outlets: an Hedonic Price Analysis

Ros\ue9 wine represents about 8,5% of world wine production (Fregoni, 2010). Europe produces about 3/4 of world production, mostly concentrated in France (30%), (21%) and Spain (18%); the Americas produces about the 23% of world production, especially in United States (18%). The ros\ue9 wine production has been driven by a strong increase in consumption in the last decade. Actually, the overall consumption of ros\ue9 wine is much lower than other wines; notwithstanding, this market segment has reported the strongest consumption increase rate at both Italian and international level. At the end of 2000s, Italian sales of ros\ue9 wines grew by 6% in value and 5% in volume. An increase in quality of ros\ue9 wines has also been reported (Ismea, 2008) because denomination of origins have been also extended to ros\ue8 wines. A survey carried out on Veneto Region (Boatto and Galletto, 2011) has depicted the shape of ros\ue9 wine consumer showing that the knowledge is fairly good (about 50% of people) often linked to some local or traditional sparkling ros\ue9 wines (eg. Rabosello, Lambrusco), the image of this wine is being young and appreciated by young people, the consumption is seasonal or occasional and mostly people drink ros\ue9 wine at home. The increasing in knowledge and, consequently, in consumption has been accomplished by a greater self space devoted to ros\ue8 wines by retailers. Actually, the consumption growth of ros\ue8 wines attracts retailers which are looking for products ensuring a better turnover, i.e., ros\ue9 wines are replacing matured red or white wines. Accordingly, strategies for ros\ue8 wines have been extended to a wide variety on intrinsic and extrinsic cues (quality, origin, bottle, label, etc.) producing a large price range. This paper presents results from a hedonic price analysis aimed to analyze factors affecting the mechanism of price fixing for ros\ue9 wines in Italian large retailers. A large literature using hedonic price functions to estimate the relationship between price and wine attributes generally supports the idea that the price is affected by characteristics that are available to consumers before purchasing (Nerlove 1995; Landon and Smith 1997; Combris et al. 2000; Oczkowski, 2001; Schamel and Anderson 2003; Lecocq and Visser, 2006; Couto and Rodrigues, 2007; Almenberg J. and Dreber A., 2011). So far, few studies have been focused on specific market segments such as ros\ue9 wines. Methodologically, a survey has been carried out on retailers by collecting data about point of sale features, wine quality (grape variety, blend, vintage, regional origin, types, sugar content, alcohol content) packaging (bottle, tap, glass, label and back label), price, brand, price promotion strategies and visual merchandising (display, facing). An hedonic price analysis (using the natural log of price as dependent variable) has been carried out on 935 records by assessing four different models (all, still, semi-sparkling and sparkling wines). A preliminary analysis on data has shown a wide variability of prices going from over 50 Euros of ros\ue9 Champagne, sold in wine shops, to 2-3 euros of table ros\ue9, sold in discount, while correlation has allowed to focus attention on discriminating variables and to exclude not significant variables and outliers. Results shows that retail prices are affected by the point of sale (big supermarkets vs. discount or small ones), certification of origin (denomination of origin vs. table wines), type of wine (still vs. sparkling), sugar content (brut vs. extra dry), alcohol content (with a maximum for medium level) packaging (bottle vs. bag in box; dark glass vs. light one), blend (blend wines vs. no blend ones), price promotion, shelf strategies (position on the shelf, facing). However, the analysis do not show significant price effects between domestic and international wines while the brand effect cannot be recognize because of scarce observations, i.e., dispersion among many brands. Most of the previous variables show significant effects also in the sub-models. However, in the still ros\ue9 model we have found a relevant role also for the international origin