Lai Maria Bonaria, Del Giudice Teresa, Pomarici Eugenio 1. Quality wine in the modern distribution

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1 Lai Maria Bonaria, Del Giudice Teresa, Pomarici Eugenio 1 Quality wine in the modern distribution Abstract This article examines the consumers preferences for wine in different distribution channels (iper and supermarket, traditional shops and others types). Using a hedonic pricing model we have analysed how the modern distribution could be an interesting alternative market for wine trade. To reach this object we analyzed a panel of Italian families. Using a patented hand-held scanner, the ACNielsen Homescan Panel record all UPC-barcoded products, variable weight and non UPCbarcoded products, from every outlet. 1. Introduction In order to analyze consumer s preferences for Italian wine in different distribution channels, we have used a panel of 9000 Italian families, pointed out by ACNielsen. Inside its, it is possible to find the customers socio-demographic characteristics and the channel using to sell and consequently to buy the product wine. These information represent the start point to define the main wine quality dimensions. Nature and presence of origin denomination inside the products purchased could be representing an important aspect of the wine s consumption characterization. Talking in term of volume, the common wine is the wine category most represented in the ACNielsen data where it has got a percentage equal to 60%. While the percentage of the typical wines, which have got an origin denomination, is 40%. These percentages become different if we consider the same typology wine in term of value. In fact more than the 50% of the total value has given by the typical wine purchase. The average price of purchase, for origin wine, is 3.8 euro per litre, more than the double of those of common wine, which is equal to 1.5 euro per litre. 1 Lai Maria Bonaria is contract professor at the Economics Faculty, University of Cagliari, V.le S. Ignazio, 17, Cagliari, Italy (mblai@unica.it). Del Giudice Teresa is researcher at Agricultural Economics and Policy Department, University of Naples Federico II, Via Università, 96, Portici (NA), Italy (agriqual@unina.it). Pomarici Eugenio is professor at Agricultural Economics and Policy Department, University of Naples Federico II, Via Università, 96, Portici (NA), Italy (pomarici@unina.it). Paragraph 2 and 5 have been written by Lai; paragraph 3 and 4 by Del Giudice. Introduction and conclusion are common to the three authors. 1

2 The main distribution channels used by the customers, included in the data, to buy the wine are the supermarkets and ipermarkets, where customers have spent euros in the Although, the others channels have a marginal role in the wine business, a good share of trade is kept by traditional and specialized retails. The figure n. 1 shows, in percentage terms, for single Italian region the number of families, which buy wine, as well as the quantity and the total cost that the families do and support to buy the same product. Figure n. 1 Quantity, cost and families number which buy wine subdivide for region 35 Families Quantity purchased Cost Piemonte Valle d'aosta Lombardia Trentino Veneto Friuli Venezia Giulia Liguria Emilia Romagna Toscana Umbria Marche Lazio Abruzzo Molise Campania Puglia Basilicata Calabria Sicilia Sardegna In the 2006 the number of families that have purchased the product wine inside the ACNiels is 6.969, representing the 68% of the total families included in the database. All this families have spent euros while the total quantity of wine bought by the same subjects is equal to hectolitres. In term demographic it is possible to describe the sample under two mean aspects: the age of the customers and the number of the persons that compose the family. The first distinguishes in age of the head of the family and age of responsible buyer inside the same family. The average age of the head of the family, includes in the database AcNielsen, is 51 years, while the average age of the responsible buyer is 48. The latter aspect shows as three persons in average compose families. If we consider the whole Italian regions, we can observe some differences. In fact, in the region take part of the so called Mezzogiorno and in the Island, families are used to be more large and young, while the age of head of the family and the age of responsible buyer are higher for the people which live in the North of Italy. 2. The sample 2

3 In this research we have defined as typical 2 all the wines that, inside the Panel ACNielsen 3, have got an origin denomination DOC or DOCG. So, going on with the research we have analyzed the importance of the purchase of quality wine in the different retails. Typology of wine, purchase channel, colour, way of production and average price are the Panel ACNiels selected variables to make the model. Each variable is divided in two or more levels. In detail, for the typology we have decided to group the wine in two classes: wine that have got an origin denomination and wine without denomination. We have identified this last class with the name common wine. For the purchase channels we have four specifications, in order supermarket, ipermarket, free service, others purchase channels. Two levels have got each one colour and way of production, red and white, organic and conventional. The dependent variable, average price, presents more than four levels. The purchase frequency subdivides for purchase channels are reported in table n.1. Table n. 1 Purchase frequency Frequency Percent Cumulative percent Supermarket ,0 49,0 Ipermarket ,4 83,4 Free service ,2 87,7 Others purchase channels ,3 100,0 Total ,0 The stuff more widespread and used to contain the product object of this research are represented by glass (69.5%) and brick (28.7%), while the capacity 75 cl is the size of the packaging which prevails inside the database (51.5%), followed by packaging of 1L with a good percentage equal to 27.6%. In refer to the customers taste it is possible to observe, as the same prefer to buy red wine (56.1%). The wine made by grapes coming from organic cultivation represents again a very little percentage of the wine Italian family s consumption. In fact, always referring to the ACNielsen data, the customers have bought biological wine with a purchase frequency equal to 103 (0.1%). The figure n. 2, considering the total amount of wine purchased by the customers belonging to the data, shows the number of typical and not typical wines bought in the different retails. 2 Here, we use this word like synonym of quality. 3 The database includes a relevant number of observations, only for the purchase of the wine. 3

4 Figure n. 2 Place to buy wine Typical No typical Supermarket Ipermarket Free service Other channels Looking the figure n. 2 it is possible to observe, so as it wrote in the firth paragraph, also for the purchase of wine with origin denomination modern retails are preferred. 3. Theory and methods In empirical investigation of hedonic models the aim is to determine how the price of a product can vary with the set and the amount of characteristics composing the product. Rosen (1974) has presented an integrated approach to hedonic theory for differentiated products in a competitive context, where he defines the hedonic price as the implicit price of the product attributes. The underlying theory relies on the characteristics approach to demand theory of Lancaster (1966) which identifies goods as a bundle of attributes, whose quality and quantity determine consumer choice. Formally, using Rosen s formulation, if Y is a product, any Y specimen y i can be fully defined by the characteristics vector Q = q 1,, q j,, q n as y i = y i (q i1,, q ij,, q in ), where q ij is the j characteristic amount present in the specimen y i of product Y. Hedonic price function then decomposes the price of Y as a function of its characteristics, that is p y = p y (q i1,, q ij,, q in ) (Freeman, 2003). The partial derivative, of this function with respect to each attribute, measures its implicit price. In perfect competition, hedonic prices can be interpreted as representing both buyers valuation and sellers cost; in a situation of imperfect competition the price of an attribute is set by sellers on the basis of their estimates of demand elasticity for characteristics, rather than on the basis of cost (Hassan & Monier-Dilhan, 2006). 4. Hedonic pricing model In order to investigate how specific wine attribute affect the price and determine different price levels in the channels trade, a Hedonic Pricing Model (HPM) analysis was performed. We chose to consider these attributes, included in the ACNielsen database: 1. dummy variable for way of production (1 for organic wine, 0 for not organic wine); 2. dummy variable for colour of wine (1 for red; 0 for white and light red); 4

5 3. dummy variable for typology of wine (1for wine with certification, DOC-DOCG, 0 for wine without denomination). The survey has continued making the matrix of the potential variables, each of them contains information about one characteristic of the product. In the hedonic model proposal, the dependent variable P has been defined as the average price (euro/litre). The hedonic model, estimate with the OLS method, can be write in this way: P = β 0 + β1 Pr oduction + β 2Colour + β 3 Typolog y + ε Initially the model has been estimated using the Box-Cox specification to prove alternative functional form. The likelihood ratio test permit us to reject the double logarithmic and the semi logarithmic functional form. So the linear functional form has been chosen. This kind of function allows to interpret the coefficients as implicit price and to obtain information about the importance of each characteristic, in the different retail. 5. Preference analysis The hedonic model has been tested for the different retails present inside the database, after we have compared the results outcome each the others. The significant of the estimated attributes, the value of the coefficients and the R square represent the indexes used to verify and to compare the different models. Besides, interpreting the coefficients like implicit prices, this kind of analysis allows us: to know what is the wine characteristic that the customers consider more important between all; and to understand how the customers percept the purchase of wine in the modern retail. The results related to consumers that buy wine in the different retail have been shown from table 2 to table 5. Each model has got a significant R square 4. The model that explains more than the others is those illustrated in table 3 and pertinent to the supermarket channel. 4 In increase order the value assumes to the R square in the different models is: for the others shops hedonic pricing model; for free service hedonic pricing model; for the ipermarket hedonic pricing model and is that for the supermarket hedonic pricing model. 5

6 Hedonic pricing model in modern retail Table n. 2 Ipermarket Coefficient St. Error t-statistic Sig. Constant 2,932 0,030 96,159 0,000 Organic 1,589 0,288 5,519 0,000 Red 0,161 0,210 7,801 0,000 Denomination 1,546 0,330 46,477 0,000 Common -1,104 0,330-33,876 0,000 Table n. 3 Supermarket Coefficient St. Error t-statistic Sig. Constant 2,843 0, ,117 0,000 Organic 1,630 0,265 6,143 0,000 Red 0,158 0,014 10,929 0,000 Denomination 1,560 0,026 59,405 0,000 Common -1,152 0,025-46,521 0,000 Hedonic pricing model in traditional retail Table n. 4 Free services Coefficient St. Error t-statistic Sig. Constant 1,734 0,060 28,991 0,000 Red 0,089 0,037 2,380 0,017 Denomination 1,521 0,066 22,927 0,000 Common -0,368 0,058-6,367 0,000 Table n. 5 Others shops Coefficient St. Error t-statistic Sig. Constant 1,633 0,046 35,595 0,000 Organic 1,503 0,849 1,770 0,077 Red 0,078 0,028 2,801 0,005 Denomination 0,837 0,050 16,623 0,000 Common -0,492 0,047-10,576 0,000 The high implicit price, for the variables typology (wine with denomination) and production (organic wine), can be interpreted like a customer index of linking about quality wine. The customers always more, search and find the quality of the wine in the modern retail. This last is for the Italian families a good purchase channel, where it is possible to find excellent wines, quality wine, because in the supermarkets the attributes that have a relevant importance coincide with some of the elements wine quality too. To produce the wine using organic grapes begets a positive impact on the purchase wine price. The implicit price is equal to 1.63 euro per litre for the wine purchased in the supermarket. Even if in Italy the producers, that use the organic agriculture to make the wine, are again a narrow number they are managed to play with this attribute taking a good portion of the wine market for their products. The implicit price for the attribute denomination is quite high in almost all the retails 5 and its highest value is 1.56 euro per litre, again one time, for the purchased in the supermarket. The coefficient of the common wine presents a negative sign this means that the Italian families like less the common wine. They pay a price up for its only if the purchase has been done in the modern retail. 5 The implicit denomination price assume value lower of 1.5 euro per litre only in the others shops model, where it becomes equal to 0.84 euro per litre. 6

7 The so high value assume to the constant means that the variables, consider to make the hedonic model, are not sufficient to explain in the best way the wine implicit price. It should be better to find new wine attributes and to test again the model with theirs. 6. Conclusions The Italian wine market, offers an extremely vast range of excellent wines, only the wine that have got an origin denomination are Some denomination applies to wines produced in large quantity, while some involve geographical areas that are of lesser size and, therefore, more limited output. One way to appreciate the various denominations, without having to travel personally to the many different regions, is offered by the trade which put on disposal to the customer, trough the different trade channels, the Italian and foreign production. An important role in this field has been attributed to the Enoteca, where it is possible to find a good wine supply. The result of the hedonic pricing model, tested in this research, prove how the modern retail is managed to increase its share market in this sector inducing most of the national producer to extend, to diversify and to complete their wine brand inside this kind of shops. This article becomes only the first step of our research in this field. In fact, the results of the different models confirm our initial idea about the few number of variables to make the hedonic model, in spite of the relevant number of observations give out from the ACNielsen database. We are going on with the study. For each wine presents inside the database we are searching new attributes like the spirits degree, not present in the database DOC and 24 DOCG. 7

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