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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="3.0" xml:lang="en">
   <front>
      <journal-meta>
         <journal-id journal-id-type="publisher-id">SJAR</journal-id>
         <journal-title-group>
            <journal-title>Spanish Journal of Agricultural Research</journal-title>
            <abbrev-journal-title>SJAR</abbrev-journal-title>
         </journal-title-group>
         <issn pub-type="epub">2171-9292</issn>
         <publisher>
            <publisher-name>Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA)</publisher-name>
         </publisher>
      </journal-meta>
      <article-meta>
         <article-id pub-id-type="publisher-id">10006</article-id>
         <article-id pub-id-type="doi">10.5424/sjar/2017154-10006</article-id>
         <article-categories>
            <subj-group subj-group-type="heading">
               <subject>Research article</subject>
            </subj-group>
         </article-categories>
         <title-group>
            <article-title>Spanish wines in the US market: What attributes do US consumers look for in Spanish wines?</article-title>
         </title-group>
         <contrib-group>
            <contrib contrib-type="author" corresp="yes">
               <name>
                  <surname>Areta</surname>
                  <given-names>Álvaro</given-names>
                  <aff>
                     <i>Coordinadora de Organizaciones de Agricultores y Ganaderos COAG, Servicios Técnicos, Dept. Economía Agraria. c/Agustín de Bethancourt 17, 28003 Madrid, Spain.</i>
                  </aff>
               </name>
            </contrib>
            <contrib contrib-type="author" corresp="no">
               <name>
                  <surname>Bardají</surname>
                  <given-names>Isabel</given-names>
                  <aff>
                     <i>Universidad Politécnica de Madrid, ETS de Ingeniería Agronómica, Alimentaria y Biosistemas, CEIGRAM, Dept. Economía agraria, Estadística y Gestión de empresas. Ciudad Universitaria s/n, 28040 Madrid, Spain.</i>
                  </aff>
               </name>
            </contrib>
            <contrib contrib-type="author" corresp="no">
               <name>
                  <surname>Iráizoz</surname>
                  <given-names>Belén</given-names>
                  <aff>
                     <i>Universidad Pública de Navarra, INARBE y Dept. de Economía, Campus de Arrosadia. 31006 Pamplona, Navarra, Spain.</i>
                  </aff>
               </name>
            </contrib>
         </contrib-group>
         <author-notes>
            <corresp>
               should be addressed to Álvaro Areta:
               <email xlink:href="aareta@coag.org">aareta@coag.org</email>
            </corresp>
         </author-notes>
         <pub-date pub-type="epub">
            <day>01</day>
            <month>12</month>
            <year>2017</year>
         </pub-date>
         <pub-date pub-type="collection">
            <year>2017</year>
         </pub-date>
         <volume>15</volume>
         <issue>4</issue>
         <elocation-id content-type="doi">10.5424/sjar/2017154-10006</elocation-id>
         <history>
            <date date-type="recibido">
               <day>26</day>
               <month>05</month>
               <year>2016</year>
            </date>
            <date date-type="aceptado">
               <day>30</day>
               <month>11</month>
               <year>2017</year>
            </date>
         </history>
         <permissions>
            <copyright-statement>© 2017 INIA</copyright-statement>
            <copyright-year>2017</copyright-year>
            <license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/3.0/">
               <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution (CC-by) Spain 3.0 License.</license-p>
            </license>
         </permissions>
         <abstract id="abstract01">
            <title>Abstract</title>
            <p>This paper analysed the impact of different attributes in Spanish quality wines on United States (US) demand behaviour. A hedonic price model was estimated in order to assess the values that US consumers give Spanish wines. The main results showed that the most influential factor on sale price was aging, which had a positive impact. US consumers valued the quality ratings provided by experts, especially in the upper price categories. The year of vintage and size of the winery were considered medium importance factors in decision-making, with the latest vintages and the smallest wineries receiving the highest ratings. Geographical origin (appellation) helped to explain consumer preferences. Although colour was the least important attribute in consumers' purchase decisions, red wines were the most highly rated in this attribute.</p>
         </abstract>
         <kwd-group>
            <title>Additional key words:</title>
            <kwd>hedonic prices;</kwd>
            <kwd>quality wine;</kwd>
            <kwd>consumer preferences;</kwd>
            <kwd>wine attributes.</kwd>
         </kwd-group>
         <funding-group>
            <funding-statement>The authors received no specific funding for this work.</funding-statement>
         </funding-group>
      </article-meta>
      <notes>
         <p>
            <bold>Author's contributions:</bold>
            Conception and design, analysis of data, and writing the paper: AA, IB, BI. Acquisition of data: AA. Supervising the work: IB, BI.
         </p>
         <p>
            <bold>Citation</bold>
            Areta, A.; Bardají, I.; Iráizoz, B. (2017). Spanish wines in the US market: What attributes do US consumers look for in Spanish wines? Spanish Journal of Agricultural Research, Volume 15, Issue 4, e0120.
            <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5424/sjar/2017154-10006">https://doi.org/10.5424/sjar/2017154-10006</ext-link>
         </p>
         <p>
            <bold>Competing interests:</bold>
            The authors have declared that no competing interests exist.
         </p>
      </notes>
   </front>
   <body>
      <sec id="S1">
         <title>Introduction</title>
         <p>
            The wine industry faces new market opportunities created by factors such as increasing trade liberalization and globalization, emerging competition from new market players, and declining consumption in traditional wine-producing countries (
            <xref ref-type="bibr" rid="b4">
               Anderson
               <italic>et al</italic>
               ., 2001
            </xref>
            ;
            <xref ref-type="bibr" rid="b83">
               Wittwer
               <italic>et al</italic>
               ., 2003
            </xref>
            ). Increasing export volumes and added value creation through differentiation strategies are the key ways to maintain profitability in the Spanish wine industry (
            <xref ref-type="bibr" rid="b1">Albisu &amp; Zeballos, 2014</xref>
            ;
            <xref ref-type="bibr" rid="b28">Del Rey, 2014a</xref>
            ). The United States (US) is one of the world's main wine importers, with growing domestic demand. Spain's wine exports to the US have shown significant growth rates, but Spanish market share still remains below that of many competing countries.
         </p>
         <p>
            In this context, it was relevant to analyse the way in which the various attributes of Spanish quality wines influenced demand behaviour in the US. Knowledge of how US consumers assessed these characteristics could be used by producers, exporters and distributors to design the necessary strategies to improve their market positioning. To be aware of what factors might influence the wine prices could help producers to take decisions about where to position their product on the market (
            <xref ref-type="bibr" rid="b25">Cousido Cores, 2017</xref>
            ).
         </p>
         <p>
            Hedonic price modelling represents a valid empirical methodology (
            <xref ref-type="bibr" rid="b13">
               Cacchiarelli
               <italic>et al</italic>
               ., 2016a
            </xref>
            ) and it is widely used to explain the decision-making process leading up to the purchase of a specific product in terms of its combined attributes, by allowing the estimation of the implicit price of each attribute. It has been applied to this end in various sectors and markets. Research on the agriculture and food industry considers products as diverse as livestock (
            <xref ref-type="bibr" rid="b78">
               Troncoso
               <italic>et al</italic>
               ., 2012
            </xref>
            ), apples (
            <xref ref-type="bibr" rid="b31">
               Dinis
               <italic>et al</italic>
               ., 2011
            </xref>
            ) or saffron (
            <xref ref-type="bibr" rid="b67">
               Sanjuán-López
               <italic>et al</italic>
               ., 2009
            </xref>
            ). The high degree of differentiation makes the wine suitable for the application of hedonic methodology, taking into account the multiple intrinsic characteristics that provide consumers with a large range of wines (
            <xref ref-type="bibr" rid="b57">Oczkowski &amp; Doucouliagos, 2015</xref>
            ). The method has, nevertheless, received some criticism because of the difficulty of selecting the appropriate variables or the need to assume that the quality attributes of wines are unrelated to their price (
            <xref ref-type="bibr" rid="b79">Unwin, 1999</xref>
            ). The selection of the attributes included as determinant of the wine price was based on the review of the literature and the information provided by several sources.
         </p>
         <p>
            The planning and implementation of long-term investment strategies could benefit from having information about the attributes more valued by consumers. The results can help in assessing the need to include specific attributes in the final product, by enabling comparison between their implicit prices and their marginal cost. This explains the widespread use of hedonic price models to determine the relative importance of the intrinsic characteristics of wine
            <sup>1</sup>
            . Some studies are focused on traditional markets, such as France (
            <xref ref-type="bibr" rid="b44">Landon &amp; Smith, 1997</xref>
            ;
            <xref ref-type="bibr" rid="b45">Lecocq &amp; Visser, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b2">Ali &amp; Nauges, 2007</xref>
            ;
            <xref ref-type="bibr" rid="b16">Cardebat &amp; Figuet, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b18">Carew &amp; Florkowski, 2010</xref>
            ), Italy (
            <xref ref-type="bibr" rid="b10">
               Brentari
               <italic>et al</italic>
               ., 2011
            </xref>
            and
            <xref ref-type="bibr" rid="b11">2015</xref>
            ;
            <xref ref-type="bibr" rid="b15">
               Caracciolo
               <italic>et al</italic>
               ., 2013
            </xref>
            ;
            <xref ref-type="bibr" rid="b64">
               Roma
               <italic>et al</italic>
               ., 2013
            </xref>
            ;
            <xref ref-type="bibr" rid="b47">Levaggi &amp; Brentari, 2014</xref>
            ;
            <xref ref-type="bibr" rid="b12">
               Cacchiarelli
               <italic>et al</italic>
               ., 2014
            </xref>
            ) or Germany (
            <xref ref-type="bibr" rid="b68">Schamel, 2003</xref>
            ), as well as new producers, such as Australia (
            <xref ref-type="bibr" rid="b55">Oczkowski, 1994</xref>
            ,
            <xref ref-type="bibr" rid="b56">2015</xref>
            ;
            <xref ref-type="bibr" rid="b73">Steiner, 2004</xref>
            ;
            <xref ref-type="bibr" rid="b27">Davis &amp; Ahmadi-Esfahani, 2005</xref>
            ), New Zealand (
            <xref ref-type="bibr" rid="b6">
               Bicknell
               <italic>et al</italic>
               ., 2005
            </xref>
            ;
            <xref ref-type="bibr" rid="b7">Bicknell &amp; MacDonald, 2012</xref>
            ), US (
            <xref ref-type="bibr" rid="b84">
               Yang
               <italic>et al</italic>
               ., 2012
            </xref>
            ;
            <xref ref-type="bibr" rid="b26">Cuellar &amp; Claps, 2013</xref>
            ;
            <xref ref-type="bibr" rid="b30">Delmas &amp; Grant, 2014</xref>
            ), Chile (
            <xref ref-type="bibr" rid="b50">
               Melo
               <italic>et al</italic>
               ., 2005
            </xref>
            ;
            <xref ref-type="bibr" rid="b77">Troncoso &amp; Aguirre, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b58">Ortuzar &amp; Alfranca, 2010</xref>
            ) or Argentina (San Martin
            <italic>et al</italic>
            ., 2008;
            <xref ref-type="bibr" rid="b32">Estrella, 2014</xref>
            ).
         </p>
         <p>
            The domestic market for Spanish wines has been analyzed from different perspectives.
            <xref ref-type="bibr" rid="b5">
               Angulo
               <italic>et al</italic>
               . (2000)
            </xref>
            estimate a hedonic price function for red wines,
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez (2002)</xref>
            for Spanish wines with
            <italic>Designation of Origin</italic>
            ,
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo (2009)</xref>
            for red wines from
            <italic>Castilla La Mancha</italic>
            , and
            <xref ref-type="bibr" rid="b62">Perza (2010)</xref>
            for Catalan wines. The acceptance of Spanish wines has also been assessed in foreign markets such as the United Kingdom (UK) (
            <xref ref-type="bibr" rid="b74">Steiner, 2009</xref>
            ), France (
            <xref ref-type="bibr" rid="b17">Cardebat &amp; Figuet, 2014</xref>
            ) and, jointly with wines from other origins, in the US (
            <xref ref-type="bibr" rid="b69">Schamel, 2006</xref>
            ).
         </p>
         <p>
            It is interesting to point out that Spain is currently the country with largest vineyeard area in the world and the top wine exporter but its wine is sold for its low price (
            <xref ref-type="bibr" rid="b61">Parga-Dans &amp; Alonso González, 2017</xref>
                  ). Considering the evolution of the US wine market, it is important to have some knowledge about which wine characteristics can contribute to achieve higher prices in that market. So far, no study offers a specific valuation of prices in wine's US markets with respect to Spanish wines, despite the importance of exports for the Spanish wine industry and the relevance of the US market. This research aimed to meet this gap, by trying to determine which features of quality Spanish wines were most valued by US consumers. Our analysis took a representative sample of Spanish wine exports to identify the attributes influencing consumer willingness-to-pay in each segment. Our hypothesis was that there are some specific attributes that can influence wine's prices. These attributes has been clustered in six groups of attributes are shown to influence wine's prices: vintage, aging, quality rating, appellation, type of wine and size of winery. Any business decision involving one of these attributes was relevant for the positioning of a wine in the US market.
         </p>
      </sec>
      <sec id="S2">
         <p>
            Hedonic price theory enables product differentiation analysis based on the utilities provided by product characteristics or attributes, through the estimation of an implicit price or hedonic price function. Pioneer studies in the literature on the hedonic price theory include
            <xref ref-type="bibr" rid="b80">Waugh (1928)</xref>
            and
            <xref ref-type="bibr" rid="b24">Court (1939)</xref>
            , but it was not until the 60s that it came into more extensive use in research conducted by
            <xref ref-type="bibr" rid="b35">Griliches (1961)</xref>
            ,
            <xref ref-type="bibr" rid="b20">Chow (1967)</xref>
            and
            <xref ref-type="bibr" rid="b53">Muth (1969)</xref>
            , and the study by
            <xref ref-type="bibr" rid="b65">Rosen (1974)</xref>
            , founded on the work of
            <xref ref-type="bibr" rid="b43">Lancaster ( 1971)</xref>
            , which estimates a perfect competition model optimizing hedonic price theory.
         </p>
         <p>A hedonic price function is a mathematical function relating the price of a good to its characteristics or attributes. Any variable influencing the consumer decision or production cost can be considered in the function and, if proved significant, it can be assumed to have consumer value or relevance in the production process. Two key parameters need to be specified: the functional form and the product characteristics to be included as explanatory variables.</p>
         <p><xref ref-type="disp-formula" rid="form1">Equation [1]</xref> describes a general hedonic function model</p>
         <p />
         <p>
        <graphic id="form1" xlink:href="sjar_e0120_form1.jpg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
         </p>
         <p />
         <p>where p denotes the price of the i-th bottle of wine and the j-th attribute. The market is assumed to be in equilibrium and consumers and producers are assumed to maximize their objective functions.</p>
         <p>
            Linear, log-linear, double logarithmic or logarithmic functional forms can be adopted (
            <xref ref-type="bibr" rid="b9">Brachinger, 2002</xref>
            ). As usual in hedonic price models, the attributes of interest were represented exclusively by dummy variables (
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez, 2002</xref>
            ;
            <xref ref-type="bibr" rid="b73">Steiner, 2004</xref>
            ;
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo, 2009</xref>
            ), which reduces the risk of impacts from measurement errors in variables and prevents from heteroscedasticity. This option also restricts the choice of functional form to linear or log-linear models. Most studies opt to estimate the log-linear model (
            <xref ref-type="bibr" rid="b73">Steiner, 2004</xref>
            ;
            <xref ref-type="bibr" rid="b50">
               Melo
               <italic>et al</italic>
               ., 2005
            </xref>
            ;
            <xref ref-type="bibr" rid="b48">
               Luppe
               <italic>et al</italic>
               ., 2009
            </xref>
            or
            <xref ref-type="bibr" rid="b18">Carew &amp; Florkowski, 2010</xref>
            ), for the variance-stabilizing properties derived from the logarithmic transformation. <xref ref-type="disp-formula" rid="form2">Equation [2]</xref> describes the log-linear model estimated by ordinary least squares
            <sup>2</sup>
         </p>
         <graphic id="form2" xlink:href="sjar_e0120_form2.jpg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
         <p>
            where
            <italic>&#946;j</italic>
            is the marginal variation in price associated with a marginal change in attribute
            <italic>X</italic>
            <sub>j</sub>
            . Estimated coefficients represent the percent variation in price for a unit change in attribute
            <italic>X</italic>
            .
         </p>
         <p>
            Since the problem involves a large number of independent variables, a closer-fitting function was constructed by using Stata software to estimate a forward stepwise regression, with a threshold of 10% significance level for a variable's inclusion in the model (
            <xref ref-type="bibr" rid="b45">Lecocq &amp; Visser, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b11">
               Brentari
               <italic>et al</italic>
               ., 2015
            </xref>
            ).
         </p>
         <p>
            The inclusion of dummies as endogenous variables meant that for each one there must be a control group, which must be excluded from the estimation. However, following the proposals of
            <xref ref-type="bibr" rid="b75">Suits (1984)</xref>
            and
            <xref ref-type="bibr" rid="b40">Kennedy (1986)</xref>
            , it was possible to adjust the estimated coefficients and include each category of the binary variables in the estimation, without affecting any other estimation properties. These adjusted coefficients were interpreted directly in relation to the sample mean price, thus making the results easier to interpret. According to
            <xref ref-type="bibr" rid="b55">Oczkowski (1994)</xref>
            , and to illustrate the method, suppose a hedonic model
            <italic>p</italic>
            <sub>t</sub>
            =
            <italic>&#946;</italic>
            <sub>0</sub>
            +
            <italic>&#946;</italic>
            <sub>1</sub>
            <italic>D</italic>
            <sub>1t</sub>
            +
            <italic>&#946;</italic>
            <sub>2</sub>
            <italic>D</italic>
            <sub>2t</sub>
            +
            <italic>&#949;</italic>
            <sub>t</sub>
            with the two dummy variables that &#931;<sup>2</sup><sub>j</sub>=1D<sub>j</sub>=1. To avoid the problem of multicollinearity, imposing the constraint that &#931;<sup>2</sup><sub>j</sub>=1&#946;<sub>j</sub><italic>w</italic><sub>j</sub>=0, where <italic>w</italic>
            <sub>j</sub>
            represents the proportion of non zero dummy observations, leads to the result that &#946;<sub>0</sub>=<italic>p</italic>  ,and &#946;<sub>1</sub>  and &#946;<sub>2</sub> are now interpreted as deviations from the average price in the sample. To estimate the function by ordinary least square, the constraint is expressed as -&#946;<sub>1</sub> = -&#946;<sub>2</sub> (<italic>w</italic><sub>2</sub>/<italic>w</italic><sub>1</sub>)
         </p>
         <p>
            Since the model considers only binary variables, the partial derivatives are not defined and the estimated coefficients do not represent the implicit price of each characteristic. To ease interpretation of the results, the relative percentage effect of the dummy variable on the price was included. The transformation procedure proposed by
            <xref ref-type="bibr" rid="b36">Halvorsen &amp; Palmquist (1980)</xref>
            with the modifications suggested by
            <xref ref-type="bibr" rid="b39">Kennedy (1981)</xref>
            was followed to avoid biased results. Thus, the percentage difference on the price associated to every dummy variable was estimated according to the expression
         </p>
         <graphic id="form3" xlink:href="sjar_e0120_form3.jpg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
         <p>
            where g is the percentage impact, c is the estimated coefficient for each dummy variable and
            <italic>var</italic>
            (c) is an estimate of the variance of c.
         </p>
         <p>
            The data were obtained from the magazine
            <xref ref-type="bibr" rid="b82">
               <italic>Wine Spectator</italic>
               (2012)
            </xref>
            , which offers a database that has been widely used in other studies (
            <xref ref-type="bibr" rid="b77">Troncoso &amp; Aguirre, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b51">
               Miller
               <italic>et al</italic>
               ., 2007
            </xref>
            ;
            <xref ref-type="bibr" rid="b66">
               San Martín
               <italic>et al</italic>
               ., 2008
            </xref>
            ;
            <xref ref-type="bibr" rid="b26">Cuellar &amp; Claps, 2013</xref>
            ;
            <xref ref-type="bibr" rid="b46">Lee &amp; Sumner, 2013</xref>
            ). The digital edition of
            <italic>Wine Spectator</italic>
            includes more than 290,000 wine ratings covering all the main wine-producing countries, and including 12,500 Spanish wines. The sample (September, 2012), which included 9,260 references
            <sup>3</sup>
            , has been segmented by price
            <sup>4</sup>
            as some authors suggest (
            <xref ref-type="bibr" rid="b5">
               Angulo
               <italic>et al</italic>
               ., 2000
            </xref>
            ;
            <xref ref-type="bibr" rid="b22">
               Costanigro
               <italic>et al</italic>
               ., 2007
            </xref>
            ) and to determine if the different market share of Spanish wines in each category (
            <xref ref-type="bibr" rid="b38">ICEX, 2014</xref>
            ) could affect the consumer valuation. Premium segments provide more possibilities for market penetration than lower price segments (
            <xref ref-type="bibr" rid="b19">Cholette &amp; Castaldi, 2005</xref>
            ;
            <xref ref-type="bibr" rid="b76">Thach &amp; Cuellar, 2007</xref>
            ). Three price categories were considered: popular premium (between US$ 3 and US$ 7 per bottle), super premium (between US$ 7 and US$ 14 per bottle) and ultra premium (over US$ 14 per bottle). <xref ref-type="table" rid="T1">Table 1</xref> shows the sample distribution and the descriptive statistics for each category. The average retail price was US$ 28 per bottle, although there was a high degree of dispersion. The average price in the popular premium category was US$ 6.25 per bottle, which was close to the upper bound, while, in the super premium category, it was US$ 10.84 per bottle, which was mid-range for the category, and, in the ultra premium category, it was US$ 40 per bottle, and the dispersion was higher.
         </p>
		 <p></p>
		 <table-wrap id="T1">
    <label>Table 1.</label>
    <caption>
    <title>Descriptive statistics of the data. </title>
    </caption>
    <graphic xlink:href="sjar_e0120_t01.jpg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</table-wrap>

         <p>Different hedonic models have been estimated for each price category and for the whole sample with the aim of evaluating the differentiated influence of the attributes in the wine's prices in the US market.</p>
         <p>
            Besides retail price, and according to the literature review, the
            <italic>Wine Spectator</italic>
            database variables considered in the estimation were aging, type or color, quality rating, geographical origin (appellation) and vintage year. A winery size variable was also included but the data were obtained from other sources.
         </p>
         <p>
            Aging is included in many studies with significant results (
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez, 2002</xref>
            ;
            <xref ref-type="bibr" rid="b50">
               Melo
               <italic>et al</italic>
               ., 2005
            </xref>
            ;
            <xref ref-type="bibr" rid="b45">Lecocq &amp; Visser, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b77">Troncoso &amp; Aguirre, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b66">
               San Martín
               <italic>et al</italic>
               ., 2008
            </xref>
            ;
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b62">Perza, 2010</xref>
            ;
            <xref ref-type="bibr" rid="b41">
               Kwong
               <italic>et al</italic>
               ., 2011
            </xref>
            ,
            <xref ref-type="bibr" rid="b42">2017</xref>
            ). Spanish regulations establish only four wine classifications based on aging:
            <italic>joven, crianza, reserv</italic>
            a and
            <italic>gran reserva</italic>
            <sup>5</sup>
            . However, analysis of the sample led us to set up a new classification,
            <italic>boutique</italic>
            , in the upper price category. These wines do not follow aging regulations, so they are usually included in the
            <italic>joven</italic>
            classification. However, their special high-quality features command higher prices. <xref ref-type="table" rid="T1">Table 1</xref> shows that almost 60% of the sample classified as
            <italic>joven</italic>
            , and belong mainly to the popular and super premium price categories.
         </p>
         <p>
            With respect to the type or color of the wine, the sample was split into three types: red, white and rosé. The reds were expected to achieve significantly higher consumer value than the whites (
            <xref ref-type="bibr" rid="b60">Panzone &amp; Sim&#245;es, 2009</xref>
            ) or rosés. Red wines made up the majority of the sample, especially in the ultra premium category, and their prices almost doubled those of the whites and triple those of the rosés.
         </p>
         <p>
            Quality ratings are typically included as a variable in hedonic price models but results and conclusions regarding their impact on consumer choice are ambiguous. Some works find them significant explaining the consumer behavior (
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez, 2002</xref>
            ;
            <xref ref-type="bibr" rid="b6">
               Bicknell
               <italic>et al</italic>
               ., 2005
            </xref>
            ; San Martin
            <italic>et al</italic>
            ., 2008;
            <xref ref-type="bibr" rid="b15">
               Caracciolo
               <italic>et al</italic>
               ., 2013
            </xref>
            ,
            <xref ref-type="bibr" rid="b12">
               Cacchiarelli
               <italic>et al</italic>
               ., 2014
            </xref>
            , or
            <xref ref-type="bibr" rid="b25">Cousido Cores, 2017</xref>
            ), but other studies report a null effect on the purchase decision (
            <xref ref-type="bibr" rid="b21">
               Combris
               <italic>et al</italic>
               ., 1997
            </xref>
            ;
            <xref ref-type="bibr" rid="b59">Panzone, 2011</xref>
            ). If their effect is significant, the wines with highest ratings can be expected to get market rewards (
            <xref ref-type="bibr" rid="b69">Schamel, 2006</xref>
            ).
            <italic>Wine Spectator</italic>
            assigns quality ratings based on a blind tasting of an expert panel not on a quality/price assessment, which could cause correlation problems. Tasting panels rate the wines on a 50-point qualitative scale, ranging from 50 (lowest score) to 100 (top score) (
            <xref ref-type="bibr" rid="b72">Shanken, 1996</xref>
            ). The ranks are: not recommended (50-74 points), mediocre (75-79), good (80-84), very good (85-89), outstanding (90-94) and classic (95-100). The most frequent ratings in the sample overall were very good and good (42% and 34% respectively). Most of the wines in the popular and super premium categories were rated as good, while in the ultra premium price category the majority received ratings of very good, followed by outstanding and good.
         </p>
         <p>
            Appellation as an attribute is generally included in wine hedonic price models, because it is accepted that it adds value to wines by certifying the presence of a differentiated quality product (
            <xref ref-type="bibr" rid="b61">Parga-Dans &amp; Alonso González, 2017</xref>
            ). It may refer to a country (
            <xref ref-type="bibr" rid="b85">
               Yoo
               <italic>et al</italic>
               ., 2011
            </xref>
            ) or a region (
            <xref ref-type="bibr" rid="b60">Panzone &amp; Sim&#245;es, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b84">
               Yang
               <italic>et al</italic>
               ., 2012
            </xref>
            ;
            <xref ref-type="bibr" rid="b14">
               Cacchiarelli
               <italic>et al</italic>
               ., 2016b
            </xref>
            ) and the significance of its role influencing price's wines has been tested in many studies (
            <xref ref-type="bibr" rid="b54">Nerlove, 1995</xref>
            ;
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez, 2002</xref>
            ;
            <xref ref-type="bibr" rid="b73">Steiner, 2004</xref>
            ;
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b10">
               Brentari
               <italic>et al</italic>
               ., 2011
            </xref>
            ;
            <xref ref-type="bibr" rid="b64">
               Roma
               <italic>et al</italic>
               ., 2013
            </xref>
            ). We analyzed US consumer willingness to purchase Spanish quality wines of different appellations. Distinct preferences within the price categories considered could support the usefulness of customer segment-based promotion strategies (
            <xref ref-type="bibr" rid="b26">Cuellar &amp; Claps, 2013</xref>
            ). The
            <italic>Wine Spectator</italic>
            database contained data from various Spanish wine-producing regions. In our analysis, appellations with fewer than 50 references were grouped into clusters based on similar geographical, soil and climate characteristics. Based on these criteria, our model considered 31 different appellations (<xref ref-type="fig" rid="F1">Figure 1</xref>). Most of the references belonged to the
            <italic>Rioja, Ribera del Duero</italic>
            ,
            <italic>Penedés</italic>
            and
            <italic>Navarra</italic>
            appellations. It is worth noting that, as the price of the wine increases, the
            <italic>Priorat, Bierzo</italic>
            and
            <italic>Ribera del Duero</italic>
            appellations gained prominence, whereas
            <italic>Penedés</italic>
            ,
            <italic>Navarra, Vinos de la Tierra de Castilla, Campo de Borja, La Mancha, Somontano</italic>
            and
            <italic>Calatayud</italic>
            lost it.
         </p>
		 <p></p>
		 <fig id="F1">
    <label>Figure 1.</label>
    <caption>
    <title>Distribution of the relative weight of every appellation in the categories of prices.</title>
    </caption>
    <graphic xlink:href="sjar_e0120_f01.jpg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</fig>

         <p>
            The vintage year is easily identifiable by the consumer, because it features on the label. Its use in research about its role as determinant of wine's prices has produced mixed results. For some authors it has little or no influence (
            <xref ref-type="bibr" rid="b70">Schamel &amp; Anderson, 2003</xref>
            ;
            <xref ref-type="bibr" rid="b69">Schamel, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b48">
               Luppe
               <italic>et al</italic>
               ., 2009
            </xref>
            ), and for others it is a determining factor (
            <xref ref-type="bibr" rid="b5">
               Angulo
               <italic>et al</italic>
               ., 2000
            </xref>
            ;
            <xref ref-type="bibr" rid="b45">Lecocq &amp; Visser, 2006</xref>
            ;
            <xref ref-type="bibr" rid="b71">
               Schroeter
               <italic>et al</italic>
               ., 2011
            </xref>
            ). The
            <italic>Wine Spectator</italic>
            database contained references from vintage years 1980 to 2011, with a higher concentration of vintage years 2004 and 2005. The distribution of vintage years was more balanced in the popular premium than in the super premium and ultra premium price categories.
         </p>
         <p>
            Finally, the inclusion of the winery size variable enables assessment of the impact of the scale factor on wine prices, as well as quantification of the exclusiveness that consumers can award to wines. Winery size is expected to be inversely related to price (
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b41">
               Kwong
               <italic>et al</italic>
               ., 2011
            </xref>
            ; or
            <xref ref-type="bibr" rid="b30">Delmas &amp; Grant, 2014</xref>
            ). Size classification was in accordance with the European Commission (EC) recommendation
            <sup>6</sup>
            . As the
            <italic>Wine Spectator</italic>
            database did not include this variable, other data sources, such as
            <italic>Sistema de Análisis</italic>
            de
            <italic>Balances Ibéricos</italic>
            (SABI),
            <italic>Informa D&amp;B</italic>
            , or direct consultation with wineries were necessary. Most of the reference wines (72.6%) were produced by micro and small businesses, which were the commonest sizes of firms producing wines in the higher price categories, while most lower priced wines were produced by medium-sized and large firms.
         </p>
      </sec>
      <sec id="S3">
         <title>Results</title>
         <p>The results of the estimated models are presented in <xref ref-type="table" rid="T2">Table 2</xref>. Except for appellation, the observed pattern for each attribute was similar across price categories, although the magnitudes varied.</p>
<p></p>
<table-wrap id="T2">
    <label>Table 2.</label>
    <caption>
    <title>Estimated hedonic prices models. </title>
    </caption>
    <graphic xlink:href="sjar_e0120_t02.jpg" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</table-wrap>

         <p>
            Aging was the most influential attribute. A positive relationship was found between aging and wine's prices in all price categories, except, importantly, the ultra premium category, where
            <italic>crianzas</italic>
            had more negative impact than
            <italic>joven</italic>
            wines. In the popular premium and super premium categories,
            <italic>gran reserva</italic>
            wines had more impact on prices, increasing the mean price in the category by 47.6% and 16.2% respectively. In the ultra premium category,
            <italic>boutique</italic>
            wines had the greatest impact on prices, raising them to 156% of the average price. It is worth noting that aging had less relative influence in the lower price categories and that the highest willingness-to-pay values were for
            <italic>boutique wines</italic>
            .
         </p>
         <p>A similar result was obtained for the quality rating attribute, which played a bigger role in the ultra premium category than in the others. However, the effect had the same sign in all price categories: impact on price was less positive, or becomes negative, as the quality rating decreased. It is worth noting that the quality ratings of the wines in the super premium category showed very little variation (only 9.77 points between the significant variables). This suggested that potential efforts to improve quality ratings would not significantly influence the demand for these wines. In the ultra premium category, there was a linear relationship between the quality rating and the price impact, which was positive only for wines that qualify as classic. These results highlighted the importance of an excellent quality rating (outstanding or classic), given that lower ratings had a negative or zero price impact.</p>
         <p>
            The results also revealed an inverse relationship between winery size and wine price. The impact of the exclusiveness factor was eroded in the lower price category, while it was stronger in the super premium category, where large firm size had a negative impact 4.14 percentage points higher than that of small firm size (-2.7%), while micro-firm size had a positive impact of 2.7%. In the ultra premium category, although large firm size was penalized (-6.7%), micro-wineries did not obtain higher positive impact than they did in the super premium category (2.6%) and, in fact, small wineries had more negative impact than medium-sized ones. A possible explanation for this is that the exclusiveness factor was captured, not by firm size, but by the
            <italic>boutique</italic>
            variable, which was the most influential variable in this price category.
         </p>
         <p>The type of wine was not significant in the popular premium category, while, in the super premium and ultra premium categories, the most negative impact was for rosés (-6% and -23.9% respectively) and reds had more positive impact than whites.</p>
         <p>
            Impacts on prices of the most recent vintages were more positive than the older ones in all three price categories. In the super and ultra premium categories, a linear relationship could be observed. However, in the popular premium category, three different behaviors could be identified. 80s vintages had the most negative impacts, while most of the 90s vintages were below the average price and their effect, while significant, was not very strong. The more recent vintages had a positive influence on sale price. Thus, as vintages approach the current year, impact on prices improved from negative scores to the top score which was assigned to vintage 2010 which had an impact of 13.4%
            <sup>7</sup>
            .
         </p>
         <p>
            With regard to appellation, in the popular premium category, the most positive impacts on prices were
            <italic>Bierzo, Penedès, Rioja, Toro, Catalunya</italic>
            region,
            <italic>Rueda, Somontano, Navarra, La Mancha, Jumilla</italic>
            and
            <italic>Calatayud</italic>
            , that is, a wide spread across the whole country. The most favorable impact labels among the super premium wines, however, were those from north and northwest Spain, while the majority of those with negative impacts were from the south, although there were also some from northern regions (
            <italic>Aragón, Navarra</italic>
            and
            <italic>Catalunya</italic>
            ). In the ultra premium category, most appellations (73%) had positive impact, the top going to wines from
            <italic>Ribera del Duero</italic>
            (+24.2%). The appellation with the greatest negative impact was
            <italic>Valdepeñas</italic>
            (-40.9%). It is worth noting that some appellations (
            <italic>Yecla, Utiel-Requena, Cariñena, Vinos de la Tierra de Castilla</italic>
            or
            <italic>Valdepeñas</italic>
            ) had no positive impact in any price category. Furthermore, the impacts for
            <italic>Valdepeñas</italic>
            wines decreased as their retail price increased, reflecting poor consumer-perceived quality, whereas some appellations, such as
            <italic>Rioja, Ribera del Duero, Priorat, Penedès, Rueda</italic>
            and
            <italic>Toro,</italic>
            had positive impact in all price categories where they were significant.
         </p>
         <p>
            It is also important to mention some of the results obtained for the two best-known Spanish appellations,
            <italic>Rioja</italic>
            and
            <italic>Ribera del Duero</italic>
            , which were also the two most represented in the sample. While the positive impact for the Rioja appellation diminished as the sale price increased,
            <italic>Ribera del Duero</italic>
            obtained its highest positive impact in the ultra premium price category, where most of the wines with this appellation were concentrated (84% of wines with this appellation class as ultra premium and 1.3% as popular premium). This concentration was a prestige factor that promoted willingness to purchase a
            <italic>Ribera del Duero</italic>
            in the upper price categories.
         </p>
         <p>
            <italic>Rías Baixas, Calatayud, Navarra</italic>
            or
            <italic>Montsant</italic>
            had negative impact in the higher price categories but positively in lower price categories. This appeared to suggest disinclination to purchase beyond a certain price threshold. Positive impact on prices of some appellations, such as
            <italic>Campo de Borja</italic>
            or
            <italic>Vinos de la Tierra de Castilla y León</italic>
            , on the other hand, increased with the price of the wine. The influence of other appellations was erratic and the price effect could be positive or negative.
         </p>
      </sec>
      <sec id="S4">
         <title>Discussion</title>
         <p>The first conclusion arising from the results of this research was that all the wine attributes considered in the hedonic function were valued by US consumers and had an impact on the sale price. So any business and marketing strategy directed at any of these characteristics is relevant to the positioning of a specific wine on the US market. The super premium category is a more complex decision-making environment, because the number of attributes influencing demand was greater. In other words, there are various potential product-positioning options. Special care must be taken with decision-making in the top and bottom price categories, however, because there were fewer attributes to enable market success, and therefore fewer factors on which to work.</p>
         <p>
            US consumers set great store by the aging of wine, which was, overall, the factor with most influence on the sale price (a similar result is obtained by
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez, 2002</xref>
            ;
            <xref ref-type="bibr" rid="b50">
               Melo
               <italic>et al</italic>
               ., 2005
            </xref>
            ; and
            <xref ref-type="bibr" rid="b62">Perza, 2010</xref>
            ), except in the super premium category, where other attributes, particularly vintage year and appellation, were more highly valued. Significantly, the US consumer valued length of aging and high-end price placement which reflects specific characteristics, as in the case of
            <italic>boutique</italic>
            wines, especially in the ultra premium price category. In this respect, it would be appropriate to analyze the associated costs of aging wines for longer periods, or producing a
            <italic>boutique</italic>
            wine targeted to this market, in order to determine whether it would increase profits. It is surprising to note, however, that
            <italic>crianzas</italic>
            were valued similarly or even lower than
            <italic>joven</italic>
            wines, so there may be no profit from aging wine to qualify as
            <italic>crianza</italic>
            , as suggested by
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo (2009)</xref>
            .
         </p>
         <p>
            On the other hand, it can be observed that the US consumer appreciated the chance to buy a quality wine for less than expected in the two lowest price categories, which suggests that marketing strategies based on discounts or special promotions might enable product positioning in these markets. This, combined with factors such as the good value for money that Spanish wine offers the average consumer (
            <xref ref-type="bibr" rid="b38">ICEX, 2014</xref>
            ), the high and increasing willingness of the US consumer to discover new wines (
            <xref ref-type="bibr" rid="b29">Del Rey, 2014b</xref>
            ), and the growing interest of young consumers in imported wines (
            <xref ref-type="bibr" rid="b81">Wine Market Council, 2012</xref>
            ), constitutes an incentive to design customer-attracting promotions and establish distributor/retailer agreements.
         </p>
         <p>
            The exclusiveness factor, measured by firm size, can serve as a market differentiation tool in the US because it represents added value for US consumers, who, according to results reported in the literature (
            <xref ref-type="bibr" rid="b52">Morilla &amp; Martínez, 2002</xref>
            ;
            <xref ref-type="bibr" rid="b63">Rodríguez &amp; Castillo, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b41">
               Kwong
               <italic>et al</italic>
               ., 2011
            </xref>
            ;
            <xref ref-type="bibr" rid="b30">Delmas &amp; Grant, 2014</xref>
            ), attach greater value to wines produced by micro-enterprises than to those produced by large wineries. Wine price decreased with size of winery in all price categories, but the effect was more marked in the super premium category. High-end wine market consumers showed greater appreciation of micro-wineries and greater rejection of large wineries than was the case with the consumers of less expensive wines.
         </p>
         <p>
            With regard to the type of wine, reds were more highly valued than whites or rosés, which were negatively valued by US consumers, which confirms the results obtained by
            <xref ref-type="bibr" rid="b74">Steiner (2009)</xref>
            for Spanish wines in the British market. This picture appears to mirror Spanish export volume and market share trends for the different types of wine in the US, where red wine exports have gained ground in recent years at the expense of rosés, which have shrunk significantly. In any event, this emerged as the least relevant attribute for consumers making a purchase decision, and it had no significance whatever in the lowest price category, despite having been reported as a relevant factor in other studies (
            <xref ref-type="bibr" rid="b60">Panzone &amp; Sim&#245;es, 2009</xref>
            ;
            <xref ref-type="bibr" rid="b85">
               Yoo
               <italic>et al</italic>
               ., 2011
            </xref>
            ).
         </p>
         <p>
            US consumers were found to attach very high value to expert quality ratings, especially at the high end of the market, where the importance of other factors decreases (
            <xref ref-type="bibr" rid="b71">
               Schroeter
               <italic>et al</italic>
               ., 2011
            </xref>
            ;
            <xref ref-type="bibr" rid="b26">Cuellar &amp; Claps, 2013</xref>
            ). This justifies efforts to improve classifications, especially in the ultra premium category. Our results showed a proportional relationship between quality rating and consumer valuation, as reported in past studies (
            <xref ref-type="bibr" rid="b70">Schamel &amp; Anderson, 2003</xref>
            ;
            <xref ref-type="bibr" rid="b12">
               Cacchiarelli
               <italic>et al</italic>
               ., 2014
            </xref>
            ). However, it is worth noting that only quality scores above 90 were significantly effective when it came to compensating the investment effort they required. Furthermore, strategies needed to be directed not only at achieving high quality scores but also at making them known to the public in order to stimulate demand and support higher prices (
            <xref ref-type="bibr" rid="b37">
               Hilger
               <italic>et al</italic>
               ., 2011
            </xref>
            ;
            <xref ref-type="bibr" rid="b17">Cardebat &amp; Figuet, 2014</xref>
            ).
         </p>
         <p>Vintage year was generally considered a factor of medium relevance in decision-making, and thought to have less importance at the high end than at the middle and low end of the wine market. Our analysis showed the most recent vintages to be the most highly valued, possibly due in part to the increased availability and familiarity of Spanish wines in the US market in the last few years. In any case, there would be little to be gained from exporting older vintages, especially from the cheaper end of the market, since the costs could outweigh the profits.</p>
         <p>
            Appellation and soil and climate conditions played a relevant role in consumer choices, confirming the findings of other authors (
            <xref ref-type="bibr" rid="b10">
               Brentari
               <italic>et al</italic>
               ., 2011
            </xref>
            ;
            <xref ref-type="bibr" rid="b3">Amrusch &amp; Wirl, 2013</xref>
            ;
            <xref ref-type="bibr" rid="b15">
               Caracciolo
               <italic>et al</italic>
               ., 2013
            </xref>
            ;
            <xref ref-type="bibr" rid="b64">
               Roma
               <italic>et al</italic>
               ., 2013
            </xref>
            ). The location of a winery can therefore either help or hinder its positioning in the US market. Potential investment in new wineries should therefore be carefully assessed, as the disadvantages of an erroneous location could not be reversed by enological treatments or short-term investment (
            <xref ref-type="bibr" rid="b77">Troncoso &amp; Aguirre, 2006</xref>
            ) or by brand strengthening tactics (
            <xref ref-type="bibr" rid="b8">
               Boatto
               <italic>et al</italic>
               ., 2011
            </xref>
            ).
         </p>
         <p>It is remarkable that, the various appellations in the upper price category received mostly positive ratings, supporting the idea of a certain prestige factor and a positive overall image in association with Spanish wines. However, there were few significant appellations in this category, so further promotion and positioning efforts are needed to increase awareness and acceptance by US consumers and thus improve that prestige factor.</p>
         <p>
            Overall, the highest ratings went to wines from northern Spain, while those from the southern, surrounding regions and
            <italic>Aragón</italic>
            received negative ratings. According to these findings, certain appellations, such as Y
            <italic>ecla, Utiel-Requena, Cariñena, Vinos de la Tierra de Castilla</italic>
            and, particularly,
            <italic>Valdepeñas</italic>
            , need to modify their promotional strategies, and work intensively to improve their positioning.
         </p>
         <p>
            Higher market penetration was found to enhance consumers' wine knowledge and raise their "liking" assessment, which is consistent with the findings of
            <xref ref-type="bibr" rid="b74">Steiner (2009)</xref>
            for Spanish wines in the British market. Wines from
            <italic>Rioja, Ribera del Duero, Priorat, Penedès, Rueda</italic>
            and
            <italic>Toro</italic>
            , all with strong presence in the sample, received positive ratings. The exceptions to this pattern,
            <italic>Navarra</italic>
            and
            <italic>Rías Baixas</italic>
            , need to intensify their promotion efforts and adjust their marketing strategies, as consumers showed no willingness to pay high prices for these wines. The ratings for wines from
            <italic>Campo de Borja</italic>
            or
            <italic>Vino de la Tierra de Castilla y León</italic>
            , on the other hand, increased with higher prices, which seems to suggest that they enjoy better positioning, especially in the upper price categories.
         </p>
         <p>
            In relation to this, there are public programs to promote firms exporting to foreign markets available to wineries and wine producers and a growing role is played by EU promotion programs in third countries (
            <xref ref-type="bibr" rid="b49">MAGRAMA, 2012</xref>
            ).
         </p>
         <p>
            Our results suggested that strategies for the Spanish wineries to obtain higher prices in the US wine market were dependent on the wine price category. In the popular premium category, the most influential attribute was aging. In the middle category (super premium), moreover of aging, the exclusivity factor measured through the size of the firm could play an important role. Marketing tools could be used in this area by wineries trying to improve their relative position. Additionally, wineries could take some advantage of the region of origin in this category, because this attribute had more influence in this segment. Finally, in the ultra premium category aging wines for longer periods or producing a
            <italic>boutique</italic>
            wine and try to obtain a good quality rating are the two main objectives to reach by wineries.
         </p>
         <p>Future studies might consider regional climate variables and their evolution over time, with a view to revealing possible influences and changes in buyer behavior. Further research could explore US consumer behavior and factors influencing willingness to purchase each of the appellations considered in this work.</p>
      </sec>
   </body>
   <back>
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