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            <front>

                <journal-meta>
                                    <journal-id></journal-id>
            <journal-title-group>
                                                                                    <journal-title>Erciyes Üniversitesi Sosyal Bilimler Enstitüsü Dergisi</journal-title>
            </journal-title-group>
                            <issn pub-type="ppub">1300-1582</issn>
                                        <issn pub-type="epub">2148-8657</issn>
                                                                                            <publisher>
                    <publisher-name>Erciyes University</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id/>
                                                                                                                                                                                            <title-group>
                                                                                                                        <article-title>Comparing Clusterings:A Store Segmentation Application</article-title>
                                                                                                                                                                                                <trans-title-group xml:lang="tr">
                                    <trans-title>Kümelemelerin Karşılaştırılması: Bir Mağaza Segmentasyonu Uygulaması</trans-title>
                                </trans-title-group>
                                                                                                    </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-9875-2299</contrib-id>
                                                                <name>
                                    <surname>Bilgiç</surname>
                                    <given-names>Emrah</given-names>
                                </name>
                                                                    <aff>MUŞ ALPARSLAN ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                    <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0003-1410-8162</contrib-id>
                                                                <name>
                                    <surname>Çakır</surname>
                                    <given-names>Özgür</given-names>
                                </name>
                                                                    <aff>MARMARA ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20180630">
                    <day>06</day>
                    <month>30</month>
                    <year>2018</year>
                </pub-date>
                                        <volume>32</volume>
                                        <issue>44</issue>
                                        <fpage>41</fpage>
                                        <lpage>57</lpage>
                        
                        <history>
                                    <date date-type="received" iso-8601-date="20171221">
                        <day>12</day>
                        <month>21</month>
                        <year>2017</year>
                    </date>
                                                    <date date-type="accepted" iso-8601-date="20180606">
                        <day>06</day>
                        <month>06</month>
                        <year>2018</year>
                    </date>
                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 1987, Erciyes University Journal of Social Sciences Institute</copyright-statement>
                    <copyright-year>1987</copyright-year>
                    <copyright-holder>Erciyes University Journal of Social Sciences Institute</copyright-holder>
                </permissions>
            
                                                                                                <abstract><p>This study focuses on one of the clusteringcomparison measures, pair counting techniques such as Rand Index, Adjusted RandIndex and Fowlkes Mallows Index. The aim is discussing their properties andshowing a marketing application of the techniques. For an application, a retailchain company’s supermarket stores are segmented with clustering analysis bytwo approach. The first clustering approach is segmenting stores based onsocioeconomic factors and the second approach is based on purchasing behaviors ofcustomers. Since consumer purchases are influenced strongly by socioeconomicfactors, this study expects to find an agreement between two clusterings. Theresults show that while Rand Index value indicates an agreement,Fowlkes-Mallows Index value has found a weak agreement and Adjusted Rand Indexvalue could not find any agreement between two clusterings.</p></abstract>
                                                                                                                                    <trans-abstract xml:lang="tr">
                            <p>Bu çalışma, kümelemelerin karşılaştırılmasıölçülerinden biri olan çiftleri sayma tekniklerini (Rand Endeksi, DüzeltilmişRand Endeksi ve Fowlkes Mallows Endeksi gibi) incelemektedir. Bu çalışmanınamacı bahsi geçen tekniklerin özelliklerini tartışmak ve tekniklerin pazarlamaalanındaki bir uygulamasını göstermektir. Uygulama olarak, zincir mağazalarasahip olan bir perakendecinin süpermarket mağazaları iki farklı yaklaşımla,kümeleme analizi kullanılarak segmentlere ayrılmıştır. İlk yaklaşımında mağazalarbulundukları yerin ve potansiyel müşterilerinin sosyoekonomik özelliklerinegöre, ikinci yaklaşımda ise mağazalar kendi müşterilerinin satın almadavranışlarına göre segmentlere ayrılmıştır. Müşteri satın alma davranışları,sosyoekonomik faktörlerden güçlü bir şekilde etkilendiği için, bu çalışmanınbeklentisi iki kümelemenin görüş birliğinde olması yönündedir. Analizlersonucunda Rand Endeksi iki kümeleme arasında bir görüş birliğinin olduğunugösterse de, Fowlkes-Mallows Endeksi zayıf bir görüş birliğine, DüzeltilmişRand Endeksi ise görüş birliğinin olmadığına işaret etmektedir.</p></trans-abstract>
                                                            
            
                                                            <kwd-group>
                                                    <kwd>comparing clusterings</kwd>
                                                    <kwd>  clustering agreement</kwd>
                                                    <kwd>  store segmentation</kwd>
                                            </kwd-group>
                                                        
                                                                            <kwd-group xml:lang="tr">
                                                    <kwd>Kümelemelerin Karşılaştırılması</kwd>
                                                    <kwd>  Kümelemelerde Görüş Birliği</kwd>
                                                    <kwd>  Mağaza Segmentasyonu</kwd>
                                            </kwd-group>
                                                                                                            </article-meta>
    </front>
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