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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Univrsity Of Tehran Press</PublisherName>
				<JournalTitle>Journal of Information Technology Management</JournalTitle>
				<Issn>2980-7972</Issn>
				<Volume>8</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>07</Month>
					<Day>22</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Ultra Innovative Approach to Integrate Cellphone Customer Market Segmentation Model Using Self Organizing Maps and K-Means Methodology</ArticleTitle>
<VernacularTitle>روش فرا ابتکاری در یکپارچه‎سازی مدل بخش‎بندی بازار مشتریان تلفن همراه تهران با استفاده از شبکه‎های خودسازمان‎ده و روش میانگین کا</VernacularTitle>
			<FirstPage>351</FirstPage>
			<LastPage>372</LastPage>
			<ELocationID EIdType="pii">57233</ELocationID>
			
<ELocationID EIdType="doi">10.22059/jitm.2016.57233</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad Reza</FirstName>
					<LastName>Karimi Alavijeh</LastName>
<Affiliation>Associate Prof., Faculty of Management, Allameh Tabatabaei University, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Saeed</FirstName>
					<LastName>Khadangi</LastName>
<Affiliation>MSc. Student in Marketing Management, Faculty of Management Allameh Tabatabaei University , Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Saleh</FirstName>
					<LastName>Torkestani</LastName>
<Affiliation>Associate Prof., Faculty of Management, Allameh Tabatabaei University, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>12</Month>
					<Day>25</Day>
				</PubDate>
			</History>
		<Abstract>The utilization of 3G and 4G is rapidly increasing and also cellphone users are briskly changing their consumption behavior, using preferences and shopping manner. Accordingly, cellphone manufacturers should create an accurate insight of their target market and provide a “special offer” to their target consumers. In order to reach a correct understanding of the target market, consumption behavior and lifestyle of the submarkets we found the appropriate number of community clusters after criticizing the traditional methods and introducing market segmentation techniques which were based on neural networks. By utilizing the fuzzy Delphi technique, variables of target market segmentation were found. Finally, the obtained clusters and segmentations of the market were refined by using the techniques of K-means and aggregation (Agglomerative). The population of this research included the consumers of mobile in Tehran with a sample of 130 specimens after collecting data through questionnaires, results demonstrated that the Tehran cellphone market was comprised of 5 Clusters, each one are capable of implementing marketing strategy and marketing mix separately with taking into account the competitive advantages of ICT companies to maximize their demand and margin.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Market segmentation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Self-organizing Maps</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Neural Networks</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Data Mining</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Delphi-fuzzy method</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Clustering</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jitm.ut.ac.ir/article_57233_529ba5a19b021522cd8fab25d27392ac.pdf</ArchiveCopySource>
</Article>
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