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Title :A data mining-based framework to identify shoppers’ missions
Alternative Title :Εφαρμογή τεχνικών εξόρυξης γνώσης για την αναγνώριση των αγοραστικών αποστολών των καταναλωτών
Creator :Griva, Anastasia
Γρίβα, Αναστασία
Contributor :Μηλιώτης, Παναγιώτης (Επιβλέπων καθηγητής)
Πραματάρη, Αικατερίνη (Εξεταστής)
Μπαρδάκη, Κλεοπάτρα (Εξεταστής)
Athens University of Economics and Business, Department of Informatics (Degree granting institution)
Type :Text
Extent :80p.
Language :en
Bibliographic Citation :Βιβλιογραφία : σ. 73-76
Abstract :Consumers' behavior and expectations for service have changed dramatically in recent years, as they have become more demanding. Many organizations have identified the need to become more customer centric, facing increased global competition (Bull, 2003; Phan & Vogel, 2010). Therefore, in order to respond to the ever increasing demands of consumers, they are trying to develop innovative methods for managing their customers (Anderson et al., 2007). At the same time computers have become far more powerful, and new technological trends have been developed, such as Big Data, Business Intelligence (BI), Data Mining (DM) (Provost & Fawcett, 2013). These new trends give us the opportunity to process large volumes of data and extract valuable information. Like any other business, so do retailers have realized the importance of applying these new technological trends to support decision making and satisfy their customers (Bertino, 2011). However, there is only sparse research in the context of retailing in order to discover patterns in customers' behavior, to empower decision making, and to satisfy the demanding consumers (Wang & Zhou, 2013).
Subject :Data mining
Consumer behaviour
Electronic data processing
Consumer motives
Consumer spending
Εξόρυξη δεδομένων
Συμπεριφορά καταναλωτή
Επεξεργασία δεδομένων
Καταναλωτικά κίνητρα
Καταναλωτική δαπάνη
Date Issued :02-2014
Licence :

File: Griva_2014.pdf

Type: application/pdf