Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1147
Title: Online Art Buying Decision Support: A Multivariate Approach
Authors: Koutsoupias, Nikos
Type: Conference Paper
Subjects: FRASCATI::Social sciences
Keywords: art sales
e-business ranking
ranking data
multiple correspondence analysis
decision support
Issue Date: 2018
Publisher: Εργαστήριο Διεθνών Σχέσεων και Ευρωπαϊκής Ολοκλήρωσης του Πανεπιστημίου Μακεδονίας
Source: Proceedings if the ICIB2017-18 Conference
First Page: 164
Last Page: 169
Volume Title: Proceedings of the International Conference of International Business
Abstract: We introduce a new perspective in visualizing rankings of online sales platforms created as a decision support tool on behalf of international fine art buyers and collectors. By means of Multiple Correspondence Analysis, a descriptive statistics multivariate data analysis method, groups of top-ranked online sellers are extracted and mapped taking into consideration all available ranking variables: Visits Movement, Purchases, Buyer and Visitor Experience. This research enables prospective online art buyers to take evidence-based decisions derived from multivariate ranking data originating from internet seller platform surveys.
URI: https://zenodo.org/record/2576124#.YqxGUHZBxPY
https://ruomo.lib.uom.gr/handle/7000/1147
Electronic ISBN: 978-618-5255-12-1
ISSN: 2241-5645
Other Identifiers: 10.5281/zenodo.2576124
Appears in Collections:Department of International and European Studies

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