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Using webcrawling of publicly available websites to assess e-commerce relationships

 
: Thorleuchter, Dirk; Poel, Dirk van den

:
Preprint urn:nbn:de:0011-n-2195592 (297 KByte PDF)
MD5 Fingerprint: 0e5e7ad15701fe8edac0896393f98ae0
© 2012 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Created on: 6.12.2012


IEEE Computer Society; Service Research and Innovation Institute -SRII-, Los Gatos/Calif.:
Annual SRII Global Conference 2012. Proceedings : Driving Innovation for IT Enabled Services; 24-27 July 2012, San Jose, California, USA
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2012
ISBN: 978-1-4673-2318-5 (Print)
ISBN: 978-0-7695-4770-1 (Online)
pp.402-410
Service Research and Innovation Institute (Annual SRII Global Conference) <2012, San Jose/Calif.>
English
Conference Paper, Electronic Publication
Fraunhofer INT ()
B-B; classification; SVD; success factor; textmining; website

Abstract
We investigate e-commerce success factors concerning their impact on the success of commerce transactions between businesses companies. In scientific literature, many e-commerce success factors are introduced. Most of them are focused on companies' website quality. They are evaluated concerning companies' success in the business-to- consumer (B2C) environment where consumers choose their preferred e-commerce websites based on these success factors e.g. website content quality, website interaction, and website customization. In contrast to previous work, this research focuses on the usage of existing e-commerce success factors for predicting successfulness of business-to-business (B2B) ecommerce. The introduced methodology is based on the identification of semantic textual patterns representing success factors from the websites of B2B companies. The successfulness of the identified success factors in B2B ecommerce is evaluated by regression modeling. As a result, it is shown that some B2C e-commerce success factors also enable the predicting of B2B e-commerce success while others do not. This contributes to the existing literature concerning ecommerce success factors. Further, these findings are valuable for B2B e-commerce websites creation.

: http://publica.fraunhofer.de/documents/N-219559.html