Characterisation of e-commerce website structures using webometrics and social network analysis methods

The hyperlinks among Web pages of intra- and inter- Websites, are believed to have valuable information that is hidden in the structure. Exploitation of these hyperlinks using Web structure mining methods is expected to increase the understanding about how Website’s internal and external hyperlink s...

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Main Author: Kannan, Rathimala
Format: Thesis
Published: 2012
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id my-mmu-ep.5220
record_format uketd_dc
spelling my-mmu-ep.52202014-02-17T01:44:57Z Characterisation of e-commerce website structures using webometrics and social network analysis methods 2012-12 Kannan, Rathimala HF Commerce The hyperlinks among Web pages of intra- and inter- Websites, are believed to have valuable information that is hidden in the structure. Exploitation of these hyperlinks using Web structure mining methods is expected to increase the understanding about how Website’s internal and external hyperlink structures are interlinked and what information they hold. This research aims to characterise the commercial Website structure of a company and investigate its relationship with the company’s Web traffic and business performance. It attempts to extract the overall structure of commercial Websites and identify the optimal internal structural design. This structure represents the Website page organisation that ensures easy navigation and improved usability which subsequently increases the Web traffic. Data for this study comes from the top five hundred Asia Pacific retail companies as they are the leaders in the retail industry of Asia Pacific region and have well established Websites. The retail companies are divided into seven subgroups based on their retail sector. 2012-12 Thesis http://shdl.mmu.edu.my/5220/ http://vlib.mmu.edu.my/diglib/login/dlusr/login.php phd doctoral Multimedia University Graduate School of Management
institution Multimedia University
collection MMU Institutional Repository
topic HF Commerce
spellingShingle HF Commerce
Kannan, Rathimala
Characterisation of e-commerce website structures using webometrics and social network analysis methods
description The hyperlinks among Web pages of intra- and inter- Websites, are believed to have valuable information that is hidden in the structure. Exploitation of these hyperlinks using Web structure mining methods is expected to increase the understanding about how Website’s internal and external hyperlink structures are interlinked and what information they hold. This research aims to characterise the commercial Website structure of a company and investigate its relationship with the company’s Web traffic and business performance. It attempts to extract the overall structure of commercial Websites and identify the optimal internal structural design. This structure represents the Website page organisation that ensures easy navigation and improved usability which subsequently increases the Web traffic. Data for this study comes from the top five hundred Asia Pacific retail companies as they are the leaders in the retail industry of Asia Pacific region and have well established Websites. The retail companies are divided into seven subgroups based on their retail sector.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Kannan, Rathimala
author_facet Kannan, Rathimala
author_sort Kannan, Rathimala
title Characterisation of e-commerce website structures using webometrics and social network analysis methods
title_short Characterisation of e-commerce website structures using webometrics and social network analysis methods
title_full Characterisation of e-commerce website structures using webometrics and social network analysis methods
title_fullStr Characterisation of e-commerce website structures using webometrics and social network analysis methods
title_full_unstemmed Characterisation of e-commerce website structures using webometrics and social network analysis methods
title_sort characterisation of e-commerce website structures using webometrics and social network analysis methods
granting_institution Multimedia University
granting_department Graduate School of Management
publishDate 2012
_version_ 1747829564969582592