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contributor authorعلی عظیمیen
contributor authorآذر کفاش پورen
contributor authorAli Azimifa
contributor authorAzar Kaffashpoorfa
date accessioned2020-06-06T13:28:20Z
date available2020-06-06T13:28:20Z
date issued2013
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/3356238?locale-attribute=en&show=full
description abstractThis study was conducted with the main aim to investigate the relationships between the demographic

characteristics of companies and the facilities required for their commercial websites. The research

samples were the top 100 Iranian companies as ranked by the Iranian Industrial Management Institute

(IMI); the method applied is data-mining, using the Association Rules through the A-priori algorithms. To

collect the data, an author-modified checklist has been utilized covering the three areas of the facilities

within commercial websites, i.e. fundamental, information–providing, and service-delivering facilities.

Having extracted the association rules between the mentioned two sets of variables, 68 rules with a

confidence rate of 90% and above were obtained and, based on their significance, classified into two

groups of must-have and should-have requirements; a recommended package of facilities is hitherto

offered to other companies which intend to enter e-commerce through their commercial websites with

regards to each company’s unique demographic characteristics.
en
languageEnglish
titleApplying the Apriori Algorithm for Investigating the Associations Between Demographic Characteristics of Iranian Top 100 Enterprises and the Structure of Their Commercial Websitesen
typeJournal Paper
contenttypeExternal Fulltext
subject keywordse-commerceen
subject keywordscommercial websiteen
subject keywordscompaniesen
subject keywordsdemographic characteristicsen
subject keywordsdata miningen
subject keywordsassociation rulesen
journal titleInternational Journal of Data Mining and Knowledge Management Processfa
pages21-39
journal volume3
journal issue6
identifier linkhttps://profdoc.um.ac.ir/paper-abstract-1054940.html
identifier articleid1054940


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