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Profiling mobile business customers for mass customization

Nowadays, traditional services are being replaced by mobile or M-business that is more efficient, faster and accessible. To enable M-business operators to service many customers efficiently but with the impression of a personalized individual service, a method called mass customization is used. For...

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Main Author: Davari, Reza
Format: Thesis
Language:English
Published: 2010
Subjects:
HE Transportation and Communications
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/11397/6/RezaDavariMFSKSM2010.pdf
http://eprints.utm.my/id/eprint/11397/
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spelling my.utm.113972017-09-26T08:24:32Z http://eprints.utm.my/id/eprint/11397/ Profiling mobile business customers for mass customization Davari, Reza HE Transportation and Communications QA75 Electronic computers. Computer science Nowadays, traditional services are being replaced by mobile or M-business that is more efficient, faster and accessible. To enable M-business operators to service many customers efficiently but with the impression of a personalized individual service, a method called mass customization is used. For this service to work, detailed information about each customer is needed and is achieved by customer profiling. The big challenge is how to profile M-business customers who have very short attention span and want to quickly conclude a transaction on their mobile device to avoid expensive air time charges and restriction to their mobility. Currently, M-business companies do not have sufficient strategic information about their customers to correctly target them for mass customization. To answer this question, research was conducted in Iran and Malaysia to determine what technique is most suitable for profiling. Various on-line psychographic profiling methods are available and three methods, namely Big Five, Neuro Linguistic Programming (NLP), and ProScan were found to be most suitable. Big Five was found to be the best method but requires customers to answer 40 to 120 questions. NLP on the other hand, only requires customers to answer a minimum of 10 questions. The number of questions to be answered matters significantly in a M-business service. This was confirmed by a survey conducted in Iran and Malaysia, on the willingness of the respondents to answer profiling questions. After NLP was chosen, another survey was conducted to determine the different NLP profiles of M-business customers. This information was used to design and implement a prototype system for a mobile news service that is able to profile customers by NLP and then mass customize news messages either in the form of text, audio, or interactive multimedia messaging system. 2010-03 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/11397/6/RezaDavariMFSKSM2010.pdf Davari, Reza (2010) Profiling mobile business customers for mass customization. Masters thesis, Universiti Teknologi Malaysia, Faculty of Computer Science and Information Systems.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic HE Transportation and Communications
QA75 Electronic computers. Computer science
spellingShingle HE Transportation and Communications
QA75 Electronic computers. Computer science
Davari, Reza
Profiling mobile business customers for mass customization
description Nowadays, traditional services are being replaced by mobile or M-business that is more efficient, faster and accessible. To enable M-business operators to service many customers efficiently but with the impression of a personalized individual service, a method called mass customization is used. For this service to work, detailed information about each customer is needed and is achieved by customer profiling. The big challenge is how to profile M-business customers who have very short attention span and want to quickly conclude a transaction on their mobile device to avoid expensive air time charges and restriction to their mobility. Currently, M-business companies do not have sufficient strategic information about their customers to correctly target them for mass customization. To answer this question, research was conducted in Iran and Malaysia to determine what technique is most suitable for profiling. Various on-line psychographic profiling methods are available and three methods, namely Big Five, Neuro Linguistic Programming (NLP), and ProScan were found to be most suitable. Big Five was found to be the best method but requires customers to answer 40 to 120 questions. NLP on the other hand, only requires customers to answer a minimum of 10 questions. The number of questions to be answered matters significantly in a M-business service. This was confirmed by a survey conducted in Iran and Malaysia, on the willingness of the respondents to answer profiling questions. After NLP was chosen, another survey was conducted to determine the different NLP profiles of M-business customers. This information was used to design and implement a prototype system for a mobile news service that is able to profile customers by NLP and then mass customize news messages either in the form of text, audio, or interactive multimedia messaging system.
format Thesis
author Davari, Reza
author_facet Davari, Reza
author_sort Davari, Reza
title Profiling mobile business customers for mass customization
title_short Profiling mobile business customers for mass customization
title_full Profiling mobile business customers for mass customization
title_fullStr Profiling mobile business customers for mass customization
title_full_unstemmed Profiling mobile business customers for mass customization
title_sort profiling mobile business customers for mass customization
publishDate 2010
url http://eprints.utm.my/id/eprint/11397/6/RezaDavariMFSKSM2010.pdf
http://eprints.utm.my/id/eprint/11397/
_version_ 1643645670736789504
score 13.211869

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