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ANALYSIS OF CUSTOMER SATISFACTION FOR COMPETITIVE ADVANTAGE USING CLUSTERING AND ASSOCIATION RULES

Afolabi, I. T. and Adegoke, Fisayo (2014) ANALYSIS OF CUSTOMER SATISFACTION FOR COMPETITIVE ADVANTAGE USING CLUSTERING AND ASSOCIATION RULES. International Journal of Computer Science and Engineering (IJCSE), 3 (2). pp. 141-150. ISSN ISSN(P): 2278-9960; ISSN(E): 2278-9979

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Abstract

Customer satisfaction is a very important factor in organizational profit and positioning for effective competitive advantage requires making decisions based on quality inferences from data mining. The aim of this paper is to provide competitive advantage inferences based on analyzing customer satisfaction data using the combination of k-means clustering and association rule mining technique. Based on the information gotten from the questionnaires administered to retrieve customer satisfaction information of mobile network service providers in Nigeria, prediction is done and inferences are generated with the help of clusters and association rules. This paper proposes an effective method to extract knowledge from questionnaire data which is very useful for improving the competitive advantage of organizations. In conclusion, the paper has been able to identify the factors that contribute to customer satisfaction in the Nigeria Mobile Network sector

Item Type: Article
Uncontrolled Keywords: Competitive Advantage, K-Means Clustering, Association Rule Mining, Data Mining Customer Satisfaction
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mrs Patricia Nwokealisi
Date Deposited: 21 Oct 2015 13:42
Last Modified: 21 Oct 2015 13:42
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/5608

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