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General Information
    • ISSN: 2010-3700
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Engineering & Technology Digital Library, Google Scholar, Crossref, ProQuest, Electronic Journals Library, DOAJ and EI (INSPEC, IET).
    • E-mail: ijmlc@ejournal.net
Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(6): 524-528 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.374

Measuring the ICT Maturity of Enterprises under Uncertainty Using Group Fuzzy ANP

Pham Xuan Kien, Le Ngoc Son, and Nguyen Thi Phuong Giang
Abstract—Generally, measuring the Information and Communication Technology (ICT) maturity is the first step to build a new knowledge system in an enterprise. Knowing their ICT maturity also helps enterprises make a plan for improving the ICT state to strengthen their competitive capability. In this paper, the ICT maturity is based on four main factors: Infrastructure, Application, Human Resource and Policy. The concept of fuzzy set is applied to Analytic Network Process (ANP) to propose a model for measuring enterprise’s ICT maturity under uncertain environment. Using group fuzzy ANP approach helps determine more efficiently importance weights of factors and indicators, especially deal with imprecise and uncertain human comparison judgments. A case study is used to illustrate the better new method of ICT maturity measurement.

Index Terms—Fuzzy logic, ANP, ICT maturity.

The authors are with University of Electronic Science and Technology of China, Chengdu, 610054, China (e-mail: pxkien@yahoo.com, lengocsonit@gmail.com, phuonggiang1179@gmail.com).

[PDF]

Cite:Pham Xuan Kien, Le Ngoc Son, and Nguyen Thi Phuong Giang, "Measuring the ICT Maturity of Enterprises under Uncertainty Using Group Fuzzy ANP," International Journal of Machine Learning and Computing vol.3, no. 6, pp. 524-528, 2013.

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