A QFD Approach for Cloud Computing Evaluation and Selection in KMS: A Case Study

Chin Nung Liao, Hsing Pei Kao

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Cloud computing services are a new information technology trend for business applications in knowledge management systems (KMS). The link between cloud computing services and KMS is a new concept, and methods for selecting multiple choice goals of cloud computing service provider have lacked a formal reference framework. From the perspectives of customer needs and technology requirements, selecting the right cloud computing service supplier for KMS is a key strategic consideration. This paper presents an integrated analytical hierarchy process (AHP), quality function development (QFD) and multi-choice goal programming (MCGP) method to address the cloud computing service provider selection problem in KMS for information service. To show the practicality and usefulness of the proposed method, a case study of a Taiwanese textbook company is presented. This paper shows that the proposed model is a good decision-making tool for the selection of new information technology.

Original languageEnglish
Pages (from-to)896-908
Number of pages13
JournalInternational Journal of Computational Intelligence Systems
Volume7
Issue number5
DOIs
StatePublished - 3 Sep 2014

Keywords

  • analytical hierarchy process (AHP)
  • cloud computing
  • knowledge management systems (KMS)
  • multi-choice goal programming (MCGP)
  • quality function development (QFD)

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