Supply chain risk driver extraction using text mining technique

Saxa Moriizumi, Bongsung Chu, Haiyan Cao, Hiroaki Matsukawa

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


In this article we extracting supply chain risk drivers, which are the source factors of risk in supply chain risk management (SCRM). The author tried to extract, classify and analyze supply chain risk drivers from existing academic research papers covered by major eight data bases, such as science direct, EBSCOhost, Interscience, oxfordjoumals, informaworld, emeraldinsight, springerlink and Cambridge. 555 papers related to SCRM were colected using keyword search from the data bases. After pre-testing the efficiency of of IBM text mining tool, the "COGNOS CONTENT ANALYTICS", applying the tool to a tipical SCRM survey paper, archived 555 abstracts were analyzed using the tool. We finally got an objective result of SCRM drivers both for process and business operations of SCM eleminating personal biases.

Original languageEnglish
Pages (from-to)1935-1945
Number of pages11
Issue number6
Publication statusPublished - 2011 Jun 1
Externally publishedYes

ASJC Scopus subject areas

  • Information Systems


Dive into the research topics of 'Supply chain risk driver extraction using text mining technique'. Together they form a unique fingerprint.

Cite this