Decision Tree based on data envelopment analysis for effective technology commercialization

So Young Sohn, Tae Hee Moon

Research output: Contribution to journalArticlepeer-review

61 Citations (Scopus)


In recent years, much governmental investment has been committed to R&D in the area of information technology industry. However, its commercialization rate is reported to be lower than expected. In order to prevent such waste, feedback information obtained from the rigorous evaluation of the finished R&D project needs to be utilized for future selection of new projects. The main purpose of our study is to provide the roadmap of the effective technology commercialization projects using the Decision Tree (DT) of data envelopment analysis (DEA) results when a company tries to develop or transfer its new technology. The environmental variables representing the characteristics of technology provider, receiver and technology itself are used as input variables for DT where the DEA results are used as a target variable. It is expected that our proposed approach can be effectively used to obtain the efficient scenario among the alternatives of several technology projects.

Original languageEnglish
Pages (from-to)279-284
Number of pages6
JournalExpert Systems with Applications
Issue number2
Publication statusPublished - 2004 Feb

Bibliographical note

Funding Information:
This work was supported by grant No. (R04-2002-000-20003-0). From the Basic Research Program of the Korea Science & Engineering Foundation.

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence


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