A quantitative approach to recommend promising technologies for SME innovation: a case study on knowledge arbitrage from LCD to solar cell

Woondong Yeo (), Seonho Kim (), Byoung-Youl Coh () and Jaewoo Kang ()
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Woondong Yeo: Korea University
Seonho Kim: Technology Opportunity Research Team, Korea Institute of Science and Technology Information
Byoung-Youl Coh: Technology Opportunity Research Team, Korea Institute of Science and Technology Information
Jaewoo Kang: Korea University

Scientometrics, 2013, vol. 96, issue 2, No 13, 589-604

Abstract: Abstract Small and medium-sized enterprises (SMEs) are more important today than in the past, due to their capabilities of creating jobs and boosting the economy. SMEs need continual innovation to survive in a competitive market and to continue growth. But SMEs suffer from the lack of information to generate innovative ideas. The objectives of this study are to suggest a new method to recommend promising technologies to SMEs that need “knowledge arbitrage” and to help SMEs come up with ideas on new R&D. To this end, this study used three analytic techniques: co-word analysis, collaborative filtering, and regression analysis. The suggested method is tested to assure its usefulness by the real case of knowledge arbitrage from LCD to Solar cell. The main contribution of this study is that it is the first to suggest the new method using recommendation algorithm (collaborative filtering) for SMEs’ knowledge arbitrage.

Keywords: Promising technology; Knowledge arbitrage; Small and medium-sized enterprises (SMEs); Collaborative filtering; Co-word analysis; Emerging technology; 68 (search for similar items in EconPapers)
JEL-codes: D83 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11192-012-0935-y

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