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

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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.

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Notes

  1. Hamel (2002) defined “knowledge arbitrage” as the process to find new applications (e.g., market, industry, product and so on) that are not originally intended. Having a related meaning to knowledge arbitrage, Carayannis (2007, 2011) used “strategic knowledge arbitrage” as “the ability to distribute and repurpose specific knowledge for applications other than the intended topic area for that knowledge or more specifically”.

  2. In this paper, technology means both the technology that the company owns and the product that the company sells.

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Acknowledgments

This research was supported by the National Research Foundation of Korea (NRF) grant (2012R1A2A2A01014729) and the Converging Research Center Program grant through the NRF(2012M3C4A7033341) funded by the Ministry of Education, Science and Technology.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Korea University, 5-Ga Anam-Dong, Seongbuk-Gu, Seoul, 136-713, Korea

    Woondong Yeo & Jaewoo Kang

  2. Technology Opportunity Research Team, Korea Institute of Science and Technology Information, 66, Hoegi-ro, Dongdaemun-gu, Seoul, 130-741, Korea

    Woondong Yeo, Seonho Kim & Byoung-Youl Coh

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  1. Woondong Yeo
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Correspondence to Jaewoo Kang.

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Yeo, W., Kim, S., Coh, BY. et al. A quantitative approach to recommend promising technologies for SME innovation: a case study on knowledge arbitrage from LCD to solar cell. Scientometrics 96, 589–604 (2013). https://doi.org/10.1007/s11192-012-0935-y

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