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, Jaewoo Kang

Research output: Contribution to journalArticle

4 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)589-604
Number of pages16
JournalScientometrics
Volume96
Issue number2
DOIs
Publication statusPublished - 2013 Aug 1

Fingerprint

small and medium-sized enterprise
Liquid crystal displays
Solar cells
Innovation
innovation
Industry
Collaborative filtering
Regression analysis
regression analysis
economy
lack
market

Keywords

  • Co-word analysis
  • Collaborative filtering
  • Emerging technology
  • Knowledge arbitrage
  • Promising technology
  • Small and medium-sized enterprises (SMEs)

ASJC Scopus subject areas

  • Computer Science Applications
  • Social Sciences(all)
  • Library and Information Sciences
  • Law

Cite this

A quantitative approach to recommend promising technologies for SME innovation : A case study on knowledge arbitrage from LCD to solar cell. / Yeo, Woondong; Kim, Seonho; Coh, Byoung Youl; Kang, Jaewoo.

In: Scientometrics, Vol. 96, No. 2, 01.08.2013, p. 589-604.

Research output: Contribution to journalArticle

@article{36c521e2f4b54aba877a6b44fb7be479,
title = "A quantitative approach to recommend promising technologies for SME innovation: A case study on knowledge arbitrage from LCD to solar cell",
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 = "Co-word analysis, Collaborative filtering, Emerging technology, Knowledge arbitrage, Promising technology, Small and medium-sized enterprises (SMEs)",
author = "Woondong Yeo and Seonho Kim and Coh, {Byoung Youl} and Jaewoo Kang",
year = "2013",
month = "8",
day = "1",
doi = "10.1007/s11192-012-0935-y",
language = "English",
volume = "96",
pages = "589--604",
journal = "Scientometrics",
issn = "0138-9130",
publisher = "Springer Netherlands",
number = "2",

}

TY - JOUR

T1 - A quantitative approach to recommend promising technologies for SME innovation

T2 - A case study on knowledge arbitrage from LCD to solar cell

AU - Yeo, Woondong

AU - Kim, Seonho

AU - Coh, Byoung Youl

AU - Kang, Jaewoo

PY - 2013/8/1

Y1 - 2013/8/1

N2 - 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.

AB - 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.

KW - Co-word analysis

KW - Collaborative filtering

KW - Emerging technology

KW - Knowledge arbitrage

KW - Promising technology

KW - Small and medium-sized enterprises (SMEs)

UR - http://www.scopus.com/inward/record.url?scp=84880132083&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84880132083&partnerID=8YFLogxK

U2 - 10.1007/s11192-012-0935-y

DO - 10.1007/s11192-012-0935-y

M3 - Article

AN - SCOPUS:84880132083

VL - 96

SP - 589

EP - 604

JO - Scientometrics

JF - Scientometrics

SN - 0138-9130

IS - 2

ER -