A bibliometric method for measuring the degree of technological innovation

Woondong Yeo, Seonho Kim, Hyunwoo Park, Jaewoo Kang

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

Knowing the degree and stage of a product's innovation is essential for technological forecasting and beneficial for governments and firms that want to come up with product promotion strategies and prioritize investments. Bibliometric analysis has been widely used as a practical tool to evaluate scientific activities. Although there were many bibliometric-based attempts to model product innovation stages, there have not been any trials that approach it from the standpoint of uncertainty reduction in technological product innovation. This paper suggests two hypotheses: 1) at a macro level, the year-to-year difference in relative research volumes of each component decreases over time as the uncertainty of a product decreases; and 2) at a micro level, the year-to-year difference in relative research volumes of each component is correlated with the technological life cycle of a product's core component. In addition, we provide empirical evidence that supports the hypotheses in the case study of mobile phones. From the evidence, we conclude that bibliometric analysis using research papers can measure the uncertainty in a product's technological innovation.

Original languageEnglish
Pages (from-to)152-162
Number of pages11
JournalTechnological Forecasting and Social Change
Volume95
DOIs
Publication statusPublished - 2015 Jun 1

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Keywords

  • Bibliometrics
  • Data mining
  • Kullback-Leibler divergence
  • Mobile phone
  • Product life cycle (PLC)
  • Technological product innovation
  • Technology forecasting

ASJC Scopus subject areas

  • Business and International Management
  • Management of Technology and Innovation
  • Applied Psychology

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