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Measuring relatedness between technological fields

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Abstract

Intensified technology convergence, increasing relatedness between technological fields, is a mega-trend in 21st century science and technology. However, scientometrics has been unsuccessful in identifying this techno-economic paradigm change. To address the limitations and validity problems of conventional measures of technology convergence, we introduce a multi-dimensional contingency table representation of technological field co-occurrence and a relatedness measure based on the Mantel–Haenszel common log odds ratio. We used Korean patent data to compare previous and proposed methods. Results show that the proposed method can increase understanding of the techno-economic paradigm change because it reveals significant changes in technological relatedness over time.

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Notes

  1. Because most countries other than the United States use a first-to-file system, which grants a patent for a given invention to the first applicant of that invention, inventors are more pressured to prepare and file the application as soon as possible. Therefore, the application date of a patent best reflects the timing of the invention.

  2. The IPC entered into force in 1975, under the Strasbourg Agreement of 1971, and it is currently being used in more than 100 countries. Korean Intellectual Property Office adopted IPC system in 1980.

  3. The analysis of patent classification data may be distorted by an “indexer bias” (Healey et al. 1986). However, the indexer bias in patent classification data is partly controlled by the strict guidelines and systematic process of IPC assignment.

  4. C ij is treated as zero or missing, because it does not indicate the frequency of co-occurrence (Mccain 1991).

  5. Nevertheless, all the information the raw data proffer is not fully utilized, because classification analysis focuses on if two focal TFs co-occur or not, and neglects other TFs’ occurrences.

  6. A comprehensive introduction to categorical data analysis is well beyond the scope of this paper. We refer readers to Agresti (2002) for details of categorical data analysis.

  7. Associations between two categorical variables can be measured by either an odds ratio or log-linear models. When C is small, relatedness between TFs can be measured by estimating first-order interaction terms of a quasi log-linear model. The quasi log-linear model for a 2C contingency table has 1 + C + C × (C − 1)/2 parameters to be estimated, and the quasi log-linear model for this example has 11 parameters. Because the number of parameters to be estimated sharply increases as C increases, it is practically impossible to apply a quasi log-linear model to measure relatedness between TFs.

  8. See Table 2.

  9. Relatedness between technological fields measured by four different measures over four periods will be provided by request.

  10. Two technological fields can be found negatively related by the Mantel–Haenszel common odds ratio (M ij ), however, no pair of technological fields is negatively related at p < 0.01. The pair of technological fields that negatively related most strongly has the p-value of 0.45.

  11. The results of S ij , R ij and τ ij will be provided by request.

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Authors and Affiliations

  1. Technology Management, Economics and Policy Program, School of Engineering, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul, 151-742, Republic of Korea

    Si Hyung Joo & Yeonbae Kim

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  1. Si Hyung Joo
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  2. Yeonbae Kim
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Correspondence to Yeonbae Kim.

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Joo, S.H., Kim, Y. Measuring relatedness between technological fields. Scientometrics 83, 435–454 (2010). https://doi.org/10.1007/s11192-009-0108-9

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