This function computes the z-score between pairs of technologies from a patent-technology incidence matrix. The z-score is a measure to analyze the co-occurrence of technologies in patent documents (i.e. knowledge combination). It compares the observed number of co-occurrences to what would be expected under the hypothesis that combination is random. A positive z-score indicates a typical co-occurrence which has occurred multiple times before. In contrast, a negative z-socre indicates an atypical co-occurrence. The z-score has been used to estimate the degree of novelty of patents (Kim 2016), scientific publications (Uzzi et al. 2013) or the relatedness between industries (Teece et al. 1994).
A patent-technology incidence matrix with patents in rows and technologies in columns
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Kim, D., Cerigo, D. B., Jeong, H., and Youn, H. (2016). Technological novelty proile and invention's future impact. EPJ Data Science, 5 (1):1–15
Teece, D. J., Rumelt, R., Dosi, G., and Winter, S. (1994). Understanding corporate coherence. Theory and evidence. Journal of Economic Behavior and Organization, 23 (1):1–30
Uzzi, B., Mukherjee, S., Stringer, M., and Jones, B. (2013). Atypical Combinations and Scientific Impact. Science, 342 (6157):468–472
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## Generate a toy incidence matrix set.seed(2210) techs <- paste0("T", seq(1, 5)) techs <- sample(techs, 50, replace = TRUE) patents <- paste0("P", seq(1, 20)) patents <- sort(sample(patents, 50, replace = TRUE)) dat <- data.frame(patents, techs) dat <- unique(dat) mat <- as.matrix(table(dat$patents, dat$techs)) ## run the function zScore(mat)
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