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Heterogeneous Combinations of Knowledge Elements: How the Knowledge Base Structure Impacts Knowledge-related Outcomes of a Firm

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  • Yoichi Matsumoto

    (Research Institute for Economics & Business Administration (RIEB), Kobe University, Japan)

Abstract

Knowledge is the preeminent resource of a firm. Although many scholars have focused on the firm's knowledge base, few studies have examined the effects of the knowledge base structure—how knowledge elements are linked or separated from each other in clusters—on firm's knowledge-related outcomes. This study examines the knowledge base structure, and tests hypotheses about the effects of heterogeneous combinations of knowledge elements on the outcomes. Through an analysis of the patents related to LCD technology, (1) the usefulness of an organization's inventions correlates positively with the density of the knowledge links between technologically different knowledge components, (2) the average usefulness of a firm's inventions correlates positively with the density of the knowledge links between technologically disparate knowledge components, (3) the number of inventions correlates negatively with the density of the knowledge links between excessively disparate knowledge components.

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File URL: http://www.rieb.kobe-u.ac.jp/academic/ra/dp/English/DP2013-15.pdf
File Function: First version, 2013
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Bibliographic Info

Paper provided by Research Institute for Economics & Business Administration, Kobe University in its series Discussion Paper Series with number DP2013-15.

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Length: 36 pages
Date of creation: Apr 2013
Date of revision:
Handle: RePEc:kob:dpaper:dp2013-15

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  1. Zvi Griliches, 1990. "Patent Statistics as Economic Indicators: A Survey," NBER Working Papers 3301, National Bureau of Economic Research, Inc.
  2. Lee Fleming, 2001. "Recombinant Uncertainty in Technological Search," Management Science, INFORMS, vol. 47(1), pages 117-132, January.
  3. Michael Hahsler & Bettina Grün & Kurt Hornik, . "arules - A Computational Environment for Mining Association Rules and Frequent Item Sets," Journal of Statistical Software, American Statistical Association, vol. 14(i15).
  4. Herbert A. Simon, 1996. "The Sciences of the Artificial, 3rd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262691914, December.
  5. Fleming, Lee & Sorenson, Olav, 2001. "Technology as a complex adaptive system: evidence from patent data," Research Policy, Elsevier, vol. 30(7), pages 1019-1039, August.
  6. repec:fth:harver:1473 is not listed on IDEAS
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