Technological composition of US metropolitan statistical areas with high-impact patents

Hyo Shin Choi, So Young Sohn, Ho Jeong Yeom

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Based on citations per patent (CPP) published from August 2010 to July 2015, this study identifies the technological impact structure of regions across US metropolitan statistical areas (MSAs). Gini coefficients are used to compare the CPP concentration levels of MSAs, while exploratory factor analysis is applied to identify the colocation of CPP fields. Hot spots of CPP factors are explored using Getis-Ord Gi*. The results reveal variations among the CPP concentration levels and colocated technology fields. The Getis-Ord Gi* results show that Syracuse (NY), Salem (OR), and Salinas (CA) are the hot spots for various fields. These findings help regions enhance their competitive advantage.

Original languageEnglish
Pages (from-to)72-83
Number of pages12
JournalTechnological Forecasting and Social Change
Volume134
DOIs
Publication statusPublished - 2018 Sep

All Science Journal Classification (ASJC) codes

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

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