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

Hyo Shin Choi; So Young Sohn; Ho Jeong Yeom

doi:10.1016/j.techfore.2018.05.013

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

Hyo Shin Choi, So Young Sohn, Ho Jeong Yeom

Department of Industrial Engineering

Research output: Contribution to journal › Article › peer-review

5 Citations (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 language	English
Pages (from-to)	72-83
Number of pages	12
Journal	Technological Forecasting and Social Change
Volume	134
DOIs	https://doi.org/10.1016/j.techfore.2018.05.013
Publication status	Published - 2018 Sept

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) ( 2016R1A2A1A05005270 ).

Publisher Copyright:
© 2018 Elsevier Inc.

All Science Journal Classification (ASJC) codes

Business and International Management
Applied Psychology
Management of Technology and Innovation

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10.1016/j.techfore.2018.05.013

Cite this

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title = "Technological composition of US metropolitan statistical areas with high-impact patents",

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.",

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AU - Choi, Hyo Shin

AU - Sohn, So Young

AU - Yeom, Ho Jeong

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

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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