DOES REGIONAL INNOVATION OCCUR ACROSS GEOGRAPHICAL BOUNDARIES?

EXAMINING UNIVERSITY-INDUSTRY LINKAGE IN SOUTH KOREA USING A MIXED METHOD

Ki-Seok Kwon, Seolah KIM & Han Woo PARK

2011. 4. 2.

Contents

I. Introduction

II. Method

III. Results

V. Discussion & Summary

I. Introduction

Introduction

Importance of the exploitation of university research has echoed academia as well as policy communities

To find the effective U-I condition, a great number of researches have been carried out

- the relationship between the internal (e.g. size and legal status) and external (e.g. loc-ation and industrial background) character-istics of the two actors (i.e. universities and firms) and their knowledge transfer activities

Introduction

Basically, the university-industry linkage can be regarded as a part of network of innovation actors. However, few studies have directly applied social network ana-lysis (Van Der Valk et al., 2010)

Different from the strong research univer-sities in developed countries (e.g. MIT and Stanford University), Korean universities’ academic research has been hardly con-nected to industrial innovation (Eom & Lee, 2010).

Geographical proximity of university to industry and universities’ KT activities

The U.S. universities located in a re-gion with a concentration of high-tech industry are more likely to be involved in knowledge-transfer activ-ity (Friedman & Silberman, 2003)

The companies closer to universities are more likely to provide R&D fund-ing to the universities in the U.S (Mansfield & Lee,1996)

Geographical proximity of university to industry and universities’ KT activities

Based on a significant positive correla-tion between the R&D expenditure of the US universities and patenting activity of local firms at state level, Jaffe (1989) fo-cuses on the localised knowledge-spillover activities of universities

In a German case, Audretsch et al. (2004) confirm that geographical proxim-ity is an important factor for human re-source flow between university and in-dustry

II. Method

Method – a mixed approach

In 2007, total of 2,395 faculty mem-bers across sixteen Korean provinces including metropolitan areas took part in the survey

Social network analysis : this study more focuses on the link (i.e. univer-sity-industry linkages) and the charac-teristics of nodes (i.e. gender, age and geographical location) of two actors

III. Results

Intra- and Inter-provincial U-I Collabor-ation in 16 Regions in South Korea

R&D Expenditure Rate by Sector of Performance and Region in 2007

Sector of

Performanc

e

R&D exp. By

sector

(mil. won)

Region (%)

TotalSE

OU

L

BU

SA

N

DA

E

G

U

IN

C

HE

O

N

GW

AN

GJU

DA

EJE

ON

ULS

AN

GY

EO

NGI

G

AN

G

W

O

N

C

H

U

N

G

BU

K

C

H

U

N

G

NA

M

JE

O

NB

UK

JE

O

N

NA

M

G

YE

O

N

G

BU

K

G

YE

O

N

G

N

M

JE

JU

PRIs 4,102,366 17.83 1.85 1.38 3.62 1.27 44.11 0.15 16.48 0.75 0.32 3.61 1.16 0.42 2.74 3.82 0.48 100

Universities 3,334,119 39.70 7.44 3.49 2.73 5.85 6.94 0.44 12.53 2.61 2.30 3.37 2.36 0.93 6.13 2.65 0.54 100

Firms 23,864,893 17.30 2.29 1.01 6.02 1.07 5.53 1.39 46.81 0.36 2.13 5.21 1.07 0.79 4.50 4.36 0.16 100

Total 31,301,377 19.76 2.78 1.32 5.36 1.60 10.73 1.13 39.18 0.65 1.91 4.81 1.22 0.75 4.44 4.11 0.24 100

Source: data based on MEST (2008), Survey of Research and Development in Korea 2008, Korean Ministry of Education, Science and Technology.

Korean Universities’ and Firms’ R&D Expenditure Rate and their degree of internal collaboration in 16 Regions in 2007

Structure of Inter-provincial Collaboration Network using a Circle Lay-out Algorithm

V. Discussion and Summary

Discussion and Summary

Seoul and Gyunggi are identified as central nodes. That is, the academics in other regions tend to collaborate with firms in this region. The rich resource condition such as R&D ex-penditure can be an explanation (Shaprio et al., 2010). However, the other regions such as Jeju and Jeonbuk Dagu with a relatively small amount of R&D expenditure have shown a strong intra-collaboration. In addition to the central hub of the network, we also identified several peripheral clusters grounded upon the geographical proximity

Discussion and Summary

However, we have not yet analysed the types of channel (e.g. consulting, ex-change of personals and co-operative re-search) in the network. In a final version of this paper, we expect to delineate a net-work with richer information by adding these factors to the analysis of the net-work.

Q & A