Triple Helix

A Journal of University-Industry-Government Innovation and Entrepreneurship

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Effect of international collaboration on knowledge flow within an innovation system: a Triple Helix approach

Triple HelixA Journal of University-Industry-Government Innovation and Entrepreneurship20152:16

https://doi.org/10.1186/s40604-015-0027-0

Received: 30 June 2015

Accepted: 20 October 2015

Published: 2 November 2015

Abstract

Research papers that studied the Triple Helix in relation to international co-authorship considered international collaboration as the fourth element of the system. This paper suggests considering three levels of study to assess the effect of international collaboration on an innovation system: the domestic one, the foreign one and the global one. The mutual information and the transmission power are used as indicators. Bibliographic data of South Korea and the West African region for a 10-year period (2001–2010) were downloaded and imported to a bibliographic software application. Searches are run to determine the Triple Helix actors and their bi- or trilateral collaboration contributions per considered area, year and level. Then, the mutual information and the transmission power were computed. Results show that at the domestic level, the South Korean innovation system is more integrated, whereas the West African one is less integrated than that of their partners. Results also show that international collaboration has strengthened knowledge sharing at the domestic level for both South Korea and West Africa, but to a different extent; in other words, the two areas have benefited from international collaboration in terms of knowledge flow.

Keywords

Triple HelixInnovationKnowledge-based economyMutual informationTransmission power

French

Les effets de la collaboration internationale sur le flux des connaissances au sein d’un système d’innovation : une approche de type Triple Hélice

Résumé

Les articles de recherche qui se sont intéressés à la Triple Hélice en relation avec les publications internationales à signatures multiples envisagent la collaboration internationale comme le quatrième élément du système. L’article considère trois niveaux d’étude pour rendre compte de l’effet de la collaboration internationale sur un système d’innovation :le niveau interne, externe, et global. L’information mutuelle et la puissance de la transmission sont utilisées comme indicateurs. Des données bibliographiques sur la Corée du Sud et l’Afrique de l’Ouest sur une période de dix ans (2001-2010) ont été téléchargées et importées vers une application bibliographique. On a recensé les acteurs de la Triple Hélice et leurs contributions de collaboration bi- ou trilatérale par zone considérée, année et niveau de collaboration. Puis, on a calculé l’information mutuelle et la puissance de transmission. Les résultats montrent qu’au niveau interne le système d’innovation de la Corée du Sud est plus intégré que celui de ses partenaires, à l’inverse de celui d’Afrique de l’Ouest qui l’est moins. Les résultats montrent aussi que la collaboration internationale renforce le partage des connaissances au niveau interne dans les deux régions mais dans une mesure différente ; en d’autres termes les deux régions ont profité de la collaboration internationale en termes de flot de connaissances.

Spanish

El efecto de la colaboración internacional en el flujo del conocimiento dentro de un sistema de innovación: La perspectiva de la Triple Hélice

Resumen

La literatura de la Triple Hélice en relación a la co-autoría considera que la colaboración internacional es un cuarto elemento del sistema. En este trabajo se sugiere considerar tres niveles de estudio para evaluar el efecto de la colaboración internacional en un sistema de innovación: el nacional, el exterior y el global. La “información mutua” y la “potencia de transmisión” se utilizan como indicadores. Datos bibliográficos de Corea del Sur y de la región de África Occidental por el período de diez años entre 2001 y 2010 fueron descargados e importados a una aplicación de software bibliográfico. Las búsquedas ejecutadas establecieron el carácter de la contribución (bi o trilateral) de los actores de la Triple Hélice según área, año, y nivel. Luego, la información mutua y la potencia de transmisión fueron calculadas. Los resultados muestran que en el ámbito interno, el sistema de innovación de Corea del Sur está más integrado que el África Occidental. El contraste es aún más claro con respecto de los socios internacionales de ambas regiones. No obstante de ello, los resultados muestran que la colaboración internacional ha fortalecido el intercambio de conocimientos a nivel nacional, tanto para Corea del Sur como para África Occidental; en otras palabras, las dos áreas se han beneficiado de la colaboración internacional en términos de flujo de conocimiento.

Chinese

在西非技术创新体系内的信息流

摘 要:

我们把交互信息和传输功率用作在创新主体之间的知识循环的指标。在科学出版物中的分析单位用至少一个基于西非的地址在科学网上进行索引收录。我们发现,在区域的层次上,大学是最大的知识生产者,其次是政府,最后是产业; 然而,在国家的层面上,在大多数国家里政府是最大的信息生产者。无论在区域还是在国家层面上,产业部门的输出都很弱。 在一些国家它甚至等于零。 交互信息表明,在区域和国家层面上都有(三螺旋)三个创新主体之间的协同作用的存在。然而,这种作用的值太低,以至于不能让知识畅快地在主体之间循环。

Russian

Влияние международного сотрудничества на движение знаний в инновационной системе: трехспиральный подход

Аннотация

В исследованиях, в которых рассматривается Тройная спираль в связи с интернациональным соавторством, международное сотрудничество выделяется в качестве четвертого элемента системы. В настоящей работе предлагается изучение эффектов от международного сотрудничества на трех уровнях: национальном, зарубежном и глобальном. В качестве показателей были использованы взаимное информирование и мощность передачи. Авторами систематизированы публикации в Южной Корее и Западно-Африканском регионе за 10-летний период (2001-2010) и исследованы в специализированном программном приложении для проведения библиографического анализа. Поиск проводился с целью выявления участников Тройной спирали и их двух- или трехстороннего сотрудничества в рассматриваемых секторах, годах и уровнях. Затем были рассчитаны взаимное информирование и мощность передачи. Результаты показали, что на национальном уровне Южнокорейская инновационная система является более интегрированной, в то время как Западно-Африканский регион демонстрируется меньшую вовлеченность по сравнению со своими партнерами. Также полученные данные позволили сделать вывод, что международное сотрудничество способствует интенсификации обмена знаний на национальном уровне как в Южной Корее, так и Западной Африке, но в разной степени; другими словами, два региона получают преимущества от международного сотрудничества в контексте движения знаний.

Portuguese

O efeito da colaboração internacional no fluxo de conhecimento dentro do sistema de inovação: uma abordagem de Hélice Tríplice

Resumo

Artigos de pesquisa que estudaram a hélice tríplice em relação com a co-autoria internacional consideraram a colaboração internacional como o quarto elemento do sistema. Esse artigo sugere considerar três níveis de estudo para avaliar o efeito da colaboração internacional em um sistema de inovação: o doméstico, o estrangeiro e o global. A informação mútua e o poder de transmissão foram utilizadas como indicadores. Dados bibliográficos da Coréia do Sul e da região da África Ocidental foram extraídos por um período de 10 anos (2001-2010) e importados para uma aplicação de software bibliográfico. Pesquisas foram realizadas para determinar os atores da Hélice Tríplice e suas contribuições de colaborações bi ou trilaterais por área considerada, ano e nível. Em seguida, a informação mútua e o poder de transmissão foram computados. Resultados mostram que, a um nível interno, o sistema de inovação Sul Coreano é mais integrado, enquanto que o da África Ocidental é menos integrado do que o de seus parceiros. Resultados mostraram também que a colaboração internacional tem reforçado o compartilhamento de conhecimento a nível nacional tanto para Coréia do Sul e África Ocidental, mas com diferenças de extensão; em outras palavras, as duas áreas se beneficiaram da colaboração em termos de fluxo de conhecimento.

Multilingual abstract

Please see Additional file 1 for translation of the abstract into Arabic.

Introduction

Two types of models of innovation were proposed up to now to explain the functioning of an economy: the linear and the nonlinear models. Each explains how growth is generated. The linear model postulated that ‘innovation starts with basic research, is followed by applied research and development, and ends with production and diffusion’ (Godin 2005; Godin 2006; Godin 2014). The nonlinear model introduced with the national innovation system concept ‘suggests that the research system’s ultimate goal is innovation and that the system is a part of a larger system composed of sectors like government, university and industry and their environment. The system also emphasized the relations between the components or sectors as the “cause” explaining the performance of innovation systems’ (Godin 2007). Both models have been criticised (Godin 2005; Godin 2006; Godin 2007) and variants of them were proposed. In the national innovation system model, analysis focuses on the flows of knowledge between actors (OECD 1997).

The Triple Helix laid down by Etzkowitz and Leydesdorff (1995) and Etzkowitz and Leydesdorff (2000) is one of the variants of the nonlinear model of innovation (cf. Etzkowitz and Leydesdorff 2000; Leydesdorff 2012; Meyer et al. 2014). The model postulates that the interactions between university, industry and government maintain a knowledge infrastructure that generates knowledge of which circulation among innovation actors drives economic growth and social welfare (Leydesdorff and Etzkowitz 2001). The mutual information (Leydesdorff 2003) was elaborated as an indicator of the Triple Helix relationships between university, industry and government. It has been used widely to assess countries or region profiles (e.g. Leydesdorff and Sun 2009; Khan and Park 2011; Shin et al. 2012; Leydesdorff et al. 2013a; Mêgnigbêto 2013a; Mêgnigbêto 2015a; Mêgnigbêto 2015b) or assess the knowledge base of economies (e.g. Park et al. 2005; Park et al. 2005; Leydesdorff and Zhou 2013; Leydesdorff et al. 2015). The transmission power was proposed by Mêgnigbêto (2014a) as the normalisation of the mutual information. It was used to assess the knowledge flow within the West African innovation systems, both at national and regional levels (Mêgnigbêto 2014b; Mêgnigbêto 2014c); it was also used to compare the knowledge production profiles of six OECD countries (Mêgnigbêto 2015a; Mêgnigbêto 2015b). Jointly with other indicators, it helped in studying the Norwegian innovation system both at national and county levels, based on data including the number of establishments in geographical, organisational and technological dimensions over a 13-year period (Ivanova et al. 2014).

The Triple Helix model lays on collaboration. When publications serve as unit of analysis, co-authorship is taken as a measurement of collaboration (Katz and Martin 1997; Bordons and Gomez 2000; Olmeda-Gómez et al. 2008; Abbassi et al. 2012); indeed, it entails the tacit transfer of information and knowledge (Olmeda-Gómez et al. 2008) and ensures diffusion of ideas and knowledge circulation (Guns and Rousseau 2014). The importance of co-authorship in knowledge creation and sharing may be measured by the international co-authorship trend. Indeed, publications on co-authorship worldwide all reported an increasing trend in the number of authors who contributed to an article (e.g. Bordons and Gomez 2000; Tijssen 2007; Leydesdorff and Wagner 2008; Boshoff 2009; Adams et al. 2010a; Onyancha and Maluleka 2011; Toivanen and Ponomariov 2011; Adams 2012; Leydesdorff et al. 2013b; Mêgnigbêto 2013b; Adams et al. 2014; Ossenblok et al. 2014). Some of them underlined the concentration of the growth in the group of papers with five or more authors, lending strong importance to collaboration. As an illustration, research collaboration networks have been evolving and countries that were at the periphery are becoming a member of the core; besides, the global international collaboration network had become denser (Leydesdorff and Wagner 2008). Globally, co-authorship has exploded recently (Adams 2012) and internationalisation of collaboration characterises science today (Adams 2013) due mainly to globalisation. Therefore, by means of collaboration, innovation actors contributed to synergy and knowledge creation at both national and international levels. Leydesdorff and Zawdie (2010) affirmed that ‘knowledge-based economy develops as a dynamic system at the global level, thus transcending national or geographical boundaries’.

At our knowledge, few papers studied international co-authorship in relation to the Triple Helix. Firstly, Leydesdorff and Sun (2009), Kwon (2011) and Kwon et al. (2012) included the internationally co-authored papers as the fourth element of the model; this method requires a huge amount of data processing and cleaning of the institutional address information (Leydesdorff and Sun 2009). Secondly, Choi et al. (2015) studied the intra-sector co-authorship at the international level. And thirdly, Shin et al. (2012) combined domestic and international collaboration by university, industry and government and their bi- or trilateral output. The abovementioned studies computed neither the synergy or knowledge the national innovation actors contributed abroad nor its effect on the synergy or knowledge creation and sharing at national level; therefore, they could not measure the real amount of knowledge that circulates among an areas’ innovation actors (Mêgnigbêto 2015a; Mêgnigbêto 2015b). Indeed, globalisation has given opportunities to researchers to collaborate worldwide regardless the distance. Besides, it has eroded some countries’ mutual information (Leydesdorff and Sun 2009; Kwon et al. 2012; Leydesdorff and Park 2014), and should have affected how knowledge is shared at the country level.

Because the mutual information at a country’s level could have been eroded by international co-authorship, it is not sufficient alone to indicate how knowledge-based an economy is (Mêgnigbêto 2015a; Mêgnigbêto 2015b). So, while comparing countries on the basis of the mutual information or derived indicators, the effect of international collaboration remains unilluminated. Thus, the comparison may be biassed. As an example, the Japanese research performance is driven by domestic activity (Adams et al. 2010b); this country’s mutual information was always higher compared with that of other countries (Leydesdorff 2003; Park et al. 2005; Ye et al. 2013; Mêgnigbêto 2014a; Mêgnigbêto 2015a; Mêgnigbêto 2015b). The conclusion that the synergy at the Japanese national level is higher than elsewhere is true, but deriving that the Japanese economy is more knowledge-based than that of another country may not be.

In this paper, we hypothesise that the synergy or knowledge contributed at the international level by a country’s domestic innovation actors may have affected the synergy or knowledge they created at the national level. In other words, foreign innovation actors can influence the synergy and knowledge creation and sharing at a country’s level. Our research question is twofold. (1) How is the synergy or knowledge contributed abroad by an area’s innovation actors due to their relations with their foreign partners measured? (2) What is the effect of international collaboration on knowledge flow within an innovation system?

Methods

The mutual information is borrowed from Shannon’s (1948) information theory. Central to this theory is the notion of entropy defined as the average quantity of information contained in a variable. The transmission power is derived from the mutual information. Appendix 1 gives the mathematical relations between entropy, mutual information and transmission power.

Domestic, foreign and global systems

Leydesdorff and Sun (2009), Kwon (2011) and Kwon et al. (2012) named ‘foreign’ institutions from partner countries and considered it as the fourth element of the innovation system composed of the three national actors that are university (u), industry (i) and government (g), leading to the computation of the mutual information (T uigf) of the Quadruple Helix. The type of the institutions involved is not taken into account (Fig. 1a). Our method suggests considering three levels of analysis: (1) the domestic one grouping the country- or area-based innovation actors as done in the literature hitherto, (2) the foreign one grouping the innovation actors from the partner countries, and (3) the global one grouping the two previously defined systems. Hence, the global system may be considered as composed of the ‘domestic’ and foreign sub-systems, each with three innovation actors leading to six actors at the global level (Fig. 1b). The two sub-systems interact and exert on each other a mutual influence that may act on the synergy within each other by the mutual relationships they entertain. The relationships existing between the actors on Fig. 1a (as represented by arrows) also exist within the domestic sub-system on the one hand and the foreign one on the other hand (Fig. 1b). Abstraction is done of these relationships on Fig. 1b, however. Studying such a Sextuple Helix (Leydesdorff 2012) requires the computation of 26 = 64 sectors data.1 A simpler way to proceed consists in considering the global system as if actors were from the same geographical area and studying separately the three domestic, foreign and global Triple Helix systems. Thus, one can compute the mutual information and transmission power of the domestic, foreign and the global systems using the formulas given above. We suggest using the normalised difference between the global and domestic transmission power as the effect of international collaboration on knowledge flow within an innovation system.
Fig. 1

Illustration of the method used by Leydesdorff and Sun (2009), Kwon (2011) and Kwon et al. (2012) (a) and the one proposed by this study (b) for integrating the international co-authorship in the Triple Helix relations. Sectors are represented by small circles meaning the intra-sectorial relations (loops)

International collaboration and transmission power

Because a record could have both foreign and domestic co-authors, the method of entropy decomposition suggested by Theil (1972) is not applicable; indeed, the number of records from ‘domestic’ and that from foreign do not sum up to the number of records at the global level. We suggest computing the mutual information and transmission power of the domestic, foreign and the global systems using the formulas given above. Hence, the method (Shin et al. 2012) used computed the domestic and global mutual informations for Saudi Arabia. If we denote τ d the domestic transmission power, τ f the foreign one and τ g the global one, the effect of the international collaboration on an area may be measured with the scalar \( \frac{\tau_{\mathrm{g}}-{\tau}_{\mathrm{d}}}{\tau_{\mathrm{g}}} \) expressed as percentage. We argue that the total synergy within such a system is measured by τ g. Therefore, one can compute the total transmission power for such a country and compare countries on this basis. In this section, we do not consider the synergy created at the foreign level solely, because it does not add any value to our interpretation; furthermore, its effects combined with that of the domestic synergy are already included into the global values.

Data collection

The data source is the Web of Science. Our research question requires the distinction between the papers originated from a geographic area’s university, industry and government relationships and those resulting from the collaboration with at least one university, industry or government abroad. If we could search for the first category with the Web of Science’s search function, we could not for the second category. Therefore, we opted for data downloading for further relevant treatment. The primary area for the application is the West African region2; however, Korea, a country which some decades ago has the same economic and social conditions as the West African countries, has been steadily studied with regard to Triple Helix dynamics (e.g. Park et al. 2005; Park and Leydesdorff 2010; Khan and Park 2011; Kwon et al. 2012; Mêgnigbêto 2015a; Mêgnigbêto 2015b); therefore, it is chosen for comparison purpose. So, this article treats the scientific data of the West African region and South Korea. West African3 and South Korean4 publication data from Web of Science5 over a 10-year period (2001–2010) were downloaded. The records resulting from these two searches were imported into two different bibliographic databases6 managed with CDS/ISIS7 thanks to a programme coded into CDS/ISIS Pascal8.

Data treatment

Based on the method of Leydesdorff (2003) and Park et al. (2005) for address assignment, a list of words or abbreviations was established to attribute each record address a label: UNIV for university, INDU for industry or GOV for government. A second CDS/ISIS Pascal programme was coded for this task. A record may contain many addresses; therefore, one record may have two or more different labels. The CDS/ISIS Pascal programmes were also instructed to read the countries’ name from the addresses and automatically add the associated area name: West Africa for the West African database and Korea for the South Korean database. Addresses that do not relate to any West African country or South Korea are labelled ‘FOREIGN’. So, in the inverted file of the databases, a university in West Africa appears under the label UNIV-WEST-AFRICA, an enterprise in South Korea appears under the label INDU-SOUTH KOREA and a foreign university (from the West Africa or South Korean point of view) under UNIV-FOREIGN, etc. As a result, the inverted file contains only the following keywords, in alphabetical order:9 GOV-FOREIGN, GOV-SOUTH KOREA, INDU-FOREIGN, INDU-SOUTH KOREA, UNIV-FOREIGN and UNIV-SOUTH KOREA for the South Korean data and GOV-FOREIGN, GOV-WEST-AFRICA, INDU-FOREIGN, INDU-WEST-AFRICA, UNIV-FOREIGN and UNIV-WEST-AFRICA for the West African data.

The CDS/ISIS search functions were used to compute the university, industry and government output and their bi or trilateral collaboration data at the three levels (Cf. Appendix 2). The print service of CDS/ISIS was used to output the publication year of the search results into text files for statistical analyses with the R software (R Development Core Team 2014); then, the repartition of records per year of publication was obtained. We coded a PHP programme that computes the sectorial entropies, the bilateral entropies and mutual informations, and the trilateral entropies and mutual information and the transmission powers according to the formulas given above. All the levels of analysis (domestic, foreign and global) were taken into account.

Result

Output and international collaboration

Table 1 provides basic data on the two areas’ scientific publishing over the considered periods of time: output, number of co-authors, average number of co-authors per paper, number and percentage of papers resulting from international collaboration. Over the decade, South Korea outputs a total of 368,729 papers and West Africa 30,717 papers; this leads to an annual average of 38,873 publications for South Korea and 3072 publications for West Africa. One South Korean publication out of five has at least one foreign co-author and about one half of West African publications has at least one foreign co-author. For both areas, the number of papers with at least one foreign address is increasing in absolute value; however, the trend seems to decrease very slowly in percentage. The number of co-authors per paper rose progressively from 2.39 in 2001 to 3.02 in 2010 in the case of West Africa and from 2.09 in 2001 to 2.65 in 2010 in the case of South Korea (Table 2).
Table 1

Total annual output and international collaboration data in the scientific publishing in South Korea (2001–2010)

Indicator

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Total

Annual output

20,512

22,369

25,559

30,283

34,661

38,817

45,740

47,854

50,677

52,257

368,729

(Co-) authors

42,958

51,462

59,090

69,485

83,158

92,318

107,731

113,332

129,140

138,592

887,266

Authors per paper

2.09

2.30

2.31

2.29

2.40

2.38

2.36

2.37

2.55

2.65

2.41

International coll.

3918

4705

5933

6334

7271

8005

8857

9685

11,142

12,243

78,093

International coll. (%)

19.10

21.03

23.21

20.92

20.98

20.62

19.36

20.24

21.15

23.43

20.98

Table 2

Total annual output and international collaboration data in the scientific publishing in West Africa (2001–2010)

Indicator

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

Total

Annual output

1646

1796

1945

2097

2779

2835

3642

4198

4735

5044

30,717

(Co-)authors

3932

4372

4998

5588

7233

7927

9916

11,745

13,080

15,215

84,006

Authors per paper

2.39

2.43

2.57

2.66

2.60

2.80

2.72

2.80

2.76

3.02

2.74

International coll.

863

927

1045

1123

1421

1464

1655

1849

2108

2386

14,814

International coll. (%)

50.79

51.61

53.73

53.55

51.13

51.64

45.44

44.04

44.52

47.30

48.23

Triple Helix sectorial outputs

The university (U), industry (I) and government (G) and their bi or trilateral collaboration (UI, UG, IG and UIG) outputs with regard to the level of production (e.g. domestic (d), foreign (f) and global (g)) are presented in Tables 3 and 4 for South Korea and Table 5 for West Africa. These tables illustrate the problematic of the study: for example, the line labelled 2001 in Table 5 indicates that for the West African region, U produces 829 publications at the domestic level, 376 publications at the foreign level and 816 publications at the global one. A closer analysis reveals that 829 − 816 = 13 publications attributed to U at the domestic level no longer belong to this sector at the global level. In fact, they were co-authored with other innovation actors (I or G) from foreign; so, they accounted for the collaboration of U (UI, UG or UIG) at the global level. For both areas, whatever the sectorial output is, the domestic value is higher than the global one for the Triple Helix actors but lower for their bi- or trilateral combinations.
Table 3

Triple Helix sectorial outputs for South Korea (2001–2010)

 

U

I

G

 

D

f

G

D

F

g

D

f

g

2001

12,836

2416

12,221

271

32

246

3107

513

2740

2002

14,400

2946

13,628

311

41

260

3238

606

2810

2003

17,685

3703

16,732

334

65

298

3899

804

3322

2004

19,595

3909

18,543

391

68

342

4108

787

3502

2005

22,412

4534

21,207

440

55

380

4853

901

4126

2006

25,114

5055

23,845

478

67

398

5390

996

4621

2007

30,263

5557

28,884

561

68

488

6591

1049

5682

2008

30,939

6195

29,349

526

46

422

6023

1152

5067

2009

33,626

6964

31,863

399

86

381

6186

1207

5105

2010

34,325

7823

32,371

381

67

289

6478

1305

5240

Total

241,195

49,102

228,643

4092

595

3504

49,873

9320

42,215

Table 4

Triple Helix sectorial outputs for South Korea (2001–2010)

 

UI

UG

IG

UIG

 

d

F

g

D

F

G

D

f

g

d

f

g

2001

276

32

334

2160

497

3246

72

11

85

57

17

102

2002

343

45

432

2551

599

3853

71

13

89

87

16

136

2003

463

44

547

3339

711

4978

78

24

103

106

21

180

2004

476

55

597

3728

842

5502

100

15

115

129

26

199

2005

541

53

654

4258

1065

6369

127

19

141

119

30

197

2006

615

79

772

4752

1084

6931

150

16

167

157

35

245

2007

742

70

888

5282

1300

7804

113

14

134

192

45

290

2008

850

70

998

6084

1479

8852

128

23

145

190

51

313

2009

962

89

1144

6989

1716

10,062

136

32

157

255

64

392

2010

994

86

1156

7658

1969

11,106

141

33

157

255

75

409

Total

6262

623

7522

46,801

11,262

68,703

1116

200

1293

1547

380

2463

Table 5

Triple Helix sectorial outputs for the West African region (2001–2010)

 

U

I

G

UI

UG

IG

UIG

 

d

F

g

D

f

g

D

F

g

D

F

G

D

f

g

d

f

g

d

f

g

2001

829

376

819

4

1

4

471

161

321

1

1

2

112

146

387

1

0

2

0

4

4

2002

940

395

896

7

5

6

474

189

307

0

3

3

134

185

458

1

0

2

0

2

6

2003

1002

471

971

10

6

6

509

180

310

3

2

8

162

212

526

1

2

4

0

6

10

2004

1149

525

1112

4

4

2

491

184

297

2

2

9

163

237

562

0

2

2

0

2

3

2005

1525

653

1450

6

6

4

673

294

421

3

2

8

272

272

774

1

1

3

0

2

5

2006

1594

700

1547

6

2

4

667

235

393

6

3

11

253

324

763

0

6

4

2

5

11

2007

2198

805

2058

9

6

9

750

285

439

8

3

12

351

350

964

1

6

6

0

6

12

2008

2632

928

2497

11

5

7

783

272

437

13

8

25

426

407

1094

5

3

6

3

14

22

2009

3055

1056

2887

10

6

7

788

308

434

12

8

22

468

492

1234

2

0

2

1

4

11

2010

3053

1160

2825

12

10

5

999

377

563

13

5

23

546

587

1457

2

3

3

2

13

28

Total

17,977

7069

17,062

79

51

54

6605

2485

3922

61

37

123

2887

3212

8219

14

23

34

8

58

112

Mutual information and transmission power time series

The mutual information and the transmission power are presented in Table 6 for West Africa and Table 7 for South Korea. They are related to the domestic, foreign and global levels. The mutual information values reveal that there is synergy within the considered innovation systems over the period of study at all levels. For the two areas under consideration, the curves of the three levels do not show the same relative positions over the period. In the case of South Korea, the domestic mutual information has the highest (absolute) value and decreased, except in 2009 where it took the median position. The global mutual information is lower (in absolute value) than the domestic one over the period; the foreign mutual information has either the top position or the median one (Fig. 2). In the case of West Africa, however, the relative positions of the curves are no longer identic (Fig. 3). Indeed, the foreign mutual information has the highest (absolute) value except in 2001 and 2006 where it has the lowest. The domestic mutual information has the highest absolute value in 2001 and 2006 and keeps the median position over the rest of the period. The global mutual information gets the lowest absolute value over the period except 2001 and 2006.
Table 6

Mutual information (T uig, in millibits) and transmission power (τ) for West Africa (2001–2010) at domestic, foreign and global levels

Year

Domestic

Foreign

Global

\( \frac{\tau_g-{\tau}_d}{\tau_g}\ \left(\%\right) \)

T uig

τ d

T uig

τ f

T uig

τ g

2001

−20.23

3.22

−17.603

5.17

−18.029

6.4

98.76

2002

−29.812

4.99

−39.916

12.35

−23.39

9.55

91.38

2003

−36.401

6.37

−41.408

14.26

−19.288

8.76

37.52

2004

−16.608

3

−23.915

8.72

−6.497

3.16

5.33

2005

−17.413

3.38

−30.6

9.09

−9.648

4.62

36.69

2006

−18.789

3.59

−7.668

2.93

−9.441

4.69

30.64

2007

−18.564

3.92

−22.536

7.94

−14.643

7.84

100.00

2008

−17.86

4.11

−20.783

8.53

−10.203

6.14

49.39

2009

−15.459

3.78

−21.543

9.14

−9.73

6.46

70.90

2010

−17.613

4

−29.975

12.55

−7.818

4.86

21.50

2001-2010

−19.411

3.96

−24.716

9.14

−11.636

6.1

54.04

Table 7

Mutual information (T uig, in millibits) and transmission power (τ) for South Korea (2001–2010) at domestic, foreign and global levels

Year

South Korea

Foreign

Global

\( \frac{\tau_g-{\tau}_d}{\tau_g}\ \left(\%\right) \)

T uig

τ d

T uig

τ f

T uig

τ g

2001

−58.151

15.32

−41.944

13.24

−49.904

17.45

13.90

2002

−59.328

16.81

−42.293

13.54

−46.684

18.08

7.56

2003

−52.915

15.77

−49.976

14.71

−43.775

18.04

14.39

2004

−54.57

16.75

−51.463

17

−44.625

18.93

13.01

2005

−52.934

15.86

−38.124

13.43

−43.132

17.97

13.30

2006

−51,671

15.61

−42,402

14.45

−40,816

16,86

8.01

2007

−54,291

15.75

−41,293

15.13

−44,681

17.55

11.43

2008

−47,751

15.8

−26,366

9.97

−36,78

17.07

8.04

2009

−35,686

12.84

−37,811

15.03

−31

15.85

23.44

2010

−33,218

12.19

−28,651

11.96

−23,898

12.93

6.07

2001-2010

−48,036

15.17

−38,561

13.89

−38,685

17

12.06

Fig. 2

Domestic, foreign and global mutual informations of South Korea (2001–2010)

Fig. 3

Domestic, foreign and global mutual informations of West Africa (2001–2010)

In summary, globally, the foreign mutual information is higher (in absolute value) than the domestic one in the case of West Africa, but the South Korean innovation system exhibits an opposite pattern. In other words, the synergy operates more at the foreign level than at the domestic one in the case of West Africa but the reverse is recorded in the case of South Korea. These results suggest that the South Korean domestic system is more integrated than the foreign one and that the West African system is less integrated than the foreign one.

At a country level, innovation actors are submitted to the same rules and policies; they have the same domestic socioeconomic backgrounds and research agendas. On the other side, the foreign actors come from different countries; they are submitted to different policies and research agendas; therefore, the cohesion in their actions could not have the same strength as in the case of national actors. West African institutional partners even coming from different horizons seem more organised than the West Africa-based innovation actors.

The global transmission power is highest in the case of South Korea. The foreign transmission power’s relative position has changed over the period: it was the lowest over the period, except in 2004 and 2009, where it was median; it has interchanged its position with the domestic transmission power (Fig. 4). The same global trend was registered in the case of West Africa: the global transmission power is higher than the domestic one but the foreign one changed positions over the period (Fig. 5). The mutual information measures the quantity of information common to the random variables in the system (Shannon 1948). It then measures the quantity of information or knowledge shared within the innovation actors. The transmission power is ‘the strength of the information flow within the system or between its actors.’ (Mêgnigbêto 2014a). Therefore, the knowledge sharing is more efficient in the global system than the domestic one, for both South Korea and West Africa. The global system ensures a better knowledge circulation among innovation actors.
Fig. 4

Domestic, foreign and global transmission power for South Korea (2001–2010)

Fig. 5

Domestic, foreign and global transmission power for West Africa (2001–2010)

Effect of international collaboration

The effect of the international collaboration on the knowledge flow is computed in the last columns of Table 6 and Table 7 and displayed in Fig. 6. If South Korea has gained a little with regard to its domestic transmission power (7–24 %, with an average of 12 % over the 10-year period), the involvement in international collaboration has even doubled the West African knowledge circulation capacity. The region has gained from 5.33 to 100 % of its knowledge-sharing capacity with an average of 54.04 % over the 10-year period.
Fig. 6

Effect of international collaboration on transmission power in South Korea and West Africa (2001–2010)

Discussion

West Africa and South Korea display opposite patterns with regard to the relative positions of the foreign and domestic mutual information curves. Indeed, whereas the domestic mutual information is higher in absolute value than the foreign one in the case of South Korea, the reverse is recorded for West Africa. According to Leydesdorff (2003) and Leydesdorff (2008), when the mutual information is negative, it indicates the level of synergy within a system, the extent to which a system is self-organised. This result leads to the conclusion that the West African innovation system is less organised than the set of its institutional partners considered as coming from the same country, and conversely that the South Korean innovation system is more integrated by itself. In fact, South Korea has strengthened its national innovation system after years of benefiting from international collaboration (Mêgnigbêto 2015a; Mêgnigbêto 2015b) following changes in its policies over decades (Kwon et al. 2012). The stead investment in research and development may have strengthened the collaboration between innovation actors at the country level and explains the performance of South Korea (Mêgnigbêto 2015a; Mêgnigbêto 2015b). It illustrates the efforts done by South Korea to catch-up with leading economies (OECD 2009).

West Africa is a ‘region’ composed of 15 countries. It is also an economic integration area with supranational institutions that have the role to conceive and apply policies at regional level. Even though the ECOWAS has formulated sectorial policies (e.g. agriculture and industry), it is recently, in 2012, that the Economic Community of West African States Policy on Science and Technology (ECOPOST) was adopted. Actually, it is hard to know the actions executed and the progress achieved toward a regional innovation system. Furthermore, not all ECOWAS member states have a science and technology policy (Oti-Boateng 2010).10 Globally, the West African national innovation system is hindered by many factors among which are the following: (1) the instability of the institutional framework, (2) the inadequate coordination within the system, (3) the lack of coordination between research programmes and research activities, (4) the lack of optimal use of human resources and loss of motivation of researchers, (5) the lack of human and financial resources and equipment, (6) the weaknesses in the institutional framework, (7) the lack or weaknesses in the actors network, (8) the weak improvement of research status and (9) the insufficiencies or inadequacies of funding and equipment (cf. (African Union et al. 2011; Mêgnigbêto 2013c). Consequently, research in this part of the word is driven by foreign actors and not by national or regional agendas. Even the intraregional collaboration is driven by international organisations or institutions with national representations in countries of West Africa (Mêgnigbêto 2013c). That explains the high rate of international collaboration in the West African science (about 50 % against 21 % for South Korea); that also explains why the West African domestic mutual information is weaker (in absolute value) than the foreign one.

In our opinion, the relative positions of the South Korean mutual information at the foreign and domestic levels seem to be the normal one. Indeed, a national system should be more integrated than a set of institutions from different horizons (named here foreign) because the components of the former are ruled by the same policies and have the same research agendas. This normal situation was also registered by (Shin et al. 2012) for Saudi Arabia.

West Africa does not appear like a single unit of analysis; indeed, member countries do not exhibit the same pattern. Some are more integrated and others less than their partners. In other words, some countries are affected positively by international collaboration (e.g. Burkina Faso, Ghana and Nigeria) and others negatively (e.g. The Gambia, Cape Verde, Cote d’Ivoire). However, the size of the sample we considered may have affected the West African results at both regional and national levels. Therefore, the resulting analysis could not be confident. The large variability of the effect of international collaboration on knowledge sharing in West Africa (cf. Fig. 6) is an illustration.

The main result of this research is that the international collaboration the two areas under study are involved in affected the synergy at their domestic level and also how knowledge is created and flows between innovation actors. In the case of South Korea, international collaboration makes that the country gained about 20 % of its domestic strength of information flow. In case of the West Africa, the effect goes up to 100 %. The relative positions of the mutual informations and the transmission powers in the two areas indicate that the West African innovation system is less integrated than the set of its international partners.

Conclusion

The objective of this paper was to measure the effect of international collaboration on the mutual information and how knowledge flows among innovations actors. We formulated two research questions. (1) How is the synergy or knowledge contributed to abroad by an area’s innovation actors due to their relations with their foreign partners measured? (2) What is the effect of international collaboration on knowledge flow within an innovation system? To answer these questions, we distinguished three levels of analysis: the domestic one grouping innovation actors based in the country under study, the foreign level grouping institutional partners and the global one merging the innovations actors from both domestic and foreign levels. We computed the mutual information and the transmission power for South Korea and West Africa for the three levels, and then, we could derive the effect of international collaboration. We found that the foreign mutual information is globally higher (in absolute value) than the domestic one in the case of West Africa, and lower in the case of South Korea meaning that the South Korean innovation system is integrated by itself, whereas the West African is less integrated than its foreign system. We also found that in the two areas, the global transmission power is higher than the domestic one meaning that international collaboration has strengthened knowledge sharing at the domestic level; in other words, the two areas have benefited from international collaboration in terms of knowledge flow.

Footnotes
1

If the number of variables is n, the system may be decomposed into 2 n subsets (Cf. Mêgnigbêto 2014a, pp. 285–286).

 
2

The West African region member states are, in alphabetic order: Benin, Burkina Faso, Cape Verde, Cote d’Ivoire, The Gambia, Ghana, Guinea, Guinea-Bissau, Liberia, Mali, Nigeria, Niger, Senegal, Sierra Leone and Togo.

 
3

The search expression was (cu=benin or cu=Burkina faso or cu=cote ivoire or cu=cape verde or cu=gambia or cu=ghana or cu=guinea or cu=guinea bissau or cu=liberia or cu=mali or cu=niger or cu=nigeria or cu=senegal or cu=sierra leone or cu=togo) and (py=2001-2010). It also selected data of countries like Equatorial Guinea and Papua New Guinea due to the term guinea. The records of these two countries that did not result from collaboration with any West African countries were deleted from our local database.

 
4

The search expression was cu=south korea and py=2001-2010.

 
5

The databases searched were Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI), Conference Proceedings Citation Index-Science (CPCI-S) and Conference Proceedings Citation Index-Social Science & Humanities (CPCI-SSH).

 
6

The two databases have the same structure.

 
7

CDS/ISIS is a text database management software application developed and distributed by UNESCO (UNESCO 1989a) (http://www.unesco.org/isis) and mainly used for bibliographic management (de Smet 2008; de Smet and Dhamdhere 2010).

 
8

CDS/ISIS provides a programming language ‘designed to develop CDS/ISIS applications requiring functions which are not readily available in the standard package’ (UNESCO 1989b). This programming language enables users to extend functions of the standard package, to make it more robust and in order to meet users’ specific needs (Mêgnigbêto 1998).

 
9

Not categorised addresses were labelled ‘NC’; so the inverted file also contained NC-WEST AFRICA, NC-FOREIGN for the West African database and NC-KOREA, NC-FOREIGN for the Korean database.

 
10

UNESCO distinguished eight ECOWAS member states in three groups: those who have national STI policy (1), incomplete/nonfunctional out dated STI policies per sector (2) and, those without any STI policy (5) (Oti-Boateng 2010).

 
11

In these formulae, the square brackets symbolises the number of records resulting from the search.

 
12

For South Korea for example, we conducted the following searches: (1) at domestic level: univ-korea, indu-korea, gov-korea and their bi and trilateral combinations; (2) at foreign level: univ-foreign, indu-foreign, gov-foreign and their bi or trilateral combinations; (3) at global level: univ-korea + univ-foreign, indu-korea + indu-foreign, gov-korea + gov-foreign and their bi and trilateral combinations.

 

Declarations

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Bureau d’études et de recherches en science de l’information
(2)
Institute for Education and Information Sciences, IBW, University of Antwerp

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© Mêgnigbêto. 2015