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Contrasting patterns and dynamics of patent offshoring in European regions

The Journal of Technology Transfer volume 48, pages 1300–1326 (2023)Cite this article

A Publisher Correction to this article was published on 10 November 2022

This article has been updated

Abstract

The paper explains the association between research and development (R&D) offshoring and regional innovation performance. Drawing on selected literature from the intersection of economics, innovation studies, strategic management and economic geography, we explore how the rate of patent offshoring reflects regional performance as well as how an increased rate of offshoring affects regions. Our results show that less developed and less innovative regions have significantly higher rates of patent offshoring. In these regions, knowledge production (measured by patent activity) is almost exclusively under the control of foreign companies. Moreover, this 20-year pattern of patent offshoring clearly trends towards increasing the outflow of patents from less developed regions towards the headquarters of multinational companies. These trends testify to the swiftly increasing globalization of R&D and, more generally, the importance of international knowledge flows to the competitiveness of multinational companies in the current era. Second, advanced regions typified by a balanced mix of knowledge bases or by a strong analytical knowledge base tend to have a lower level of patent offshoring than less developed regions with a dominant synthetic knowledge base. Third, growing patent offshoring tends to be intertwined with higher patenting activity among domestic companies.

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Fig. 1

Source: Questel—Orbit; Eurostat; own calculations

Fig. 2

Source: Questel—Orbit; Eurostat; own calculations

Fig. 3

Source: Questel—Orbit; Eurostat; own calculations

Fig. 4

Source: Questel—Orbit; Bureau van Dijk— Amadeus; own calculations

Change history

Notes

  1. The analytical knowledge base consists mainly of economic activities in the region, which require research, knowledge of natural laws and relationships. Codified knowledge is dominant in economic activities. These activities are less dependent on geographical distance (Asheim et al., 2007). With some simplification, the key question is the ‘know-why’.

  2. Within the synthetic knowledge base, economic activities predominate; innovations arise mainly as a result of a combination and synthesis of existing knowledge. Innovations or improvements responding to current needs and customer demand are also common. Tacit knowledge is therefore more important than in the case of the analytical base. This is typical especially for selected branches of the manufacturing industry (e.g., mechanical engineering). The key issues are ‘know-how’ and ‘know-who’.

  3. The symbolic knowledge base is formed by industries and economic activities of the creative industry, for which tacit knowledge, the geographical proximity of actors and personal interactions are key. Typical fields using a symbolic knowledge base include marketing, fashion, design and so on.

  4. In Austria’s case, the regional innovation scoreboard is set only for NUTS1 regions. Therefore, we assigned the innovation performance of NUTS2 according to the superior NUTS1 region.

  5. We use 3-year moving averages for the 1999–2018 period.

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Acknowledgements

Financial support of Grant Agency of The Czech Republic (No: 21-26655S) is greatly acknowledged.

Author information

Authors and Affiliations

  1. Department of Social Geography and Regional Development, Faculty of Science, Charles University, Albertov 6, 128 43, Prague 2, Czechia

    Vojtěch Kadlec, Viktor Květoň, Jiří Blažek & Petr Horák

  2. Department of International Economic Relations, Faculty of International Relations, University of Economics and Business, Prague, Czechia

    Jana Vlčková

Authors
  1. Vojtěch Kadlec
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  2. Viktor Květoň
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Correspondence to Viktor Květoň.

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The original version of this article was revised: The original version of this article unfortunately contained a mistake. Figure 4 was incorrect. The corrected figure is given below. The original article has been corrected.

Appendices

Appendices

1.1 Appendix 1: Orbit dataset general descriptions

Country

No. of patents with only domestic inventors (1999–2018)

No. of offshored patent (1999–2018)

Netherlands

77,767

7293

Austria

29,142

7076

Czechia

5126

1529

Romania

1791

1290

  1. Source: Questel—Orbit; own data extraction

1.2 Appendix 2: Orbit dataset general descriptions, L&S and M&M innovators

Region

No. of patents with only domestic inventors (1999–2018)

No. of offshored patent (1999–2018)

Region

No. of patents with only domestic inventors (1999–2018)

No. of offshored patent (1999–2018)

NL11

794

84

CZ01

1083

278

NL12

716

113

CZ02

632

134

NL13

580

107

CZ03

435

147

NL21

2699

485

CZ04

205

104

NL22

5115

596

CZ05

860

199

NL23

491

62

CZ06

934

424

NL31

3765

657

CZ07

548

131

NL32

8119

1034

CZ08

429

112

NL33

11,124

1460

RO11

125

96

NL34

353

76

RO12

290

261

NL41

39,496

1979

RO21

166

134

NL42

4515

640

RO22

73

41

AT11

312

63

RO31

64

48

AT12

3697

844

RO32

749

448

AT13

4609

1680

RO41

50

30

AT21

1455

508

RO42

274

232

AT22

4467

822

   

AT31

5475

811

   

AT32

1520

338

   

AT33

2230

483

   

AT34

2383

481

   
  1. Source: Questel—Orbit; own data extraction

1.3 Appendix 3: Orbit dataset general descriptions

Country

Total companies

Domestic companies

Foreign companies

N/A

Netherlands

8457

5106

2317

1034

Austria

3655

2963

659

33

Czechia

3943

3022

475

446

Romania

1053

580

252

221

  1. Source: Questel—Orbit; Bureau van Dijk—Amadeus; own data extraction

1.4 Appendix 4: Pearson correlation of economic performance and patent offshoring rate

Year

Productivity*

GDP per capita PPS 2013

Pearson’s r

p value

Pearson’s r

p value

2000

− 0.021

0.905

− 0.092

0.594

2001

− 0.057

0.749

− 0.11

0.535

2002

0.378

0.027

0.336

0.052

2003

− 0.238

0.176

− 0.231

0.19

2004

− 0.316

0.069

− 0.377

0.028

2005

− 0.339

0.05

− 0.408

0.016

2006

− 0.475

0.003

− 0.442

0.006

2007

− 0.609

< 0.001

− 0.649

< 0.001

2008

− 0.504

0.002

− 0.439

0.007

2009

− 0.348

0.035

− 0.244

0.146

2010

− 0.585

< 0.001

− 0.514

0.001

2011

− 0.656

< 0.001

− 0.608

< 0.001

2012

− 0.709

< 0.001

− 0.628

< 0.001

2013

− 0.624

< 0.001

− 0.494

0.002

2014

− 0.702

< 0.001

− 0.603

< 0.001

2015

− 0.631

< 0.001

− 0.514

0.001

2016

− 0.741

< 0.001

− 0.62

< 0.001

2017

− 0.793

< 0.001

− 0.641

< 0.001

2018

− 0.751

< 0.001

− 0.622

< 0.001

  1. Source: Questel—Orbit; Eurostat; own calculations
  2. *Gross value added at basic prices (mil. of EUR) per employees (1000 employees from 15 to 64 years)

1.5 Appendix 5: Pearson correlation of Regional Innovation Index and patent offshoring rate

Year

Pearson’s r

p value

2011

− 0.644

< 0.001

2013

− 0.822

< 0.001

2015

− 0.798

< 0.001

2017

− 0.881

< 0.001

2019

− 0.916

< 0.001

  1. Source: Questel—Orbit; European Commission; own calculations

1.6 Appendix 6: Regression analysis of patent offshoring and domestic and foreign companies in regions with different levels of innovation

Variables

Patents (all)

Patents domestic

Patents foreign

Number of patents (all) lag

1.124074

1.108955

1.193839

Offshore rate

16.04825

8.37883

7.755473

P >|t|

0.003

0.005

0.036

Year dummies

Yes

Yes

Yes

No. of observations

629

629

629

F statistic

6582.78

7855.54

664.84

Groups/instruments

37/36

37/36

37/36

AR (2)

0.195

0.131

0.323

Hansen statistic

0.036

0.032

0.076

Variables

Patents (all)

L&S Patents

M&M Patents

Number of patents (all) lag

1.124074

1.117376

1.06819

Offshore rate

16.04825

8.240549

4.216174

P >|t| of offshore rate

0.003

0.636

0.087

Year dummies

Yes

Yes

Yes

No. of observations

629

340

289

F statistic

6582.78

155,560.64

53.65

Groups/instruments

37/36

20/36

17/36

AR (2)

0.195

0.414

0.029

Hansen statistic

0.036

0.917

1.000

Variables

Patents domestic

L&S Patents

M&M Patents

Number of patents (all) lag

1.108955

1.102163

1.056238

Offshore rate

8.37883

− 1.156885

2.289849

P >|t| offshore rate

0.005

0.881

0.269

Year dummies

Yes

Yes

Yes

No. of observations

629

340

289

F statistic

7855.54

648.36

11.75

Groups/instruments

37/36

20/36

17/36

AR (2)

0.131

0.588

0.028

Hansen statistic

0.032

0.979

1.000

Variables

Patents foreign

L&S Patents

M&M Patents

Number of patents (all) lag

1.193839

1.183487

0.6362821

Offshore rate

7.755473

6.745423

− 3.477691

P >|t| offshore rate

0.036

0.587

0.068

Year dummies

Yes

Yes

Yes

No. of observations

629

340

289

F statistic

664.84

17,907.03

28.72

Groups/instruments

37/36

20/36

17/36

AR (2)

0.323

0.367

0.010

Hansen statistic

0.076

0.963

1.000

Variables

Patents per 1000 EA person

L&S Patents

M&M Patents

Number of patents (all) lag

1.097024

1.065883

1.06731

Offshore rate

0.0208968

− 0.0056994

0.0066841

P >|t| offshore rate

0.027

0.734

0.123

Year dummies

Yes

Yes

Yes

No. of observations

629

340

289

F statistic

7585.28

4517.74

4229.34

Groups/instruments

37/36

20/36

17/36

AR (2)

0.016

0.052

0.112

Hansen statistic

0.055

1.000

1.000

Variables

Domestic patents per 1000 EA person

L&S Patents

M&M Patents

Number of patents (all) lag

1.089463

1.077202

1.038207

Offshore rate

0.012437

− 0.0145701

0.0021014

P >|t| offshore rate

0.052

0.249

0.625

Year dummies

Yes

Yes

Yes

No. of observations

629

340

289

F statistic

9153.28

418,848.05

32,978.43

Groups/instruments

37/36

20/36

17/36

AR (2)

0.063

0.100

0.097

Hansen statistic

0.078

0.997

1.000

Variables

Foreign patents per 1000 EA person

L&S Patents

M&M Patents

Number of patents (all) lag

1.103016

0.9736157

0.6826516

Offshore rate

0.0050038

0.008883

− 0.0062613

P >|t| offshore rate

0.153

0.413

0.008

Year dummies

Yes

Yes

Yes

No. of observations

629

340

289

F statistic

1576.05

4915.89

354.89

Groups/instruments

37/36

20/36

17/36

AR (2)

0.051

0.188

0.012

Hansen statistic

0.018

0.999

1.000

  1. Source: Questel—Orbit; Bureau van Dijk —Amadeus; own calculations

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Kadlec, V., Květoň, V., Vlčková, J. et al. Contrasting patterns and dynamics of patent offshoring in European regions. J Technol Transf 48, 1300–1326 (2023). https://doi.org/10.1007/s10961-022-09968-4

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