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The Value of Knowledge, Network Relationships and Governmental Support for Chinese Firms’ Early Internationalization: Survey Evidence

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Value Creation in International Business

Abstract

Firms’ early internationalization has received considerable research attention. According to studies on born globals (Madsen and Servais 1997) and international new ventures (Oviatt and McDougall 1994), firms enter far markets soon after establishment. However, according to studies on slower internationalizers – for instance, in the case of innovation-related internationalization models (Bilkey 1978) and the Uppsala model (Johanson and Vahlne 1977, 1990) – internationalization takes more time and starts from the closest and/or more familiar markets.

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Notes

  1. 1.

    Several definitions of BGs have been developed. We follow the one by Kuivalainen et al. (2007) that such firms should achieve at least 25 % of turnover from abroad and enter culturally distant foreign countries during the first three years of establishment. We also agree with Madsen and Servais (1997, p. 579) that they should ‘seek to derive significant advantages from … the sale of outputs to multiple countries/continents right from their legal birth’. Thus, we expect BGs to enter at least one continent outside Asia in three years or less from establishment and achieve a minimum 25 % export share during this period.

  2. 2.

    An international new venture should also internationalize fast – according to Crick (2009) in three years or less from establishment while according to McDougall et al. (2003) within a maximum of six years – but it does not have to enter other continents.

  3. 3.

    Experiential knowledge is accumulated during foreign operations. Knowing more, in turn, increases the firm’s commitment to that market as then it becomes easier to identify further expansion opportunities and also, the market will be perceived as less risky (Johanson and Vahlne 1977).

  4. 4.

    Effectuation logic means that, to choose a marketing strategy, entrepreneurs start from taking into account their own traits, tastes, abilities, knowledge, and social networks instead of analysing different markets and evaluating different foreign market entry methods systematically (Andersson 2011).

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Acknowledgments

This work was supported by the Institutional Research Funding IUT20-49 of the Estonian Ministry of Education and Research and by the Estonian Research Council’s grant PUT 1003.

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Appendices

Descriptive Statistics

 

Total

NBG

BG

Number

Mean

Number

Mean

Number

Number

Sample 1

The year of establishment

380

1996.61

261

1996.54

119

1996.76

Turnover (2010)

380

31.92

261

30.41

119

35.22

The number of employees (2010)

380

231.83

261

221.66

119

254.12

The year of first export outside Asia

369

1999.83

250

2000.93

119

1997.51

The export share (2010)

380

39.42

261

24.70

119

71.69

The year when achieved 25 % export share

243

2001.27

124

2002.94

119

1999.53

Number of countries (any foreign operations)

380

3.22

261

1.93

119

6.06

The overall success of internationalization (subjective estimation) (max = 100 points)

380

75.99

261

75.54

119

76.97

Sample 2

The year of establishment

332

1998.32

122

1996.65

210

1999.30

Turnover (2007)

332

78.88

122

79.64

210

78.43

Turnover (2010)

332

76.86

122

64.60

210

76.65

Turnover (2011)

332

83.65

122

84.69

210

83.05

The number of employees (2007)

332

306.85

122

355.93

210

278.34

The number of employees (2011)

332

326.13

122

387.49

210

290.48

The year of first export outside Asia

332

2000.62

122

2000.62

210

2000.63

The export share (2007)

332

42.85

122

39.20

210

44.98

The export share (2011)

332

45.11

122

41.48

210

47.22

The year when achieved 25 % export share

332

2001.43

122

2001.97

210

2001.11

Number of countries (any foreign operations) (2007)

332

5.90

122

5.28

210

6.26

Number of countries (any foreign operations) (2011)

332

6.24

122

5.72

210

6.54

The overall success of internationalization (subjective estimation)

332

74.82

122

74.65

210

74.90

The Most Popular Markets

 

Sample 1, 1st market

Sample 1, 2nd market

NBG

%a

BG

%

Total

%

NBG

%

BG

%

Total

%

USA

134

36.31

76

20.60

210

56.91

9

3.88

9

3.88

18

7.76

Germany

30

8.13

13

3.52

43

11.65

16

6.90

24

10.34

40

17.24

UK

17

4.61

5

1.36

22

5.96

12

5.17

22

9.48

34

14.66

Italy

13

3.52

0

0.00

13

3.52

7

3.02

2

0.86

9

3.88

Australia

10

2.71

5

1.36

15

4.07

7

3.02

9

3.88

16

6.90

Canada

7

1.90

7

1.90

14

3.79

17

7.33

24

10.34

41

17.67

France

2

0.54

1

0.27

3

0.81

3

1.29

5

2.16

8

3.45

The Netherlands

4

1.08

1

0.27

5

1.36

5

2.16

5

2.16

10

4.31

Russia

9

2.44

3

0.81

12

3.25

1

0.43

0

0.00

1

0.43

Other

24

6.50

8

2.17

32

8.67

37

15.95

18

7.76

55

23.71

Total

250

67.75

119

32.25

369

100

114

49.14

118

50.86

232

100

 

Sample 1, 3rd market

Sample 2, 1st market

NBG

%

BG

%

Total

%

NBG

%

BG

%

Total

%

USA

2

1.16

8

4.62

10

5.78

46

13.86

95

28.61

141

42.47

Germany

4

2.31

16

9.25

20

11.56

13

3.92

25

7.53

38

11.45

UK

4

2.31

9

5.20

13

7.51

10

3.01

19

5.72

29

8.73

Italy

2

1.16

3

1.73

5

2.89

2

0.60

0

0.00

2

0.60

Australia

4

2.31

18

10.40

22

12.72

13

3.92

8

2.41

21

6.33

Canada

4

2.31

11

6.36

15

8.67

17

5.12

27

8.13

44

13.25

France

5

2.89

10

5.78

15

8.67

4

1.20

3

0.90

7

2.11

The Netherlands

2

1.16

12

6.94

14

8.09

0

0.00

3

0.90

3

0.90

Russia

4

2.31

4

2.31

8

4.62

7

2.11

10

3.01

17

5.12

Other

27

15.61

24

13.87

51

29.48

10

3.01

20

6.02

30

9.04

Total

58

33.53

115

66.47

173

100

122

36.75

210

63.25

332

100

  1. aPercentage of all respondents that selected this market as their 1st, 2nd or 3rd market

Knowledge Characteristics (1: Not at All, 7: Very Much)

 

Sample 1

Sample 2

1st market

2nd market

3rd market

1st market

N

Mean

Std. dev.

N

Mean

Std. dev.

N

Mean

Std. dev.

N

Mean

Std. dev.

Customers

NBG

261

3.40

1.184

115

3.45

1.428

61

3.51

.942

122

2.32

1.26

BG

119

1.31****

.767

117

1.19****

.776

114

1.06****

.466

210

2.39

1.02

Total

380

2.74

1.444

232

2.31

1.611

175

1.91

1.347

332

2.36

1.11

Suppliers

NBG

260

3.63

1.209

115

2.74

.849

61

3.49

.924

122

1.80

.95

BG

119

1.55****

.661

117

1.13****

.580

114

1.04****

.264

210

2.10

1.03

Total

379

2.97

1.440

232

1.93

1.085

175

1.89

1.311

332

1.99

1.01

Foreign market conditions

NBG

261

3.48

1.090

115

3.10

1.059

61

3.03

.774

122

1.95

.84

BG

119

1.20****

.720

117

1.09****

.491

114

1.04****

.264

210

2.16**

.89

Total

380

2.76

1.446

232

2.09

1.296

175

1.73

1.078

332

2.08

.88

Competitors

NBG

260

3.12

1.106

115

3.60

1.362

61

2.87

.785

122

1.90

.75

BG

119

1.18****

.481

117

1.16****

.682

114

1.04****

.264

210

2.13**

.93

Total

379

2.51

1.312

232

2.37

1.625

175

1.67

1.013

332

2.05

.88

Foreign norms, rules and values

NBG

260

3.16

1.151

115

2.21

.960

61

3.16

1.036

122

1.70

.75

BG

119

1.13****

.536

117

1.10****

.480

113

1.03****

.210

210

2.04****

.88

Total

379

2.53

1.373

232

1.65

.937

174

1.78

1.203

332

1.92

.85

Foreign government, laws and institutions

NBG

260

2.98

1.263

115

2.13

.874

61

2.87

.846

122

1.75

.81

BG

119

1.09****

.390

117

1.09****

.508

114

1.04****

.264

210

2.01***

.89

Total

379

2.39

1.382

232

1.61

.881

175

1.67

1.030

332

1.92

.87

  1. *p < 0.1, **p < 0.05, ***p < 0.01, ****p < 0.001 based on the robust test of equality of means (Welch and Brown-Forsythe). The results of Welch and Brown-Forsythe tests are used in the cases where the results of Levene’s test are significant (p < 0.05), because it means that the equal variances are not assumed and we have heterogeneity and cannot rely on ANOVA results

Other Market Selection Criteria (1: Not at All, 7: Very Much)

 

Sample 1

Sample 2

1st market

2nd market

3rd market

1st market

N

Mean

SD

N

Mean

SD

N

Mean

SD

N

Mean

SD

Good learning opportunities

NBG

261

3.15

1.089

114

2.09

1.209

56

3.04

.687

122

4.09

1.40

BG

119

2.95*

.964

118

1.49****

.814

115

2.90

.706

210

4.02

1.31

380

3.08

1.054

232

1.78

1.067

171

2.94

.700

332

4.05

1.34

Strong contacts before entry

NBG

260

2.08

1.209

114

2.99

1.327

57

1.72

.921

122

1.95

1.12

BG

119

1.49****

.735

118

1.08****

.417

115

1.03****

.263

210

2.45****

1.46

379

1.89

1.116

232

2.02

1.367

172

1.26

.654

332

2.27

1.36

A foreign customer’s contact

NBG

261

5.03

1.011

114

4.96

.866

58

6.14

.511

122

4.80

1.31

BG

119

6.40****

.751

118

5.81****

.653

115

6.37****

.597

210

4.87

1.26

380

5.46

1.133

232

5.39

.876

173

6.29

.578

332

4.84

1.27

Support from the Chinese government

NBG

259

4.76

1.316

114

5.87

.888

55

6.40

.494

122

4.48

1.12

BG

119

5.71****

.741

118

5.92

.764

115

6.30

.499

210

4.29

1.24

378

5.06

1.245

232

5.90

.826

170

6.34

.498

332

4.36

1.20

Support from the foreign government

NBG

258

1.65

.926

114

1.48

.778

57

1.30

.626

122

2.62

1.37

BG

118

1.41**

1.015

118

1.34

.527

115

1.10**

.295

210

2.36*

1.21

376

1.57

.960

232

1.41

.665

172

1.16

.442

332

2.45

1.28

Rich (a high income per capita)

NBG

261

5.72

1.305

114

5.42

1.038

58

5.07

1.349

122

5.10

1.35

BG

119

5.89

.998

118

5.74**

.938

115

5.71****

.886

210

5.16

1.26

380

5.77

1.219

232

5.58

.999

173

5.50

1.103

332

5.14

1.29

Big (population)

NBG

261

5.47

1.275

114

4.59

1.196

56

4.84

1.262

121

5.10

1.11

BG

118

5.80***

1.034

117

4.74

.957

114

4.96

1.258

210

5.07

1.11

379

5.57

1.214

231

4.67

1.082

170

4.92

1.257

331

5.08

1.11

The firm’s product/service was better

NBG

259

4.41

.860

114

4.43

.912

58

4.14

.847

122

3.92

1.39

BG

119

4.28

.882

118

4.20**

.780

115

3.75***

.736

210

3.75

1.43

378

4.37

.868

232

4.31

.853

173

3.88

.794

332

3.81

1.42

Good for production

NBG

260

4.60

1.196

114

3.10

1.182

57

2.53

.684

122

4.93

1.14

BG

119

5.53****

.973

118

2.86*

.899

115

2.23***

.465

210

4.82

1.11

379

4.89

1.210

232

2.97

1.052

172

2.33

.563

332

4.86

1.12

Less risky

NBG

261

2.59

1.158

114

2.95

.920

58

3.22

.702

122

3.25

1.20

BG

119

2.67

1.082

118

2.81

.765

115

3.06

.753

210

3.22

1.15

380

2.62

1.134

232

2.88

.846

173

3.12

.738

332

3.23

1.16

Empty: no similar services/products

NBG

259

2.54

1.035

114

2.57

.872

58

2.55

.882

122

3.52

1.30

BG

118

2.47

.903

118

1.98****

.773

115

2.31*

.583

210

3.29*

1.18

377

2.52

.995

232

2.27

.873

173

2.39

.704

332

3.37

1.23

Close to China

NBG

261

1.83

1.464

114

1.98

1.439

58

2.02

1.584

122

2.34

1.37

BG

119

1.53**

1.134

118

1.48****

.771

115

1.37***

.820

210

2.30

1.44

380

1.73

1.375

232

1.73

1.173

173

1.58

1.171

332

2.32

1.41

  1. *p < 0.1, **p < 0.05, ***p < 0.01, ****p < 0.001 based on the ANOVA and robust tests of equality of means (Welch and Brown-Forsythe). The results of Welch and Brown-Forsythe tests are used in the cases where the results of Levene’s test are significant (p < 0.05), because it means that the equal variances are not assumed and we have heterogeneity and cannot rely on ANOVA results

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Vissak, T., Tsukanova, T., Zhang, X. (2017). The Value of Knowledge, Network Relationships and Governmental Support for Chinese Firms’ Early Internationalization: Survey Evidence. In: Marinova, S., Larimo, J., Nummela, N. (eds) Value Creation in International Business. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-39369-8_9

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