Does the Firm’s Internationalization Influence Entrepreneurs’ Well-Being? No, the Firm’s Internationalization Influences Economic Outcomes

Introduction

The performance of internationalization has been a research stream studied and meta-analyzed several times (Bausch & Krist, 2007; Fern- haber, 2013; Marano, Arregle, Hitt, Spadafora, & van Essen, 2016; Schwens et ah, 2018). In general, studies find a positive relationship between internationalization and performance. More specifically, research finds that components of internationalization - degree of internationalization and scope of internationalization - are positively associated with profitability and growth.

In this study, we aim to corroborate the positive influence of internationalization on economic performance outcomes. We, specifically, study the impact of the degree and scope of internationalization on international profits and other measures of financial performance. More interestingly, however, this study also aims to explore the relationship between internationalization and non-economic outcomes. Particularly, we examine the association between degree and scope of internationalization with the entrepreneur’s life satisfaction and happiness. Previous literature in entrepreneurship has pointed to the direction that entrepreneurship positively affects well-being (Nikolaev, Boudreaux, Sc Wood, 2019; Stephan, 2018). One of the reasons why entrepreneurship affects well-being argues that the growth aspirations of the entrepreneur impact his/her sense of achievement, self-acceptance, autonomy, engagement, meaning, and purpose (Dana, 1995; Wiklund, Davidsson, & Delmar, 2003), which, in turn, can contribute to life satisfaction and happiness. In this sense, internationalization, as a growth aspect of the entrepreneurial activity, can also play a role in the growth aspirations of the entrepreneurs and, in turn, in their well-being. To date, the link between internationalization and entrepreneur’s well-being remains an important research opportunity that deserves attention. By finding a link between internationalization and well-being, we can argue that businesses not only pursue internarionalizarion with economic gains in mind bur also with non-economic gains in the heart (satisfaction and happiness).

We study these issues using a survey data set of internationalized Indigenous businesses based in Alberta and British Columbia, Canada. We perform several robustness checks and compare results with a sample of internationalized businesses owned by self-identified non-Indigenous owners to tease out potential ethnic differences on the relationship between internationalization and (economic and non-economic) outcomes.

Our study makes the following contributions to the literature on the internationalization-performance link. First, our findings corroborate results that degree and scope of internationalization positively affect firms’ international profits. Second, our results were unable to show a significant association between internationalization measures and entrepreneur’s life satisfaction or entrepreneur’s happiness. It seems, then, that internationalization - as studied in this research - creates only economic outcomes.

This study is organized as follows: We start describing our conceptual framework. Then, we explain the methodology, including sample, operationalization of variables, and techniques for analysis. Results are then presented, followed by a discussion and suggestions for future research.

Conceptual Framework: Economic and Non-economic Outcomes of Firms’ Internationalization

In this study, we examine the influence of internationalization on economic and non-economic performance outcomes, as indicated in Figure 3.1. Internationalization encompasses degree of internationalization and scope of internationalization (Schwens et al., 2018; Zahra & George, 2002). Degree of internationalization refers to the level of international sales out of total sales, while scope of internationalization refers to the number of countries to which the business sells products.

Economic performance outcomes include international profits and subjective financial performance. In this study, subjective financial performance refers to the business owner’s evaluation of market share growth, sales growth, and profitability. Non-economic performance outcomes refer to the well-being of the entrepreneur and specifically include life satisfaction and happiness.

The literature has studied the influence of internationalization on performance. Pertinent is a recent meta-analysis of the relationship between internationalization (degree, scope, and speed) on growth and profitability. Schwens et al. (2018) find that the degree of internationalization and the scope of internationalization are positively and significantly associated with firm performance, while speed of internationalization is not related to firm performance. They also find that, overall, internationalization is positively related to growth and profitability.

Entrepreneurs’ Well-Being & IB 51

The influence of firm’s internationalization on economic and non-economic outcomes

Figure 3.1 The influence of firm’s internationalization on economic and non-economic outcomes.

There are several potential arguments as to why degree and scope of internationalization drive economic performance. Internationalized businesses can have access to a larger customer base which offers the opportunity to obtain additional revenues which, in turn, may affect profit and growth (Fernhaber, 2013; McDougall & Oviatt, 1996; Schwens et al., 2018). Businesses also have the opportunity to achieve economies of scale and thus create efficiencies which, in turn, can positively affect performance (Khavul, Perez-Nordtvedt, & Wood, 2010; Qian & Li, 2003). Businesses with international operations in several countries can also spread the risk of internationalization (Hilmersson, 2014; Schwens et ah, 2018; Zahra, Ireland, & Hitt, 2000) and create efficiencies (e.g., by distributing overheads or exploiting factor cost differences across countries) leading to higher firm performance (Khavul et ah, 2010; Schwens et ah, 2018).

While the literature on the relationship between internationalization and economic performance outcomes has been vibrant, the literature on the relationship between internationalization and non-economic outcomes is being developed. The stream of research that we will use to build our arguments on the influence of internationalization on noneconomic outcomes is the entrepreneurship literature. Nikolaev et al. (2019) as well as Stephan (2018) argue that entrepreneurship is positively associated with well-being. Nikolaev et al. (2019) suggest that entrepreneurs perceive work-related stressors (e.g., higher level of uncertainty, job insecurity, more extended work hours, role ambiguity, and intense time-pressure) as less relevant mainly because entrepreneurs do not follow a set of rules and procedures prescribed by others (Baron Sc Shane, 2007). Nikolaev et al. (2019) also indicate that entrepreneurs are more likely to find their job challenging and enjoyable (Benz Sc Frey, 2008), and they gain satisfaction from vast opportunities for personal learning and growth which contributes to their well-being.

In this study, we argue that internationalization is aligned with entrepreneur’s growth aspirations and therefore can contribute to entrepreneur’s life satisfaction and happiness. As Nikolaev et al. (2019) argue, future growth aspirations can be critical for entrepreneurs’ well-being as their sense of achievement, self-acceptance, autonomy, engagement, meaning, and purpose (Dana, 1995; Wiklund et al., 2003) can contribute to life satisfaction and happiness.

Methodology

Sample

The sample for this study includes 150 self-identified Indigenous business1 owners (First Nations, Inuit, Metis) who own a private company (not owned by the community). These businesses are already international and are based in Alberta or in British Columbia. A market research company located in Edmonton collected the data. The methodology used for the data collection involves a hybrid process. A random sample of respondents was called and then given the opportunity to complete the survey over the phone or online. The data collection started in August and finalized in October 2017. For more information on the data collection methodology, please review Chapter 1 of this book.

Operationalization of Variables

International profits. We use the percentage of international profits out of total profits.

Subjective financial performance. We employ three items to measure this variable: market share growth, sales growth, and business profitability. These items are rated relative to major competitors and based on a 1 (much worse) to 5 (much better) scale. In the survey question, these items appeared in a randomized order, to avoid order bias when responding. We use exploratory factor analysis, principal components, and varimax rotation. The Kaiser-Meyer-Olkin measure of sampling adequacy equals 0.716. The total explained variance is 79.62%, and the Cronbach’s alpha for this variable is 0.872.

Life satisfaction. The measure of life satisfaction includes five items: in most ways my life is close to my ideal, the conditions of my life are excellent, I am satisfied with my life, so far I have gotten the important things I want in life, and if I could live my life over, I would change almost nothing (Diener, Emmons, Larsen, & Griffin, 1985). Respondents rate these items on a scale of 1 (strongly disagree) to 5 (strongly agree). These items appeared in a randomized order in the survey, to avoid response order bias. To reduce these items into the life satisfaction variable, we employ exploratory factor analysis with principal components and varimax rotation. The Kaiser-Meyer-Olkin measure of sampling adequacy is 0.853. The total explained variable equals 66.29% and the Cronbach’s alpha is 0.865.

Subjective happiness. We measure happiness with four items: compared to most of my peers, I consider myself ([1] less happy to [7] more happy); some people are generally very happy, they enjoy life regardless of what is going on, getting the most out of everything, to what extent does this characterization describe you? ([1] not at all to [7] a great deal); some people are generally not very happy, although they are not depressed, they never seem as happy as they might be, to what extent does this characterization describe you? ([1] not at all to [7] a great deal); and I describe myself as very happy (from [1] strongly disagree to [5] strongly agree) (Lyubomirsky & Lepper, 1999). We also used exploratory factor analysis, principal components, and varimax rotation. The Kaiser-Meyer-Olkin measure of sampling adequacy equals 0.755. The total explained variance is 59.32%. Cronbach’s alpha for this construct equals 0.739.

Fitted degree of internationalization. We employ a two-stage approach to measure the fitted degree of internationalization given the potential endogeneity problem. In the first stage, we run an ordinary least squares regression using the percentage of international sales to total sales as the dependent variable and the following independent variables: personal network, business network, government network, internet, labor seeking motivation, supply seeking motivation, technology seeking motivation, brand seeking motivation, government incentives, market seeking motivation, identity self-categorization, and identity prominence. We also used the following control variables: firm size, firm age, entrepreneur’s gender, and entrepreneur’s business experience and industry. For details on the operationalization of the independent variables, the reader is asked to review Chapter 1. We then estimate the unstandardized predicted values of the percentage of international sales to total sales. We use the predicted value as the measure of fitted degree of internationalization in the performance models. Details of the descriptive statistics, correlation matrix, and regression estimations of the degree of internationalization model are presented in Appendices 3.1, 3.2, and 3.3.

Fitted scope of internationalization. We measure fitted scope of internationalization using the same procedure as fitted degree of internationalization. In the first stage, the number of foreign countries to which the business sells its product/service is used as the dependent variable in the regression model. The independent and control variables used are the same as for the degree of internationalization model. The unstandardized predicted values for the number of foreign countries to which the business sells its product/service is the measure for fitted scope of internationalization, and these values are used in the performance models. Appendices 3.1,3.2, and 3.3 provide details of descriptive statistics, correlation matrix, and regression model for the scope of internationalization equation.

Control variables. We used the following variables as controls:

Firm size. The number of total employees.

Firm age. We subtract the year the company started operations from the year 2017 (when data was collected).

Entrepreneur’s gender. We use a binary variable: 0 for male and 1 for female respondents. All respondents are majority owners.

Entrepreneur’s business experience. We use the number of businesses the entrepreneur has owned or started in the past without considering the current one: 0, 1, 2, 3, or more.

Industry. We use a binary variable, where 1 equals manufacturing industry and 0 equals otherwise.

Analytical Techniques

We employ two models for each outcome variable because fitted degree of internationalization and fitted scope of internationalization are highly correlated, and introducing both independent variables simultaneously creates multicollinearity. In model 1, we present the effects of controls and fitted degree of internationalization on the outcome variable; while in model 2 we show the effects of controls and fitted scope of internationalization on the outcome variable. Each outcome variable (international profits, subjective financial performance, life satisfaction, and happiness) has its own table with results. Effects presented are standardized for comparability reasons, and all models are based on ordinary least squares regressions.

Empirical Findings

Descriptive Statistics

Table 3.1 presents the descriptive statistics of variables in the analysis. On average, Indigenous businesses in the sample attain approximately 28% international profits out of total profits. Fitted degree of

Table 3.1 Descriptive statistics

Variables

Mean

SD

International profits

27.98

21.146

Subjective financial performance

0.41

0.745

Life satisfaction

-0.128

0.76

Subjective happiness

0.072

0.73

Fitted degree of internationalization

26.579

12.741

Fitted scope of internationalization

2.102

1.282

Firm size

12.47

12.496

Firm age

14.52

13.911

Entrepreneur’s gender

0.33

0.474

Entrepreneur’s business experience

0.43

0.790

Industry

0.09

0.283

N = 81.

internationalization is about 26.6% international sales out of total sales, while fitted scope of internationalization is approximately 2.1 countries, on average, in the sample of Indigenous businesses. Indigenous businesses in the sample have 12.5 employees and have been doing business for about 14.5 years. Thirty-three percent of owners in the sample are identified as female. Business owners in the sample have owned in the past 0.43 businesses on average. Nine percent of businesses in the sample compete in the manufacturing industry.

In Table 3.2, we can see the correlations among variables. To note, fitted degree of internationalization and fitted scope of internationalization are both positively correlated with international profits. Firm size (+) and firm age (-) are both correlated with subjective financial performance. Fitted scope of internationalization (+) and entrepreneur’s gender (-) are correlated with life satisfaction.

International Profits Models

Table 3.3 presents results of empirical models related to international profits. In model 1, fitted degree of internationalization has a significant impact on international profits (0.582, p < 0.001). In model 2, fitted scope of internationalization has also a significant effect on international profits (0.546, p < 0.001). In both models, r-squares are significantly different from zero, indicating a significant model fit. Multicollinearity is not a problem given that the maximum variance inflation factor in model 1 is 1.416 and in model 2 is 1.539.

Subjective Financial Performance Models

In Table 3.4, we can observe results of subjective financial performance models. In model 1, fitted degree of internationalization does not

Variables

1

2

3

4

5

6

7

8

9

10

11

1. International profits

1

2. Subjective financial performance

0.223*

1

3. Life satisfaction

0.178

0.231*

1

4. Subjective happiness

-0.012

-0.012

0.463**

1

5. Fitted degree of internationalization

0.375**

-0.043

0.004

-0.100

1

6. Fitted scope of internationalization

0.463**

0.092

0.245*

-0.072

0.773**

1

7. Firm size

0.018

0.259*

-0.040

0.101

-0.042

0.172

1

8. Firm age

0.074

-0.245*

-0.088

-0.046

0.063

0.172

-0.002

1

9. Entrepreneur’s gender

-0.004

-0.089

-0.221*

-0.028

0.156

-0.140

-0.168

-0.061

1

10. Entrepreneur’s

business experience

0.158

-0.205T

0.154

-0.084

0.267*

0.463**

-0.063

0.124

-0.122

1

11. Industry

-0.033

-0.033

-0.008

-0.036

0.399**

0.279*

0.324**

0.306**

-0.217T

0.111

1

**p < 0.01; »р< 0.055*р< 0.10.

Table 3.3 Models of international profits, beta coefficients

Variables

Model 1

Model 2

Beta

p-Value

Beta

p-Value

Firm size

0.074

0.442

-0.080

0.426

Firm age

0.038

0.686

-0.038

0.697

Entrepreneur’s gender

-0.056

0.562

0.105

0.289

Entrepreneur’s business experience

-0.016

0.873

-0.114

0.318

Industry

-0.239

0.028

-0.046

0.655

Fitted degree of internationalization

0.582

0.000

Fitted scope of internationalization

0.546

0.000

N

97

97

R-square

0.276

0.000

0.221

0.001

Adjusted R-square

0.227

0.17

Maximum variance inflation factor

1.416

1.539

Bold means values are statistically significant.

Table 3.4 Models of subjective financial performance, beta coefficients

Variables

Model 1

Model 2

Beta

p-Value

Beta

p-Value

Firm size

0.248

0.019

0.193

0.065

Firm age

-0.204

0.047

-0.224

0.028

Entrepreneur’s gender

-0.089

0.387

-0.053

0.595

Entrepreneur’s business experience

-0.165

0.125

-0.264

0.029

Industry

-0.080

0.493

-0.055

0.610

Fitted degree of internationalization

0.121

0.288

Fitted scope of internationalization

0.250

0.041

N

99

99

R-square

0.135

0.034

0.163

0.01

Adjusted R-square

0.079

0.109

Maximum variance inflation factor

1.442

1.595

Bold means values are statistically significant.

show a significant impact on subjective financial performance (0.121, p > 0.10). However, in model 2, fitted scope of internationalization has a significant effect on subjective financial performance (0.25, p < 0.05). In both models, firm age (+) and firm size (-) have significant effects on subjective financial performance, while entrepreneur’s business experience (-) has a significant effect only in model 2. R-squares of both models are statistically significant. Maximum variance inflation factors are within acceptable ranges, multicollinearity, thus, is not a problem.

58 Entrepreneurs’ Well-Being & IB Life Satisfaction Models

Table 3.5 shows empirical results for life satisfaction models. Unfortunately, r-squares for model 1 and model 2 are not statistically significant different from zero and therefore models do not present a good fit. In model 1, fitted degree of internationalization does not have a significant impact on life satisfaction (0.029, p > 0.10). In model 2, fitted scope of internationalization neither has a significant effect on life satisfaction (0.198, p > 0.10). Both internationalization variables examined in this study do not have significant effects on life satisfaction.

Subjective Happiness Models

Table 3.6 presents empirical results for subjective happiness models. In model 1, r-square is not statistically different from zero (0.046, p > 0.10). In model 2, r-square is not statistically significant either (0.046, p > 0.10). Fitted degree of internationalization, in model 1, does not have a significant effect on subjective happiness (-0.043, p > 0.10). Fitted scope of internationalization, in model 2, does not have a significant impact on subjective happiness neither (0.037, p > 0.10). Fit for both models is not statistically apparent, and both internationalization variables do not have significant effects on subjective happiness in this study.

Robustness Checks

We re-run empirical models for the sample of self-identified Caucasian businesses. We find that fitted degree of internationalization has a significant effect on international profits (0.571, p < 0.001) and that fitted scope of internationalization has a significant effect on international

Table 3.S Models of life satisfaction, beta coefficients

Variables

Model 1

Model 2

Beta

p-Value

Beta

p-Value

Firm size

-0.026

0.801

-0.065

0.535

Firm age

-0.079

0.433

-0.091

0.364

Entrepreneur’s gender

-0.124

0.234

-0.099

0.328

Entrepreneur’s business experience

0.046

0.667

-0.049

0.677

Industry

-0.053

0.644

-0.055

0.604

Fitted degree of internationalization

0.029

0.798

Fitted scope of internationalization

0.198

0.102

N

109

109

R-square

0.026

0.838

0.051

0.489

Adjusted R-square

-0.031

-0.005

Maximum variance inflation factor

1.376

1.54

Table 3.6 Models of subjective happiness, beta coefficients

Variables

Model 1

Model 2

Beta

p-Value

Beta

p-Value

Firm size

0.178

0.086

0.178

0.090

Firm age

-0.049

0.623

-0.049

0.622

Entrepreneur’s gender

-0.046

0.651

-0.050

0.622

Entrepreneur’s business experience

0.031

0.768

-0.003

0.983

Industry

-0.112

0.325

-0.130

0.219

Fitted degree of internationalization

-0.043

0.700

Fitted scope of internationalization

0.037

0.756

N

110

110

R-square

0.046

0.546

0.046

0.553

Adjusted R-square

-0.009

-0.01

Maximum variance inflation factor

1.375

1.565

profits (0.388, p < 0.01). Life satisfaction and subjective happiness models are not statistically significant. These results corroborate our main findings that internationalization significantly affects only economic performance outcomes.

Because level education has been suggested as an influencer of wellbeing, we include it as an additional control variable in empirical models for life satisfaction and subjective happiness, in the Indigenous sample. We find the fit of models does not change compared to main models.

We re-run all models assuming no endogeneity of degree and scope of internationalization, in the Indigenous sample. In other words, we entered the observed degree of internationalization and the observed scope of internationalization as independent variables. We find that degree of internationalization has a significant effect on international profits (0.94, p < 0.001) and that scope of internationalization has a significant impact on international profits (0.303, p < 0.01). These results confirm the economic performance impact of internationalization.

Finally, given that current literature also studies the influence of speed of internationalization on performance (Schwens et al., 2018), we also examine the effect of speed of internationalization on economic and non-economic performance outcomes in the Indigenous sample. We measure speed of internationalization as the number of years that have passed from starting up operations to the first international sale. We reverse coded this measurement so that lower numbers indicate slower speed while higher numbers indicate faster speed. Similar to fitted degree and scope of internationalization, we also compute fitted speed of internationalization. Our findings indicate that fitted speed of internationalization does not significantly affect international profits, subjective financial performance, life satisfaction nor happiness. We repeat the analysis using the observed speed of internationalization (instead of the fitted values) and find speed of internationalization significantly affects only subjective financial performance (-0.179, p < 0.10).

Discussion and Conclusion

This study set up to explore the performance impact of internationalization. In particular, we examined the influence of degree and scope of internationalization on economic and non-economic performance outcomes. We focused on international profits and subjective financial performance as measures of economic performance outcomes; and, on entrepreneur’s life satisfaction and subjective happiness as variables for non-economic outcomes. We employed a sample of internationalized Indigenous businesses based in Alberta and British Columbia, Canada to explore these relationships. We run several robustness checks to corroborate findings. Our results indicated that degree and scope of internationalization significantly impact international profits, scope of internationalization significantly affects subjective financial performance, and that neither degree of internationalization nor scope of internationalization significantly influence entrepreneur’s life satisfaction and happiness.

Implications for the Literature on Internationalization and Performance

Our findings that degree and scope of internationalization positively and significantly affect economic performance outcomes contribute to the literature in several ways. These findings confirm findings from previous literature that internationalization affects performance. For instance, Schwens et al. (2018) found a positive relationship between internationalization and performance. Bausch and Krist (2007) and Marano et al. (2016) also found a positive association between internationalization and performance. Our findings are also consistent with previous findings indicating that scope and degree of internationalization affect international profits. Schwens et al. (2018) found that both degree of internationalization and scope of internationalization affect profitability and growth, although they also found that the effect of scope of internationalization is larger than the one of degree of internationalization. In our robustness checks, we find that speed of internationalization does not affect international profits. These findings are also in line with Schwens et al. (2018) findings. They find that speed of internationalization does not exhibit a direct relationship with performance. Overall, our findings of the effects of internationalization degree, scope, and speed on economic performance outcomes confirm findings of previous literature. Internationalization - as measured in this study - has positive economic performance implications in the Indigenous context. In the future, literature can explore the role of moderators in the relationship between internationalization and performance, as suggested by Schwens et al. (2018).

That internationalization does not show a direct significant relationship to non-economic outcomes (well-being) is a major finding of this study. This finding is not only in the case of Indigenous businesses but also in the sample of non-Indigenous firms. Previous research has not accounted for the relationship between internationalization and noneconomic outcomes such as entrepreneur’s life satisfaction and happiness. Based on the entrepreneurship literature, we expected a positive and significant relationship between internationalization and well-being because of the growth aspirations of entrepreneurs, which can also affect their sense of achievement, self-acceptance, autonomy, engagement, meaning, and purpose (Dana, 1995; Wiklund et al., 2003). Our findings however indicate that neither degree of internationalization nor scope of internationalization significantly affect life satisfaction or happiness neither positively nor negatively. Given that, in this study, we are unable to find direct links between internationalization and non-economic performance, future research is encouraged to examine critical mediators. For instance, Nikolaev et al. (2019) study the mediation influence of psychological functioning (personal functioning and social functioning) as a pathway to entrepreneur’s well-being. It could be the case as well that entrepreneurs achieve well-being after internationalization creates a positive impact on their businesses’ international profits or growth.

From the findings of this research, internationalization seems to impact economic performance outcomes and not entrepreneur’s well-being. Internationalization may be an activity with only economic goals. Entrepreneurship has been demonstrated to affect well-being directly and indirectly (e.g., Nikolaev et ah, 2019) and to affect economic outcomes at the level of the business and macroeconomically (Pergelova & Angulo-Ruiz, 2014). Internationalization activities-as part of entrepreneurship - seem to only affect the economic aspect of entrepreneurship and therefore internationalization may be just an economic activity of businesses. In this line of reasoning, expecting internationalization to affect non-economic outcomes such as entrepreneur’s well-being might be out of focus. Another potential explanation of why internationalization does not affect non-economic performance is endogeneity; in this situation, those entrepreneurs with internationalized and non-internationalized businesses may be satisfied with life and happy. Future research needs to disentangle the intriguing finding that internationalization is not related to entrepreneur’s well-being directly.

Limitations

Future research should verify our findings of the lack of significant association between internationalization and entrepreneur’s well-being. While we use an interesting sample of Indigenous and non-Indigenous businesses, our sample is cross-sectional and small. Future research should collect longitudinal primary or secondary data with a large number of observations in order to assure the reliability of our findings. In the future, researchers can also test the association between internationalization and entrepreneur’s subjective well-being using businesses from different contexts and countries.

Future research should also embark in analyzing the impact of mediators and moderators on the relationship between internationalization and well-being. Profitability can be a potential mediator that may explain the influence of internationalization on well-being; in other words, entrepreneurs will show positive well-being only after internationalization has showed profits. Other psychological aspects may also play a mediator role. Additionally, it may be the case that internationalization can be an outcome of well-being instead of an antecedent. Future work should clarify the association between internationalization and well-being.

Note

1 For more information on the Indigenous context, please refer to Chapter 1 of this book.

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Zahra, S. A., Ireland, R. D., 5c Hitt, M. A. (2000). International expansion by new venture firms: International diversity, mode of market entry, technological learning, and performance. Academy of Management Journal, 43(5), 925-950.

Appendix 3.1 Descriptive statistics of variables in models related to degree and scope of internationalization

Variables

Mean

SD

Degree of internationalization

28.40

23.98

Scope of internationalization

2.24

2.15

Personal network

4.09

1.22

Business network

4.55

0.81

Government network

2.20

1.07

Internet

4.73

0.72

Labor seeking

0.21

0.84

Supply seeking

0.09

0.83

Technology seeking

0.01

0.85

Brand seeking

0.06

0.85

Government incentives

0.15

0.85

Market seeking

-0.33

0.95

Identity self-categorization

3.78

0.68

Identity prominence

3.63

0.79

Firm size

11.90

11.90

Firm age

14.35

13.15

Entrepreneur’s gender

0.36

0.48

Entrepreneur’s business experience

0.45

0.82

Industry

0.08

0.27

N = 106.

Appendix 3.2 Correlation matrix of variables in models related to degree and scope of internationalization

Variables

7

2

3

4

5

6

7

8

9

70

77

72

73

74

75

76

77

18

79

1. Degree of

internationalization

1

2. Scope of

internationalization

0.41**

1

3. Personal network

-0.30**

-0.32**

1

4. Business network

-0.00

-0.06

0.20*

1

5. Government network

0.04

0.07

0.03

0.06

i

6. Internet

0.16

0.03

0.10

0.06

-0.03

1

7. Labor seeking

0.03

0.10

0.13

0.09

0.26»»

0.13

1

8. Supply seeking

-0.02

-0.09

-0.04

-0.05

0.22*

0.26**

0.10

1

9. Technology seeking

0.02

0.21*

0.28**

0.05

0.38**

-0.26**

0.26**

0.11

1

10. Brand seeking

-0.18T

-0.14

0.08

-0.02

0.13

-0.01

0.19*

0.08

-0.02

1

11. Government incentives

-0.08

0.01

-0.15

0.23»

0.35»»

0.01

0.15

0.04

0.03

0.0.5

1

12. Market seeking

0.38**

0.38**

-0.36»»

0.12

0.09

0.15

0.12

-0.01

-0.02

0.18*

0.13

1

13. Identity

sel f-categori zati on

-0.10

-0.01

0.19*

0.05

-0.07

-0.04

0.00

-0.18*

0.08

-0.02

-0.01

-0.14

1

14. Identity prominence

-0.16

0.01

0.2*

-0.05

-0.11

-0.03

0.01

-0.09

0.14

0.06

0.05

-0.07

0.7**

1

15. Firm size

-0.06

0.09

0.03

0.16

0.35**

-0.13

0.18*

0.09

0.19

0.02

0.19*

-0.05

0.03

-0.03

1

16. Firm age

0.02

0.07

-0.09

-0.38**

-0.05

-0.14

-0.05

0.04

0.13

0.02

-0.18*

-0.15

0.01

0.1

0.04

1

17. Entrepreneur’s gender

0.03

-0.17*

0.27»»

0.18

0.00

0.15

0.06

-0.05

0.08

0.02

-0.16*

-0.05

-0.02

0.11

-0.16

-0.07

1

18. Entrepreneur’s business experience

0.19*

0.37»»

-0.35»»

-0.00

-0.03

-0.16

-0.18*

-0.13

-0.12

-0.2»

0.04

0.18*

-0.06

-0.07

-0.09

0.03

-0.17*

1

19. Industry

0.19*

0.14

-0.29»»

-0.24*

0.1

-0.04

0.0.5

0.29»'

• -0.02

-0.02

-0.13

0.07

-0.17*

-0.14

0.25»'

* 0.24*

-0.21»

0.15

1

”p < 0.01; *p< 0.05; *p< 0.10.

Appendix 3.3 Models degree and scope of internationalization, beta coefficients

Independent variables

Dependent variable: Degree of internationalization

Dependent variable: Scope of internationalization

Beta

p-Values

Beta

p-Values

Firm size

-0.062

0.553

0.126

0.185

Firm age

0.042

0.675

0.020

0.824

Entrepreneur’s gender

0.082

0.418

-0.098

0.286

Entrepreneur’s business experience

0.050

0.622

0.281

0.003

Industry

0.147

0.182

0.000

0.998

Personal network

-0.203

0.093

-0.238

0.028

Business network

0.029

0.785

-0.043

0.654

Government network

0.052

0.652

-0.054

0.601

Internet

0.190

0.080

0.224

0.023

Labor seeking

0.015

0.882

0.080

0.370

Supply seeking Technology seeking

  • -0.104
  • 0.140
  • 0.320
  • 0.230
  • -0.159
  • 0.361
  • 0.094
  • 0.001

Brand seeking

-0.187

0.058

-0.114

0.196

Government incentives

-0.106

0.327

-0.097

0.324

Market seeking

0.306

0.006

0.276

0.005

Identity self-categorization

0.089

0.486

0.000

0.997

Identity prominence

-0.145

0.264

0.061

0.598

N

106

109

R-square

0.314

0.005

0.427

0.000

Adjusted R-square

0.181

0.32

Maximum variance inflation factor

2.137

2.137

Bold means values are statistically significant.

 
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