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UNDERSTANDING SMEINTERNATIONALIZATION:
“WHAT IS THE RELATIONSHIP BETWEEN TOP MANAGERS’HUMAN CAPITAL AND SMEINTERNATIONALIZATION?”
UNIVERSITY OF GRONINGEN
FACULTY OF ECONOMICS AND BUSINESS
MSC BASMALL BUSINESS &ENTREPRENEURSHIP
FABIAN MAHOUTCHIAN
S3490092
SUPERVISOR:DR.SAMUELE MURTINU
CO-ASSESSOR:DR.CLEMENS LUTZ
DATE:25TH OF JUNE 2018 WORD COUNT:9.780
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Abstract
Globalization and international trade are more prominent than ever. However, international competition challenges small and medium-sized firms in their domestic markets. In order to stay competitive, firms must internationalize. Since small and medium-sized companies are highly influenced by their top managers, the relationship between top managers’ human capital and firm internationalization has been largely investigated. To date however, no study has challenged their findings by analyzing this relationship under modified circumstances. Furthermore, the effect of top managers’ gender on internationalization has been almost completely neglected in extant research.
Moreover, most studies focus only on one dimension of internationalization. Therefore, this study analyzes how the top manager’s industry-specific experience and gender concur to the firm’s propensity and degree of internationalization. Additionally, a scenario analysis is conducted to validate whether findings hold when a severe obstacle is introduced. I find that male top managers and top managers with more industry-specific experience are more likely to internationalize. Surprisingly, industry-specific experience is negatively related to the degree of internationalization. Eventually, the effect that human capital has on firm internationalization revokes almost completely when the firm is confronted with a financial obstacle.
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Content
Introduction ... 4
Theory and Hypotheses Development ... 6
SMEs ... 6
Internationalization ... 6
Human Capital and Internationalization ... 7
The role of industry-specific experience. ... 8
The role of gender. ... 9
Human Capital and Internationalization considering a Financial Obstacle ... 10
The role of industry-specific experience. ... 10
The role of gender. ... 11
Data & Methodology ... 12
Sample ... 12
Variables ... 13
Research Methodology ... 14
Results ... 15
Descriptive Statistics ... 15
Findings ... 17
Discussion ... 19
Management Implications ... 21
Limitations ... 21
Conclusion ... 22
References ... 23
Appendices ... 28
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Introduction
Small and medium sized enterprises (SMEs) represent up to 95% of all enterprises across all economies (WTO, 2016 p.13). Moreover, SMEs amount the major part of employment in most economies. In developed countries two thirds of employment can be attributed to SMEs (WTO, 2016 p.17). However, SMEs are on average less productive than large firms and therefore contribute only 30 to 40 per cent to their country’s GDP (WTO, 2016 p.18). Moreover, accelerated globalization and mounting trade agreements fuel overall competition as foreign companies enter local markets.
As a matter of fact, SMEs expand their activities to new markets to survive. For instance, Cerrato & Piva (2012) argue that internationalization enhances SME’s long-term growth and this improves chances to survive. More recently, Puig et al. (2014), who conduct their research on Spanish manufacturers, find that firms increase their chances to survive significantly when going international.
When it comes to internationalization, exporting displays the most common entry mode to foreign markets among SMEs (Johanson & Vahlne, 1977). While research on firm internationalization is largely existent, the importance of top managers’ human capital in SMEs’ internationalization is not sufficiently examined (Westhead et al., 2001).
The Resource-Based View (RBV) argues that a firm’s sustainable competitive advantage relies on its endowment of capabilities and resources (Wernerfelt, 1984; Barney, 1991). Barney (1991) argues that resources must be valuable, rare, inimitable, and non-substitutable to add to a firm’s sustainable competitive advantage. Resources can be tangible and intangible, although the latter are considered to be more critical in RBV since intangible resources are less prone to be perfectly imitated by competitors. The most common example for an intangible resource is the top manager’s (TM) human capital, which is a critical factor for a firm’s development of a sustainable competitive advantage, and thus for a firm’s chances to survive.
According to entrepreneurship literature and Human Capital Theory (HCT) high levels of human capital lead to venture success (Rauch et al., 2011), and partially compensate the lack of financial resources (Chandler & Hank, 1998) because high levels of human capital improve TM’s ability to detect and exploit opportunities (Shane & Venkataraman, 2000). For instance, Shepherd & De Tienne (2005) stress that prior knowledge in a specific industry, which contributes to human capital, is prevailing in recognizing opportunities (Kirzner, 1997). However, Hitt et al. (2001) suggest that industry-specific experience represents a critical dimension of human capital and the least imitable form of knowledge, which adds to an organization’s competitive advantage. Moreover, internationalization itself is an opportunity that can add to the firm’s competitive advantage. For example, Oviatt & McDougall (2005) state that ventures internationalize because SMEs find key
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advantages in internationalization such as access to larger markets and the discovery of exceptional opportunities.
Nevertheless, Johanson & Vahlne (1977) reason that internationalization is a risky endeavour with many obstacles and that a lack of financial resources reduces SMEs’ claim to internationalize (Leonidou, 2000). More precisely, limited access to financial resources drastically reduces flexibility and the ability to finance the process (Leonidou, 2000). As a result, SMEs facing financial obstacles are less inclined to expand to new markets.
But a recent study on the determinants of early firm internationalization in Chile found that TMs’ human capital is among others a key driver for firm internationalization (Amoros et al., 2016).
Furthermore, they argue that the TM’s human capital can mitigate the liability of newness in a new market and thus, diminish the extent of certain obstacles. Several scholars (Dencker & Gruber, 2015;
Marvel, 2013; Shane, 2000; Shepherd & DeTienne, 2005) have outlined the importance of top mangers’
experience accumulated in an industry for the overall assessment of his human capital. Accordingly, more experienced managers are more likely to implement successful strategies which are particularly important for internationalization. Therefore, industry-specific experience is a critical dimension for human capital.
Moreover, Orser et al (2008) suggest that the TM’s gender displays an important factor for firm internationalization. In most patriarchal societies, women are more often confronted with rejection, especially in business environments that are dominated by men. Consequently, women who succeed in this environment are likely to be more persistent and show higher tolerance levels for challenging situations. Hence, female TMs are less inclined to retreat from their decision of internationalization when facing the challenging process and thus, are more likely to overcome task related obstacles.
Above all, extant research on SMEs’ internationalization has mostly focused on a specific industry in one country (mainly the United States); further, most studies have used only one proxy for measuring internationalization, that is, either a dichotomous variable on whether the firm exported or not, or a continuous variable measuring the proportion of export to overall sales value (Westhead, 2001; Cerrato & Piva, 2012).
The goal of this study is to overcome above limitations and to refine current understanding of how human capital affects SME internationalization. I seek to provide a comprehensive study on SME internationalization by investigating both, the propensity and the degree of internationalization of 14.826 SMEs across multiple industries in 32 countries. In other words, this study assesses which effect the two defined dimensions of human capital have on SME internationalization and subsequently tests how effects change when the SME is confronted with financial constraints. Therefore, the following research question is being addressed:
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Do a TM’s gender and a higher industry-specific experience positively affect the propensity and degree of internationalization of an SME when it is confronted with a financial obstacle?
The remainder of this study is structured as follows. In section two, the theoretical background is discussed and the hypotheses regarding the predictor variables and internationalization are derived.
Subsequently, data are presented and the research methodology is outlined. Results are then reported. Conclusively, findings are summarized and discussed, followed by the potential implications and limitations of this study.
Theory and Hypotheses Development
SMEs
The definition of small and medium sized enterprises attends upon a firm’s staff headcount and yearly amount in turnover or the magnitude of the balance sheet (European Commission, 2018).
According to the European Commission a firm can be classified as an SME when the total amount of staff is less than 250 employees and turnover does not exceed 50 million Euros respectively the total balance sheet does not exceed 43 million Euros. For the purpose of this research, I will utilize the total amount of full time employees that was employed at the time of data collection to identify SMEs.
Internationalization
Many scholars have devoted their research to SME internationalization however; there is no general agreement on one single definition. According to some scholars, internationalization is a broad concept that explicates the boundaries of a firm (Buckley & Casson, 2009; Javalgi & Todd, 2011).
Similarly, Calof & Beamish (1995) define internationalization as a firm’s adaptation to the international environment. However, Turnbull (1987) finds that most studies depict internationalization as the outward movement of a firm’s operations. Then again, Bradley (1995) points out that internationalization is a strategical process with at least two choices namely, which foreign market should be entered first and how should it be entered? Likewise, the well-known Uppsala stage model by Johanson & Vahlne (1977) proposes that internationalization is a gradual process, which starts by entering neighboring countries at first and more remote countries at a later stage. Furthermore, the choice of a market entry reveals the firm’s level of commitment in a certain market. Accordingly, exporting products and services represents the first mode of entry and the lowest commitment while foreign direct investment represents the highest commitment.
Consequently, the export of goods and services can be referred to as the first step of SME internationalization (Andersen, 1997). In fact, Pukall & Calabro (2014)’s comprehensive review on
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internationalization reveals that most studies implicitly refer to the proportion generated outside a firm’s domestic market to identify international SMEs.
Extant literature has proposed several explanations for SME internationalization. For instance, internationalization theory explains internationalization by stressing potential cost reduction when transferring goods and services across national borders while strategic management theory proposes that firms choose opportunistically when confronted with changing market opportunities (Westhead, 2001). Dunning (1980)’s eclectic paradigm addresses three motivations for internationalization: (1) to exploit efficiencies derived from worldwide operations, (2) to exploit ownership-specific advantages in resources and capabilities or (3) to take advantage of the host countries’ favorable business environment (Liang et al., 2014). More recent, international business research has built on Dunning’s arguments, arguing that internationalization constitutes a requirement to survive in times of global competition, especially for SMEs (Cerrato & Piva, 2012). Concordantly, several scholars agree on SME internationalization being a strategic choice that is critical in promoting growth, increasing profitability and thus enhancing chances to survive (Morgan & Katsikeas, 1997; Skrt & Antoncic, 2004; Ruzzier et al., 2007).
Building upon RBV, the development of a sustainable competitive advantage relies on the organization’s endowment of strategic resources and capabilities to develop required resources (Barney 1991, Wernerfelt, 1984). Since internationalization displays an opportunity that can enhance growth and lead to a competitive advantage, it depends on the firm’s resources and the possibility to access required resources (Westhead, 2001; Fernandez & Nieto, 2006).
On the other hand, strategic management literature identified the TM’s abilities to be a determining factor when it comes to explaining SME behavior, especially regarding SME internationalization (Aragon-Sanchez & Sanchez-Martin, 2005). By extension, the TM’s abilities, referred to as human capital, constitute a firm’s critical intangible resource affecting SME internationalization. Accordingly, the TM’s human capital will be the focal point of the following section.
Human Capital and Internationalization
The concept of human capital was established to measure the economic value of an individual’s skillset (Schultz, 1961). Schultz (1961) suggests that human capital can be improved through investments and most likely results in higher pecuniary returns for the organization. More precisely, the basic assumption of HCT is that humans’ ability to learn contributes to the purpose of the firm (Nafukho et al., 2004; Lucas, 1988). With reference to RBV, a great level of human capital represents a non-tangible and thus a critical resource to the firm (Barney, 1991; Rangone, 1999).
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According to Barney (1991), human capital consists out of several dimensions such as general and industry-specific human capital (Neal, 1995).
Specific human capital refers to a person’s individual experience in a certain business field or industry. More accurately, industry-specific human capital refers to capabilities that are more valuable for one specific industry than they are for other industries. As a matter of fact, industry-specific human capital was found to be a reliable predictor for firm success (Brüderl et al., 1992; Cooper et al., 1994).
On the other hand, general human capital refers to the general background and comprises among others a person’s gender and education. While a person can influence its level of education, gender is usually not modifiable. In fact, Cooper et al. (1994) argue that gender is related to how accustomed a person is to encounter obstacles. The idea is that the hurdles encountered over time sustainably shape the individual’s human capital. Women are expected to face more difficulties in a patriarchal society and therefore have fewer opportunities to develop expertise (Sexton and Robinson, 1989). Consequently, gender represents an accurate proxy for general human capital (Cooper et al., 1994). To put it in a nutshell, in this study a TM’s human capital is represented by industry-specific experience and gender. Hence, I will elaborate on both dimensions develop hypotheses.
The role of industry-specific experience.
A TM’s industry-specific experience is characterized by the fact that it is beneficial in one specific industry and yet less valuable in other industries. According to existent research on internationalization, a manager’s prior experience is a critical dimension of human capital when it comes to firm internationalization (Fletcher, 2004; Losocco et al.,1991). Moreover, Cooper et al. (1994) argue that industry-specific experience is the tacit knowledge “of the products, processes, and technology to specific human capital investment in relationships and goodwill with specific customers, suppliers, or stakeholders” (p. 378) are embodied in people and it is inherently nontransferable (Becker, 1993).
The significance of this dimension stems from its characteristics as a resource. Arguing from the RBV perspective, a TM’s prior industry experience represents an intangible resource to the firm.
Resources are critical and contribute to the firm’s sustainable competitive advantage, if they are valuable, rare, and hard to imitate or to substitute (Barney, 1991). Respectively, intangible resources have the potential to be more critical than tangible resources when pursuing a sustainable competitive advantage because they are more difficult to be observed by competitors (Hitt et al., 2001).
Accordingly, a TM’s industry-specific experience displays a critical factor when it comes to business decisions. Not surprisingly, scholars found a TM’s industry-specific experience to be beneficial for SME survival and growth of new ventures (Cooper & Bruno, 1977; Bosma et al., 2004), while general work experience had little or no effect (Van Praag, 2003). In fact, Cooper et al. (1994) argue that a great
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industry-specific know-how can help to prevail the liability of newness which arises because of a lack of supplier and customer relationships, poorly conceived business practices, and difficulties in obtaining resources (Stinchcombe, 1965).
Internationalization constitutes a business opportunity to exploit advantages in foreign markets (Hanel & Ghauri, 2016) and opportunities discovery is more likely to happen via recognition than via active search (Shane, 2000). Managers with prior industry-knowledge and an advanced information network are more likely to pursue profit maximization and to identify opportunities across national borders (Westhead et al. 2001). Furthermore, Westhead et al. (2001) discover that industry- specific knowledge was a strong predictor for firm internationalization. More precisely, older principals with considerably high prior experience were more likely to be exporters. Additionally, more experienced managers are significantly more likely to detect opportunities than their younger counterparts (Ucbasaran et al., 2009). Similarly, Fariborzi & Keyani (2018) claim that SME internationalization is related to a higher risk of business failure if there is a lack of industry experience.
According to Delmar & Shane (2006), prior industry experience is extremely useful for exporting because social ties with suppliers and customers are built over time and this ultimately facilitates the establishment in a new market. Taking all things together, the greater a manager’s industry-specific- experience the more likely he or she is to internationalize the SME.
Therefore, this study suggests the following hypothesis:
H1a: A greater TM’s industry-specific experience positively affects SME internationalization
The role of gender.
Research on gender and venture performance has received respectable attention during the past decades. Nevertheless, studies have reported controversial findings and to date, results remain mixed (Post & Byron, 2015). For instance, Sexton & Robinson (1989) find that organizations led by women are more likely to perform poorly, while Kalleberg & Leicht (1991) propose that there is no significant difference in the performance between women and men (Cooper et al. 1994). However, the allegation that women-led firms significantly underperform men-led firms, is routed in the fact that most women-led firms are rather small. Several scholars have argued that women have fewer opportunities to gain valuable experiences and furthermore, they inherit higher risk aversity (Sexton
& Robinson, 1989; Cooper et al. 1994; Marlow & McAdam, 2013).
That said, Marlow & McAdam (2013) argue that women-led businesses clearly represent the norm of small businesses since, in general, they do not grow into big firms. Furthermore, they rout this misconception (women-led businesses underperform those of their counterparts) to the socio- economic context where women are historically discriminated against on the grounds of sex (Marlow
& McAdam, 2013). In fact, this explanation finds support in the ‘glass-ceiling theory’ and refers to a
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transparent barrier that detains women in business from equal remuneration and climbing up the career ladder to the board of directors (The Economist, 2005).
Considering that women in most societies continue to not be fully emancipated, I expect that women-led firms are less involved in international activities. Therefore, this study suggests the following hypothesis:
H1b: SMEs with a female TM negatively affect SME internationalization.
Human Capital and Internationalization considering a Financial Obstacle
The role of industry-specific experience.
As mentioned earlier, internationalization is a challenge for SMEs and requires a considerable allocation of strategic resources including access to financial resources to fund the endeavor. Leonidou (2000) argues that a lack of financial resources constitutes a main reason to firms to stay clear from internationalization. Furthermore, Gorodnichenko & Schnitzer (2013) find that financial constraints can mitigate a firm’s initial desire to internationalize. In fact, even opportunities that arise through information networks and social ties in an industry built over time often require a minimum of financial resources to be accessed and exploited. Moreover, abundant financial resources can enable a firm to react faster to the conditions of the environment, resulting in a greater flexibility. As a matter of fact, access has been argued to be even more valuable than other resources. For instance, Brush et al.
(2001) reason that financial resources and social resources are more important for the success of internationalization than human resources for SMEs.
However, although SME internationalization might require abundant financial resources, it is the TM who must guide the path and manage the process successfully. Certainly, the great progress in technology can reduce traditionally severe entry barriers as well as boundaries. To demonstrate, e- commerce can compensate the disadvantage of physical absence through digital marketing and customer service. Technology provides a possibility to mitigate a lack of financial resources. In fact, it is most probably that the TM will find an alternative route when confronted with a financial obstacle, especially when equipped with a high industry-specific experience. Hence, looking only at firms that are facing financial obstacles, those firms that managed to internationalize are more likely to be led by TMs with a great industry-specific experience. Therefore, this study proposes the following hypothesis:
H2a: A greater TM’s industry-specific experience positively affects SME internationalization when confronted with a financial obstacle.
11 The role of gender.
Access to finance has been argued to display more of a barrier to women than to men. Carter
& Shaw (2006) conduct a literature review and find that women-led firms have less access to finance and must provide more collateral. Then again, Cole & Mehran (2009) analyze loan approval in the US from 1987-2003 and report that women are in average not more credit constrained than men. Other than that, women-owned SMEs are more likely to start with less capital and throughout the lifecycle prefer personal over external finance (Carter & Shaw, 2006). Likewise, Coleman (2000) discovers that women-led firms do indeed use external finance less often. However, she finds no gender-based discrimination by lenders, which implies that women tend to avoid external finance. Interestingly, Marlow & Carter (2006) reason that women prefer to run smaller firms and thus demand for less external funds. Stefani & Vacca (2017) document that scholars suggested the moderate demand for finance is due to women’s higher risk aversion, which reduces women’s inclination to build on external capital (Dohmen et al., 2005).
In contrast to previous findings, Adams & Funk (2012) find that women directors are more risk loving and less security oriented than their male equivalent. Hence, women that ‘break the glass ceiling’ exhibit distinct characteristics that are traditionally being referred to male directors. More precisely, women that are used to overcome obstacles tend to be less disinclined by any additional obstacle.
With reference to women and SME internationalization there are only few studies to cover this topic and only one is conducted on a large scale. Orser et al. (2008) investigate on a sample of 8112 Canadian SMEs if male-led SMEs differ from female-led SMEs, regarding their propensity to internationalize and find that women-led businesses are in general less likely to do so. However, they discover that women-led exporters were significantly more likely to seek financial resources than their male counterparts. Thus, female top-managers do not show higher risk aversity than male TMs when operating in competitive levels.
All things considered, this research suggests that SMs that encounter a financial obstacle and still managed to internationalize are more likely to be led by female TMs. Therefore, this study suggests the following hypothesis:
H2b: SMEs with a female TM positively affect SME internationalization when confronted with a financial obstacle.
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Figure 1 visualizes the suggested relationship between human capital and SME internationalization in a conceptual model. Stage 1 presents the proposed relationship between the two dimensions of human capital (TM’s industry-specific experience and TM’s gender) and internationalization. However, the internationalization is operationalized by the means of two dependent variables. The first dependent variable is the propensity to internationalize, a dichotomous variable, and the degree of internationalization, a continuous variable.
In stage 2, the relationship of the two dimensions of human capital on the two dependent variables is examined however, this time under the precondition that the SME claimed to have financial obstacles.
Data & Methodology
Sample
The data analyzed in this research entirely derived from the fifth round of the Business Environment and Enterprise Performance Survey (BEEPS V). The survey was realized by the European Bank for Reconstruction and Development and the World Bank Group. It was conducted in 32 countries in the region of Eastern Europe and Central Asia. Top and senior managers of 16,566 firms with at least five employees have been interviewed on a comprehensive set of topics, including infrastructure, sales, competition, innovation, crime, finance, government relations, use of consulting services, and management practices.
I excluded firms with more than 250 employees since this study focuses on SMEs as defined by the European Commission. Furthermore, I excluded data when the respondent failed to provide answers to the TM’s gender and industry-specific experience, the establishment’s foundation year, the establishment’s share of total sales obtained domestically as well as from exports in the last fiscal year or the establishment’s industry. Finally, this sample consists out of 14,826 observations from all 32 countries (Albania, Armenia, Azerbaijan, Belarus, Bosnia, Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Georgia, Greece, Hungary, Kazakhstan, Kirgizistan, Kosovo, Latvia, Lithuania, Macedonia,
Figure 1 Conceptual Model
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Moldavia, Mongolia, Montenegro, Poland, Romania, Russia, Serbia, Slovakia, Slovenia, Tajikistan, Turkey, Ukraine and Uzbekistan). The quality of the applied data is highly reliable and has been used several times for research on business and business owner characteristics in transition economies
Variables
Dependent Variables. I use two variables to measure SME internationalization, that is, a dichotomous and a continuous variable. Although there is no ultimate consensus on which variable suits best to measure whether a firm is international, this study follows previous research utilizing SME’s exports as percentage of absolute sales (Amoros et al. 2016; Javalgi & Todd, 2010). The propensity to export is represented as the dichotomous variable (export sales>0=1; no export sales=0) and determines the precondition for the degree of internationalization, which captures the magnitude of export sales. This is consistent with previous research on internationalization (Reuber & Fischer, 2002).
Independent Variables. Human capital is the independent variable presented in this model.
Building on previous research this study suggests two dimensions of human capital: gender and industry-specific experience. The first is a dummy variable taking the value 0 when the TM is male and 1 when the TM is female, while the latter is defined by the amount of years the TM has spent his professional life in.
Scenario Analysis. This study aims to examine the effect of the independent on the dependent variable in the scenario of facing a financial obstacle. The interviewee was asked to rate to what degree access to finance displays an obstacle to the current operations of the establishment on a five-point Likert scale (0=no obstacle, 1=minor obstacle, 2=moderate obstacle, 3=major obstacle, 4=very severe obstacle).
For the purpose of the scenario analysis, I created a dummy variable based on the answers.
After testing for several thresholds (see Appendix), a cut-off point was found at “minor obstacle”
dividing the data set into two scenarios (0=no obstacle, minor obstacle / 1= moderate obstacle, major obstacle, very severe obstacle). In other words, I categorized all the SMEs that claimed to have no or minor obstacles with the value 0 and all the others with the value 1.
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Control Variables. This study identifies four control variables that possibly influence SME internationalization: firm size, firm age, industry, and the region it is located.
The firm size must be considered because scholars argued that international firms tend to be larger than their counterparts (Spence et al., 2011). To account for the skewness, the logarithm of this amount is utilized (Fariborzi & Keyani, 2018).
Moreover, I control for firm age since the Uppsala stage model suggests that firms internationalize gradually. Firm age is measured as the difference of years between the year of the interview and the years of foundation. Analog to firm size, the logarithm of firm age is being applied to account for the skewness.
For every observation the respective industry classification was compiled according to the official industry classification provided by the International Trade Centre. Since this research provides a comprehensive overview across four industries (manufacturing, other manufacturing, service, and retail) I created a dummy variable for each industry. For instance, when testing for manufacturing, all observations within that industry were given the value 1, while all other observations were given the value 0. This procedure was repeated for the four industries resulting in four dummy variables.
Finally, I controlled for regional differences in SME internationalization. Analog to the previous control variable, I generated several dummy variables. By grouping countries together based on their geographical location, four geographical regions were identified. Table 1 presents how countries were allocated to the respective geographical region.
Table 1 Regional allocation of countries examined in this research
Region Country
Eastern Europe Belarus, Czech Republic, Estonia, Latvia, Lithuania, Poland, Russia, Slovakia, Slovenia, Ukraine
Balkan Peninsula Albania, Bosnia, Bulgaria, Croatia, Greece, Hungary, Kosovo, Macedonia, Moldavia, Montenegro, Romania, Serbia
Central Asia Kazakhstan, Kirgizistan, Mongolia, Tajikistan, Uzbekistan Caucasus Armenia, Azerbaijan, Cyprus, Georgia, Turkey
Research Methodology
The conceptual model in figure 1 shows that the analysis is performed in two stages. First, the whole data set will be analysed according to above formulated hypotheses. Second, the data set will be split into firms that claimed that access to finance presents no or minor obstacles versus those who stated to face moderate, major or severe obstacles in terms of accessing finance. Subsequently, the
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suggested hypothesis will be tested on the split data set. Within each stage, I analyse which effect the predictor variables have on both, the dichotomous dependent variable (i.e., the propensity to internationalize) and the continuous variable (i.e., degree of internationalization).
I apply logistic regression to test for the dichotomous dependent variable, propensity to internationalize. Thereafter, I use a multiple regression (forced entry) to test for the effect on the continuous variable, the degree of internationalization. However, ‘non-exporters’ were excluded from the multiple regression, because that would have diluted the results, since the majority of the entire data set are ‘non-exporters’. This procedure is in line with previous research on internationalization (Westhead, 2001).
Results
Descriptive Statistics
The survey and interviews were conducted between 2011 and 2016 however, 60% of the data was collected in 2013. More than 47% of the companies examined in this data set are located in Eastern Europe, whereas 25% are on the Balkan peninsula, 16% in the Caucasus region, and finally 12% are based in Central Asia.
Regarding industries, 32% of the SMEs are allocated in the manufacturing industry. Moreover, an additional 8% can be accounted to ‘other manufacturing’. Furthermore, 35% are companies in in the service industry and eventually 25% of the SMEs account for the retail industry.
Since most of the data was collected in countries that belonged to the ex-Soviet Union and most firms used to be owned by the government, the owner structure of SMEs is outlined. Different from that, 92% of the SMEs are fully owned by private domestic individuals or companies and 2,6% by private foreign individuals or other companies. The remaining 5,4% are joint-ventures, including partial ownership of domestic and foreign parties. In fact, throughout the whole set, governments mostly only hold a fraction of company shares.
With respect of the company level, the average company is 14 years old and comprises 31 employees.
That said, 90% of the examined SMEs are younger than 22 years and started with fewer than 40 employees, which means that according to the European Commission most firms started as small companies (<50 employees). According to extant small business literature most businesses do not grow into large businesses (Aragón-Sanchez& Sánchez-Marín, 2005).
This seems to be particularly true as the average firm grew only by 2,5 employees since foundation average, at least regarding growth in terms of full-time employees.
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Furthermore, more than 80% of the SME’s TMs are men and only 20% of them are female.
Male TMs have spent in average 17 years in their respective industry while female TMs reach an average amount of 15,6 years in their respective industry. In total and regardless of gender differences, one third of all companies have a TM with less than 10 years of industry-specific experience and 10%
have less than 5.
Concerning international activities, the clear majority of 79,4% SMEs operate solely domestically. Thus, only 3.047 out of 14.826 SMEs can be identified as exporting SMEs. Out of those exporting SMEs 15% are led by female TMs.
The average exporting SME starts exporting approximately 6 years after foundation. However, 30% of exporting SMEs internationalize within their foundation year, so called “born globals” (Fariborzi
& Keyhani, 2018). Out of the born globals, 17% of led by female TMs with an average industry-specific experience of 16,7 years. On the other hand, 83% (of born globals) are led by male TMs with an average industry-specific experience of 18,5 years.
Table 2 Correlations
Mean Std. dev. 1 2 3 4 5 6 7
8 Financial obstacle (1/0) - threshold 1 ,54 ,498 -,023** -,010 ,015 -,022** ,029 -,028 ,009
9 Financial obstacle (1/0) - threshold 2 ,37 ,483 -,005 -,013 ,019* -,012 ,030 -,021 ,005
10 Financial obstacle (1/0) - threshold 3 ,19 ,394 ,024** -,019* ,014 -,003 ,023 ,010 -,009
11 Firm size (ln) 2,852 1,0401 ,096** -,104** ,221** ,188** ,067** ,019 ,037**
12 Firm age (ln) 2,4174 ,71917 ,428** -,025** ,143** ,088** ,570** -,210** -,041**
13 Eastern Europe ,47 ,499 -,121** ,062** -,044** -,071** -,031 -,072** ,018*
14 Balkan peninsula ,25 ,432 ,102** -,004 ,081** ,049** ,006 ,068** ,005
15 Kaukasus ,16 ,371 ,117** -,097** ,064** ,110** ,037 ,002 -,010
16 Central Asia ,12 ,325 -,083** ,022** -,113** -,080** -,014 ,014 -,023**
17 Manufacturing ,31 ,464 ,048** -,102** ,166** ,118** ,063** -,071** -,010
18 Other manufacturing ,08 ,270 ,063** ,040** ,178** ,223** -,068** ,109** -,037**
19 Retail ,23 ,423 ,006 ,148** -,160** -,143** ,027 -,062** ,013
20 Service ,37 ,482 -,098** -,053** -,117** -,112** -,045* ,025 ,018*
8 9 10 11 12 13 14 15 16 17 18 19 20
8 1
9 ,709** 1
10 ,451** ,636** 1
11 -,001 ,000 -,019* 1
12 -,015 -,016 -,006 ,200** 1
13 ,041** ,056** ,020* ,014 -,126** 1
14 ,012 ,035** ,034** -,075** ,126** -,538** 1
15 -,047** -,088** -,033** ,030** ,082** -,415** -,255** 1
16 -,026** -,032** -,038** ,044** -,067** -,346** -,212** -,164** 1
17 ,025** ,016* ,018* ,147** ,062** ,037** -,077** ,076** -,042** 1
18 ,009 ,003 ,002 ,096** ,051** -,058** ,005 ,092** -,024** -,198** 1
19 -,055** -,051** -,040** -,139** ,057** -,128** ,118** -,023** ,067** -,372** -,161** 1
20 ,024** ,032** ,021* -,065** -,145** ,126** -,027** -,139** ,001 -,513** -,223** -,420** 1
**. Correlation is significant at the 0.01 level (2-tailed).
*. Correlation is significant at the 0.05 level (2-tailed).
c. Cannot be computed because at least one of the variables is constant.
17 Findings
In table 3 the results of the logistic regression on the propensity of SME internationalization is presented. As mentioned above, in stage 1 the regression is conducted on the entire data set, regardless of any preconditions. Within the first stage, model 1 involves only the control variables while model 2 includes the prediction variables. Eventually, in stage 2 the scenario analysis is performed in model 3 and model 4. All models are significant with x² close to zero.
In a similar manner, the results of the multiple regression on the degree of internationalization are listed in table 4. Likewise, stage 1 shows the results of the regression, performed on the entire data set. Again, model 1 includes only the control variables and the predictor variables are added in model 2. Finally, stage 2 displays the results of the scenario analysis in model 3 and model 4. All models are significant with a F-value significance close to zero. Not surprisingly, all the control variables are highly significant which endorses their integration in the model for the overall validity.
Hypothesis 1a suggested that a great TM’s industry-specific experience would positively affect SME internationalization. Since SME internationalization is operationalized in two dependent variables, the effect on the propensity to internationalize will be examined first in Table 3, model 2. I find that a TM’s industry-specific experience (TMEXP) is highly significant (p<0,05) with a slightly positive beta (β=0,008) constituting a positive effect on SME’s propensity to internationalize.
Moreover, model 2 in table 4 reveals that TMEXP is also highly significant on the degree of internationalization. Surprisingly, there seems to be a negative relationship between TMEXP and SMEs’
degree of internationalization (β=-0,11). Consequently, Hypothesis 1a can only be partially confirmed.
Hypothesis 1b proposed that female TMs are less inclined to internationalize their SMEs. In fact, model 2 in table 3 shows that a TM’s gender (TMGEN) is highly significant with a negative effect on the propensity to internationalize (β =-0,242). That said, results for the degree of
Table 3 Logistic Regression: The effect of human capital on the propensity to internationalize
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internationalization unveil a completely different picture. As a matter of fact, TMGEN positively affects the degree of internationalization (β =2,99) at a significant level (p<0,1). Therefore, Hypothesis 1b can only be partially confirmed.
In hypothesis 2a I suggest that a TM’s industry-specific experience proves to be particularly beneficial for the purpose of SME internationalization when the firm is under stress, namely facing a financial obstacle. Model 4 in table 3 shows how the effect of TMEXP on the propensity to internationalize changes when the firm is facing a financial obstacle. I find that TMEXP has no significant (p>0,1) effect on a firm’s propensity to internationalize anymore when confronted with a financial obstacle. Additionally, I checked for the effect on the degree of internationalization.
Interestingly, model 4 in table 4 reveals that TMEXP is still highly significant on the degree of internationalization but the negative effect is even stronger than it was in model 2 (β=-0,29). Since none of results provides support for the proposed relationship, hypothesis 2a must be rejected.
Finally, hypothesis 2b suggests that SMEs with female TMs are positively related to internationalization when confronted with a financial obstacle. Starting with the suggested effect on SME’s propensity to internationalize, thus model 4 in table 3, I find that there is still a negative effect (β=-0,116) for female TMs on SME’s propensity to internationalize. However, different from model 2 in table 3, TMGEN is not significant anymore (p>0,1) which indicates that there is no significant difference between male and female TMs when facing a financial obstacle. Hereafter, the effect of TMGEN on the degree of internationalization when facing a financial obstacle is presented in model 4 of table 4. I find that TMGEN is not significant (p>0,1) as it was compared to model 2. However, there is an increase in the positive effect (β=3,77) on the degree of internationalization when the firm is
Table 4 Multiple Regression: The effect of human capital on the degree of internationalization
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confronted with a financial obstacle. Since TMGEN is not statistically significant on neither of the two dependent variables, hypothesis 2b must be rejected.
Table 5 Overview: Hypotheses vs. Results
Ind. Variable Hypothesis Dep. Variable Results
TMEXP
H1a) + Propensity to Int. +
H1a) + Degree of Int. -
TMGEN
H1b) - Propensity to Int. -
H1b) - Degree of Int. +
Financial Obstacle
TMEXP
H2a) + Propensity to Int. Ns. *
H2a) + Degree of Int. -
TMGEN
H2b) + Propensity to Int. Ns. *
H2b) + Degree of Int. Ns. *
*Not significant at the 0,1 level
Discussion
The purpose of this study was to shed light on the importance of TMs’ human capital and SME internationalization. More precisely, the analysis reveals which influence a TM’s industry-specific experience and gender pledge on the propensity and the degree of internationalization of an SME in general and when confronted with a financial obstacle. Ultimately, the research question must be negated, a greater human capital does not positively affect SME internationalization when the firm experiences a financial obstacle. Results reveal that only two out of eight assumptions can be confirmed (see table 5). In the remainder of this section I provide potential explanations for why the results turned out the way they did.
In contrast to what I expected, industry-specific experience does not affect the degree of internationalization positively. In fact, the relationship is negative. At this point it must be noted that, this study measures industry-specific experience in total years and thus, the more experience accumulated, the older the TM. Hence, it is possible that a greater level of industry experience is related to a rather conservative attitude and higher risk aversity simply because they are disinclined to put their family’s economic security at risk (Davis & Harveston, 2000). Similarly, Rauch & Rijsdijk (2013) who find a negative relationship between industry-specific experience and firm growth, argue that industry-specific experience is not easily transferrable to other industries and this increases the risk for managers with high specific experience. Consequently, managers with a great industry-specific
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experience could be likely to show higher risk-aversity simply because they depend on their life success of their endeavor and are reluctant to additional risk which comes with higher international exposures.
As a matter of fact, managers perceive foreign activities to be more risky than domestic activities (Johanson & Vahlne, 1977) since it requires taking decisions under great uncertainty.
However, March and Simon (1958) argue that older managers tend to be less flexible in their decisions than younger manager because they rely stronger on their own set of logics built according to their experience. Following this logic, older TMs who acquired their experience in their domestic environment would be less inclined to expose their business to a new environment because their set of logics might not apply there. In fact, Davis & Harveston (2000) suggest that older managers are less willing to push their business into foreign markets than younger managers.
Facing financial obstacles immediately increases the overall risk for the firm. Following the presented logic TMs with higher industry specific experience are even more retroverted to any additional risk exposure like a high degree of internationalization. Indeed, this is particularly true since the effect for industry-specific experience turned out to be stronger once the firm is confronted with a financial obstacle. Conclusively, a greater TM’s industry-specific experience (measured in years) is related to older TMs with higher levels of risk-aversity.
Furthermore, the assumptions on TMs’ gender did not exactly turn out to be as expected.
Nevertheless, this is particularly interesting, because the results prove that female TMs are less likely to internationalize in the first place but once they do, they export significantly more than male TMs (see distribution of export rates in Appendix 2). When relating internationalization to additional risk, this result indicates that female TMs are more risk-taking than male TMs and provides support for recent findings on ‘beyond the glass-ceiling theory’ (Adams & Funk, 2012). Although I expected to observe this effect only when confronted with an additional obstacle, the effect is still in line with what I argued in the literature review.
Finally, considering a financial obstacle, gender turns out not to be statistically significant anymore. Though, it reveals that female TMs are not significantly less likely to internationalize than male TMs when confronted with a severe obstacle. Likewise, gender is not statistically significant (p=0,16) on the degree of internationalization when confronted with a financial obstacle. With that in mind, it is remarkable that the beta coefficient for gender sprouts up from β=2,35 (no obstacle) to β=3,77 (obstacle). This indicates that female TMs manage to increase their degrees of internationalization although confronted with a financial obstacle and although not significantly.
However, this could be interpreted supportive for the ‘beyond the glass-ceiling theory’.
Then again, other factors may influence the effect of gender on internationalization in a way that the result did not turn out to be significant. For instance, the obstacle itself may be so severe, that the TM retreats, regardless of TM’s sex. The additional analysis section (Appendix 1) shows that having
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a financial obstacle (FIN_OBS2) alone already significantly accounts for lower degrees of internationalization. In other words, it could be possible that the financial obstacle imposes such a severe obstacle, that it is simply not reasonable for TMs to sustain high degrees of internationalization.
Management Implications
The results have implications for consultants who advise SMEs on their expansion strategies.
For instance, consultants should inform business owners about the promoting effect the TM’s industry- specific experience has on the propensity to internationalize but with the addition that they account for moderate export rates. Hence, a more experienced TM facilitates internationalization yet a less experienced TM pushes the degree of internationalization. Furthermore, female TMs were found to be a strong predictor for higher degrees of internationalization. Then again, this applies only if the firm has abundant access to financial resources or is not facing any financial constraints. In fact, financial obstacles are detrimental to higher degrees of internationalization. Thus, any financial constraints should be removed beforehand. Finally, female TMs do not significantly differ from male TMs in the internationalization process when considering financial obstacles. Consequently, a gender-based selection of the TM in turbulent phases does not significantly affect the outcome of the internationalization process.
Limitations
This study builds on the BEEPS V survey conducted in cooperation with the World Bank Group and the European Bank for Reconstruction and Development. Since the data is collected in a professional survey, the quality of the data set is remarkably high and thus has been used for several studies. Furthermore, it constitutes an unprecedented coverage of information allowing scholars to analyze research questions across 32 countries and multiple sectors.
In contrast to most studies, this research analyzes the presented relationships across countries and sectors, which enables this study to overcome limitations outlined by previous scholars. However, the analysis builds on a snapshot of the data. Consequently, interpretability is limited to one specific point in time and information is to a great extent self-reported (by the manager), which increases the risk of biased information. Since the presented data set is the fifth round of this survey, a longitudinal study build on panel data could reduce that limitation and increase the interpretability of the results by analyzing how the export rate changes in accordance to the TM.
Moreover, the focal variable of this study, industry-specific experience, is solely measured via the amount of years a TM has spent within a certain industry. Measuring experience in a certain business field by building only one dimension limits the legitimacy with which implications can be drawn, because experience is a complex construct that depends on many factors such as the way
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experience was obtained. Moreover, this measurement implies that a higher level of industry experience can only be accumulated by the time spent within the industry. The fact that in this study a greater industry experience always comes with a higher age, must be accounted for. Although the amount of years presents a reasonable proxy for experience, experience does not necessarily grow linearly. In fact, learning curves are more likely to be steep at the beginning and flatten out after a while. To increase quality, more dimensions should be taken into account such as prior management experience and network range considering suppliers and customers, since these dimensions resemble how well the individual knows the industry.
Conclusion
This study researched the effect of TMs’ human capital on SME internationalization. More precisely, I analyzed the impact of TMs’ industry-specific experience and gender on SMEs’ propensity to internationalize and its degree of internationalization. Additionally, I investigated how the relationship changed when the firm was exposed to a financial obstacle. Results show that SMEs are more likely to be international when the TM accumulated more industry-specific work experience.
However, a higher range of industry-specific experience affects the degree of internationalization negatively. In other words, TMs with great industry experience are more likely to internationalize their companies but only at moderate levels. When confronted with a financial obstacle, the level of industry-specific experience does not affect whether a firm internationalizes. However, TMs with higher industry-specific experience are even stronger negatively related to export ranges when facing financial obstacles.
Moreover, female TMs were found to be less likely to internationalize. But among exporting SMEs, those which were led by female TMs, exhibited higher degrees of internationalization. Then again, when confronted with a financial obstacle, female-led firms are not significantly less likely to internationalize. In fact, female TMs positively affect the degree of internationalization but when facing a financial obstacle, this effect is not statistically significant anymore. Above all, financial obstacles do not only constitute a severe threat to firms but they clearly lead to a reduction of firms’
engagement in international activities.
