W. s. van der Galiën (S3849716) Rijksuniversiteit Groningen Master Thesis IB&M Supervisor: Dr. H.J. Drogendijk

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THE RELATIONSHIP BETWEEN CEO INTERNATIONAL EXPERIENCE AND FIRM PERFORMANCE: EFFECT OF INDIVIDUAL TRAITS

W. s. van der Galiën (S3849716) Rijksuniversiteit Groningen

Master Thesis IB&M

Supervisor: Dr. H.J. Drogendijk

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Abstract

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Introduction

Why do organizations behave as they do? This field of research has been studied for decades and the answer is constantly evolving. One aspect within this field of study is ‘the CEO effect’, which can be defined as: “the proportion of variance in performance that is attributable to CEOs” (Quigley & Hambrick, 2015). According to Quigley and Hambrick (2015), CEOs impact the way firms behave through for example making strategic decisions and organizational design choices. Additionally, they claim that this CEO effect has strengthened in recent decades due to various developments in the business environment. Subsequently, as literature claim CEOs to affect the way firms behave, is the ability of a CEO to make strategic choices a source of heterogeneity?

Hambrick & Mason (1984) posit that strategic choices and therefore organizational outcomes are to some extent predicted by individual background characteristics. They argue that one’s managerial background affects his/her cognitive base and values. This implies that previous experience gained by a CEO affects the way he/she makes strategic choices. Thus, as CEOs differ in their experience based knowledge, individual decision making can be described as a source of heterogeneity at firm-level in strategic decision making (Maitland & Sammartino, 2019; Hamrick and Mason, 1984). In addition, when relating this to international business, to effectively influence firm outcomes through strategic change, CEOs need the ability to understand how to work in foreign contexts (Le & Kroll, 2017). Le & Kroll claim that CEO international experience has a positive effect on firm performance. Consequently, a CEO’s international experience can be recognized as a valuable resource for a firm.

The previous paragraph focuses on the ability of CEOs to make the right strategic choices. This is believed to impact the way a firm behaves and is influenced by individual managerial background characteristics. Nonetheless, CEOs have different reactions to the same learning experience (Kolb, 1976). Kolb argues that based on an individual’s past life experience and the demands of the present environment, he/she develops dominant learning abilities. Thus, instead of only focusing on if a CEO possesses international experience, the ability to make strategic choices also depends on how a CEO learns from international experience. This is likely to be influenced by personal traits and learning styles (Kolb, 1976; Caligiuri & Tarique, 2012). In short, this indicates the existence of a research gap, referring to whether individual traits and learning styles impact a CEO’s learning and development in a foreign context. Do CEOs have the same ability to make strategic choices when having the same international experience? Or do they differ in this ability due to particular individual characteristics and/or learning styles? In particular, this research will study the moderating role of individual traits, resulting in

different ways of learning in a foreign context, on the relationship between a CEO’s international experience and firm performance. Because there are too many individual traits to

cover all in one research, this research will explore this issue focusing on gender, cultural

background, and educational background. These items are highlighted in several studies

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Literature review

International experience: Firm level versus individual CEO level

According to the resource based view, a firm is a bundle of resources, including all assets, information, knowledge, etc. that are controlled by the firm (Barney, 1991). Barney argues that when resources used for value enhancing strategies are valuable, rare, inimitable, and non-substitutable they can be viewed as sustainable factors enhancing firm performance. An important resource of a firm is knowledge (Dimov & Martin De Holan, 2010). This is acquired through experiential learning (Kolb, 1984). When analysing firm level experience, experiential learning is essential for the internationalization process (Schwens, Zapkau, Brouthers, & Hollender, 2018). Schwens et al. (2018) claim that previously gained knowledge supports the development of for example processes and routines that enhance future uses of same entry modes, which reduces uncertainty, and leads to better firm performance.

Carlsson et al. (2005) claim that the experience of the firm affects performance rather than the experience of an individual manager, as they claim that a firm’s ability to learn cannot simply be described as the sum of the learning abilities of employees. This depends on how well a firm can transfer knowledge across and within its business units (Cohen & Levinthal, 1990; Carlson et al., 2005). Therefore, firm experience matters. However, firm employees, including the CEO, are part of a firm’s human capital resources, which is argued by Grigorescu & Chiper (2016) as vital for any organization. According to studies related to CEO international experience, CEOs significantly affect firm performance (Le & Kroll, 2017; Magnusson & Boggs, 2006; Quigley & Hambrick, 2015). Additionally, the more power the CEO has, the higher his/her impact on firm performance (Adams, Almeida, & Ferreira, 2005), which in other words can be described as the amount of individual discretion a CEO has (Crossland & Hambrick, 2011). In short, according to the literature, both firm experience and CEO experience impact firm outcomes. However, this research will focus on the individual level impact of CEOs.

The CEO effect and Managerial cognition

The idea that CEOs have impact on firm outcomes is not new within the field of strategic management and international business. Various research activities have been dedicated to the impact of CEOs on firm outcomes, which in other words can be described as the CEO effect (Crossland & Hambrick, 2011; Quigley & Hambrick, 2015). That CEOs matter, was studied by Wiersema and Bantel (1992), who supported that top management teams have significant effect on strategic choice and found that demographic characteristics of top managers impact this relationship. Furthermore, Lafley (2009) argues that the CEO acts as the link between the organization and the external environment e.g. the economy, markets, technology, and customers. In short, this indicates that CEOs matter. They are the ones that make important strategic decisions, which are of significant value for a company, require a high cognitive ability, and are highly uncertain (Adams, Keloharju, & Knüpfer, 2018; Wai & Rindermann, 2015).

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5 specific consequences or alternatives. Moreover, these givens form a filter that impact a CEO’s perception of the situation and the course of action related to the situation. Nevertheless, Hambrick and Mason (1984) argue that CEOs cannot perceive every aspects of the internal and external environment. This limited perception is caused by the CEO’s field of vision, selective perception, and interpretation. Thus, they point out that the combination between a CEO’s eventual perception of the situation and his/her values will be the basis for strategic choice. Therefore, as CEOs differ in their experience, resulting in individual-level differences, individual decision making and learning is likely to cause heterogeneity in firm-level strategic decisions (Maitland & Sammartino, 2019).

Finkelstein and Hambrick (1987) developed the concept of managerial discretion, referring to the latitude of action available to top managers. They found that the relationship between the characteristics of top managers and firm outcomes is moderated by the degree of discretion. In addition, Crossland and Hambrick (2011) confirmed this relationship arguing that top managers only influence firm outcomes in proportion to the amount of discretion they have. This partially depends on how national institutions are shaped. Therefore, while recognizing that context significantly impacts a CEO’s latitude of action, it still remains valid to argue that CEOs are likely to influence firm outcomes individually.

Quigley and Hambrick (2015) claim that the proportion of variance in performance, that is attributable to the CEO, has increased in the past decades. They affirm that this is due to the increased emphasis on shareholder returns (encouraged to consider more risky actions), a more dynamic and fast paced business environment, and an increased availability of strategic options caused by internationalization. This indicates that due to the increased importance of CEOs, the individual decision making process of CEOs is of high influence. In short, CEOs make strategic choices and therefore impact firm performance, while the ability to make these strategic decisions depends on their individual cognitive base and values. This is to a great extent determined by past experiences.

Experiential learning theory

As the ability of a CEO to make strategic choices depends on his/her managerial cognition, previous experiences are the starting point of his or her choices (Maitland & Sammartino, 2019). However, not every CEO learns the same from a particular experience (Kolb, 1976). Kolb (1984), author of the experiential learning theory, defined learning as: “the process whereby knowledge is created through the transformation of experience”. He argues that learning is a four-stage cycle, indicating that ‘the learner’ possesses four abilities, namely concrete experience, reflective observation, abstract conceptualization, and active experimentation. In other words, this ‘perfect cycle’ implies that he/she must experience situations without having any bias; have the ability to reflect on and observe the experiences from multiple angles; form concepts that combine these observations into theories; and be able to solve problems by using these theories in making the right decisions. Nevertheless, Kolb claims that this cycle is hard to achieve as it requires abilities that are polar opposites. Thus, this allows individual managers to express unique styles of learning, implying that individuals develop dominant learning abilities.

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6 on thinking instead of feeling. Last of all, the fourth learning ability is described as active experimentation, which is a learning ability that focuses on actively influencing humans and changing situations. Based on the four learning abilities, Kolb defined four dominant management learning styles that occur most frequently (Figure 1).

Figure 1: Experiential learning cycle (Kolb, 1976)

Firstly, the accommodator is best at concrete experience and active experimentation. He/she can be described as a risktaker that has great strength in doing things and involving himself/herself in new experiences, while having the ability to quickly adapt to the specific situation. Secondly, having reflective observation and abstract conceptualization as dominant learning abilities, the assimilator is less of a risktaker, focusing more on theoretical models. The assimilator has great strength in incorporating several observations into an integrated explanation. Thirdly, the converger is best at abstract conceptualization and active experimentation. He/she is a manager that is excellent in the practical application of ideas and excels in solving problems that only have one correct answer. This style is close to the assimilator, but is more concentrated on existing theories. Lastly, with having concrete experience and reflective observation as dominant learning abilities, the diverger can be described as a creative manager with a strong imaginative ability, which implies that he/she can view situations from various perspectives.

Learning styles and firm performance

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7 the ability to influence humans, change the situation, take risks, adapt quickly, and focus on the uniqueness and complexity of the situation (Kolb, 1976; Kolb 1984)

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Hypothesis development

International experience and firm performance

Before discussing individual traits, the main relationship that this study builds on is the impact of international experience on firm performance. Le & Kroll (2017) claim that CEO international experience has a positive effect on firm performance. They argue that CEO international experience assists in developing skills, broader worldviews, and forming international networks. Additionally, the authors also mention that CEO international experience enhances the ability to process complex and dynamic information. As CEOs are the driving force of strategic change, all these capabilities can be viewed as a competitive advantage for a firm. Thus, this is likely to positively relate to firm performance (Le & Kroll, 2017). Furthermore, Hsu, Chen, & Cheng (2013) also affirm this relationship claiming that international experience enhances capabilities that are essential for dealing with complex international environments. For example, the authors mention that CEOs without relevant international experience might spend suboptimal time and attention to examining the international environment, the integration process of subsidiaries, and their own role within the operations. This might lead to suboptimal performance. Therefore, CEO international experience is expected to have a positive effect on firm performance.

Hypothesis 1: A CEO’s international experience is likely to positively relate to firm

performance.

Gender and learning styles

Gender equality in top management has become an important item for society. Although men still dominate the top management positions, the amount of female CEOs has increased over time (Ho et al., 2015). Ho et al. (2015) claim that decision making differs between female CEOs and male CEOs. They found for example that female CEOs have a greater orientation towards ethical behavior.

Furthermore, Garber, Hyatt, & Boya (2017) studied two hundred twenty business students that actively engaged in a series of business games. Their study also revealed the existence of differences in learning styles between males and females. They found that females have a dominant orientation towards concrete experience and males have a dominant orientation towards abstract conceptualization. As previously mentioned, Armstrong and Mahmud (2008) argue that participants with a dominant preference towards the accommodator style achieved the highest levels of managerial tacit knowledge from experience. The accommodator has concrete experience and active experimentation as dominant learning abilities. Consequently, due to the accommodator learning style being closely related to concrete experience, and females having a dominant orientation towards this learning ability, it is expected that female CEOs gain higher levels of managerial tacit knowledge from their international experiences than male CEOs. This is due to the fact that female CEOs excel in learning from experiences that require a personal approach with concern to the uniqueness of the situation, which is closely related to the tasks that CEOs need to perform (Adams et al., 2005; Armstrong & Mahmud, 2008; Garber et al., 2017; Kolb, 1984; Lafley, 2009). On the contrary, Male CEOs excel in learning from experiences that require logic, ideas, and concepts (Garber, Hyatt, & Boya, 2017; Kolb, 1984), which is not always possible in the case of CEOs working in a highly uncertain environment (Adams et al., 2018).

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9 summary, female CEOs are likely to gain more managerial tacit knowledge from international experience than male CEOs, which therefore implies that international experience of female CEOs might have a stronger positive effect on firm performance than international experience of male CEOs.

Hypothesis 2: A CEO’s gender is likely to moderate the relationship between

international experience and firm performance such that the positive relationship will be strengthened when the CEO is female.

Uncertainty avoidance and learning styles

Next to gender, culture is also related to learning styles (Joy & Kolb, 2009). As culture is a broad concept, and due to lack of time and resources, this study will focus on the uncertainty avoidance dimension. This dimension is part of the six dimensional framework developed by Hofstede, one of the pioneers in cross-cultural research, also including the dimensions masculinity, long-term orientation, indulgence, power-distance, and individualism (Hofstede & Bond, 1984). Hofstede and Bond (1984) defined uncertainty avoidance as: “the extent to which people feel threatened by ambiguous situations, and have created beliefs that try to avoid these”. Barr and Glynn (2004) argue that uncertainty avoidance is an important aspect in strategic action as it is linked to the perception of the controllability of strategic issues. With controllability the authors imply the distinction between threats, which are associated as uncontrollable, and opportunity, which is associated as controllable. This is based on Dutton and Jackson's (1987) original idea, who claim that classifying an issue as threat or as opportunity influences the information processing and motivation of the decision maker. Therefore, this is likely to impact organizational actions in response to the issue. Barr and Glynn (2004) address the Hofstede uncertainty avoidance dimension to be most related to controllability.

In addition, Barr and Glynn (2004) claim that in high uncertainty avoidance countries, the rules, regulations and laws are broadly applied in order to control and predict an otherwise uncertain environment. Consequently, the authors found that uncertainty avoidance influences the degree to which humans perceive controllability as threat or opportunity. This implies that individuals from high uncertainty avoidance countries have a significantly stronger association with viewing the lack of controllability as a threat compared to individuals originating from low uncertainty avoidance countries. Thus, as labeling strategic issues as threats or opportunities impacts organizational actions (Dutton and Jackson, 1987), the level of uncertainty avoidance can be seen as an important determinant in how CEOs make strategic decisions.

Joy & Kolb (2009) found that the higher the degree of uncertainty avoidance within a society the greater the reliance on the learning abilities abstract conceptualization and reflective observation. This indicates a preference for the assimilator learning style. When relating this to managerial tacit knowledge, CEOs originating from countries with high uncertainty avoidance are expected to achieve less managerial tacit knowledge than CEOs originating from low uncertainty avoidance countries. This is due the fact that CEOs from high uncertainty avoidance are less likely to have a dominant preference for the accommodator learning style, which relies on experiences that involve high uncertainty, rely on open and creative learning situations that allow room for sense of empiricism (Joy & Kolb, 2009). Based on this, individuals originating from high uncertainty avoidance countries are likely to perceive a mismatch between context and dominant learning style when performing in a highly uncertain environment.

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10 countries have greater ability to make strategic choices than CEOs from low uncertainty avoidance countries, which is predicted to have greater positive effect on firm performance.

Hypothesis 3: A CEO’s cultural background, narrowed down to uncertainty avoidance,

is likely to moderate the relationship between international experience and firm performance such that the positive relationship will be strengthened when the CEO is originated from a low uncertainty avoidance country.

Education and learning styles

A dominant preference towards the accommodator learning style is positively related to achieving higher levels of managerial tacit knowledge from experiences. However, despite having any dominant preference towards a learning style, how somebody learns from international experience is also related to one’s general cognitive competency. This is to some extent related to an individual’s educational background (Furnham, Swami, Arteche, & Chamorro-Premuzic, 2008; Kolb, 1984). Various research papers highlight the role of CEO educational background on firm performance (Elsaid, 2014; Frey & Detterman, 2004; Gottesman & Morey, 2010). Some claim the existence of a significant relationship between these two variables, while others argue this relationship to be insignificant. Nonetheless, one aspect is certain within this research field; A CEO’s cognitive competencies are significantly improved by education (Falch & Sandgren Massih, 2011).

An individual’s general cognitive competency involves his/her mental capability regarding problem solving, information processing, and the implementation of creative ideas (Endicott, Bock, & Narvaez, 2003; Godart, Maddux, Shipilov, & Galinsky, 2015). In addition, when a CEO’s general cognitive competencies are high, he/she has greater ability to assimilate new knowledge (Cohen and Levinthal, 1990). This concerns one’s absorptive capacity, which Cohen and Levinthal (1990) define as: “the ability to recognize the value of new information, to assimilate it, and eventually to apply it”. In other words, high general cognitive competencies lead to high absorptive capacity. This indicates that CEOs with a high cognitive competency have greater chance that their cognitive schemas (knowledge, memories, past experience, etc) can recognize and assimilate the information presented, consequently not requiring any restructuring of cognitive frameworks (Fee et al., 2013).

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11 In summary, it is likely that CEOs who have an educational background in business education and/or who have had a high quality education will be more able to gain managerial tacit knowledge from their international experience than CEOs with lower quality educational backgrounds. This might positively relate to firm performance.

Hypothesis 4a: A CEO’s educational background is likely to moderate the relationship

between international experience and firm performance such that the positive relationship will be strengthened when the CEO has an educational background of high quality.

Hypothesis 4b: A CEO’s educational background is likely to moderate the relationship

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Methodology

Sample and Data collection

This study focuses on CEO-level data. The CEO data was collected from the secondary database Boardex. This database offers four board summaries, including one of the United States, one the United Kingdom, one of Europe, and one of the rest of the world, providing data of hundreds of thousands board members over the past decades. These board summaries (raw data excel files) give information about board members’ their name, role, age, compensation, company etc.

As this research focuses on the impact of a CEO on firm performance, and a CEO’s strategic impact is mostly visible after the moment of succession and the years after (Herrmann & Datta, 2002), this study exclusively selected newly appointed CEOs. Thus, the study was required to determine a starting year in which the CEOs have been appointed. Based on the balance between the availability of financial information (annual reports) and the actuality of the information, this study used 2014 as starting point.

In order to proceed from multi-year data of all kinds of board members to exclusively newly appointed CEOs in 2014, the four board summary data files were filtered down by role (only CEOs), by annual report date (December 2014), and by time in company (maximum of one year). After the filter process, the data of 356 CEO’s remained, which were transferred into one data file. Subsequently, each CEO within this data file was screened. This refers to analyzing if the particular CEO is currently active on LinkedIn and is working in a company that has disclosed the annual reports of 2014, 2015 and 2016. If these requirements were fulfilled, the necessary data was collected and added into an separate excel file. Eventually 90 CEOs remained, indicating this research will use a sample of 90newly appointed male/female CEOs in 2014.

As men still dominate in top management positions (Ho et al., 2015), the sample is to a great extend represented by male CEOs. Furthermore, the collected CEO data is from multiple countries based in different continents. This is important because the focus of this research is partially on cultural- and educational background, consequently requiring data that represents cultural- and educational diversity. Unfortunately, due to lack of available information concerning CEOs originating from South-America, Middle-America, Africa, Asia, and Oceania, the sample is dominated by CEOs originated from Europe, North-America, and the United Kingdom. However, there still exists plenty of diversity within the sample.

All CEOs that are included in this sample work for multinational companies, referring to companies that operate in more than one country. Multinational companies provide room for CEOs with international experience to actually exploit their extended international knowledge on the company’s strategic actions. This allows this research to measure the impact of international knowledge on firm performance more thoroughly.

Dependent variable

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13 because it measures the effectiveness of a firm’s strategy (Thornhill & White, 2007). In order to fully capture the CEO’s impact after his appointment on the company’s financial performance, this study has used the average operating margin of 2014, 2015 and 2016. The operating income is obtained from annual reports.

Table 1: Summary dependent variable

Variable description Source Measurement

Financial performance

“Operating margin” Annual report of the particular company (Operating income/Revenue)

Average Operating margin of 2014, 2015, and 2016

Independent variable

The independent variable of this research is international experience. Recent research has conceptualized one’s individual international experience by taking into consideration multiple aspects, such as the number of countries in which he/she has worked abroad (breadth), cultural distance, and the length of time he/she has spent abroad (depth) (Hsu et al., 2013; Le & Kroll, 2017). For this study both data concerning breadth and depth have been collected. However, the two measurement variables show a significant correlation of 0,76 (Appendix 1) and variation inflation factors of 3,178 and 3,069 (Appendix 2), indicating a potential sign of multicollinearity.

Based on the multicollinearity concern, it has been decided to only use one of the two variables, namely depth, to capture international experience. The average number of countries in which the CEOs (used in this sample) have worked abroad is below 1. This indicates not much variation in the breadth measurement variable. Consequently, this study has chosen to use depth to conceptualize a CEO’s international experience, as depth is believed to relatively capture a CEOs overseas experience more effectively.

International experience has been measured via a CEO’s LinkedIn profile. Based on the CEO’s prior work experience, it has been collected how many years each particular CEO has worked abroad. In addition, a minimum of one year international experience is required to claim a CEO to have substantial international experience. With experience, this study refers to work-related experience, excluding an individual’s study time abroad.

Table 2: Summary independent variable

International experience LinkedIn Depth = amount of years a CEO has worked abroad

Moderating variables

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14 countries act as the external environment (rules, laws, language, etc.) in which individuals interact, support formal institutions in order to provide a well-developed institutional framework, and generate a national identity (Maseland & van Hoorn, 2017). Therefore, it can be argued that using the Uncertainty Avoidance Index within this research still holds relevance. Next to uncertainty avoidance, the third moderator is educational background. In order to test hypothesis 4, each CEO’s educational background (psychology, physics, business, etc.) and quality of education have been measured. Educational background has been collected from LinkedIn. Additionally, with quality of education, this study refers to the overall rank of the university where a particular CEO has enjoyed his/her education. The ‘university rank’ has been collected from the world’s university rankings of 2014 available on Times Higher Education. Table 3: Summary moderating variables

Gender BoardEx (H2) 0=male /1=female

Uncertainty avoidance Hofstede country comparison

(https://www.hofstede-insights.com/)

(H3) Uncertainty avoidance index of country of origin (1-100)

Educational background LinkedIn

Times higher education

(https://www.timeshighereducation.com/)

(H4a) 0=Business / 1= other educational background (H4b) University Rank (1-1001)

Control variables

To control for other than the hypothesized individual-level conditions, CEO age (collected from BoardEx) has been included as a control variable. The older the CEO becomes the more international experience he/she has been able to collect (Belenzon, Shamshur, & Zarutskie, 2019; Cline & Yore, 2016). Furthermore, previous studies have associated firm size with firm performance (Atinc, Simmering, & Kroll, 2012; Zhang & Rajagopalan, 2010). Consequently, to control for firm-level conditions, this study has included the amount of revenue as a control variable. This data has been collected from annual reports. To control for industry-level effects, this research has added a dummy variable that distinguishes between manufacturing companies and service companies, which has been collected from BoardEx. Last of all, to control for country-level (macroeconomic) conditions, this study has included economic growth of the particular home countries in the analysis. Economic growth data has been obtained from the World Bank.

Table 4: Summary control variables

Age Boardex A CEO’s age in years

Revenue Annual reports Average amount of Revenue in $

of 2014, 2015, and 2016

Type of industry Boardex 0=Service / 1= Manufacturing

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Empirical methodology

This study presents a cross sectional analysis, comparing differences among CEOs. To conduct this comparison a quantitative statistical analysis has been executed including descriptive statistics, a correlations-matrix and a regression analysis. Hypotheses 1 tests a direct relationship between international experience and firm performance, which is analyzed by regressing and correlating the international experience measurement variable (depth), including the control variables, against the average operating margin of 2014 to 2016. Hypothesis 2, 3, 4a and 4b present the moderating role of gender, uncertainty avoidance, and educational background on the relationship illustrated by hypothesis 1. By testing the effect of these moderating variables, this study aims to investigate if and how various individual traits, resulting in different learning styles, moderate the relationship between a CEO’s international experience and firm performance. The overall conceptual model of this research is visualized in figure 2.

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Analysis & Results

In order to test the hypotheses, a cross-sectional analysis has been performed. Table 5 presents the descriptive statistics, table 6 the correlation-matrix, and table 7 the regression analysis. When elaborating on the summary statistics, the average operating margin is -9.6% suggesting that on average, the companies do not seem to execute their strategies very effectively. The average number of years that the CEOs have spent working abroad is 4,3, which suggests they have substantial international experience. The other statistics do not show any features that stand out, other than the sample representing a low amount of female CEOs (as expected), and there being sufficient variation among the variables “Uncertainty

avoidance”, “Quality of education”, and “Educational background”. When analyzing the

correlation-matrix, all significant correlations between the variables are below 0.7, implying no concerns for multicollinearity within this statistical analysis.

Table 5: Descriptive statistics

Variable Mean Std.Dev. Min Max

(N=90) Operating Margin -9.6% 1.4% -1232.3% 140.8% Depth 4.3 6.8 0 28 Gender 0.1 0.30 0 1 UA Index 49.5 16.9 8 100 Quality of education 175 198 1 801 Educational background 0.39 0.49 0 1 CEO Age 50 6.3 35 69

Firm Size 7.38e+09$ 2.24e+10$ 3.030.000$ 1.57e+11$

Industry 0.26 0.44 0 1 Economic Growth 2,4% 0,14% -2,1% 7,9% Table 6: Correlation-matrix Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (1) Operating Margin (2) Depth 0.142 (3) Gender 0.005 -0.030 (4) UA Index 0.053 0.049 -0.167 (5) Quality of education 0.017 -0.030 0.027 -0.013 (6) Educational background -0.084 -0.057 -0.038 -0.151 0.039 (7) CEO Age 0.002 0.027 -0.057 0.060 -0.068 0.040 (8) Firm Size 0.049 0.063 0.312* -0.004 -0.032 -0.002 0.048 (9) Industry -0.150 0.032 0.144 0.139 -0.050 0.003 0.071 0.127 (10) Economic Growth 0.041 0.238* 0.060 -0.382* -0.027 0.066 -0.168 0.209* -0.259* Test of hypothesis 1

As described previously, hypothesis 1 presents the main direct relationship between international experience and firm performance. Column H1 in table 7 presents the regression between “Operating Margin”, “Depth”, and the control variables. When analyzing H1, unfortunately, not one coefficient is proven to be significant. In addition, the overall F-statistic is insignificant and the R squared is notably low, indicating little explanatory power of the model. This would imply no support for hypothesis 1. However, when conducting the same regression with robust standard errors (Table 8), the coefficient between “Depth” and

“Operating margin” does show significance at the 0.1 level. Therefore, although the regression

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Test of hypothesis 2, 3, 4a and 4b

Hypothesis 2, 3, 4a and 4b describe the moderating effect of gender, culture and education on the relationship between international experience and firm performance. Column H2, H3, H4a, and H4b illustrate the regressions between the moderating interactions of

“Gender”, “UA index”, “Quality of education”, and “Educational background” against the

dependent variable “Operating Margin”, including the control variables. When analyzing column H2, H3, H4a in table 7, all coefficients show no significance, subsequently finding no evidence for the moderating interactions. Additionally, similar to hypothesis 1, all the moderating interactions show an insignificant F-statistic and an extremely low R squared. Therefore, this study finds no support for hypothesis 2, 3, 4a.

Besides that, using the same procedure as for hypothesis 1, this study finds partial support for hypotheses 4b (Table 8), implying that an educational background in business might strengthen the relationship between international experience and firm performance. Again, this support is at the minimum level due to the slightly positive coefficient, low R squared and the omission of the F-statistic.

Table 7: Regression Analysis

Variable H1 H2 H3 H4a H4b (DV: Operating Margin) Independent variable Depth 0.032 (0.157) Moderators Gender x Depth -0.004 (0.947) UA Index x Depth 0.001 (0.204)

Quality of education x Depth 0.000

(0.352)

Educational background x Depth 0.029

(0.388) Control variables CEO Age -0.001 (0.978) 0.002 (0.948) 0.000 (0.986) 0.001 (0.969) -0.001 (0.959) Firm Size 0.000 (0.506) 0.000 (0.519) 0.000 (0.499) 0.000 (0.595) 0.000 (0.571) Industry -0.562 (0.114) -0.514 (0.151) -0.561 (0.116) -0.558 (0.121) -0.533 (0.135) Economic Growth -3.180 (0.620) -1.492 (0.896) -3.148 (0.781) -3.862 (0.739) -4.346 (0.713) Model F statistic 0.487 0.792 0.534 0.657 0.676 Adjusted R² 0.051 0.028 0.046 0.038 0.036 *** p<0.01, ** p<0.05, * p<0.1 Tests for robustness

Due to the concern for multicollinearity and insufficient variation, this research paper used “Depth” as independent variable to measure international experience. This assumption has been tested in multiple ways. Firstly, it has been tested to use “Breadth” as independent variable (Appendix 3). Secondly, despite the concern for multicollinearity, there has been an attempt to use both “Depth” and “Breadth” as independent variables to capture international experience (Appendix 1). Lastly, based on a factor analysis (Appendix 4) showing that

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18 variables would result in a different outcome. This has been conducted by using the average of the two variables as measure for international experience (Appendix 5).

Furthermore, next to the independent variable, it has been investigated if there might be different ways to measure the dependent variable financial performance. The first idea was to use the average net operating income of 2014 to 2016 to measure firm performance. However, due to its high correlation with the control variable “Firm size”, the use of this variable was not deemed as valid. The second idea was to use the average percentage change in net operating income from 2014 to 2015 and 2015 to 2016 with 2014 as index year. Nonetheless, this study did not find a way to calculate percentual change when the operating income in one of the years was negative. Consequently, the study was obligated to choose another measure for financial performance. As firm revenue (“Firm size”) and net operating income were already collected, this study chose to use operating margin (average of 2014 to 2016) as dependent variable. This choice was affirmed by various authors arguing that the operating margin is deemed to measure the effectiveness of a firm’s strategy (Thornhill & Roderick, 2007), which relates to the fact that CEOs affect firm outcomes through strategic action (Wiersema & Bantel, 1992).

Various research papers argue that the impact of CEOs on firm performance is mostly visible in the years after succession (Georgakakis & Ruigrok, 2017; Shen & Cannella, 2002). Thus, as previously assuming CEOs to impact firm performance directly after the moment of succession (Herrmann & Datta, 2002), this study tested if dropping 2014 and using the average operating margin of 2015 and 2016 as dependent variable would affect the results (Appendix 6).

Nevertheless, overall, various assumptions have been tested to analyze if the results could have been different. None of these tests did provide profound evidence for the hypotheses. Consequently, the findings remain minimal, other than the regression with robust standard errors (table 8) finding modest support for hypothesis 1 and 4b.

Table 8: Regression analysis with robust standard errors

Variable H1 H2 H3 H4a H4b (DV: Operating Margin) Independent variable Depth 0.032* (0.095) Moderators Gender x Depth -0.004 (0.588) UA Index x Depth 0.001 (0.124)

Quality of education x Depth 0.000

(0.176)

Educational background x Depth 0.029*

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19

Discussion & Conclusion

The purpose of this study has been to investigate if individual traits of CEOs, theorized to result in different ways of learning in a foreign environment, impact the effect that the CEO’s international experience has on firm performance. In particular, this study investigated whether gender, cultural background, and educational background of CEOs influence the relationship between the individual’s international experience and firm performance. This research finds evidence at the minimum level for international experience being positively related to firm performance. With regard to the moderating role of certain personal traits of CEOs, the results only propose modest support for an educational background in business to strengthen the relationship between international experience and firm performance, while none of the other hypotheses on the moderating role of personal characteristics are supported.

This research attempts to contribute to the strategic management and international business literature. However, the results do not find strong evidence for CEO international experience being positively related to firm performance and for individual traits to influence this relationship. To start with the main relationship, as mentioned in the literature review, there might be a possibility that firm experience instead of individual experience (e.g. experience of a CEO) relates to firm outcomes (Carlsson et al., 2005). Pervan, Pervan, and Ćurak (2017) confirm the importance of firm experience, since it allows a firm to benefit from accumulated knowledge in business aspects that are of significant importance such as well-established relations with suppliers, costumers, etc. In any case, it might be beneficial for future research to clarify the dynamics between firm experience, CEO experience, and firm performance. Nevertheless, various studies do confirm the positive relationship between CEO international experience and firm performance to exist (Le & Kroll, 2017; Hsu et al., 2013) and this research also finds modest support. Subsequently, it remains valid to argue that this relationship holds power.

Besides the main relationship, this study finds minimal support for the moderating interaction of individual traits within this relationship. One aspect that can be questioned is whether in general individual traits of CEOs impact firm outcomes. Various research activities have explored this field of research. Literature appears to be indecisive, showing mixed results (Belenzon et al., 2019; Nguyen, Rahman, & Zhao, 2018; Peni, 2014; Saidu, 2019). Subsequently, it would be valuable for future research to conduct a meta-analysis on the current view with regard to the relationship between individual traits of CEOs and firm outcomes. Nevertheless, despite these results, CEOs do differ in experience and thus in how they make strategic choices (Hambrick & Mason, 1984). What, if and how individual traits impact a CEO’s learning and development in a foreign context, and thus the relationship between international experience and firm performance, remains to a great extent inconlusive. Perhaps the latitude of action available to CEOs (managerial discretion) outweighs the influence of individual traits (Crossland & Hambrick, 2011; Finkelstein & Hambrick, 1990). Nonetheless, in the current global, ever changing, and dynamic business environment, CEOs remain of significant importance for firm outcomes (Lafley, 2009; Wiersema & Bantel, 1992).

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20 The results of this research must be considered within the boundaries of its limitations. Firstly, due to the available time, this study has used a sample of 90 CEOs. Sample size is linked to statistical power (Hackshaw, 2008), indicating that it can be questioned whether the sample size of 90 CEOs is deemed to be sufficient to find statistical evidence for the proposed relationships. Additionally, the sample is dominated by male CEOs from the United states, United Kingdom, and Europe. Despite there being diversity, it can be questioned whether this diversity is sufficient to allow proper testing of the hypotheses. Secondly, international experience is collected via LinkedIn. A CEO’s work experience on LinkedIn is not always specified in detail, which might affect the validity of the variable. For example, work experience of a consultant that only visited the particular foreign company for a few times differs from work experience of a fulltime working CEO within a foreign company.

Thirdly, it might be questioned whether there are more appropriate designs for conducting this research, which would go along with different results. To start off, this study suggests future research to investigate the same relationship with the use of a larger and more diverse sample. Furthermore, there might be alternative options to conceptualize the measurement variables. For example the use of ‘return on assets’ as measure for financial performance, which is widely used by other studies (Richard et al., 2009), might be a valuable alternative dependent variable. In addition, as this research is focused on the role of CEO international experience, it might be beneficial to measure firm performance in a more detailed way, narrowing down to a firm’s international performance. An alternative approach might be to use a sample of multinational companies that are identical in size and subsequently purely focusing on the change in profit generated from international operations. Besides this, in order to clearly define the most relevant individual traits to investigate, a suggestion for a similar study would be to first use a qualitative research design that analyses which individual traits affect learning from international experience the most. Nevertheless, unfortunately, due to time and resources, this study has not been able to further elaborate on the current research design.

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Appendix

Appendix 1: Correlation and regression including both “Breadth” and “Depth” as measures for international experience.

Variable H1 H2 H3 H4a H4b (DV: Operating Margin) Independent variable Breadth 0.137 (0,489) Depth 0.012 (0.753) Moderators Gender x Breadth -0.228 (0,816) Gender x Depth 0.024 (0.863) UA Index x Breadth 0.003 (0.378) UA Index x Depth 0.000 (0.904)

Quality of education x Breadth 0.001

(0.396)

Quality of education x Depth 0.000

(0.898)

Educational background x Breadth 0.195

(0.552)

Educational background x Depth -0.003

(0.957) Control variables CEO Age -0.002 (0.934) 0.001 (0.971) -0.001 (0.961) -0.001 (0.978) -0.002 (0..924) Firm Size 0.000 (0.498) 0.000 (0.509) 0.000 (0.520) 0.000 (0.558) 0.000 (0.516) Industry -0.590 (0.100) -0.508 (0.161) -0.606* (0.093) -0.605* (0.097) -0.549 (0.127) Economic Growth -3.180 (0.795) -1.068 (0.927) 1.057 (0.932) 0.990 (0.939) -3.153 (0.793) Model F statistic 0.555 0.875 0.567 0.676 0.7437 Adjusted R² 0.056 0.0283 0.055 0.046 0.0404 *** p<0.01, ** p<0.05, * p<0.1 Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (1) Operating Margin 1.00

(2) International experience - Breadth 0.14 1.00

(3) International experience - Depth 0.14 0.76* 1.00

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Appendix 2: Analysis multicollinearity “Breadth” and “Depth” (VIF)

VIF 1/VIF Depth 3.178 .315 Breadth 3.069 .326 Economic Growth 1.729 .578 UA Index 1.328 .753 Firm Size 1.215 .823 Gender 1.188 .842 Industry 1.164 .859 Quality of education 1.073 .932 CEO Age 1.061 .943 Educational background 1.039 .963 Mean VIF 1.604 .

Appendix 3: Regression using “Breadth” as measure for international experience.

Variable H1 H2 H3 H4a H4b (DV: Operating Margin) Independent variable Breadth 0.187 (0.122) Moderators Gender x Breadth -0.080 (0.864) UA Index x Breadth 0.003 (0.123)

Quality of education x Breadth 0.001

(0.209)

Educational background x Breadth 0.180

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Appendix 4: Factor analysis including the variables “Breadth” and “Depth”

Factor Eigenvalue Difference Proportion Cumulative

Factor1 1.759 1.519 0.879 0.879

Factor2 0.240 . 0.121 1.000

LR test: independent vs. saturated: chi2(55) = 76.15 Prob>chi2 = 0.0000 Rotated factor loadings (pattern matrix) and unique variances

Variable Factor1 Uniqueness

Breadth 0.938 0.120

Depth 0.938 0.120

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Appendix 6: Regression using the average operating income of 2015 and 2016 as measure for financial performance. Variable H1 H2 H3 H4a H4b (DV: Operating Margin) Independent variable Depth 0.038 (0.198) Moderators Gender x Depth -0.007 (0.940) UA Index x Depth 0.001 (0.242)