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Master Thesis

The effect of board diversity on strategic decision making in

times of uncertainty.

A Brexit case-study on the effect of gender and nationality diversity in boards

on the decision to relocate parts of firms operating in the UK financial sector.

Author: Robbert Mulder Student number: S3540480 Email: r.mulder.18@student.rug.nl

Supervisor: Dr. S.R. Gubbi Co-assessor: Dr. H.U. Haq

Faculty of Economics and Business University of Groningen

Duisenberg Building, Nettelbosje 2, 9747 AE Groningen, The Netherlands P.O. Box 800, 9700 AV Groningen, The Netherlands

http://www.rug.nl/feb

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2

Abstract

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3

Table of contents

Introduction

4

Theory and hypothesis development

6

Methodology

16

Results

18

Discussion & limitations

23

Conclusions

26

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4

Introduction

Since the 1970s researchers have investigated the factors affecting a firm’s decision to relocate (part) of its operations (Brouwer et al, 2004). The studies of Keeble (1968) and Townroe (1972) were the first to consider that the relocation decision was impacted by internal mechanisms of the firm. The more recent studies are primarily focused on internationalizing the firm as part of a growth strategy to explore new markets and extend their customer base, or to achieve cost effectiveness by relocating to low production cost countries. These attributes have caused a surge into research in the field of firm relocation in combination with globalization and multinational companies (Fosgren et al. 1995; Strauss-Kahn & Vives, 2009).

Scholars and governments have a strong interest in firm migration patterns because of the influx of jobs and the effect on the local economies it can create, and cost when firms decide to relocate out of an area (Graham & Krugman, 1995). Because of this relocation literature is crucial for the development and deployment of government policies on how to distribute industries in a specific country or region (Loewendahl, 2001).

Currently the interest in firm migration is one the rise because of the global political landscape. External macro events create business turmoil that have a heavy impact on local and clustered economies. Countries like the United States of America and China have intensive trade wars and prohibit the use of products of companies to protect their interests. The COVID-19 (corona) virus heavily impacts production economies and creates major supply chain issues which in turn impact the production of western economies. These external macro events go hand in hand with governmental protectionist measures and nationalistic feelings. Another example of a macro event that has a heavy impact on the economy of the world and more specifically the European union is the invocation of article 50 of the treaty on the European Union by the government of the United Kingdom on the 29th of march 2017. This invocation was the result of a country wide referendum where a majority of 52% of United Kingdom nationals voted to leave the European Union against all expectations.

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5 regarding the best way to continue the relationship. The United Kingdom could have access to the free market without a total European Union membership (Norwegian model). A model like Canada (Canadian European Trade Agreement / CETA) where there is a single trade agreement but no free movement, or even the Swiss model that does include free movement but individual agreements with each country. Ultimately, there is also the “hard” Brexit that the current UK Prime minister is lobbying for, cutting all ties and creating new trade agreements with all necessary parties. The scala of possibilities creates a surge of uncertainty for firms situated in the United Kingdom (Thomas, 2019), which caused a lot of these firms to relocate (parts) of their firm out of the United Kingdom into a member state of the European Union (Laker & Roulet, 2019).

When a novel external event as Brexit occurs it creates an interesting opportunity to reassess existing literature and theories and see if the assumptions hold and help understand how firms react to an event of this magnitude. Existing research on firm migration mainly focuses on longer timespans or multi country datasets where internal firm level factors as revenue, firm size or age are regarded as drivers (Birkinshaw et al., 2006; Lamaanen et al., 2012). These researches are not focused on a specific external event and therefor a research gap has presented itself. The unprecedented de-globalization characteristic of Brexit does offer this research opportunity (Giles, 2018). The withdrawal of a large economy (the United Kingdom is the 6th world economy looking at GDP) of the biggest free trade bloc of the globe (European Union) has not yet presented itself in modern times. It is however not unlikely that a similar event will happen in the near future because of the rise of nationalism and dissatisfaction of policies like the current migration crisis. The study focusses on the financial services sector because of the leading role it has in the United Kingdom and the availability of data on firm migration. Another reason is that the fixed assets of financial firms are lower in comparison to other industries expected to be hit hard like the aviation and the automotive industries.

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6 organizational literature. Researchers have emphasized the institutional function of the board structure, arguing that by increasing its diversity help to link the organization to its external environment (Mintzberg, 1983; Pearce and Zahra, 1992; Pfeffer, 1972, 1973). The strategic role of the board involves taking important decisions on strategic change to help the firm adapt to important and impactful changes in the business environment (Mintzberg, 1983; Pearce and Zahra, 1992; Pfeffer, 1972, 1973). Besides the characteristics being a field of interest for scholars, there seems to be a surge in inclusivity legislation to make boards more equal and diverse, Which makes the topic even more interesting and actual.

Combining the above themes 48 UK stock listed financial firms have been selected with more than 100 employees. This paper focusses on the effect of board diversity on the strategic decision to relocate (parts) of the firm. The main aim of this paper is to answer the question:

“How do board diversity characteristics influence the strategic decision to relocate parts of the firm operating in the financial sector during times of uncertainty”

Theory and hypothesis development

Firm characteristics and migration

Research on firm migration has been getting renewed attention the past years because of ongoing macro-economic effects. Trade wars, protectionist actions and nationalism have made the drivers of firm relocation a hot topic for scholars, journalists and policy makers. For the sake of clarity it is important to know why firms are able to relocate and what this paper regards as a firm relocation.

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7 specialized roles to increase the strength of their mandate. Nowadays, since some multinationals are getting bigger than nations (De Grauwe & Camerman, 2002) and have up- and downstream activities in many different countries it is vital to have several business unit headquarters or regional headquarters. Because of the transfer from single unit (parent – daughter) organizations to the intermediary units within a hierarchy of a MNC (multiple regional headquarters) scholars have repositioned their vision and place more emphasis on these kind of structures (Mahnke et al., 2012; Hoenen et al., 2014; Zhou, 2015).

Forsgren et al., 1995 have distinguished three degrees of internationalization. Internationalization starts with exporting and outsourcing parts of production or sales (Benito et al., 2002; Barner-Rasmussen et al., 2007), these activities can develop themselves to foreign strategic centers with more responsibility. The final and third degree is based on the internationalization of the headquarter itself (Barner-Rasmussen et al., 2007; Lamaanen et al., 2012). The Brexit phenomenon can cause firms that have internationalized in the second or third degree lose their competitive advantage because of the loss of access to the other EU member states. The loss of this resource causes transaction costs to increase which is negative in both the field of the resource based view (RBV) and transaction cost economics (TCE). This research focusses on the third degree of internationalization namely the relocation of the headquarters or intermediary headquarters (vital parts of the firm). Prior research has shown that headquarters are not that likely to relocate (Meyer & Benito, 2016) but intermediary headquarters are relatively mobile (Benito et al., 2011; Lamaanen et al., 2012). In this research, we follow the definition of Brouwer et al., (2004) who has two broad types of relocation events: 1) the complete migration of the firm of one place to another and 2) a partial relocation where a subsidiary is set up or a existing business relocates. This paper regards both relocation types as the same, a relocation. Firms that are operating with intermediary headquarters are often internationalized already. This has been done to attain a foothold in foreign markets and therefor attain a competitive advantage (Porter, 1990). This is creates the assumption that larger international firms would be earlier to relocate in case of an event that creates uncertainty.

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8 been conducted on the behavioral aproach on firm relocation, which is the goal of this paper and will be discussed.

Uncertainty and macro economic events

External macro events are heavily influencing this research. The underlying concept of uncertainty is often central to the behavioral approach to firm relocation. It has also been one of the primary focusses of “Brexit” news broadcasted by news agencies. If we take the Netherlands as an example we can see that there are multiple banks, think tanks and consultancy firms that carefully track the exodus of firms situated in the United Kingdom that have announced their plans to relocate. Some scholars have even gone so far as considering the United Kingdom as a resemblance of an emerging market (McNamee & Kokkinogeni, 2019). As the environment’s dominant discourse changes, it can have a dominant effect on the decision to relocate.

Treatments of risk in IB-literature largely focus on specific uncertainties to the exclusion of other interrelated uncertainties. Miller (1992) has been one of the most prolific researchers on the topic of firms dealing with these uncertainties. Miller has created a framework using general environmental uncertainties. These general environmental uncertainties are divided into 5 categories: political uncertainties, government policy uncertainties, macroeconomic uncertainties, social uncertainties and natural uncertainties. Political uncertainties are comprised of examples as democratic changes in governments or political turmoil. Fiscal and monetary reforms and trade restrictions fall under governmental policy uncertainties. Miller (1992) has also taken into account industry uncertainties, which involves three major categories: input market uncertainties, product market uncertainties and competitive uncertainties. These uncertainties are directed to a specific industry as for example the finance industry. The third set of uncertainties are firm specific uncertainties comprising out of; operating uncertainties (labour uncertainty and raw material shortage), liability uncertainties, research and development uncertainties, credit uncertainties and behavioural uncertainties.

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9 control strategy (Allaire & Firsirotu 1989), geographical diversification as a flexibility strategy (Porter 1985) or divestment as an avoidance strategy (Wernerfelt & Kamani, 1987).

This paper is zooming in on the effects of the uncertainty that surround Brexit. Following Miller’s framework on general environmental uncertainties Brexit can be linked to multiple categories: There is political turmoil (political uncertainty), trade restrictions can be put in place because of regulation de-harmonization (government policy uncertainty), the terms of general trade will be altered (macroeconomic uncertainty) and there are massive social concerns and social unrest because of the upcoming changes (social uncertainties). As mentioned in the introduction Brexit is one of the firms forms of de-globalization in a world that has formed unilateral connections and deals in the past decades. Brexit has not been finalized in ultimo yet but all the possible outcomes are expected to have a strong negative impact on the economy of the United Kingdom. Setting up new trade deals requires extensive collaboration between countries or trade blocs (like the European Union) and can take years to develop.

Using the macro economic event of Brexit as a projector of uncertainty, his paper focusses on the financial industry of the United Kingdom. With the United Kingdom leaving the European Union a harmonized regulatory framework for the financial services will be majorly impacted (Lavery et al., 2019). When the European Union was formed London and Frankfurt were established as the European financial centers. One of the biggest uncertainties at the moment is if that cooperation can still co-exist or if both sides will opt to try and protect their own economy and interests (Lavery et al., 2019).

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10 As London is currently a financial hub, a lot of American and Asian financial services firms have chosen it as their gateway to the European Union. Losing the access to the single market would mean that this gateway function will cease to exist. This creates both competitive and product market uncertainties (industry uncertainties). Looking at the singular firms within the financial industry, around 18% of the workforce is derived from the European Economic Area. Larger firms are expected to be even more internationalized and therefor experience a spike in labour unrest in the event that the free passporting will be cancelled. Industries expected to hit hard by Brexit like to automotive or pharmaceutical industry have the massive constraint of relocating their fixed assets in order to make revenue. These industries are expected to be hit hard as well but are often part of a large supply chain organization. As the financial services industry is serviced based their contingency plants are much less focussed on their supply chain mechanics. The sheer importance of the financial services sector for the United Kingdom is one of the main reason this paper focusses solely on this industry. The financial services industry of the United Kingdom accounts for 7-12 % of their GDP and 11% of tax revenue for the government. It also provides the largest trade surplus for any sector of the economy of the United Kingdom with a valuation of 58 billion pounds (House of Lords EU Committee ,2016; Armour, 2017). To prepare for the uncertainty of Brexit many companies that have a strong revenue and client base in the EU have announced to what Laamanen et al., (2012) describes as the ultimate business decision; “relocating the firms headquarter”.

Board diversity

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11 important for the board composition. Less research has been done on the effect of nationality diversity on decision making.

The general argument in favor of heterogeneity and thus diversity is that it results in a broader perspective on strategic decision making which allows better weighed outcomes and more in-depth conversations regarding risks and opportunities in the boardroom (Watson et al., 1998). This is the result of the mixture of backgrounds and thus perspectives of heterogenic boards (Robinson & Dechant, 1997).

Heterogeneity in the boardroom may also have a negative or null effect on decision making processes because of the divide in the in-group (majority) and out-group (minority) (Westphal & Milton, 2000). If a member of the group differs from je majority he or she tends to have a lower commitment to group loyalty (Randoy et al., 2006) and a lower psychological commitment level, paired with a higher level of turnover intent (replacement) (Marimuthu and Kolandaisamy, 2009). Another interesting factor, with the rise of nationalism in the political landscapes, is that some diversity scholars suggest that heterogeneity has a negative effect if the personal values of board members do not align with the diversity standards of today (van Knippenberg & Schippers, 2007). Finally, heterogeneity in the board room can slow down the group decision process when searching for a consensus because of the difference in perspectives and backgrounds.

The effect of board diversity on strategic decision making

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12 “dominant coalition” results into the strategic decisions of the firm. The grounding of the upper echelon theory is that the different mixture of board characteristics (professional and personal) influences their perspective and therefor strategic decision making. As the combined board makes strategic decisions on their individual cognitive base and values it is near to impossible to get a board that has incorporated all possible perspectives. This creates a limited field of vision of the board which in turn impacts the strategic decision. The process of strategic decision making with this limited field of vision is shown in figure 1 (Hambrick & Mason, 1984).

Figure 1:Strategic choice under conditions of bounden rationality by Hambrick & Mason (1984)

As mentioned board diversity ensures that strategic decisions are made with a broader view because of the difference in individual characteristics (Rose, 2007). As decisions regarding the relocation of (parts) the firm are incredibly complex and go paired with high expenses, one would argue that a more diverse debate will result in a better weighed decision of higher quality. Keeping the uncertainties of Mill (1992) in mind, previous studies have also shown that when the environmental uncertainty is high, heterogeneous /diverse boards achieve better performance (Hambrick et al., 1996; Nielsen, 2010).

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13

Board gender diversity

One of the most actual and significant board diversity characteristics faced by modern corporations is gender diversity (Carter et al., 2003). Politicians often argue over an enforced cap of females in the board because of the current lack of them (Kang et al., 2007). The pressure of society and governments to increase the number of females on corporate boards is a phenomenon that is surging around the globe. Examples of countries that have adopted legislative or voluntary initiatives to improve the gender ratio are; Norway (legal quota of 40% of females in the board), Sweden ( a voluntary initiative of 25% females with the threat of making it legislation if unpursued by firms) and France (legislative to make all public firm boards in gender parity (50/50)) (Bohren and Strom,2010). Even in predominantly Muslim countries in the middle east there is a surge of recognition of female participation in boards (Singh et al., 2008). All these political initiatives paint a picture that the percentage of female presence in boards have a positive impact on their corporate governance and strategic decisions (Adams & Ferreira, 2009). The results of research on gender diversity in boards are mixed. Where some scholars find positive relationships between gender diversity and firm performance (Erhardt et al., 2003; Carter et al., 1997) others finds negative or no significant relationship ( Smith et al., 2006; Rose, 2007; Adams & Ferreira, 2009).

As the upper echelon theory describes that the cognitive base and values eventually lead to strategic decision making we can assume that these differ greatly between genders. This assumption is backed by scholars that argue that there are significant differences in perceptions, values and believes between male and females in general (Eagly et al., 1995; Powell, 1990). One of academically accepted reasons of this is that female board members have often faced discrimination or a stereotypical challenge that restricts their ability to fully contribute to the firm’s corporate strategy (Arfken et al., 2004, Galbreath, 2011). This is directly linked to the aforementioned political pressure of politicians on quota but also the so called “gender gap”.

Combining the research on strategic decision making (firm relocation) and gender diversity on boards in this paper the expectation is that a more gender diverse board makes a different decision than less diverse, homogeneous, boards. The first hypothesis is therefor formulated as:

H1: The higher the proportion of female board members, the higher the likelihood of a

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14

Board Nationality Diversity

Individuals national origin mirrors the institutional environment of the country in which they devote the most of their influential years (Hambrick et al., 1998). A nationwide mix of formal and informal institutions guide individuals and organizations in dealing with anxiety, interpreting the environment and taking relevant actions (Crossland and Hambrick, 2007). Formal institutions are definite and codified. They consist of political and economic rules and contracts, that govern property rights and transactions in a society, whereas informal institutions consist of tacit norms, conventions, and values that shape social interaction (North, 1990). Therefore, institutions form a constitution shifting from the taken for granted to the legally enforced and interact with each other in shaping human attitude.

A great deal of previous research into multinational teams has focused on the effects of informal institutions, or national culture, described as a system of jointly held values and beliefs (Hofstede, 1980). In early childhood cultural patterns of feeling, thinking and action are acquired because at that time humans are most affected to learning and assimilation. Once these deeply rooted patterns are established within a human’s mind, they are not probable to extensively change through subsequent experiences (Hofstede, 2005). There is evidence that national culture has an enduring impact on board members mindsets (Geletkanyez, 1997) and interpretation and reaction to strategic concerns (Schneider & De Meyer, 1991).

Thus far, culture provides only limited explanation for the influence of national-level institutions on executive decision making (Crossland & Hambrick, 2011). Formal institutions are important for lowering uncertainty about the behavior of others and granting actors to make conceivable commitments to one another. Formal institutions add capacities for the exchange of knowledge among actors, the sanctioning of defection from cooperative endeavor, and the monitoring of behavior (Scott, 2008). Since formal institutions hold down and monitor economic behavior, they influence information processing and problem solving in executive decision making.

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15 a board abroad. This means, that formal and informal institutions of a manager's country of birth jointly affects his/her field of selective perception, vision and interpretation of strategic situations as shown in figure 1 (Hambrick & Mason, 1984). As such, nationality can be seen as a superordinate construct that encompasses the influences of both informal and formal institutionally embedded events on executive orientation and decision making. In line with the decision-making/information-processing perspective, nationally divergent teams contribute to an extension of knowledge of, and experiences with varied institutional environments. As multicultural teams strive to blend and appease their differing institutionally embedded experiences, they engage in consideration of various alternatives, generation of new creative ideas, and in-depth discussions (Hambrick et al., 1998). As a result, teams with a mix of nationalities are better at solving convoluted tasks and bring about more innovative solutions. According to Watson et al., (1993) multinational groups outperform homogenous groups in a range of perspectives. Since, strategic decision making is a task characterized by anxiety, high complexity and absence of routines, nationality diversity is expected to improve the comprehensiveness and quality of the board’s strategic decisions, which in turn has effect on firm performance.

At the same time, social categorization theory (Turner, 1987) suggests that variation in team nationality may also come at costs for the team dynamic. As nationality, and specifically informal institutions (culture) determines communication patterns and interaction styles, multinational teams may encounter lower cohesiveness, affective conflict, and slower decision making (Earley & Mosakowski, 200; Hambrick et al., 1998). Nonetheless, Elron (1997) found that while national cultural diversity may boost issue-based conflict, it is positively related to general team and supplementary performance. Equivently, Gong (2006) described that supplementary board nationality diversity improved supplementary labor productivity of Japanese firms. Thus, on balance, the advantages associated with improved creativity and problem solving of nationally diverse boards are assumed to exceed any affective costs related to team dynamics.

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16 institutionally embedded experiences to survive difficulties of coordinating and managing a geographically and culturally dispersed organization with a large proportion of business networks, foreign staff, customers, and suppliers. Nationality diversity could enable relevant knowledge of informal and formal institutions of distinct countries to be unified into strategic decisions. Also, it can be source of lowering the information-processing expenditures of globalization as a result of that more nationally diverse boards can attend to more environmental cues and have greater processing capacity (Luo, 2005). Furthermore, multinational boards have access to scarce and important knowledge, expertise, resources, and network contacts in relation to multinational management, which could help lowering the expenditures of liability of foreignness (Hymer, 1976). As board nationality diversity is more beneficial for firms faced with complex internationalization decisions the expectation is that a more diverse board in terms of nationality has a positive impact on the likelihood of the relocation of the firm.

H2: The higher the diversity of nationality on the board, the higher the likelihood of relocating.

Methodology

This section provides an overview of the research methodology used to test the formulated hypotheses so that other scholars can reconstruct the research. The data sources and extraction of data will be described as well as the argumentation for the operationalization of the dependent, independent and control variables used in the research.

Data sample & data collection

For the selection of firms, the Orbis database was used. To make sure data was available on all the selected firms the first requirement is that each firm is listed which narrowed the search down to +-90.000 hits. Because the impact of the socia-political Brexit uncertainty is

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17 meant to be measured only firms operating in the United Kingdom were selected which narrowed it down further to 903. Industry NACE codes (64, 65 and 66) were added to focus on the financial industry in the United Kingdom resulting in 275 firms. In order to focus on larger companies that have reported their intention to relocate only companies with more then 100 employees were selected resulting into 52 firms, this is in line with prior research of Lamaanen et al., (2012). Orbis has also provided data for the annual revenue and employee numbers.

When the first selection of 52 firms was created all the corresponding tickers (stock listings) on the London stock exchanges were gathered and run through the BoardEx database. This resulted in missing data of some companies that could not be extracted by other measures as the annual report or other database, therefor the dataset got narrowed down to 48 companies.

Where cited research on firm relocation has often provided bigger datasets, the nature of Brexit has a considerably smaller timespan. This research regards the referendum day of Brexit ( 24th of June 2016) as the moment firms started to actively announce relocation decisions.

This data acts as the trigger point for relocation announcements because any announcements before that data are not paired with concrete plans but act more as a mechanism to possibly swing voters. As the timespan of this research is very limited (45 days) the relocation data of the original thesis idea was consulted. This data has a range of 24th of June 2016 to September 30th 2019.

Variables used in the model

Dependent variable

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18 Independent variables

The first independent variable is board gender diversity. To acquire this the BoardEx database was used which holds statistics on the percentage of men on boards. This means that if the value is 0 the board consists completely out of female directors. If the value is 0,5 the male/female board members are perfectly balanced (parity) and if the value is 1 the board exists entirely out of male board members.

The second independent variable is board nationality diversity (nationality mix). Nationality is the country of birth or the country where a board member has lived most of his/her life. This data was also extracted from the BoardEx database. Board nationality or “nationality mix” with a value of 1 indicates that there are no double nationalities in the board. A value of 0 indicates that all board members are of the same nationality.

As mentioned, both independent variables were collected by using the BoardEx database and thus consists purely out of secondary data.

Control variables

Prior research suggest that firm size has both an effect on internationalization and decision making (Bausch & Krist, 2007). There is already accounted for this partially by selecting firms with > 100 employees but the difference in the dataset is substantially high so it would be wise to add control variables for size. To account for firm size firm employees (Nielsen & Nielsen, 2013) and operating revenue (Voget, 2011) are included as control variables to ensure the output has the highest explanatory value. Both variables were collected by using the Orbis database and consulting the annual reports of the respective companies.

Results

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19 multiple nationalities (25%). It also shows that the difference in operating revenue and number of employees is high and therefor has a high standard deviation.

Table 1: Descriptive statistics

To check for collinearity a Pearson test was conducted which is shown in table 2. This is important because multicollinearity issues could affect the reliability of the models (Alin, 2010). The numbers in the Pearson correlation coefficient test range from 1 to -1. The closer the value is to one of the extremes, the stronger the correlation between tested variables. A positive sign shows the positive correlation and vice versa. In other words, an increase will result in a decrease in the other (negative correlation). Coefficients between +-0,5 and 1 have a strong correlation, between +-0,3 and 0,49 there is assumed to be a medium correlation and +-0,29 is assumed to be small. All correlations are quite “high” in the first observation. This raises multicollinearity concerns. To account for these concerns another test has been conducted to evaluate the VIF (variance inflation factor), this test is shown in table 3. The VIF with a value of >10 or a tolerance (1/VIF) of <0,1 indicates the presence of multicollinearity (Tabachnick & Fidell,(2001), Neter et al. (1989)). In this case each factor’s VIF and tolerance fall within the parameters deemed acceptable. This is regarded as satisfactory evidence for the lack of multicollinearity problems.

N Minimum Maximum Mean Std. Deviation Relocation announcement in 1 (yes) or 0 (no) 48 0 1 0,37 0,489 Operating revenue USDM 48 5561 59953205 5329057 13221304 48 106 235000 12843,02 37679,381

Gender Ratio (Male) 48 0 1 0,79 0,125

Nationality Mix 48 0 0,8 0,25 0,255

Descriptive Statistics

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Table 2: Pearson test

Table 3: VIF test

The next step is testing the applicability of the model. A binary logistic regression has been used which processed all the data available in the sample. The results from this test reconfirm that no missing cases are present (table 4).

Table 4: Case Processing Summary

The first output of the regression is a null model or stage zero model. This model contains no independent variables but only the dependent, in this case the relocation decision in some way

1 2 3 4 5 1. Relocation 1 2. Operating revenue 0,494** 1 0 3. Employees 0,373** 0,735** 1 0,009 0 4. Gender (male) -0,168 -0,18 -0,267 1 0,254 0,222 0,067 5. Nationality Mix 0,343* 0,408** -0,431** -0,121 1 0,017 0,004 0,002 0,412 Tolerance VIF 1. Relocation 2. Operating revenue 0,45 2,225 3. Employees 0,423 2,366 4. Gender (male) 0,928 1,078 5. Nationality Mix 0,796 1,256 N Percent Included in Analysis 48 100 Missing Cases 0 0 Total 48 100 0 48 100 Selected cases

Case Processing Summary

Unselected Cases Total

Unweighted Casesa

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21 yes/no. The null model (table 5) shows that the initial model predicts that no firm will announce to relocate (100%). The overall percentage is 62,5 which indicates that the model was able to correctly predict 62,5% of the relocation decisions without using any of the independent variables and control variables.

Table 5: Classification table null model

The independent and control variables have been added to create the “full model”. To test the robustness of the model the Chi-squared test has been used as shown in table 6. The table shows to be significant with a P value of 0,000. The degrees of freedom (df) denote that the 2 independent and 2 control variables have been added.

Table 6: Omnibus tests of Model Coefficients

Adding these variables results into a new classification table (table 7) that shows strong differences with the zero/null table. The model is able to predict 97,7% of the firms that did not announce to relocate, and 72,2% of the firms that did. The total model was able to predict 87,5% of the results, which is a strong increase from the 62,5% in the zero/null model. This shows that the variables improve the understanding of the model of the strategical decision to relocate or not. Percentage Correct Observed 0 1 0 30 0 100 1 18 0 0 62,5 Predicted

Classification Table (null model) a,b

a. Constant is included in the model. b. The cut value is ,500

Relocation announcement in 1 (yes) or 0 (no) Relocation announcement in 1 (yes) or 0 (no) Overall Percentage Chi-square df Sig. Step 33,156 4 0 Block 33,156 4 0 Model 33,156 4 0

Omnibus Tests of Model Coefficients

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Table 7: Classification table full model

Table 8: Model summary explanatory value

In table 8 the Cox & Snell R square is shown, this explains the variation in the model. In this case the Cox & Snell R square is 0,499, which means that the two independent variables and the two control variables together account for 49,9 percent the explanation if a firm decides to relocate or not.

Table 9: Regression results

As the decision to relocate is either 0 or 1 the variable is dichotomous. Because of this a binary logistic regression analysis was done which output is shown in table 9. This analysis provided the coefficient of each independent and control variable. This coefficient highlights the interaction of the variable with the intercept (constant). The goal of this research is to see if the board room diversity has an impact on strategic decision making (relocate).

Percentage Correct Observed 0 1 0 29 1 96,7 1 5 13 72,2 87,5 a. The cut value is ,500

Classification Table a

Predicted Relocation announcement in 1

Relocation announcement in 1 (yes) or 0 (no)

Overall Percentage

-2 Log likelihood

Cox & Snell R Square

Nagelkerke R Square

30,355a 0,499 0,680

a. Estimation terminated at iteration number 9 because parameter estimates changed by less than ,001.

Model Summary

B S.E. Wald df Sig. Exp(B)

Operating revenue USDM 0,00002 7,71E-07 7,096 1 0,008 1

Employees 0,000298 0,000155 3,712 1 0,054 1

Gender Ratio (Male) 2,936 3,892 0,569 1 0,451 18,842

Nationality Mix 1,236 2,221 0,309 1 0,578 3,441

Constant -4,627 3,366 1,89 1 0,169 0,01

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23 The Beta of Gender Ratio (Male) is 2,936 which suggest that an increase in male board members increases the probability / likelihood a firm will make a relocation decision. However, the result is not statistically significant with a significance value of 0,451. This is well above the generally accepted p<0,05 or even p<0,10 limit. This means there is no statistical basis to accept the hypothesis and therefor hypothesis 1 is not supported.

The Beta of Nationality Mix is 1,236 which suggests that an increase in the nationality mix (zero is singular nationality in the board and 1 is all different nationalities) increases the probability / likelihood of a firm relocating. However this case also shows an insignificant significance of 0,578. Therefor hypothesis 2 is not supported.

Discussion & Limitations

This research attempted to broaden the scope of the behavioral approach by using the upper echelon theory and thus the impact of the board diversity on the decision to relocate in uncertain times. Unfortunately, the results presented in the previous section show that there are no outcomes that can be supported or deemed statistically significant. The discussed theories and literature provide a strong basis for the argument that gender diversity or nationality diversity has a considerable impact on strategic decision making and thus the decision to relocate. As the significance of both independent variables was far from the p<0,05 and even the p<0,10 accepted values the hypotheses cannot be supported.

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24 Even though this research offers little to no empirical evidence it can be used as a starting point for other scholars to build on. There is a strong theoretical foundation that offers and interesting research gap.

Limitations

Using Brexit as a phenomenon has both advantages and limitations. The advantage is that there is a mass exodus of firms (or vital parts of the firms) that have announced to leave the UK. The limitation is that during the writing of this paper Brexit has not been finalized yet and therefore the full effects of it is not yet clear. This creates a significant limitation in the data because firms don’t know the full extent and the effects that Brexit will have on them. I do argue that it is defendable as searching “Brexit + financial services” generates >25.000 hits on Google Scholar and >180 academic papers in SmartCat. Which means that the effects of a macro economic event like Brexit is already broadly researched and can thus create insights for other scholars.

Another limitation is the relatively low sample size. Increasing the sample size and focusing on smaller firms could provide more statistically significant and usable data. This does create the mentioned barrier of unavailable data as only a small fraction of firms is stock listed. This research (initial submission) was originally meant to incorporate all financial firms leaving the United Kingdom but the lack of additional data provided an inadequate base for research. This thesis focusses on financial services because of the broad news coverage and impact on the city of London together with the value for other EU member states. This does however limit the data sample when only using listed firms. By adding other industries, the dataset could be expanded with other listed firms to get a more significant result.

When looking at the decision to relocate or not it is measured by an announcement in a major news outlet. This means that not all relocations have been completed in full. It also means that all forms of relocations have been grouped together even though some firms only transferred 50 employees or a vital department, and others decided to relocate the entire firm. These differences account into the importance that should be linked to the upper echelon theory.

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25 incorporate other variables. An important note is that the Cox & Snell R has a value of 0,499 which means that adding extra control variables would not increase the significance of the used independent variables.

Future research

A social political event that has enormous macro-economic implications like Brexit is extremely interesting for scholars and policy makers alike. These phenomena of de-globalization and market disruptions are scarce but not non-existent. How the corporate governance of firms and therefor indirectly their board structure is organized and acts in highly stressed times of uncertainty is also an underdeveloped field. Future researched could therefor build on this paper to deepen out the understanding of the upper echelon theory. The firm migration pattern is clearly visible and when Brexit is finalized it would be very interesting to reassess and expand the research conducted here. Future researchers should take into account that expanding the dataset with more financial firms bear great obstacles. The first obstacle is that most financial firms that have announced to relocate have no available data in secondary databases. An example is the Ashmore Group that has moved its asset management division to Dublin. Its corporate ownership is divided by the government of Norway, Allianz Global Investors, Montanaro Asset Management, Dimensional Holding & JP Morgan Chase. Allianz Global investors is in turn owned by Allianz SE. Allianz SE is owned by 5 other entities of which one based in the UK (but in a JP Morgan Asset trust which is in turn owned by a US company). It would therefor be near impossible to gather the financial and board data of all these migrating companies.

Because of the struggle to work with the proper data, even after Brexit is finalized, I would suggest future researchers to add other industries that are massively impacted by Brexit (or even all) like the automotive, pharmaceutical and aviation industry. Again a strong warning would go that gathering data with Reuters / NexisUni is a very time consuming process. This could be avoided by waiting long enough for the firm migration to have been finalized so the relocation data can be extracted from available secondary sources.

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26

Conclusion

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