The liability of foreignness, cross-national distance, and their influence on human right violations in the extractive industry

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The liability of foreignness, cross-national distance,

and their influence on human right violations in

the extractive industry

Eric ter Heijden 10060057

Supervisor: Michelle Westermann-Behaylo Second reader: Johan Lindeque

University of Amsterdam Master Business Administration Track: International Management

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Statement of originality

This document is written by Eric ter Heijden, who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

Human rights violations, especially by businesses, has become an increasingly important field of study in the recent years. This research paper discusses how cross-national distance affects the relationship between the liability of foreignness and human rights violations. It evaluates human rights and the connection to business practices, considering how the liability of foreignness could influence the number of human rights violations. Specifically, this research examines the effect of cross-national distances such as geographic-, economic-, and administrative distance that

moderate the relationship between the liability of foreignness and human rights violations. A panel data set of human rights violations in the extractive industries from 2009 – 2013 extracted from the Corporations and Human Rights Database serves as the basis for this research. A Poisson regression model has been used to analyze the data. The findings of this research show no significant relationship between human rights violations and the liability of foreignness, meaning no effect has been found to indicate that multinational enterprises are more prone to committing human rights violations than domestic firms. More research using more extensive data sets is required to come to a better understanding of a possible relationship.

Key words: human rights violations, liability of foreignness, cross-national distance, multinational enterprise

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1. Introduction

Globalization and foreign direct investment have driven global economic growth and

development in the final quarter of the 20th century. The multinational enterprises (MNEs) grew larger and across continents, and with them their influence on the global and local markets (Dunning, 2012). MNEs contribute to economic development and increase employment opportunities, creating interdependencies between government and corporations. Some

governments treat certain MNEs more favorably than domestic firms or other MNE competitors, due to these interdependencies (Huijstee et al, 2012). For example, Shell used their first-mover advantage and political influence in Nigeria to secure a monopoly on oil exploration for over fifty years (Frynas et al, 2000). Unfortunately, as MNEs try to navigate through different legal and governmental frameworks in each country in which they operate, they become more and more difficult to manage (Ruggie, 2013). This can have disastrous side-effects, as Shell has recently paid settlements for polluting rivers (Mouawad, 2009) and being involved in executions in Nigeria (Pilkington, 2009). These environmental and labour-related violations are known as corporate human rights violations. As MNEs have expanded their investments and trade flows, it has created an imbalance between firm and state – a governance gap. This governance gap, with on one side the MNEs that do not know which standards to uphold in all the different countries they operate in, and on the other side, a lack of governmental power to provide adequate sanctioning and remedy options for victims of human rights abuses, needs to be addressed (Ruggie, 2008). To address these issues, John Ruggie created a framework of three core principles: the State’s duty to protect against human rights abuses from third parties, including businesses; the corporate responsibility to respect and uphold human rights; and the need for access to remedies against human rights violations. (Ruggie, 2008).

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This framework was adopted unanimously by the United Nations in the UN Guiding Principles for Business and Human Rights (UNGP). The first pillar of the UNGP, the State duty to protect, should integrate corporate culture and policy alignment to close the governance gap. The imbalance between state and corporates is extra problematic for developig countries. The second pillar, the corporate responsibility to respect, entails a baseline responsibility for MNEs to respect human rights. This requires due diligence, and strict dedication from MNEs to be

compliant to human rights in their entire sphere of influence. Finally, the third pillar, access to remedies, includes judicial- and non-judicial grievance mechanisms for both state and

corporations to uphold,and should include access at every level for both parties, to secure that any violations are reported and dealt with accordingly (Ruggie, 2008).

The UNGP framework of protect, respect and remedy is a great start in the prevention and restorative processes of human rights violations. One industry that is overrepresented in human rights violations is the extractive industry, shown to have 28 per cent of total corporate human rights allegations in 2008 (Wright, 2008). The extractive industry has, by its very nature, an adverse and invasive impact on the environment and communities. Extraction operations can create irreparable harm and pollution to the air, water supply, or ground. A large number of the mineral reserves are located in developing countries which have political and governmental instability and a no effective regulatory framework to provide oversight of the industry (Sethi et al, 2011). This is reflected by Hamann et al (2009), where their researched showed how the extractive industry scored higher on community impact versus other industries. The prospect of having rapid growth of extractive industries is very appealing to these developing countries, as the wealth derived from the mining and oil extraction could revitalize a struggling economy (Hilson, 2012).

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The prospect of wealth and prosperity leads to MNEs engaging in business in countries far beyond their regular territories, and competing with domestic firms in these foreign countries. When MNEs compete with domestic firms, they suffer from liabilities of foreignness. These are the disadvantages foreign firms suffer from operating in a host-country, compared to native firms operating locally (Zaheer, 1995). Liabilities of foreignness can range e.g. from language barriers to costs incurred by host governments restrictions and hostility (Sethi & Judge, 2009). The liabilities of foreignness influence the cost of doing business abroad, and this research argues that MNEs that suffer from these liabilities are more surceptible to human rights violations than domestic firms. This research also argues that the relationship between liability of foreignness and human rights violations is moderated by cross-national distance. Cross-national distance compares the magnitude of the differences between the host- and home country of an MNE. This research will focus on geographic, economic and institutional (administrative) distance

(Ghemawat, 2001; Berry et al, 2010) to influence the relationship. It is expected that the liability of foreigness will positively correlate with the number of human rights violations in the

extractive sector, with cross-national distance positively moderating this relationship.

The contributions of this Master’s thesis will be the evaluation of a connection between the liability of foreignness, cross-national distance, and human right violations. The outcome of this work deepens the understanding of MNEs and their relation with human right violations, to perhaps work as a predictive measure or as a starting point for future research in the causation of human right violations.

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The first section of this master’s thesis will explain the research gap. Afterwards, the literature review will summarize the current research status, followed by a theoretical framework challenging the status quo. The methodology section will present the research methods used in this study. The analysis section will show the results of the calculations and methods. This thesis will conclude with a discussion to evaluate and classify the findings, will explain limitations and recommendations for further research.

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2. Literature review

Before the link between business and human rights are discussed, a general overview of human rights and their development will be given. After these topics, the literature on the link between the extractive industries and human rights (violations) will be discussed. This literature review will close with an analysis of cross-national distance and the liability of foreignness.

2.1 Human rights

The first mention of human rights as we know them today was in the Universal Declaration of Human Rights (UHDR), adopted after the Second World War by the United Nations General Assembly in 1948. The UHDR set out, for the first time, fundamental human rights to be

universally protected (United Nations, 1948). The UHDR contains thirty articles detailing diverse rights from the right to equality, to the right to freedom of opinion and expression, and the right to education. This declaration opened the door for states, international organizations and other actors to place human rights on the international agenda. Almost sixty years after the signing of the UHDR, its efforts have led to the creation and expansion of a worldwide system of

international law designed to identify and protect a number of basic human rights (Hafner-Burton & Tsutsui, 2005).

The UHDR led to most states now being bound by one or more multilateral conventions concerning human rights, but the importance of the UHDR still stands today. Neumayer (2001) states that even though many global and regional human rights treaties have been concluded, that treaty ratification rarely had an unconditional effect on human rights. A positive effect on treaty ratification was shown by the strength of the civil society and democracy in countries. Where civil society was absent and in pure autocracies, human right treaty ratification can have an adverse effect.

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This shows that even though treaties are being signed between countries, the direct effect on its human rights are not so easily taken for granted (Neumayer, 2005). Hafner-Burton and Tsutsui (2005) share this concern, where they examine the impact of the international human rights regime on governments’ human rights practices, calling it a ‘paradox of empty promises’. Using data from 1976 to 1999, they could find no systematic evidence to suggest that the ratification of human right treaties improves human rights practices. They did find that the growing attention and legitimacy of human rights in the international civil society provided leverage for non-governmental actors to pressure rights-violating governments to change their behaviour.

Therefore, even though states ratified treaties and did not act on them, the fact that they ratified them indirectly engaged organizations to demand and force, actual change to happen (Hafner-Burton & Tsutsui, 2005). States certainly bear a responsibility when it comes to human rights, but to get the full picture on human rights, how they can happen and how they can be prevented, human rights in business need to be discussed.

2.2 Human rights in business

Even though corporations have, in some jurisdictions, a formal obligation to uphold certain human rights (e.g. labor, consumer protection, and environment) (de la Cuesta, Valor, &

Holgado, 2012), there is no globally agreed legal responsibility for corporations to uphold human rights. A lack of such a framework, either voluntary or mandatory, does not bode well for human rights (Ruggie, 2007). The United Nations also realized this, and realized a more practical approach was needed for corporations. In 2005, John Ruggie was asked to become the United Nations Special Representative of the Secretary-General on the issue of business and human rights. In this role, Ruggie created the ‘protect, respect, and remedy’- framework that was implemented in the UNGP.

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Earlier treaties and frameworks failed due to the lack of an authoritative institution for stakeholders to turn to (Ruggie, 2008). With the unanimous acceptance of the UNGP by the United Nation’s Human Rights Council, it was ensured that this framework would not suffer the same fate.

The first principle of the UNGP is directed at states, and their duty to protect human rights. Each principle has been divided into foundational- and operational principles. The foundational principles start by emphasizing the importance of states to protect against human rights abuses within their territory, including business enterprises. They should set clear expectations for all business within their territory to respect human rights throughout their operations. The operational principles further explain a state’s general regulatory and policy functions to do not constrain but enable business respect for human rights. There is emphasis on (partially) state-owned or state-controlled enterprises as these are grey areas prone to human rights violations, requiring human rights due diligence. States should exercise oversight, and promote respect for human rights. In conflict-affected areas, states should have additional oversight on enterprise operations, as there are higher risks of corporate human rights abuses (Ruggie, 2011). The second principle of the UNGP is created for corporations, and entails the corporate responsibility to respect human rights. This principle has been divided into

foundational- and operational principles. The foundational principles state that enterprises should: respect and avoid infringing upon human rights, respect the international bill of human rights, avoid causing human rights violations, directly and indirectly and have policies in processes in place to facilitate this principle. The operational principles entail how these policy commitments should be stated, how enterprises should perform their human rights due diligence to assess actual and potential impacts and where enterprises have caused or contributed to violations, they should provide for or cooperate in their remediation (Ruggie, 2011).

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Finally, the last Guiding Principle is the access to remedy. Here it is the state’s responsibility to include judicial, administrative, legislatitative or any other means to ensure that when a human rights violation occurs, those affected have access to effective remedies. The operational principles includes judicial- and non-judicial grievance mechanisms for both state and

corporations to uphold,and should include access at every level for both parties, to secure that any violations are reported and dealt with accordingly (Ruggie, 2008). Unfortunately, Ruggie argued in 2014 that even though the UNGP are effective, he continues to have doubts for the future of businesses and human rights violations, as he says: ‘inadequate enforcement (of human rights treaties by states) is the main shortcoming of the current system’ (Ruggie, 2014). If states are the main shortcoming of the current system, perhaps that the MNEs show more promise.

The MNEs grew larger and across continents in the twentieth century, increasing their wealth, power and influence on global and new local markets (Dunning, 2012). Giuliani and Macchi (2013) argue that regardless of host country conditions, MNEs can have adverse impacts on the host economy. For example, strong industry competition can damage domestic firms and set the conditions for foreign firms to reach efficiency goals by neglecting (abusing) human rights. This depends on the industry- and MNE-level factors, but it is still a grim picture. On the other hand, innovative subsidiaries of MNEs may moderate the effect of competition on MNE’s human rights impact. (Giuliani & Macchi, 2013). The article shifts the focus of human rights impact more to a management issue between home (or headquarter) country and host (local) country of operations. This emphasizes the difference between the strategic role of the home country housing the corporate headquarter and the operational role of the subsidiary in the developing country.

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The difficulty in the corporate human rights issue also lies in the degree of commitment of the MNEs. Cuesta et al (2012) analysed the Corporate Social Responsibility (CSR) reports of Spanish IBEX-35 companies to examine business recognition of human rights. Their report concluded that MNEs have, in some jurisdictions, a formal obligation to uphold only certain human rights. They determined that the drivers for a better management of human rights are external. Financial markets and reputational hazards determined the commitment level. This lack of internal drivers for human rights commitment bears great concern for human rights activism, as both external drivers are based in a very reactive approach. An intrinsic motivation to uphold human rights would be far more effective (de la Cuesta et al, 2012). Hamann et al (2009) agree, as they analysed the antecedents of human rights due diligence. They performed a content

analysis of public report from the top 100 companies listed on the Johannesburg Stock Exchange, using Ruggie’s Guiding Principles to determine what entailed human rights due diligence. They found that a company’s human right due diligence is influenced by explicit leadership

commitment, emphasizing the importance of intrinsic motivation. Other important roles were played by government regulations and stock exchange listing rules, which is in line with De la Cuesta et al (2010) (Hamann et al, 2009). When combining governmental influences with financial and reputational drivers, it paints a worrying picture for the upholding of human rights. This worrying picture is especially noticeable in the extractive industries, and the next part of this review will analyse the relation between human rights and the extractive industries.

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2.3 Human rights in the extractive industries

With 28 per cent of all human rights abuses (Wright, 2008), the extractive industry is a

concerning sector for human rights. An explanation for this higher rate is that the MNEs go to wherever the resources are, where their invasive nature of operations combined with efficiency goals lead to the neglect of human rights. In strong institutional settings, where governments have the political will and institutional capacity to enforce regulations, human rights seem to be far less of an issue to uphold. Unfortunately, the extractive industry mostly operates in countries where the opposite is true, where the lacking institutional and governmental framework allows corporations to bend the government to their will, disregarding human rights in the process (Canel, Idemudia, & North, 2010). Combined with multinational companies being involved in almost all stages of public policy- and economic rule-making today. It leads to a shift, where governments are not controlling corporate activity, but corporations are increasingly dictating governmental policy options (Wettstein, 2010). Shankleman (2007) notes that the main

characteristic of resource-seeking investments is the short-term focus of business under pressure to deliver financial returns quickly (Shankleman, 2007). Bishop´s (2008) article about the limits of corporate human rights obligation emphasizes how a for-profit organization is exactly that, for profit. He poses that the obligation to spend corporate resources on human rights fulfillment is confined to contributing to specific corporate projects. The societies in which these human rights are fulfilled fall outside the scope of corporations, as he argues that corporate obligations are substantially different from those of governments (Bishop, 2008).

Crilly, Ni & Jang (2016) researched the effect of do-no-harm social responsibility (CSR) versus the effect of do-good social responsibility, and their effect on the liability of foreignness.

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Do-no-harm social responsibility is in line with Bishop’s (2008) view, where a firm focuses on attenuating negative externalities, minimizing risk and exposure. Do-good social responsibility on the other hand, confirms Haman et al (2009) view, showing a focus on proactive engagement creating positive externalities. The liability of foreignness is minimized in do-good CSR, but is substantial in do-no-harm CSR (Crilly, Ni, & Jiang, 2016). This presents another reason for corporations to engage proactively in CSR practices. The bulk of the literature focuses on the relation between MNEs, states, and their approach towards human rights. The liability of

foreignness gives an insight into how a MNE manages its subsidiaries when operating on a global scale, which could explain a certain approach towards human rights.

2.4 Liability of foreignness

Zaheer´s (1995) seminal article on overcoming the liability of foreignness identifies the liability of foreignness (LOF) as “the cost of doing business abroad that result in a competitive

disadvantage for an MNE subunit” (Zaheer, 1995, p. 342). The LOF can originate from four, not independent, sources. First are the costs arising from spatial distance, such as transportation. Second are the firm-specific costs originating from the lack of roots and unfamiliarity in a local environment, such as translation costs and setting up a business network. The third source are the costs arising from the host-country context, associated with preferred treatment to local

enterprises. The final source are the costs from the home-country context. All these costs result in a disadvantage for the MNE’s subsidiary from which the local firms do not suffer (Zaheer, 1995).

Eden & Miller (2004) agree, and expand the four sources of Zaheer. They argue that the liability of foreignness distinguishes into three hazards that provide a disadvantage to foreign firms over local firms in the host country. The first hazard is the unfamiliarity hazard, which encompasses the lack of knowledge of or experience in the host country of the foreign firms.

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The second hazard, the discrimination hazard, originates in differential treatment by the home- or host governments, public or consumers in the host country. Finally, the relational hazard comes in the form of higher costs of managing the relationships between parties involved in doing business abroad (Eden & Miller, 2004). The liability of foreignness stresses the social cost of doing business abroad, opposed to the economic cost of doing business abroad (e.g. production or marketing). Eden & Miller’s (2004) analysis states that the liability of foreignness is mostly driven by institutional distance, originating in the differences between the normative (society’s values and attitudes) systems and cognitive (collective programming of a group’s mind) views of two countries.

Sethi and Judge’s (2009) article makes a clear division between two different types of LOF. On the one hand are the discriminatory LOF, which are costs exclusively targeting MNE subsidiaries. On the other hand, are incidental LOF-related costs, which contain the costs

associated with the unfamiliarity and lack of roots in a host-country environment. Incidental LOF decrease over time, as the MNE becomes more and more familiar in the host country.

Discriminatory LOF are reducing as countries are easing their regulations that specifically target MNE subsidiaries (Sethi & Judge, 2009).

Recent literature departs from the liability of foreignness, and tries to better define the concept. Johanson & Vahlne (2009) coin the term ‘liability of outsidership’, referring to the fact that the country-specificity of MNEs’ problems and opportunities is becoming less of a matter due to the increased levels of globalization. They argue that regardless of the country, the

problems associated with e.g. market entry are the same with those associated with entry into any other market (Johanson & Vahlne, 2009).

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Qian et al (2013) researched the liability of foreignness and its effect on performance. To explain mixed findings in the costs of inter- and intra-regional diversification, the study

differentiated between the liabilities of foreignness at the country and regional levels. I.e. when a Dutch firm enters the Italian market, the firm only suffers from the liability of country

foreignness. If the Dutch firm were to diversify into the Chinese market, it has to face both liabilities of country foreignness and liabilities of regional foreignness. The research showed that the intra-regional diversification strategy could be less costly than an inter-regional one. It also shows how the liabilities increase for firms operating outside of a region because of political, economic and cultural cohesion between the firms in different countries within a region (Qian, Li, & Rugman, 2013).

Hymer (1960) defined home country as the country in which the firm was founded. Zhou & Guillén (2015) are of the opinion that that definition is no longer sufficient to determine the origin of a firm when looking at the liability of foreignness. They argue for the use of the home base, "a combination of countries in which the firm has grown and accumulated operational experience until a given point in time, including the home country” (Zhou & Guillén, 2015, p. 909). By using home base instead of home country, the liability of foreignness takes a more dynamic form, factoring in its experience in foreign expansion (Zhou & Guillén, 2015).

The above research clearly shows the significance of the liability of foreignness on the cost of doing business abroad, by influencing performance, social costs and the human rights approach. Crilly et al (2016) show a negative correlation between a firm’s foreignness and its impression on the host-country compared to domestic firms. This research defines the liability of foreignness as a disadvantage that a foreign firm suffers over a local firm in the host country, which results in hurting the competitive advantage of the foreign firm.

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In this research, the home country is the home base, where the global headquarters is located. The host country is the country where the MNE subsidiary operates. Hymer (1960) noted how when the distance between the host- and home country increases, the liability of foreignness increased with it. There are different kinds of distance used in this research and this concept will be described in the following section.

2.5 Cross-national distance

The concept of cross-national distance is a key concept in the field of management. There are different dimensions along which distance can be measured and defined. The differences in these dimensions are important, as different types of distance can affect firm decisions in different ways, depending on the dimension (Berry, Guillén, & Zhou, 2010).

The first type of distance which most people think about is geographic distance.

Geographic distance can be defined as physical remoteness (Ghemawat, 2001) between home- and host-country. Due to e.g. the size of country, the lack of a common border or a sea in

between countries the geographic distance between countries can result into serious costs. These costs can range from transportation costs to adapting your factory to the host-country climate. Geographic distance also includes the information networks used. Geographic distance has an effect on international trade, foreign direct investment and other types of economic activity between countries (Anderson, 1979; Deadorff, 1998). Even though the recent advancements in information technology have made the world much more connected and ‘smaller’ (Sorenson & Baum, 2003), decision makers still face information and access constraints, leading to spatially biased decisions (Duerloo et al. 1990, Golledge, 2002).

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Disdier & Head (2008) show, that on a macro level, geographic distance still effects bilateral trade and continues to do so consistently (Disdier & Head, 2008). On the micro level,

internationally oriented small firms are also affected by geographic distance (Brock, Johnson, & Zhou, 2011).

Economic distance is the differences in wealth between countries (Ghemawat, 2001). Economic distance has a serious effect on the levels of trade and the types of partners a country trades with. Economic distance can be measured in numerous ways, e.g. by comparing the GDP per capita between host- and home-country (Berry, Guillén, & Zhou, 2010). Companies that rely on economies of scale and scope generally focus more on countries with similar economic

profiles, so they can replicate their business models more easily (Ghemawat, 2001). According to Dow and Karunaratna (2006), economic distance also influences the norms that firms use to communicate and interact within the country, which spillover into business practices in regards to business-to-business communication and interactions norms. These economic differences then come with additional costs and uncertainty for firms’ international business transactions.

Administrative distance contains the institutional differences between countries. Also, referred to as political or governance distance, it is “the extent to which two countries differ with regard to the regulatory and governance system” (Hutzschenreuter et al, 2013, p.42). These differences in bureaucratic patterns can arise due to lack of colonial ties, language, religion and the legal system (Ghemawat, 2001; Berry et al, 2010). A country’s governance plays a great role determining the relationship and interactions between firm and government and between a firm and its customers/other firms. Unfamiliarity with a regulatory environment could expose a firm to more risk, coming from e.g. misjudging governmental reactions or political interventions (Dow & Karunaratna, 2006). An increase in administrative distance is likely to lead to an increase in both the costs and the risks of doing business in a foreign country (Zurawicki & Habib, 2010).

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Recent literature shows an expansion concerning the types (or dimensions) of distance. The types of distance have been expanded upon greatly. Berry et al (2010) identified and reviewed nine different types of distance: economic, financial, political, administrative, cultural, demographic, knowledge, connectedness, and geographic. Their research found that different dimensions of distance have differential effects on foreign investment decisions (Berry, Guillén, & Zhou, 2010).

Finally, Berry et al (2010) show how different dimensions of distance can have opposing effects, showing the importance of a nuanced approach to distance research. Even though there are multiple dimensions of distance, this research paper will use the geographic, economic, and administrative distance to determine the moderation of the relation between the liability of foreignness and human rights violations. These three dimensions have been chosen because of their diverse and encompassing nature. The following chapter will further elaborate why these dimensions have been chosen, and how they connect to the liabilities of foreignness and human rights violations.

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3. Theoretical framework

In this section the theoretical framework is discussed. First, the liability of foreignness and its influence on human rights violations will be discussed. Secondly, the moderating relationship between the different types of distance and their effect on human rights violations is reviewed.

3.1 The liability of foreignness and human rights violations

The liability of foreignness is a disadvantage that a foreign firm suffers over a local firm in the host country, which results in hurting the competitive advantage of the foreign firm (Zaheer, 1995). The increased costs for doing business abroad due to being multinationals can influence an already very efficiency oriented industry. Shankleman (2007) notes that the main characteristic of resource-seeking investments, the short-term focus of the business, is under pressure to deliver financial returns quickly. This short-term focus combined with efficiency goals can have serious impact on human rights. Firms that focus on the short term, and maintain a do-no-harm social responsibility approach suffer from substantial liabilities of foreignness (Bishop, 2008; Crilly et al, 2016). This research strives to find a correlation between the liability of foreignness and human rights violations by MNEs. Due to the competitive disadvantage of the foreign firm, as opposed to the domestic firms, the following hypothesis was developed:

(H1): The liability of foreignness has a direct effect on human rights violations by MNEs.

3.2 Geographic distance and human rights violations

Geographic distance is the physical remoteness between home- and host country (Ghemawat, 2001). As Duerloo et al (1990) and Golledge (2002) noted, decision makers face information and access constraints due to geographic distance. These constraints have to be overcome in the extractive sector, as the corporations have to go wherever the resources are.

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Qian et al (2013) show that firms suffer from an additional liability of foreignness when they operate outside their own region. The liability of regional foreignness increases costs and therefore it is expected that a larger geographic distance positively moderates the relation between the liability of foreignness and human rights violations. The following hypothesis was developed:

(H2): Geographic distance has a moderating effect on the relationship between the liability of foreignness and human rights violations.

3.3 Economic distance and human rights violations

Economic distance is the difference in wealth between countries (Ghemawat, 2001). The prospect of having the sustainable growth of extractive industries is very appealing to developing

countries, as the wealth derived from mining and oil extraction could revitalize a struggling economy (Hilson, 2012). Ghemawat (2001) has shown that business models can be more easily transferred to countries with similar economic development. Also, economic distance influences the norms that firms use to communicate and interact within the country, which spillover into business practices in regards to business-to-business communication and interactions norms (Dow & Karunaratna, 2006). These economic differences then come with additional costs and uncertainty for firms’ international business transactions, increasing the liability of foreignness and potentially having an adverse effect on human rights. It is expected that a higher economic distance between home- and host country leads to human rights violations by MNEs. The following hypothesis was developed:

(H3): Economic distance has a moderating effect on the relationship between the liability of foreignness and human rights violations.

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3.4 Administrative distance and human rights violations

Administrative distance indicates the institutional differences between countries. Reiman et al (2015) found that administrative distance between a MNE’s home and emerging economy host countries is negatively associated with their strategic commitment to corporate social

responsibilities. Reiman et al (2015) suggest that MNEs struggle with committing to their

corporate social responsibilities in emerging economies because of the significant challenges and liability of foreignness they encounter when operating in an emerging economy (Reiman, Rauer, & Kaufmann, 2015). The contextual uncertainties in developed countries with rising

administrative distance lead to more liabilities of foreignness, which in turn hurt a company’s CSR efforts (Campbell, Eden, & Miller, 2012). A lack of corporate social responsibility can, in turn, hurt human rights effort. It is expected that a larger administrative distance positively moderates the relation between the liability of foreignness and human rights violations. The following hypothesis was developed:

(H4): Administrative distance has a moderating effect on the relationship between the liability of foreignness and human rights violations

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3.5 Conceptual model

The literature review and the developed hypotheses lead to the following conceptual model:

The liability of foreignness of a corporation has an impact on human rights violations (H1). This relation is moderated by different forms of cross-national distance based on geographic

differences (H2), economic differences (H3), and administrative differences (H4). In order to test the validity of the hypotheses mentioned above, chapter 5 will carry out empirical analysis. The following chapter describes the research method of this analysis.

Liability of foreignness Human rights violations Cross-national distance H1 H2 H3 H4

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4. Research methodology

The field of corporate human rights violations is relatively new, with only five to ten years of research on this particular topic (Bernhagen & Mitchell, 2010). The Corporate Human Rights Database (CHRD), the result of a joint program of the University of Denver and the University of Oxford, strives to create a dataset for quantitative research on business and human rights

violations to accelerate more research. The access to this database is restricted, as it is still under construction. Students are asked to help with the coding of several cases, and get access to the database in return. In a three week period, I coded twenty-five different cases of corporate human rights violations in different African countries. After the coding was approved, access to the database was granted.

This research will use secondary data about corporations, the countries in which they operate, and human rights violations. A panel data set will be used to analyze a period of five years (2009 – 2013). A panel dataset has a clear advantage over cross-sectional and case-based research as it is able to factor in time, which can lead to a better understanding of the subject (Field, 2013).

This section will describe the data sources, dependent-, independent-, and control variables, and how they come together in this research to find a correlation between the liability of foreignness and human rights violations.

4.1 Data sources

The panel dataset is a combination of the Corporate Human Rights Database (2017), Orbis (2017), World Bank (2017) and Freedom House (2017) databases, the CIA’s World Factbook (2017) and the Human Development Report (2016). Data has been extracted for the years 2009 through 2013.

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The Corporate Human Rights Database is used to obtain the human rights violations and the related corporations for this research. The CHRD contains over 1200 cases of corporate abuse allegations (CAAs), which is extracted and analyzed from the data of the Business & Human Rights Resource Centre (BHRRC). The BHRRC tracks the human rights policy and performance of over 7000 companies in over 180 countries (Business & Human Rights Resource Centre, 2017).

Orbis provides the company data in this research, as it contains over 220 million

companies and covers all countries worldwide (Orbis, 2017). As the CHRD provides the name of the corporation that committed the violation, Orbis provides the corporations global ultimate owner, supplying the home country location. This is important for this research to calculate the geographic, economic, and administrative distances. Orbis’ global footprint greatly helped to determine the reach of the global corporations, but provided little data on the domestic firms in African and South-American countries. This will be further discussed in paragraph 6.2.

The World Bank’s “World bank open data”-database contains free access to economic and financial data from all over the world, listed by country (World Bank, 2017). This data has been used to determine the economic distances between the home- and host countries of corporation. The GDP per Capita (in US $) for each country has been obtained from this database.

Freedom House delivers a yearly report on civil liberties and political rights called “Freedom in the World”. This report evaluates the state of freedom in 195 countries yearly. By assessing the political rights and civil liberties of the individual in each country or territory, a score on a 1 – 7 scale is reported. The methodology behind the calculation of these scores is derived from the Universal Declaration of Human Rights (Freedom House, 2017). The separate scores for political rights and civil liberties are used in this research.

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For the calculation of the geographic distance, the CIA Factbook has been used to gather the coordinates of the capitals of the home- and host countries of corporations who have

committed human rights violations. America’s Central Intelligence Agency produces the World Factbook, a collection of global intelligence, made for policymakers in the USA (Central Intelligence Agency, 2017).

The Human development report is a yearly report by the United Nations Development Programme. It strives to be an approach that is focused on people and their opportunities and choices (United Nations Development Programma, 2017). Every country is graded upon scales which directly enhance human capabilities (e.g. standard of living) and scales which create conditions for human development (e.g. promoting environmental sustainability) to determine the Human Development Index. Data from this report is used to provide the research with its control variable, country of origin.

4.2 Sample selection and variable overview

The sample of this research is decided by human rights violations in the extractive industries. In this dataset, the extractive industry contains diamond, coal, gold, silver, uranium, platinum, and nickel mining, oil and gas exploitation, biofuels, logging and lumber, and stone quarries. This industry is selected because it is a concerning sector for human rights, with 28 per cent of all human rights abuses in the extractive sector (Wright, 2008), making it highly represented in the CHRD (2017). The industry has also been chosen because of the good representation in the Orbis (2017) database, as the extractive industry is very capital intensive, increasing presence and quality of data in Orbis.

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Human rights violations is the dependent variable, and is provided by the CHRD (2017). The panel dataset has been limited to a time frame of five years, from 2009 through 2013. These years have been chosen because it contains the largest number of violations in the extractive industry, and to paint a recent picture on the state of human right violations whilst still accounting for time. The dependent variable in this research is a count variable: it shows the number of human rights violations for a firm per year.

The main independent variable is the liability of foreignness. This research defines the liability of foreignness as a disadvantage that a foreign firm suffers over a local firm in the host country, which results in hurting the competitive advantage of the foreign firm (Zaheer, 1995; Sethi & Judge, 2009). In the sample, the liability of foreignness is defined by whether a firm is a domestic firm, or a multinational firm. This data was created by combining the CHRD’s

company data and checking the global ultimate owner’s headquarter location in Orbis. This created the home- and host country of each firm related to a human rights violation, which were then used to determine the distances.

The majority of the human rights violations in the CHRD originate in Africa (22 %), Latin America (18 %) and Asia & The Pacific (28%), showing a possible correlation between human rights violations and the regions in which they occur (Wright, 2008). To control against this effect, the control variable country of origin has been introduced. The Human Development Index distributes into four categories: Very high - , high-, medium-, and low human development (United Nations Development Programma, 2017). In the sample, this variable is linked to the home country of each firm related to a human rights violation. This is an ordinal variable, where in the sample it is coded as: “4” is very high- , “3” is high-, “2” is medium-, and “1” is low human development.

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Finally, the distances have been calculated for the sample. The distances are the moderating variables. All the moderating variables are real numbers. Economic distance was calculated by measuring the difference in GDP per capita of the home- and host country of each firm related to a human rights violation. The GDP per capita functions as a widely accepted standard measure for the size of a country’s economy (Berry, Guillén, & Zhou, 2010). The administrative distance is calculated by measuring the differences of Freedom House’s civil liberty and political rights scores (Berry et al, 2010; Freedom House, 2017). The geographic distance is calculated using the great circle distance between the capitals of the home- and host countries (Berry et al, 2010). The coordinates of the capitals were provided by the CIA World Factbook.

The following table gives an overview of all the variables, their names, definition, variable type and sources.

Table 1. Variables and sources

Variable Name Definition Type of variable Values Source

Dependent Human rights

violation

The amount of human rights violations a firm committed in a year

Count - CHRD, 2017 Control Human Development Index – Country of Origin (COO)

HDI of the home country of the firm / Headquarter location

Ordinal 4=very high

development 3=high development 2=medium development 1=low development HDI report, 2016 Independent H1 Liability of Foreignness

Whether or not a firm suffers from the liability of foreignness. Categorical 0 = No LOF (Domestic firm) 1 = LOF (MNE) CHRD, 2017, Orbis 2017 Moderator H2 Geographic distance

The great circle distance between home- and host country’s capitals

Continuous - CIA World

Factbook, 2017

Moderator H3 Economic

distance

GDP per capita - distance between home- and host country

Continuous - World

Bank, 2017

Moderator H4 Administrati

ve distance

Distance between Freedom score between home- and host country

Continuous - Freedom

House, 2017

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5. Analysis and results

5.1 Descriptive statistics

The panel data set contains 210 companies with data over a five year period, creating a total of 850 cases. 530 Firms suffer from the liability of foreignness, leaving 320 firms as domestics. The Human rights violations show high levels of skewness, due to 638 cases were no human rights violations were reported (Appendix 1). 212 Cases of human rights violations are reported, with a maximum of 5 violations in a single year. The Human Development Index (HDI) shows a mean of 3.247, showing that the majority of the corporations come from a country of an at least high human development level. Geographic distance, calculated by the great circle distance formula, shows a mean average of 17,254 kilometers of distance between home- and host country. The economic distance shows a mean of 21,163 US dollars, but with a standard deviation of almost the same size, 21,517 US dollar. This shows high variability, which indicate that it may not be an accurate reflection of the population (Field, 2013). Administrative distance shows the same problem, with a standard deviation of 1.684 and a mean of 1.025. Attempts were made to transform the data (absolute values, Ln, and square root transformations) but none of these transformations had a significant effect on the results of the analysis.

Table 2 Descriptive Statistics

N Minimum Maximum M SD Skewness Kurtosis Human rights violation 850 0.000 5.000 0.295 0.573 2.446 9.169 Liability of Foreignness 850 0.000 1.000 0.624 0.485 -0.511 -1.743 Human Development Index - COO 850 1.000 4.000 3.247 0.907 -0.982 -0.021 Geographic distance 850 0.000 17253.834 4957.487 4804.784 0.464 -0.967 Economic Distance 850 -1120.026 87172.760 21162.993 21517.135 0.347 -1.323 Admin Distance 850 -4.000 5.500 1.025 1.684 0.569 0.890

The correlation matrix shows the interplay between the variables to each other. It shows no significant correlations between the violations and any of the other variables. There are positive

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relations with human rights violations, but all show very small Pearson correlations, with no r exceeding 0.044. The other variables do show significant correlations. The liability of foreignness shows high significant (p > 0.01) correlations with the HDI of the home countries, with a Pearson correlation of 0.721. The geographic and economic distance variables are also strongly correlated with the liability of foreignness, with Pearson correlations of 0.802 and 0.765 respectively. Administrative distance shows a weaker, but still strong and significant correlation with the liability of foreignness with an r of 0.473. All the distance variables also show strong and significant correlations with each other, implying that as one distance increases, the other distances increase as well.

Table 3 Descriptives and Pearson Correlations matrix

# Variable M SD N 1 2 3 4 5 6

1 Human rights violation 0.295 0.573 850 1 2 Liability of Foreignness 0.624 0.485 850 .040 1 3 Human Development Index - COO 3.247 0.907 850 .032 .721** 1 4 Geo distance 4957.487 4804.784 850 .044 .802** .634** 1 5 Economic Distance 21162.993 21517.13

5 850 .043 .765** .782** .685** 1 6 Admin Distance 1.025 1.684 850 .010 .473** .488** .371** .624** 1

Notes: Two-tailed Pearson correlation coefficients are reported for the unstandardized variables. In case of missing values, cases are excluded listwise. **. Correlation is significant at the 0.01 level (2-tailed). Other correlations are not significant. Listwise N=850

The high and significant correlations could be a sign of multicollinearity, where two or more variables are very closely linearly related, making the variables more difficult to interpret (Field, 2013). A linear regression was performed to check for the presence of multicollinearity. In this regression, the Durbin-Watson statistic was 2.159, which is 1.5 < DW < 2.5, meaning there is no evidence to suggest that the variables are not independent (Field, 2013). The variance inflation factors (VIF) are another measurement to test for multicollinearity. The variance inflation factors were all between 1 and 5, indicating moderate correlation, but that the variables are independent and do not suggest multicollinearity (Field, 2013), enabling the next step of the analysis.

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5.2 Results

A Poisson regression is utilized when a researcher has count data on some dependent measure that represents the rate of incidence of some event (Hoffmann, 2004). The Poisson distribution is fitting for this research, as the zero value is highly represented in the dependent variable

(appendix 1). The normal distribution would not be fitting, as the level of skewness in Human Rights Violations is far too high (2.446). A generalized linear model with a Poisson distribution and a log link function has been chosen for the hypothesis testing. An advantage of using this generalized linear model is that the SPSS automatically creates the required dummy variables for testing.

Five instances of the Poisson regression model (GLM) with Log Link function were run. The first model only checks the direct relationship between the liability of foreignness and human rights violations. The second model adds the control variable Human Development Index – COO. The third models adds the moderating variables, to test their direct effect on the human rights violations. The fourth model adds the control variable on the interaction and the final model includes the full model, with all the moderators and the control variable, to test the relation and the moderating effects. The incremental build of the model is good for identifying the effect each variable introduced has on the model.

Table 4 shows the results of the analysis. For the goodness-of-fit-test, the deviance value is observed. The deviance value of each model is > 0.860, supporting that the distribution of the data set does follow the Poisson distribution, validating the use of the generalized linear model. Akaike’s Information criterion stays stable through the different models, implying how adding and removing variables to the model does not affect the outcome.

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Model 5 shows that the relation between the liability of foreignness and human rights violations is positively correlated with 0.354, implying that an increase in liability of foreignness, could show an increase in human rights violations. This relation is not significant though,

resulting in support for the null hypothesis. A lack of support for H1 shuts down the possibility for the moderators (H2, H3 and H4), as is reflected in model 5 with redundant parameters and zero values, also showing support for those null hypotheses. The control variable Human Development Index of Country of Origin did show to effect the relationship between liability of foreignness and human rights violations, but also with no significant values.

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Table 4: Poisson Regression Model (GLM) with Log Link function

Dependent: Violations Model 1 Model 2 Model 3 Model 4 Model 5 (Intercept) -1.326*** -1.139*** -1.139*** -1.139*** -1.139*** (0.107) (0.257) (0.257) (0.257) (0.257)

[LOF=1] 0.165 0.074 0.038 0.354 0.354

(0.136) (0.232) (0.268) (0.417) (0.417)

[LOF=0] 0a ₀a ₀a ₀a ₀a

[HDI COO index=4] -0.062 0.017 0.223 0.223

(0.356) (0.447) (0.584) (0.584)

[HDI COO index=3] -0.235 -0.244 -0.222 -0.222

(0.299) (0.299) (0.302) (0.302)

[HDI COO index=2] -0.227 -0.222 -0.288 -0.288

(0.304) (0.304) (0.312) (0.312)

[HDI COO index=1] 0a ₀a ₀a ₀a

Geographic distance 0 0 0 (0.000) (0.000) (0.00) Economic Distance 0 0 0 (0.000) (0.000) (0.00) Administrative Distance -0.032 -0.035 -0.035 (0.051) (0.050) (0.05)

[LOF=1] * [HDI COO index=4] -0.618 -0.618

(0.759) (0.759)

[LOF=1] * [HDI COO index=3] -0.392 -0.392

(0.491) (0.491)

[LOF=1] * [HDI COO index=2] 0a ₀a

[LOF=1] * Geographic distance 0a

[LOF=0] * Geographic distance 0a

[LOF=1] * Economic Distance 0a

[LOF=0] * Economic Distance 0a

[LOF=1] * Administrative Distance 0a

[LOF=0] * Administrative Distance 0a

Deviance (value/df) 0.861 0.862 0.864 0.865 0.865

Log Likelihoodb _-587.752 _-587.025 _-586.656 _-586.242 _-586.242 Akaike's Information Criterion (AIC) 1179.504 1184.049 1189.311 1192.484 1192.484 Finite Sample Corrected AIC (AICC) 1179.519 1184.121 1189.483 1192.746 1192.746 Bayesian Information Criterion (BIC) 1188.995 1207.776 1227.273 1239.936 1239.936

N 850 850 850 850 850

Notes: 0a_{is set to zero because the parameter is redundant. Reported values are the estimates of the Poisson} regression analysis. Values in parentheses are standard errors. †p < 0.10, *p<0.05 , ** p < 0.01, *** p < 0.001 .

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6. Discussion

6.1 Implications of the study

The extractive industry is no stranger to human rights violations with 28 per cent of all corporate human right allegations in 2008 (Wright, 2008). The invasive nature of the industry has an adverse impact on the environment and the communities (Hamann et al, 2009). This research paper set out to find a difference between the impact of domestic and multinational firms on human rights violations in the extractive industry. As multinational firms suffer from a liability of foreignness whilst domestic firms do not, this research assumed that the multinationals would have a greater impact on human rights violations. This hypothesis is based on the competitive disadvantage the liability of foreignness brings to the multinational firm.

The relation between liability of foreignness and human rights violations was assumed to be moderated by three dimensions of cross-national distance. As geographic distance increases, spatial costs like transportation increase. Economic distance shows the difference in wealth between countries, influencing the business practices and adding to the bottom line.

Administrative distance refers to the regulatory and governance distances, creating more costs for firms trying to operate in distant locations. As firms in the extractive industry need to go

wherever the resources are, they end up in countries and regions far away from their

headquarters, forced to suffer from all the costs that cross-national distance brings them. This influence in an industry which is already very efficiency-based, is assumed to increase the effect of the liability of foreignness even more on human rights violations.

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The independent variable liability of foreignness was found to not significantly impact the number of human rights violations. So when the liability of foreignness was present, there is no evidence to suggest that the impact on human rights violations is more severe than without the liability of foreignness. There were high correlations between the independent variable and the moderators, showing that even though there is no significant relation with human rights

violations, liability of foreignness is significantly correlated with the concepts of geographic-, economic-, and administrative distance. This could prove a good starting point for future research.

6.2 Limitations

This research has limitations regarding the internal validity of the results and the research design. The first limitation lies in the databases used to collect the sample data. The Corporate Human Rights Database is still in its infancy. This means that the number of cases with human rights violations in the period 2009 – 2013 is limited. Moreover, the cases in the CHRD are coded by students and scholars who base their coding strategy on newspaper articles and public NGO reports, introducing a level of subjectivity into the data. Human rights violations by businesses is also an inherently hard topic to collect data on, as business would prefer to not disclose them at all and that there is a large grey area of who to blame for a violation. This grey area is created by states supporting large corporates because of the employment and wealth these companies bring to the countries (Shankleman, 2007), making it hard to point the finger at the violating party. The CHRD is the only database containing such a vast number of human rights violations that allows quantitative research, making it unique and the limitation to this research acceptable.

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Another limitation comes from the database used for company information, Orbis. Orbis’ large database contains over 220 million companies and has global coverage. Even though all companies were found in Orbis, the additional company information such as firm size, revenue and age of operation were severely lacking for domestic companies in African and South-American countries. This reduced the amount of control variables planned for this research.

The third limitation could be found in the use of the extractive industry as a restriction to the dataset. A larger data pool would have contained more valid cases, increasing the chances for significant results. The CHRD industries that were not included were e.g. manufacturing, apparel, utilities and telecom.

The fourth limitation lies in the distance moderators. The way this distance is measured is two-way, meaning it does not take the direction of the distance into account. This makes it hard to determine if the high distance is caused by the properties of the home-country or the other way around. Also, this research only focused on geographic-, economic-, and administrative distances, to restrict the scope of the study. Other dimensions distances, like demographic or cultural, could increase the level of insight into possible correlations.

The final limitation could be found in the independent variable liability of foreignness. The binary approach in which firms are or are not affected by liability of foreignness could be a restriction because it is a crude variable. A more structured approach by incorporating the liability of regional foreignness could have presented a stronger independent variable.

6.3 Future research

Future research could take a more detailed approach to liability of foreignness, to create a range in the independent variable and to accommodate more recent liability of foreignness literature (Qian, Li, & Rugman, 2013).

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To increase the validity of liability of foreignness even more, using Zhou & Guillén home base concept instead of home country could improve the results of the analyses. This would require a more detailed company database, as Orbis was not sufficient enough for this research.

Even though the CHRD is still in its infancy, it is being updated on a regular basis, increasing the number and quality of cases and by doing so, increasing the quality of the database. This will allow future researchers to be able to have a better dataset for research, and get more valid results. Another factor for future research could be to disregard the industry restriction and test the entire database. This could create more missing values due to certain types of data missing for moderators, but would bring a larger population to work with, and increase the chance for

significant results.

The final suggestion for future research was already noted in the previous paragraph, to introduce more distance moderators into the model. For example, cultural distance has not only shown to have impact on foreign market entry and entry mode choice (Werner, 2002), but also has a prominent position in Whitley’s (1992) business systems and Ghemawhat’s (2001) CAGE-model for strategy making. This is just one example of how another distance dimension could affect the relation between business and human rights violations.

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7. Conclusion

The extractive industry is overrepresented in human rights violations, and holds great presence in developing countries. The companies in charge are usually thousands of miles away from the violations, but there are also domestic firms committing violations. This study set out to look for a relationship between whether a firm suffers from the liability of foreignness (multinational) or not (domestic). This study looks for a relationship between the liability of foreignness and the number of human rights violations in the extractive industries, using three concepts of cross-national distance as moderators.

No significant results were found between the liability of foreignness and human rights violations. The reason that no significant results were found could be due to the limited and specific data available in this study. The research did find correlations between the liability of foreignness and the distance moderators, creating the possibility that future research using more extensive datasets could come to a significant understanding of a possible relationship.

Researchers have an obligation to continue their work in the field of human rights and business due to the large economic, social and humanitarian impacts these violations have. More research could shift the current reactive approach, to a proactive approach against human rights violations.

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The liability of foreignness, cross-national distance, and their influence on human right violations in the extractive industry