MNE and indigenous community conflict: prior community involvement and community autonomy as predictors of the nature of conflict

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MNE and indigenous community conflict: prior community

involvement and community autonomy as predictors of the

nature of conflict.

Malin Nystrom

Student ID: 11087609

24 June 2016

Master Thesis: Draft

MSc Business Administration – International Management

Supervisor: Dr. Ilir Haxhi

Second reader: Dr. Niccolo Pisani

University of Amsterdam

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Statement of Originality

This document is written by Malin Nystrom 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

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5.3 Variables………..……….24 5.3.1 Dependent variable……….…...……….24 5.3.2 Independent variable..……….25 5.3.3 Moderator……….…….………..25 5.3.4 Control variables……….……….…….………..26 5.4 Model summary………28 6. Results………...……….29 6.2 Descriptive statistics………29

6.3 Multicollinearity and correlation analysis………..30

6.4 Regression analyses……….…33 6.4.1 Level of violence………33 6.4.2 Length of conflict………...36 7. Discussion………..40 7.2 Findings………40 7.3 Contribution……….…44

7.4 Limitations and suggestions for future research……….…45

8. Conclusion………..48

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1. Abstract

Community involvement is considered one of the main ways of reducing MNE-community

conflict by addressing some of its underlying causes. Paradoxically, trends show increasing

levels of MNE social performance while also pointing at an increase in the frequency and

intensity of conflicts. This is because increasing recognition of indigenous peoples’ rights

empowers communities to oppose projects which they feel infringe on their way of life, but

also because firms’ efforts to manage community relations often fall short, failing to

compensate for this effect. This study cross sectional study analyses 675 cases of

MNE-community conflict, examining the predictive power of the degree of prior MNE-community

involvement and the degree of community autonomy on conflict between extractive industry

firms and indigenous communities, with the purpose of gaining greater insight into the

dynamics that shape the nature of such conflict.

While the results support that prior community involvement reduces the level of violence,

they also show that higher degrees of community autonomy lead to higher levels of

violence, as well as having a positive moderating effect on the relationship between

community involvement and violence – cancelling out the effect as autonomy increases.

This contributes to the current literature by challenging the key argument that prior

community involvement is the best means of preventing MNE-community conflict, adding

to our understanding, not only whether, but also when and why this is the case. By doing so

the study also creates a stronger link between two strands of the literature, and creates

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2. Introduction

The story of indigenous peoples and multinational enterprises (MNEs) is a complicated one

that requires a nuanced approach and adaptable thinking. The topic has been receiving

increasing attention in global political environments and the media, as well as in

management literature and corporate agendas, and the conflicts that have arisen come under

ever closer scrutiny.

With resources becoming increasingly sought after at the same time as supply is

diminishing, companies in extractive industries are drawn further and further into

unexploited areas. Such areas have often been left untouched, and so has the cultures and

the way of life of the people inhabiting them. (Calvano, 2008) When MNEs implement

projects in such areas, indigenous peoples and the environment far too often suffer severe

consequences. (Scassola, 2013; Hilson, 2001) While there is increasing international

pressure being put on governments to strengthen the rights of their indigenous peoples, there

is still a huge gap between the adoption of standards and their implementation, and

extraction activities are often approved and justified by goals of economic development.

(Acuna, 2015; Adamson and Pelosi 2014; UNDRIP, 2013)

From a business perspective, in particular for MNEs in the extractive resources industry,

this creates significant threats in terms of costs and reputation. (Laplante and Spears, 2008)

A large number of studies have examined the best solutions for MNEs to handle conflict,

whether that is through solving, mitigating or preventing them. (Castro and Nielsen, 2001;

Davis and Franks, 2011; Frynas 2010; Franks, 2009; Foster, 2012; Lertzman and

Vredenburg. 2005; Shankleman, 2010; Kemp, 2010; Kemp et al, 2001; Nish and Bice, 2011)

While there is not one universal strategy which can be applied in all cases, there is a

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6 understanding and dialogue, is key to the firm’s success. With one of the main causes for

community opposition being the feeling of not being in control of one’s own destiny,

involving indigenous communities in the process, prior to the implementation of a new

project is believed to reduce the risk, and the intensity of MNE-community conflict.

(Laplante and Spears, 2008; Nish and Bice, 2011; Harvey and Bice, 2014; Murphy and

Arenas, Kemp et al. 2001) This is consistent with UNDRIP’s (2013) call for free, prior and

informed consent to all extractive activities on their territorial land. However, with most

previous articles using qualitative methods, there is a gap in the literature, testing the

statistical significance of this recommended solution. Therefore, it is appropriate to ask:

- RQ1; What is the relationship between prior community involvement and the nature

of the conflict in cases of conflict between extractive industry MNEs and indigenous communities?

At the same time, another strand of the literature, headed by Hodge (2014), draws attention

to an interesting paradox. While extractive industry firms continue to improve their social

and environmental performance, MNE-community conflict is also increasing. Supported by

sceptics to the reality of MNEs implementing community involvement strategies, he argues

that this phenomenon is due to the rise in recognition of indigenous community rights,

empowering them to oppose MNE agendas. (Hodge, 2014; Brereton, 2014; Castro and

Nielsen, 2001; Hamann, 2014; O’Faircheallaigh, 2013) This suggests that companies’

attempts to act more responsibly might not have the desired effect, which adds another layer

to the discussion on how to avoid MNE-community conflict. Currently, there is a gap in the

literature, failing to consider how the rise in community autonomy might affect the solutions

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7 - RQ2: Does community autonomy have a moderating effect on the relationship

between community involvement prior to extractive industry projects and the nature of the conflict?

The purpose of the study is to gain a greater insight into the dynamics that shape the nature

of MNE-community conflict by examining prior community involvement and community

autonomy as predictors of the level of violence and the length of conflict. This will be done

through a cross-sectional study, examining 675 cases of MNE-community conflict through

a stepwise, multiple regression analysis.

From a theoretical standpoint, the study tests a key argument in the previous literature –

community involvement as a means of reducing conflict - while also bridging the gap

between two different strands of research on MNE-community conflicts. This way the

results add to the understanding of not only whether, but when and why community

involvement might be an effective choice. This also has practical implications by drawing

attention to potential issues relating to community involvement, creating awareness which

can lead to better community management practices in the future.

The study will start by reviewing the previous literature on the topic. The literature review

in turn sets the context for the theoretical framework which provides motivation for the

research questions which the study seeks to address, as well as the hypotheses which are

formed to explore them. The next chapter will discuss the methodology, with a description

of the data collection process, sample, and the different variables. This is followed by a

section presenting the results from the analyses used to determine the statistical relations hip

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8 their ability to answer the set out research questions and how this ties in with the previous

literature. It will also discuss limitations and suggestions for future research, before

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3. Literature review

3.2 MNE-community conflict: causes and consequences

With a rising demand for natural resources, multinational enterprises (MNEs) move in

closer on areas which have previously been left untouched - areas often inhabited by

indigenous peoples. In such situations, the interests of MNEs and indigenous communities

are likely to collide which can lead to conflict, unless managed properly. (Calvano, 2008;

Bebbington and Bury, 2009)

Most documented cases of MNE-community conflict, sometimes referred to as

‘socio-environmental conflicts’ are with companies who fall within the category of 'extractive industries'. (Acuña, 2015:85) These include, but do not exclusively refer to mining, oil and

gas, and forestry. These industries are often accused of having significant negative

environmental impacts, ranging from deforestation or erosion before and during the

projects, to the risk of environmental disasters such as oil leaks. But these types of projects

can also have negative socio-economic impacts in the areas where they are implemented,

including land dispossession or dispossession of identities. (Calvano, 2008; Scassola, 2013;

Hilson, 2001; Acuña, 2015)

But extractive industries do not only present a significant threat for the preservation and

rights of indigenous communities and their territorial lands. From a business perspective,

operating in areas of indigenous peoples also present a significant risk to MNEs. The nature

of extractive activities requires large capital and long-term investments which might not

have an immediate pay off, making the industry particularly vulnerable to delay caused by

conflict. (Hodge, 2014) MNEs who end up facing community opposition may run the risk

of suffering both financial and reputational costs. (Laplante and Spears, 2008; Hodge, 2014)

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10 between the MNE and the affected indigenous communities before, during and after the

implementation of projects.

Not following good community practices can have devastating consequences for the firm.

(Franks, 2009; Davis and Franks, 2011) Yet, as pointed out by authors such as Kemp and

Owen (2013) and Laplante and Spears (2008), so far, company efforts have been

underwhelming in this respect, with most CSR strategies failing to capture the complex

nature of these type of conflicts and address the underlying causes to opp osition.

To understand the relationship between MNEs and indigenous communities, Santoyo

(2006) draws attention to the importance of the complex history which indigenous

communities around the world have had to withstand. Since the colonial era, indigenous

communities have been forced to live as a part of a national system which they did not

choose for themselves. This has a led to relationships, with both government and companies,

characterised by conflict and opposition, where the community is usually at a disadvantage

due to the uneven power distribution which exists between communities, governments and

MNEs. (Calvano, 2008) Furthermore, historically speaking, it is the indigenous communities

situated in the most resource rich lands that are affected the most profoundly by such conflicts,

this phenomenon is known as the resource curse and means that countries with a higher level

of resources, tend to have a lower level of economic development, and it is the indigenous

populations that feel the brunt. (Parlee, 2015)

Efforts are being made on an international level to improve the situation for, and strengthen

the rights of indigenous peoples. In 2007, the general assembly adopted the United Nations

Declaration of the Rights of Indigenous Peoples (UNDRIP). UNDRIP calls, among other

things, for indigenous peoples free, prior and informed consent to all extractive activities

taking place on their territorial land. As of now, over 140 countries have signed the

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11 Zealand, and Australia, all countries with large indigenous populations, were among the last

to join. When doing so, they argued for the non-binding nature of the agreement, giving

them significant interpretational freedom and weakening its impact. (Adamson and Pelosi,

2014; Ingimundarson and Magnusdottir, 2013; UNDRIP, 2013) Further, when it comes to

projects involving resource extraction, despite contradictions with UNDRIP, governments

often choose to justify them through an argument of economic development, something in

which indigenous communities typically have not had much say. (Banerjee, 2001; Acuna, 2015) Hodge (2014:28) defines development as the aim “to expand or realise the potentials of; bring gradually to a fuller, greater, or better.” This definition is problematic since what

is “better” for a country, people, or area will depend on who’s perspective you choose to adopt, and the ambiguity of the pledge leaves it open to reneges.

Banerjee (2001:39) describes indigenous communities as often having "very different

social, cultural, political and economic agendas from those of industry". Calvano (2008)

follows a similar level of reasoning to Banerjee (2001), arguing that there is a perception

gap between the different actors' ideologies, which underpins their unique point of view.

These types of conflicts of interest between different stakeholder groups makes creating and

maintaining a good relationship between stakeholders increasingly difficult. (Banerjee,

2001)

Extractive activities can cause major concerns for indigenous peoples, however, the

situation does not always need to be a negative one. Both Lertzman and Vredenburg (2005),

and Foster (2012), recognise the fact that foreign direct investment in indigenous regions

can provide opportunities for its people as well as presenting threats. However, even when

the community members recognise and are positive about the potential benefits that a

project could bring, there is a lot of uncertainty involved. While these types of projects tend

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12 position. Whether or not that happens, the nature of the projects mean that they do not last

forever and for a community which has lived on the land for generations, there is an

understandable concern also for what will happen once the firm leaves. (Acuña, 2015)

The main issue arises when the community feels that a project affects their way of life in a

negative way and when they lack the power or resources to oppose it. (Acuna, 2015) Laplante and Spears (2008:76) argue that “communities are primarily concerned with questions of control over their own destinies”. When they feel that an MNE threatens this

sense of control, the indigenous community is likely to oppose their project.

3.3 Solving, mitigating and preventing MNE-community conflict

With the serious risks involved for both indigenous communities and MNEs, it is

understandable that one of the main focuses in MNE-community conflict literature is on the

subject of ways in which MNEs can either solve, mitigate or prevent MNE -community

conflicts. (Castro and Nielsen, 2001; Davis and Franks, 2011; Frynas 2010; Franks, 2009;

Foster, 2012; Lertzman and Vredenburg. 2005; Shankleman, 2010; Kemp, 2010; Kemp et

al, 2011; Nish and Bice, 2011) In most countries, the existing legal framework does not

sufficiently support the contrasting needs of MNEs, governments and indigenous peoples.

Therefore, it is important that MNEs acknowledge their responsibility towards their

stakeholders. (Adamson and Pelosi, 2014; Foster, 2012)

Lertzman and Vredenburg (2005) and Foster (2012) believe in the potential for positive

outcomes, promoting an ethical approach to resource extraction, building on cooperation

and understanding between community, management and environmental science. However,

as discussed, for the general population, change has not yet come far enough and MNEs

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13 MNE-community relations. (Lertzman and Vredenburg, 2005; Foster, 2012; Kemp and

Owen, 2013; Laplante and Spears, 2008) While, from a bigger perspective, it makes

considerable business sense to engage in good community management practices, the direct

benefit of effective community management might not be as easily identifiable. The firm’s

desire to get a new project up and running risks interfering with good community practices

since this might cause the firm to skip important steps that are necessary for understanding

the full context and building good relationships with the affected community. (Brereton,

2014) As such, “Inequities, the short-term perspective of management and decision-making,

the underlying commercial pressures and incentives that prioritize company over

community culture and quality of life. All serve as resistance to dialogue.” (Hodge,

2014:32)

There is no definitive, universal strategy which is suitable in all cases, however, while

suggesting slightly different approaches, there is a general consensus that the one of the key

factors for better MNE-community relations is knowledge and understanding. This relates

to the values of both parties, as well as to the underlying causes, and the consequences that

conflict can have - financial and reputational for the firm, and for the way of life of

indigenous peoples. This, in turn, can only reasonably be achieved when the MNE and the

community engage in meaningful dialogue in an attempt to decrease the perception gap.

(Calvano, 2008; Benito and Gripsrud, 1992; Hodge, 2014; Nish and Bice, 2011; Harvey and

Bice, 2014) In fact, the majority of studies where maintaining a good relationship between

the firm and the community is considered a key success factor, argues for discussions

between the MNE and the indigenous community as an absolute minimum before

implementing a new project or entering a new area. (Castro and Nielsen, 2001; Davis and

Franks, 2011; Nish and Bice, 2011; Frynas 2010; Franks, 2009; Murphy and Arenas, 2010;

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14 being one of the main causes for MNE-community conflict, the more involved the affected

community can be in the process, the better. This assumption corresponds with UNDRIP’s

call for indigenous peoples free, prior and informed consent, known as FPIC. Adam and

Pelosi (2014) provides a broad definition of FPIC as “the principle that a community has the right to give or withhold its consent to proposed projects that may affect the lands they

customarily own, occupy or otherwise use.” (Adamson and Pelosi, 2014:11) Without

cooperation between the firm and the community, it is difficult to build trust. (Murphy and

Arenas, 2010; Harvey and Bice, 2014) An important takeaway from UNDRIP’s

recommendation being that efforts are likely to be effective when implemented prior to the

project, rather than responding to opposition as it begins to gather. At that stage the firm

already risks delays and unwanted media attention. Engaging prior to the project will also

allow communication channels to raise any potential concerns, this way the MNE can

receive early warning signals, acting on issues before the conflict escalates. (Kemp et al.

2011) Starting an open and two-way dialogue with indigenous populations from the earliest

stages of a project seems logical, but it is often overlooked and subsequently plays a big part

in many of the conflicts.

3.4 Community autonomy

From a stakeholder perspective, MNEs have a responsibility towards the local communities

in which they wish to hold, or already undertake extractive activities. (Freeman et al. 2010;

Banerjee, 2001) When there is a lack of government intervention, the responsibility to

enforce the type of good community management practices discussed above, lies solely o n

the company. (Hilson, 2001) However, some researchers suggest that the nature of the

potential conflict does not only depend on whether or not the MNE chooses to include the

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15 of community involvement, Brereton (2014) and Hamann (2014) also critiques the practical

reality of bridging the existing gap between MNE and community interests, questioning whether companies’ commitment to community dialogue and involvement can be relied upon. “Given the financial and other constraints under which mining companies operate,

we need to be realistic about what can be achieved through the mechanisms of voluntary

action and self-regulation”. (Brereton, 2014:38) Similarly, Castro and Nielsen (2001)

recognise that co-management efforts are often more complicated than first anticipated.

In this context, Hodge (2014) draws attention to an interesting paradox. While there is

evidence that the social and environmental performance of MNEs in extractive industries is

increasing, so is the number and intensity of MNE-community conflicts in indigenous community regions. Brereton (2014:37) summarises the explanation for this as “while companies are changing, the world around them is changing even more quickly”.

O'Faircheallaigh (2013) argues that an increasing recognition of indigenous rights gives

increasing leverage to oppose MNE decisions to both indigenous and non-indigenous

people who are affected by extractive industries operating in their region. What this really

means is that, as indigenous communities become increasingly empowered by higher

recognition from governments, pushed for by global human rights organisations and media

attention, they are increasingly able to oppose planned projects in their territories.

As discussed above, communities are often at a disadvantage when extractive industry

projects are planned and implemented due to the uneven power distribution between

government, MNEs and indigenous communities (Calvano, 2008). However, the findings

by Hodge (2014), indicate that making the distribution of power more even between the

different stakeholders might not be enough to avoid MNE-community conflict as long as

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16 Clearly, the dynamics of MNE-community conflict are more complicated than a simple

cause and effect. Calvano (2008:793) summarises this nicely by stating, that for this new

accountability of MNEs to effectively manage their relationships with indigenous

communities “managers must first understand the causes of conflict with local communities,

and communities must understand what courses of action are available to challenge activities they deem harmful to their interests”.

4. Theoretical Framework

4.2 Research gap and questions

Most of the current literature on MNE-community conflict focus on one of two sides of the

debate, either on the underlying reasons of conflict, or on different ways for MNEs to solve,

mitigate or avoid conflicts with indigenous communities. One of the key success factors

which is put forward in the literature, lies in involving the indigenous community in the

process prior to the implementation of a new project. The reason for this is that community

involvement addresses what is considered as one of the main underlying causes for

MNE-community conflict – namely, the feeling of not being in control of one’s own life and

destiny. This is in line with the United Nations Declaration of the Rights of Indigenous

Peoples (UNDRIP) and the call for indigenous peoples’ free, prior and informed consent to

all extractive activities on their territorial land. (UNDRIP, 2013) While there is no definitive

strategy that will fit every situation, there is a clear consensus that MNE -community

relations will benefit from mutual understanding and increased knowledge-sharing between

stakeholders, as this will create trust and decrease the existing persistence gap. (e.g. Harvey

and Bice, 2014; Kemp et al. 2011) However, most studies to date are of a qualitative nature,

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17 testing the effect of this proposed solution on the nature of conflict situations . Therefore,

an appropriate research question to ask is:

- RQ1; What is the relationship between prior community involvement and the nature

of the conflict in cases of conflict between extractive industry MNEs and indigenous communities?

A different strand of literature draws attention to an increase in the recognition of

indigenous community rights which empowers communities to oppose MNE projects that

encroach on their territorial lands. (O’Faircheallaigh, 2013) This is believed to be one of

the reasons for an apparent paradox where, despite rising social and environmental

performance in extractive industries, MNE-community conflict is continuously increasing

in both frequency and intensity. (Hodge, 2014) This adds another layer to the discussion on

how to avoid MNE-community conflict as it puts into question whether companies’ attempts

to act more responsibly is actually having the desired effect. Currently, the literature does

not address how the rise in community autonomy might affect the solutions that are being

put forward. Therefore, the second research question asks:

- RQ2: Does community autonomy have a moderating effect on the relationship

between community involvement prior to extractive industry projects and the level of nature of the conflict?

4.3 Hypotheses

To answer these research questions, six hypotheses are developed. These hypotheses make

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4.3.1 Prior community involvement

The previous literature puts forward community involvement as the best way to prevent or

mitigate MNE-community conflicts. (Acuna, 2015, Laplante and Spears, 2008; Nish and

Bice, 2011; Harvey and Bice, 2014; Murphy and Arenas, Kemp et al. 2011; Calvano, 2008;

Benito and Gripsrud, 1992; Hodge, 2014) Involving the community prior to the project’s

implementation does not only correspond with UNDRIP’s call for free, prior and informed

consent, but also allows for communication between the parties, increasing both knowledge

and understanding, thereby reducing the perception gap and allowing issues to be brought

up before conflicts arise. (UNDRIP, 2013; Kemp et al. 2011; Banerjee, 2001) According to

Harvey and Bice (2011), one of the main motivations for involving communities in the

process, is that it increases trust. Further, it reduces the feeling of not being in control of

not being in control of one’s own destiny, which is considered one of the main causes for

conflict. (Acuna, 2015; Laplante and Spears, 2008)

In this way it is argued that community involvement acts as a way of increasing the sense

of control that community members feel over their own destiny, in turn, reducing the need

to oppose MNE actions.

For example, Kemp et al. (2011:94) argues that cooperating with the community and giving them channels to voice their concerns can “serve as ‘early warning systems’ for both companies and communities; prevent the risk of conflict escalation; and help identify

systematic issues rather than dealing with community grievances on an ad hoc basis”. Not

only does this display how involving the community can increase understanding, but they

also go on to argue how this provides a way for the community to gain a sense of control,

either through co-development of knowledge, or merely by building trust, as “The

introduction of such regulating forces may also be seen in the context of lo cal communities

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19 economies, rather than have these determined by powerful corporate entities”. (Kemp et al. 2011:94)

The first two hypotheses (H1 and H2) address the relationship between prior community

involvement and the nature of the conflict in cases of conflict between extractive industry

MNEs and indigenous communities, hypothesising that:

- H1: Higher degrees of community involvement prior to the project leads to lower

levels of violence.

- H2: Higher degrees of community involvement prior to the project leads to shorter

conflicts.

4.3.2 Community autonomy

Hypothesis 1 (H1) tests the assumption, based on previous literature, that the best way to

avoid conflict is through involving the community in the process. (e.g. Murphy and Arenas,

2010; Kemp et al. 2011; Calvano, 2008) That is to say that the degree of community

involvement changes the nature of the conflict. Another branch in the literature on

MNE-community conflict discusses the effect that MNE-community empowerment has on the frequency

and intensity of conflict. (Hodge, 2014; O’Faircheallaigh, 2013; Nelles and Alacantara,

2014) Hodge (2014) draws attention to an apparent paradox – while the social and

environmental performance of extractive industry firms is showing an upwards trend, the

number and intensity of MNE-community conflict is increasing. This paradox is explained

by an increase in the recognition of indigenous peoples’ rights. While the power distance that exists between MNEs, governments and indigenous communities have often meant

communities have very little say in extractive activities on their territorial lands, w ith

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20 when their interests collide. (Hodge, 2014; O’Faircheallaigh, 2013; Banerjee, 2001; Acuna,

2015)

On the basis of this, it is possible to argue that increasing community autonomy could in

fact lead to an escalation of conflicts, as communities can amount stronger opposition, either

through increased violence or by resisting MNE powers for longer periods, thereby dragging

out the conflict.

While involvement could be argued to lead to increased power by gaining sense of control

of the process, O’Faircheallaigh (2013) explains that autonomy does not guarantee the

community to be given more control by the firm, however, it does increase their power in a

different sense, giving them leverage to stand up against MNEs who they feel infringe on

their rights and threaten their way of life.

Therefore, it is hypothesised that:

- H3: Higher degrees of community autonomy leads to higher levels of violence.

- H4: Higher degrees of community autonomy leads to longer conflicts.

4.3.3 Moderation

While there is a consensus in the literature that involvement is necessary to create good

MNE-community relations, some raise concerns that it might be more complex than many

authors make out. Brereton (2014) and Hamann (2014) are two of the authors to question

whether firms invest enough in achieving effective involvement. Murphy and Arenas (2010)

argue that co-management will ultimately lead to less conflict, but according to Castro and

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21 and companies risk falling short. (Kemp et al. 2001; Kemp and Owen, 2013; Laplante and

Spears, 2008)

Assuming that hypothesis 1 (H1) and hypothesis 2 (H2) are supported, we can argue that

while higher levels of involvement change the nature of the conflict by lowering the level

of violence and the length of the conflict. With the challenges surrounding effective

community involvement, this effect risks being weakened when levels of autonomy are

high, since high levels of autonomy would lead to higher levels of violence, creating two

competing effects.

The example of this can be seen in Hodge’s (2014) paradox. Despite the fact the companies’

social and environmental performance is increasing, the frequency and intensity of

MNE-community conflict continues to increase. This paradox is explained by both Hodge (2014)

and O’Faircheallaigh (2013) by communities gaining increasing recognition. Therefore, it is hypothesised that:

- H5: The degree of community autonomy has a positive moderating effect on the

relationship between the degree of community involvement prior to the project and the level of violence.

- H6: The degree of community autonomy has a positive moderating effect on the

relationship between the degree of community involvement prior to the project and the length of the conflict.

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4.4 Conceptual model

The above stated hypotheses result in the following conceptual model (Figure 1):

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5. Data and method

This study takes a quantitative approach, using a cross-sectional research design to

determine the relationship between the degree of community involvement prior to an MNE’s project affecting an indigenous community, and the nature of the conflict, measured by its level of violence and the length of the conflict, as well as the moderating effect of

community autonomy on that relationship. This is done by examining the results of both

correlation analysis and multiple regression analysis. However, before running the analyses

there will be a description of the data collection process and the sample, as well as the

different variables, their measurement and a model summary.

5.2 Data collection and sample

The data was collected through a number of sources. Mostly via databases on MNE

activities affecting indigenous communities, but also with support from other sources such

as MNE public data and non-profit reports. The total sample consists of 675 cases of

community conflict. The number of cases was only restricted based on what was reasonable

for the timeline of study, and covers cases from all types of extractive industries as well as

a cases involving indigenous communities and MNEs from all over the world. T his is

believed to create greater generalisability across the population of conflict between

indigenous communities and extractive industry companies. Cases which did not include

sufficient data on the variables used in the study were excluded from the initial sample

which was gathered, resulting in the final sample of 675 cases. For the purpose of this study,

indigenous peoples are defined broadly, covering communities which are officially

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24 nations, aboriginals etc., as suggested by The UN Declaration of the Rights of Indigenous

Peoples. (UNDRIP, 2013)

The next section takes a closer look at the data in the sample and gives a description of the

dependent, independent and moderator variables and their measures, including examination

through some descriptive statistics such as frequency, distribution, standard deviation and

mean.

5.3 Variables

5.3.1 Dependent variable

The dependent variable is the nature of the conflict. This will be represented by two

variables - the length of the conflict, and the level of violence.

The length of conflict indicates how long it took to resolve the conflict, which is considered

a sign of its severity as longer conflicts tend to be more devastating for both the community

and the MNE. (Kemp et al. 2011) The length of the conflict is measured from the first

recorded instant of disagreement, until the conflict has ended, i.e. when there is an absence

of instances of disagreement, usually because the conflict has been resolved in some way.

For conflicts which are still ongoing, the length is measured up until the time of this study,

namely June 2016. The length of the conflict is then coded in three categories, short

conflicts of less than three years, medium length conflicts between three and eight years,

and long conflicts which go on for longer than 8 years.

The level of violence in the conflict is used to reflect on the nature of the conflict as it

demonstrates the intensity of the conflict. (Calvano, 2008) Here, different types of violence

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25 but do not exclusively refer to – no- to low level of violence includes peaceful protests and

negotiations; low level of violence includes court actions; medium level of violence

includes intimidation; high level of violence includes physical damage; and finally, extreme

level of violence includes kidnapping or deaths.

5.3.2 Independent variable

The independent variable used in the study is the degree of community involvement prior

to the project. As discussed in previous sections, community involvement is considered a

key success factor for good community relationships which prevent or mitigate MNE

-community conflict. (e.g. Castro and Nielsen, 2001; Nish and Bice, 2011; Frynas 2010;

Franks, 2009; Murphy and Arenas, 2010; Kemp et al. 2001) This variable’s measure

contains four different levels - no involvement, discussions with community, agreement

with the community, and involvement of the community in some degree of co-development

of the project – scoring from 0 to 3 depending on the degree of involvement. For the highest

degree of involvement- involvement of the community in co-development – the two lower

degrees of involvement, both discussions and agreement with the community is considered

a prerequisite.

5.3.3 Moderator

The moderator is the degree of community autonomy for the affected community. This

variable measures the relationship that the indigenous community has to the government,

arguing that increasing recognition of indigenous communities, associated with higher

levels of community autonomy makes communities more empowered, whereas lower levels

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26 (O'Faircheallaigh 2013; Hodge, 2014; Adamson and Pelosi, 2014). The variable ranges

across five degrees of community autonomy, from no autonomy at all, to cultural

recognition, limited recognition of rules, partial recognition of rules or right of consultation,

through to almost full- to full recognition of community rules with autonomy or right of

consent.

5.3.4 Control variables

To further determine the significance of the results in the analysis, control variables were

used at the country, firm and community level. While it is not possible to account for all

potential influencers, the control variables were chosen as they represent factors that may

further impact governance mechanisms in conflict situations.

At a country level, institutional strength will be used as a control variable as countries with

weak institutions are expected to generally provide less support to their indi genous

communities. (Calvano, 2008) For example, better regulatory frameworks would serve as

better protection for the communities that reside within the country’s borders. (Bebbington, 2009) The institutional strength was determined by calculating the average of a country’s

Worldwide Governance Indicators, provided by the World Bank. These include Voice and

Accountability, Political Stability and Absence of Violence, Government Effectiveness,

Regulatory Quality, Rule of Law, and Control of Corruption. (The World Bank, 2016)

The control variable at the firm level is the MNE’s experience with indigenous communities, measured in number of years at the start of the conflict. This variable is used

since MNEs might learn from previous experiences, making them likely to handle conflict

situations better when encountering resistance again. Benito and Gripsrud (1992) argues that

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27 considered an important aspect of good community relations management, MNE experience

is likely to have some influence.

Finally, at the community level of analysis, cultural isolation is used as a control variable.

Communities which are culturally isolated from broader ethnic groups are likely to

experience wider perception gaps, limiting understanding between the parties and thereby

making conflict situations more likely to arise. (Tang and Tang, 2001; Banerjee, 2011)

Cultural isolation is coded over three levels, where one means the community is highly

isolated, for example having their own language and not being connected to any broader

ethnic group, the second type is communities which are connected to a broader ethnic group

but are isolated within that group, and finally, the third encompasses communitie s which

can be considered to be embedded within a broader, mainstream ethnic group, thereby not

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28

5.4 Model summary

Table 1shows a summary of the model specifications used for analysis. Model 1-4, focuses

on the first dependent variable – the level of violence, whereas model 5-8 examines the

second dependent variable – the length of conflict. The analysis is completed through a

stepwise approach, starting by entering the control variables, followed by the in dependent

variable – the degree of community involvement. Next, the direct effect of the second

predictor variable – community autonomy, is tested, before finally running a moderation

analysis, incorporating all variables with community autonomy as the mod erator. The

procedure is repeated for the two dependent variables.

.

Table 1. Summary of Linear Regression Analyses

CVs DVs IV M

Institutional Strength MNE Experience Cultural Isolation Level of Violence Length of Conflict Involvement Autonomy

Model 1 x x x x Model 2 x x x x x Model 3 x x x x x Model 4 x x x x x x Model 5 x x x x Model 6 x x x x x Model 7 x x x x x Model 8 x x x x x x

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29

6. Results

To determine the results, we will investigate the different hypotheses in two main steps –

correlation analysis and multiple regression analysis. The correlation analysis will give us

initial indications on whether the different variables are related to each other and the

strength of those relationships. This is a pre-condition for continuing with the analysis. The

multiple regression will test the direction of the relationships indicated in the first step of

the analysis, as well as testing whether the degree of community autonomy has acts as a

moderator. This section will also examine some descriptive statistics and ensure that the

results are not negatively affected by multicollinearity.

6.2 Descriptive statistics

Examining some descriptive statistics will give us a better picture of the data in the sample.

First we will look at the dependent variables. The dependent variable - length of conflict -

has a mean of 2.24. With options ranging from 1 to 3 we can see somewhat of a tilt towards

the higher end, with 301 cases being longer than 8 years. The distribution between the

different levels of violence is relatively even, with no- to low levels of violence occurring

180 times in the sample of 675 cases. The remaining levels have a frequency between 114

and 131. This is also seen through a mean of 2.79.

For the moderator variable, the different degrees of community autonomy that are observed

in the sample each have a frequency between 89 and 171, with the middle level – limited

recognition of rules – being the most frequent observation. With a mean of 3.18, the

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30 Next, the descriptive statistics show that out of the 675 cases of MNE-community conflict there was a total of 412 cases where there was no prior community involvement for the

project, with a steep, continuous drop between the different levels and a no more than 32

out of the 675 cases scoring at the highest level, indicating that the community was involved

in some form of co-development of the project. This is reflected by a mean of .57. This is

not too surprising. Research is showing that companies in the extractive industries are

increasing their social and environmental performance, putting more emphasis on

community relationship management, but they still have a long way to go. (Hodge, 2014)

However, it should be noted that the sample only includes cases where conflict has occurred,

therefore not accounting for the degree of prior involvement which was implemented in

cases where MNEs operated successfully in a region with indigenous people without

spurring MNE-community conflict.

All variables display a standard deviation below 1.5, except MNE experience which has a

standard deviation of 24.184. This is due to the nature of the variable which is measured in

number of years, rather than being split into categories.

Means and standard deviations can be seen in table 3.

6.3 Multicollinearity and correlation analysis

When two or more predictor variables in a model are correlated, there is a risk of

multicollinearity. This can significantly impact the results of the analysis by decreasing the

reliability of the results. Field (2009) suggests two approaches for detecting

multicollinearity. The first step is checking the correlation between the variables – if the

correlation between two variables is higher than 0.8, this could indicate multicollinearity.

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31 using the Variance Inflation Factor (VIF). Field (2009) argues that for VIF values under 10,

with a tolerance level above 0.2, multicollinearity is not likely to occur. As presented in

table 2,the variables in the models are within these thresholds and therefore do not display

any signs of multicollinearity.

The next step looks at the relationship between the different variables is through a

correlation analysis. A correlation analysis will determine the strength of the relationship

between all the variables - the degree of autonomy, the total level of community

involvement, the level of violence, the length of the conflict, the institutional strength, the

degree of cultural community isolation, and MNE experience, using Pearson correlation

coefficients. Preliminary analyses were performed to ensure that no violation of the

assumptions of normality, linearity and homoscedasticity occurred.

First of all, the two dependent variables - the level of violence and the length of conflict -

are significantly correlated at r = .231, p < .01, showing that high levels of violence are

associated with longer conflicts. The results show a weak, negative correlation between the

degree of involvement and the level of violence, at r = -.098, p < .05, with high levels of

involvement being associated with low levels of violence. Next, the correlation analysis

reveals a small, positive correlation between community autonomy and the level of

violence, at r = .109, p < .01, with high levels of autonomy being associated with high levels

Table 2. Multicollinearity Statistics

Tolerance VIF Level of Involvement .949 1.054 Degree of Autonomy .875 1.143 Institutional Strength .829 1.207 MNE Experience .941 1.063 Cultural Isolation .932 1.073

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32 of violence. There is no significant correlation between the length of conflict and either of

the predictor variables – the level of involvement and the degree of autonomy.

Finally, there is a small, positive correlation between community autonomy and the degree

of involvement, at r = .128, p < .01, which means that there is an association between high

levels of autonomy and high levels of involvement in the sample.

Looking at the control variables the highest observed correlation occurs between the length

of conflict and institutional strength, with a significant negative correlation of r = -.347, p

< .01, followed by the correlation between the level of violence and institutional strength,

with a significant negative correlation of r = -.284, p < .01. This means that when the

institutional strength is high, both the level of violence in the conflict and the length of the

conflict is low. Meanwhile, for countries with low institutional strength, both length and the

level of violence in the conflict is greater. Institutional strength also has a relatively high,

significant positive correlation with the degree of community autonomy, at r = .311 p < .01,

indicating that communities in countries with strong institutions have higher a utonomy. The

rest of the control variables – MNE experience and cultural isolation display weak

correlation within the -2 < p > 2 threshold. (Hayes, 2013)

While all of the relationships between the dependent variable, independent variable and

moderator can be considered as weak, or even non-significant in the case of the dependent

variable length of conflict, the size of sample means that they still reach statistical

significance, which allows us to continue with the analysis. (Pallant, 2010) The information

is summarised in a correlations matrix below (Table 3), including means and standard

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33 Correlation of course, does not necessarily mean causation. While it gives us an indication

of the strength of the relationships, it does not inform us about their nature or direction. To

test this, we need to use regression analysis.

6.4 Regression analyses

As stated above, to determine whether the hypotheses are supported or not we need to use

a regression analysis. The description of the results will address one hypothesis at the time,

following the order described in the model specification from the method section (Table 1),

followed by a look at the effect of the different predictor variables in comparison with the

control variables.

6.4.1 Level of violence

Addressing our first hypothesis (H1), Model 2 tests the relationship between the degree of

community involvement and the level of violence, hypothesizing that higher degrees of

community involvement prior to the project leads to lower levels of viol ence. The results

show that on its own as a predictor, the degree of involvement does not have a significant Table 3. Means, Standard Deviations and Correlations

Variable Mean Std. Deviation 1 2 3 4 5 6 7

1. Level of Violence 2.79 1.448 -2. Length of Conflict 2.24 .776 .231** -3. Level of Involvement .57 .841 -.098* -.059 -4. Degree of Autonomy 3.18 1.312 .109** -.019 .128** -5. Institutional Strenght 3.576 1.388 .284** .347** .188** .311** -6. MNE experience 15.99 24.184 -.155** -.168** .117** .084* .191** -7. Cultural Isolation 1.99 .673 -.166** -.094* -.034 -.103** .157** .141**

-*Correlation is significant at the 0.05 level (2-tailed) ** Correlation is significant at the 0.01 level (2-tailed)

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34 relationship with the level of violence, as b = -.080, p = .217. As such, hypothesis 1 (H1)

does not appear to be supported.

For Model 3, which tests the relationship between the degree of community autonomy and

the level of violence in the conflict for hypothesis 3 (H3) - higher degrees of community

autonomy leads to higher levels of violence - the findings show that autonomy is a

significant predictor of violence, as b = .229, p < .001. From this we can establish that for

every 1 unit increase in the degree of community autonomy, we get a .229 unit increase in

violence. Therefore, hypothesis 3 (H3) is supported. Model 3 also displays an adjusted R2

of .136, meaning that the model, including control variables, accounts for 13.2% of the

variance in the level of violence. As such, as a predictor of the level of violence, the degree

of community autonomy only contributes to 3.8% of the variance (R2 chan ge = 0.038).

Turning to the third, and final hypothesis for the degree of violence (H5), testing the

potential moderating effect of the degree of autonomy on the relationship between the

degree of involvement and the level of violence, the variables for au tonomy and

involvement were mean-centered to compute an interaction term before running Model 4.

The interaction shows a positive moderation effect, as b = .218. This effect is significant at

p < .001 and accounts for 6.4% (RQ2change= .064) of the variance in the level of violence.

The overall model explains 16.1% (adjusted R2 = .161). This supports hypothesis 5 (H5) -

the degree of community autonomy has a positive moderating effect on the relationship

between the degree of community involvement prior to the project and the level of violence.

Interestingly, when introducing the interaction effect, the relationship between the

independent variable, community involvement, and the dependent variable, the level of

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35 To get a better picture of how the interaction works, we can examine the conditional effect

of the degree of involvement on the level of violence at different values of the degree of

autonomy (Table 5). This shows that for low levels of community autonomy b = -.361, p <

.001. This means that for low levels of community autonomy, every 1 unit of invol vement

gives us a .361 decrease in violence. For average levels of community autonomy, we get b

= -.076, p = .227. Thus, at average levels of community autonomy, the relationship between

the degree of prior community involvement and the level of violence is not significant –

which corresponds with the results achieved in Model 2. Finally, for high levels of

community autonomy, the relationship becomes significant again at b = .210, p < .05.

However, these results indicate that the nature of the relationship changes so that at high

levels of community autonomy, high degrees of involvement leads to higher levels of

violence. Therefore, H1 gets conditional support. This is explained by the fact that the

positive moderation makes so that the higher the degree of autonomy the more positive the

effect of the degree of involvement on the level of violence. In other words, because the

relationship between involvement and violence is negative, and the relationship between

autonomy and violence is positive, and the degree of autonomy acts as a moderator,

community autonomy cancels out the negative effect of community involvement.

When viewing the results, it should be kept in mind that the effects cannot be compared to

each other based on their b-value, as, for example, 1 unit of community involvement cannot

be considered equal to 1 unit of community autonomy since these represent different

measures. Therefore, table 4 also reports on the variables’ beta values which are

standardised coefficients. This shows that the effect of all control variables – institutional

strength, MNE experience, and cultural isolation – reach statistical significance in all

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36 highest beta value in all models except Model 4, where both the effect of community

involvement (beta = -.446) and the interaction effect (beta = .455) is higher.

6.4.2 Length of conflict

Moving on to the second dependent variable – the length of conflict – the first hypothesis

(H2) states that higher degrees of community involvement prior to the project leads to

shorter conflicts. The results from Model 6 show that b = .012, p = .726, indicating that the

relationship between the degree of community involvement and the length of the conflict is

not significant, therefore, we reject hypothesis 2 (H2). This is further strengthened by the

fact that, while the overall model accounts for 12.7% of the variance in the length of conflict

(adjusted R2 = .127), the degree of community involvement contributes with 0% (R2 change

= .000).

Model 7 tests hypothesis 4 (H4) – that higher degrees of community autonomy leads to

longer conflicts. Here, b = .059, p < .01, which means that the relationship is significant

and for every 1 unit increase in the degree of community autonomy, we get a . 059 unit

increase in the length of conflict. The degree of community involvement accounts for 0.9%

of the variance in the length of the conflict (R2 change = .009), out of 13.5% which is

explained by the model in total (adjusted R2 = .135). Consequently, hypothesis 4 (H4) is

supported.

The final hypothesis (H6) states that the degree of community autonomy has a positive

moderating effect on the relationship between the degree of community involvement prior

to the project and the length of the conflict. This relationship is tested in Model 8. The

results show that neither the interaction (b = .018, p = .590), nor the relationship between

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37 overall model accounts for 13.3% of the variance in the length of conflict (adjusted R2 =

.133), the interaction accounts for only 0.09% (R2 change = .009), which is not enough to

reach significance. Therefore, hypothesis 6 (H6) is rejected – community autonomy does

not have a moderating effect on the relationship between the degree of community

involvement and the length of the conflict.

Further, comparing the beta values for the models relating to the dependent variable length

of conflict, we can see that both the effect of institutional strength and MNE experience

reach statistical significance, with institutional strength being the stronge st predictor in all

models (Model 5-8), with beta values ranging from -.322 to -.358.

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38 Tab le 4. Li ne ar R egr es sion A nal ys is Re su lts De pe nd en t Vi ol en ce Le ng th Con trol s H1 H3 H5 Con trol s H2 H4 H6 M ode l 1 M ode l 2 M ode l 3 M ode l 4 M ode l 5 M ode l 6 M ode l 7 M ode l 8 B be ta sig B be ta sig B be ta sig B be ta sig B be ta sig B be ta sig B be ta sig B be ta sig Con trol Ins tit ut ion al St re ng th -.260 -.249 .000 -.251 -.241 .000 -.331 -.317 .000 -.329 -.315 .000 -.180 -.322 .000 -.182 -.325 .000 -.198 -.355 .000 -.200 -.358 .000 M NE E xpe rie nc e -.005 -.091 .015 -.005 -.087 .021 -.006 -.006 .007 -.005 -.090 .013 -.003 -.102 .006 -.003 -.103 .005 -.003 -.106 .004 -.003 -.106 .004 Cul tur al Isol ati on -.245 -.114 .002 -.253 -.075 .002 -.173 -.173 .030 -.161 -.075 .042 -.033 -.028 .433 -.032 -.028 .455 -.014 -.013 .736 -.012 -.011 .777 In de pe nd en t Com mun ity Invol ve me nt -.080 -.046 .217 -.768 -.446 .000 .012 .013 .726 -.049 -.053 .590 M od er at or Com mun ity Aut on om y .229 .207 .000 .059 .099 .010 In te rac tion Invol ve me nt x A ut on om y .218 .445 .000 .018 .069 .509 Con sta nt 4. 297 4. 322 3. 689 4. 029 2. 998 2. 994 2. 841 2,867 R .322 .325 .376 .410 .363 .363 .375 .375 R2 .104 .106 .142 .168 .132 .132 .140 .141 Adj us ted R2 .100 .101 .136 .161 .128 .127 .135 .133 R2 ch an ge .104 .002 .038 .064 .132 .000 .009 .009

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39

Table 5. Conditional Effect at Different Levels of the Variable – DV: Level of Violence

Community Autonomy B sig.

Low -.361 .000

Average -.076 .227

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40

7. Discussion

This study examines how prior community involvement and community autonomy affect

the nature of conflicts between MNEs in the extractive industries and indigenous

communities in the areas they operate in. This section will provide a discussion of the

findings from the analyses above, in relation to the theories discussed in the literature

review, answering the research questions proposed described earlier, as well as the study’s

theoretical and practical contributions, limitations, and suggestions for further research.

7.2 Findings

Starting with the first research question (RQ1) - what is the relationship between prior

community involvement and the nature of the conflict in cases of conflict between

extractive industry MNEs and indigenous communities? The literature considers the

involvement of indigenous communities prior to the implementation of a project as a good

way of preventing or reducing MNE-community conflict because it addresses one of the

main underlying reason for such conflicts and a driver for resorting to violence, namely, the feeling of lack of control over one’s own life and destiny. (Acuna, 2015; Laplante and Spears, 2008) Involvement is also argued to allow for increased knowledge and

understanding between the different parties, making the perception gap that exists

between them smaller, facilitating better relationships. (Nish and Bice, 2011; Banerjee,

2001) Further, dialogue can provide early warning signs of conflict, allowing preventive

measures, rather than reacting to issues as they arise, whereby significant damage might

already have been caused. (Kemp et al. 2011) However, when testing the relationship

between the degree of prior community involvement and the level of violence and the

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41 prior to the project leads to lower levels of violence in the conflict, and that (H2) – higher

degrees of community involvement prior to the project leads to shorter conflicts – neither

is supported as the effects fail to reach statistical significance. Clearly, here the data fails

to provide statistical evidence that, as suggested in previous studies, prior community

involvement works as a method for limiting MNE-community conflict.

Looking at the descriptive statistics, the most notable result is the uneven distribution for

the degree of community involvement. Out of the 675 cases of MNE -community conflict

there was a total of 412 cases where there was no prior community involvement for the

project, with a steep drop between the different levels and only 32 out of the 675 cases

scored at the highest level, indicating that the community was involved in some form of

co-management. This could be a sign that, as suggested by the likes of Kemp and Owen

(2013), and Laplante and Spears (2008), MNEs still have a long way to go in terms of

community management practices. Although, here it is also worth mentioning that the

sample only includes cases where some sort of conflict has occurred. This means that the

results do not account for the potential cases where MNEs have operated projects

successfully without attracting conflict with the community, which could negatively affect

the results.

However, to fully answer the first research question (RQ1), we must also explore the

second research question (RQ2) - Does community autonomy have a moderating effect on

the relationship between community involvement prior to extractive industry projects and

the level of violence in the conflict?

First, hypothesis 3 and 4 looks at the direct effect of community autonomy on the intensity

of the conflict. H3 argues that higher degrees of community autonomy lead to higher levels

of violence, while H4 argues that higher degrees of community autonomy lead to longer

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42 O'Faircheallaigh (2013), states that increasing recognition of indigenous communities

empowers them to stand up again MNEs imposing on their territorial lands, thereby

intensifying conflicts. While the results show support for both hypotheses, community

autonomy is shown to be stronger predictor of the level of violence than the length of the

conflict.

Hypothesis 5 and 6 address the potentially moderating effect of community autonomy on

the relationship between the degree of prior community involvement and the nature of the

conflict. H6, hypothesising that community autonomy has a positive moderating effect on

the relationship between community involvement and the length of conflict, is rejected. This

confirms the previous result that there is no significant relationship between community

involvement and the length of conflict. H5 however, hypothesising that community

autonomy has a positive moderating effect on the relationship between community

involvement and the level of violence, is supported – both that community autonomy acts

as a moderator, and that the moderation effect is positive. This answers the second research

question (RQ2).

To fully understand this relationship, we looked at the conditional effect of the degree of

involvement on the level of violence at different values of the degree of community

autonomy. First of all, we can see that only at average levels of community autonomy, the

relationship between community involvement and the level of violence is non-significant.

In fact, at low levels of community autonomy, H1 is supported so that higher degrees of

prior community involvement lead to lower levels of violence. In other words, for

communities with no or limited autonomy, there is evidence that involving the community

prior to the project will make the conflict less intense, thereby confirming the method

proposed in previous literature. As the degree of autonomy rises, this relationship is cancel

MNE and indigenous community conflict: prior community involvement and community autonomy as predictors of the nature of conflict