Social ambidexterity and firm performance in emerging markets

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SOCIAL AMBIDEXTERITY AND FIRM

PERFORMANCE IN EMERGING MARKETS

MSc Business Administration – International Management

Faculty of Economics and Business

Name: Danielle van der Linden

Student number: 11430923

Date of submission: 22nd of June 2017

Supervisor: dr. C.V. (Carsten) Gelhard

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Statement of originality

This document is written by Student Danielle van der Linden 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 or completion of the work, not for the contents.

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Acknowledgments

First, I would like to thank my supervisor dr. Carsten Gelhard for his critical feedback and

interesting discussions during the thesis process. His supervision helped me to get the most

out of myself in the final part of my study, where I am very grateful for.

The thesis topic, as well the process, were challenging for me, and definitely not the easiest

choice I could have made of writing my Master thesis. Corresponding with my time in

college, in which the easiest way has never been my preferred choice. Therefore, there are

two persons who I would like to thank for their unconditional support in the past six years.

My parents, Arie and Andrea, have always been concerned with my study progress and

personal development. Therefore, I would like to thank my parents for their mental support,

enabling me with opportunities to pursue my ambitions, and relaxing moments when I came

home.

Special thanks to Erik for his faith in me, support, and patience in the past year. Moreover, I

would like to thank Erik for handling my chaotic moments. He said he enjoyed, but I still

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Abstract

The purpose of this research is deepen the understanding of corporate social responsibility of

corporations established in emerging markets (EM-MNEs). Specifically, exploring the

rationales behind EM-MNEs’ engagement in social initiatives. The balance between moral

and instrumental initiatives is labeled in this research as ‘social ambidexterity’. This research investigates to what extent social ambidexterity affects social and financial performance,

contingent on emerging markets. By doing this, a new perspective of ambidexterity is

explored in this research. A multiple hierarchical regression analysis and a multi group level

analysis are used to test the hypotheses. The results of the analyses show that social

ambidexterity positively affects corporate social performance. The results do not show that

social ambidexterity has an impact on corporate financial performance. Furthermore,

emerging markets do not weaken or strengthen the relation between social ambidexterity and

corporate social performance. The overall objective of this research is to empirically

investigate if the rationales behind a social initiative have an impact on firm performance,

and if so, is this strengthened or weakened by emerging markets.

Key words: • ambidexterity • rationales • social initiatives • emerging markets • corporate

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1. Introduction

In recent years, the increase of corporate scandals has drawn internal and external

pressures on corporations established in emerging markets (Marten et al., 2015), for instance,

the milk scandal in China. Milk suppliers were adding melamine to boost the protein readings

of their milk, which affected thousands of children who became sick of this incident. This

corporate scandal increased the awareness of customers, employees, and government (Jia et

al., 2012). In the literature of international management, researchers advocate deepening the

understanding of corporate social responsibility (CSR) in emerging markets (Li et al., 2010).

Extensive research has been conducted on CSR in developed markets, however, a lack of

understanding exists about CSR in emerging markets (Li et al., 2010). CSR is defined as “the

firm’s consideration of, and response to, issues beyond the narrow economic, technical, and legal requirements of the firm to accomplish social and environmental benefits along with the

traditional economic gains which the firm seeks” (Aguilera et al., 2007, p.837). In other

words, CSR advocates social issues in which the corporation engages, beyond the economic,

technical, and legal requirements.

1.1. Research Problem

Despite the drastic increase of social issues in emerging markets, the literature lacks

empirical investigations on rationales of corporations established in emerging markets in

order to engage in social initiatives (Alon et al., 2010). Hahn et al. (2016) argue that

corporations face two rationales to engage in social initiatives; the moral and instrumental

rationale. The moral rationale is concerned with ethical standards, meaningful existence, and

moral principles (Aguilera et al., 2007). The instrumental rationale states that corporations

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rationales contribute to firm performance, however, they are fundamentally different (Hahn et

al., 2016). Hahn et al. (2016) labeled the balance between moral and instrumental rationales

‘ambidexterity’. The ability to balance moral and instrumental initiatives leads to a higher level of corporate social performance (CSP) (Hahn et al., 2016). Ambidexterity is a widely

investigated topic in the literature of strategic management, and is defined as “a firm’s ability

to simultaneously balance different activities in a trade-off situation” (Rothaermel &

Alexandre, 2009, p. 759). The literature discusses different perspectives of ambidexterity:

organizational ambidexterity, structural ambidexterity, and contextual ambidexterity (Gibson

& Birkinshaw, 2004). Different authors argue that ambidextrous corporations obtain optimal

financial performance (Uotila et al., 2009). This research investigates an understudied

perspective of ambidexterity, namely: the balance between moral and instrumental rationales

in social initiatives. In this research, this perspective of ambidexterity is referred to as ‘social ambidexterity’. The research of Hahn et al. (2016) proposes that there is a positive relationship between ambidexterity and corporate social performance. However, their

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1.2. Research Goal and Question

This research empirically investigates the proposition of Hahn et al. (2016) and fills in

the gap in the literature about the influence of ambidexterity on social performance. Other

perspectives of ambidexterity lead to optimal financial performance (Uotila et al., 2009). This

research investigates if this new perspective of ambidexterity, social ambidexterity, also leads

to financial performance. Furthermore, this research fulfills the requirement of deepening the

understanding of CSR in emerging markets, and the gap in the literature about the rationales

EM-MNEs face in order to engage in social initiatives. MNEs established in emerging

markets refer to EM-MNEs, and are defined as “international companies that originated from

emerging markets and are engaged in outward firm direct investment, where they exercise

effective control and undertake value-adding activities in one or more foreign countries” (Luo

& Tung, 2007, p. 482).

Therefore, the goal of this research is to empirically investigate the relationship

between social ambidexterity and CSP, and social ambidexterity and corporate financial

performance (CFP). Furthermore, the goal of this research is to explore if EM-MNEs weaken

or strengthen those relations. Based on the research goals, the following research question

arises:

‘To what extent does social ambidexterity affect social and financial performance, contingent on emerging markets?’

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1.3. Relevance

Scientifically, this research is highly relevant for the literature of international

management, and contributes to the understanding of CSR in emerging markets. The lack of

understanding about EM-MNEs’ rationales of engagement in social initiatives is covered in

this research. Moreover, this research contributes to the literature of strategic management.

By exploring the outcomes of a new perspective of ambidexterity, social ambidexterity, this

research extends the literature of ambidexterity.

This research is practically relevant for business executives dealing with investment

decisions for social initiatives. The results of this research can help business executives to

improve CSP and CFP. Furthermore, business executives of EM-MNEs can use the results of

this research to estimate the role of emerging markets in investment decisions of social

initiatives.

1.4. Structure of the Thesis

The thesis is structured as follows. First, a literature review provides detailed

background of the variables included in this research. Second, the hypotheses are provided,

corresponding with the conceptual model. After that, the method is described, which includes

the research sample, data collection for each variable separately, and the research design

adopted in this research. Fourth, the results of the quantitative data analysis are discussed.

Fifth, the discussion part includes an interpretation of the results, limitations of the research,

managerial implications, and future research implications. The last part of this research

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2. Literature Review

Corporations deal with two major concerns to survive in this social complex world:

CSP and CFP (Griffin & Mahon, 1997). The important role of multinational enterprises

(MNEs) in the process of global diffusion of corporate CSR practices has received

compelling evidence in the literature of international management (Fernandez-Feijoo et al.,

2014). Increasing internal and external pressure arising from institutional complexity, force

MNEs to engage in CSR practices (Aguilera et al., 2007). Institutional complexity refers to

“the multiplicity and heterogeneity of CSR institutional forces to which MNEs are exposed” (Greenwood et al., 2011, p. 318). This implies that MNEs operate in a complex environment,

and deal with multiple and conflicting institutional forces (Fernandez-Feijoo et al., 2014).

MNEs are embedded in systems, varying from country to country (Williams & Aguilera,

2008). In those different systems, MNEs deal with different rationales in order to engage in

social initiatives (Aguilera et al., 2007). Extensive research has been conducted on CSR in

developed countries. However, the literature provides little evidence for CSR in emerging

countries (Li et al., 2010). In this section, a literature review of the following topics is

discussed. First, the debate in the literature about the outcome of CSR on corporate social

performance is discussed. Second, the outcome of CSR on corporate financial performance

as discussed in prior research is considered. Third, the rationales of corporations behind

engagement in social initiatives are evaluated. After that, the concept of ambidexterity, and

social ambidexterity as a new perspective of ambidexterity are discussed. Lastly, the role of

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2.1. Corporate Social Performance

Corporate Social Performance (CSP) is integrated into the literature of CSR, and has

been a topic of academic study for several decades (Wood, 1991). A major concern of firm

performance is CSP (Griffin & Mahon, 1997). However, CSP is a poorly examined topic in

the literature of international management. A reason for this limitation is a lack of a shared

definition (Zhang et al., 2014). Another reason is that ‘the CSP domain has remained

controversial, fluid, ambiguous and difficult to research’ (Wood, 2010, p. 50). The ambiguity

is found in the different definitions offered in the literature, which can be classified in two

different approaches. The first approach treats CSP as a multidimensional construct. On the

one hand, CSP is a multidimensional construct because it has to conform with multiple

responsibilities such as economic, legal, ethical, and discretionary responsibilities (Carroll,

1979). On the other hand, CSP is a multidimensional construct because it encompasses the

principles of the corporation, it observes practices and outcomes, and it responses to rising

social issues (Wood, 1991). The second approach casts CSP as a function of how

stakeholders demands are met (Post et al., 2002).

Wood (1991, 2010) offered two different definitions for CSP. He defined CSP as “a business organization’s configuration of principles of social responsibility, processes of social responsiveness, and policies, programs, and observable outcomes as they relate to the firm’s social relationships” (Wood, 1991, p. 693). The key element of this definition is the multidimensional construct of CSP, applicable on the first approach. An extensive stream of

research has led to a second definition offered by Wood (2010), about 19 years later, where

he defined CSP as “the business activity, focusing on the impacts and outcomes for society,

stakeholders and the firm” (Wood, 2010, p. 54). This definition is applicable to the second

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demands. This research uses the second definition offered by Wood (2010) and treats CSP as

a concept responding to demands arriving from society, stakeholders, and the firm.

Even though the literature shows that there is no shared definition of CSP, many

authors agree about three important components of CSP; legitimacy, stakeholder

management, and social issues (Dowling & Pfeffer, 1975; Stanwick & Stanwick, 1998).

Legitimacy is defined as “the appraisal of action in terms of shared or common values in the

context of the involvement of the action in the social system” (Parsons, 1960, p.175).

Organizational legitimacy is the outcome of actions that affects the norms and values of other

groups and organizations. corporate survival depends on existence, continuity, and growth.

Therefore, corporations are pressured by changes in environmental norms and values

(Dowling & Pfeffer, 1975). The second component of CSP is stakeholder management.

Primary stakeholder groups are investors, employees, customers, and suppliers (Hillman &

Keim, 2001). Primary stakeholders are defined as those who ‘bear some form of risk as a result of having invested some form of capital, human or financial, something of value, in a

firm’ (Clarkson, 1995, p. 5). Another group of stakeholder management deals with the legal responsibility to the government or the law (Hillman & Keim, 2001). This group is called the

public stakeholders of the firm, and is defined as “the governments and communities that

provide infrastructures and markets, whose laws and regulations must be obeyed, and to

whom taxes and other obligations may be due” (Clarkson, 1995, p.106). Stakeholder

management is an important component of CSP, because ‘the survival and continuing

profitability of the corporation depends upon its ability to fulfill its economic and social

purpose, which is to create and distribute wealth or value sufficient to ensure that each

primary stakeholder group continues as part of the corporation’s stakeholder system’ (Clarkson, 1995, p.107). The third component of CSP is social issue participation, which

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primary stakeholders. Examples of participation in social issues are to avoid nuclear energy,

refuse to sell to the military, and not engage in the tobacco industry (Hillman & Keim, 2001).

Hillman & Keim (2001) argue that investments in social issue participation does not have the

same outcome as investments in primary stakeholder relations. Investing corporate capital in

primary stakeholder relations creates shareholder value. However, investments in social issue

participation is negatively related to shareholder value creation (Hillman & Keim, 2001).

In the past 30 years, CSP has been a widely investigated topic in the literature of

international management. However, no consensus is yet achieved about the relation between

CSR and CSP (de Bakker et al., 2005). In many articles, CSR is explained by the inclusion of

CSP principles (Wood, 1991; van Beurden & Gössling, 2008). Other authors argue that CSP

is an outcome of CSR practices. For the latter, there is a lack of empirical evidence

(McWilliams & Siegel, 2000). This means that the relation between CSR and CSP is not

substantiated in the literature.

2.2. Corporate Financial Performance

Nowadays, corporations’ interest is not only to maximize profit. Successful

corporations also work for a better society at large (Shaheer et al., 2015). Successful

corporations need a healthy society, and a healthy society needs successful corporations

(Porter & Kramer, 2006). Since the 60’s, the relation between CSR and CFP is widely investigated (Cochran & Wood, 1984). However, the literature lacks consensus about the

relation between CSR and CFP. Some authors argue that CSR is negatively related to CFP

(Bragdon & Marlin, 1985; Vance, 1975; Friedman, 1970), while other authors argue that

CSR and CFP are positively related to each other (McGuire et al., 1988; Raza et al., 2012).

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state that the additional costs involved with CSR practices have a negative impact on CFP.

Friedman (1970) argues that the only responsibility of a corporation is to maximize profit. He

states that the corporate executive, the employee of the business owner, has responsibilities

towards stockholders, employees, and the business owner. The corporate executive is an

agent serving the interests of his principal. If he would spend money on social issues, he

would spend the money of his primary stakeholders. Therefore, Friedman (1970) states that

CSR and CFP are negatively related. Other authors argued that CSR is negatively related to

CFP, because high responsibility results in additional costs. Those additional costs put a

corporation in an economic disadvantage, compared with corporations that are less

responsible (Bragdon & Marlin, 1985; Vance, 1975). Additional costs involved with CSR

result from social initiatives, for instance: charitable contributions, establishing

environmental production procedures, and maintaining plants in economically depressed

locations (Bragdon & Marlin, 1985; Vance, 1975). The other group of authors, arguing that

CSR and CFP are positively related, state that CSR improves reputation and goodwill of a

corporation (McGuire et al., 1988). Moreover, social initiatives may improve a corporation’s

standing with important constituencies such as bankers, investors, and government officials

(McGuire et al., 1988). Therefore, those authors argue that economic benefit raises from

social initiatives.

In order to maximize profit, the question asked by corporate executives is ‘does it pay to be good?’ Over the last 40 years, more than 100 studies are completed about the relation

between CSR and CFP. The overall finding is slightly positive, which means that a

corporations’ engagement in social initiatives and CFP are positive related in most of the studies.

Margolis et al. (2007) investigated the empirical link between CSP and CFP of 167

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this is an ongoing debate in the literature (Margolis et al., 2007), and will not be discussed in

this research.

2.3. Social Ambidexterity

Corporations consider different rationales to engage in social initiatives. A social

initiative in the business context is defined as “any program, practice, or policy undertaken by

a business firm to benefit society” (Simcic Bronn & Vidaver –Cohen, 2009, p. 92).

Porter & Kramer (2006) argued that corporations face four rationales to engage in

social initiatives; moral obligations, sustainability, the license to operate, and reputation. The

moral appeal states that corporations ‘achieve commercial success in ways that honor ethical values and respect people, communities, and the natural environment’ (Porter & Kramer, 2006, p. 81). The sustainability rationale states that corporations meet their needs, without

abusing future generations to meet their needs. The third rationale offered by Porter &

Kramer (2006), license to operate, states that every corporation needs permission from

communities, governments, and other stakeholders to do business. The last rationale,

reputation, refers to the justification of business practices. Reputation is used to improve the

corporations’ brand image, and increase goodwill (Porter & Kramer, 2006). Porter & Kramer (2006) argued that business and society need each other to be successful. On the one hand,

health care, education, and equal opportunities are necessary conditions in a society for a

successful corporation. On the other hand, social conditions, the creation of jobs, and

innovation for improved living standards are conditions of a corporation that are necessary

for a successful society (Porter & Kramer 2006). The mutual dependence, and integration of

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choices of a corporation must benefit both sides in order to be successful, as well business as

society (Porter & Kramer, 2006).

Aguilera et al. (2007) argued that corporations face three rationales to engage in social

initiatives; relational, moral, and instrumental. The relational rationale states that the

corporation is concerned with relationships among group members (Aguilera et al., 2007).

The moral and instrumental rationales of Aguilera et al. (2007) correspond with the two

rationales described by Hahn et al. (2016), which are moral and instrumental as well. The

moral rationale is concerned with ethical standards, meaningful existence, and moral

principles. The concern in this rationale is what one sees as ethically appropriate (Aguilera et

al., 2007). Corporations following the moral rationale in social initiatives, are pursuing to solve social problems by ‘doing the right thing’ (Hahn et al., 2016). The instrumental rationale is described as a self-interest driven rationale. Control seeking can maximize the

favorability of outcomes. Therefore, corporations with an instrumental rationale are

motivated to seek control by engagement in social initiatives (Aguilera et al., 2007).

Corporations are extrinsically driven to engage in social initiatives, and will only address

social problems when they are economic driven (Hahn et al., 2016). The article of Aguilera et

al. (2007) provided a multilevel theoretical model for the rationales of engagement in social

initiatives. This model considers CSR rationales on the individual, organizational, national,

and transnational level. Hahn et al (2016) collaborated on the organizational level of analysis,

-and investigated the ambidextrous ability of moral and instrumental initiatives. Table 1

shows an overview of the authors discussed above, providing different rationales of social

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Table 1

Rationales for social initiatives

Rationale/Author Porter & Kramer (2006)

Aguilera et al. (2007)

Hahn et al. (2016)

1. Moral obligation Moral Moral

2. Sustainability Instrumental Instrumental

3. License to

operate

Relational

4. Reputation

Hahn et al. (2016) argued that the ambidextrous ability of rationales to engage in

social initiatives leads to superior firm performance. The ambidextrous ability refers to the

balance between moral and instrumental rationales. Moral and instrumental rationales both

contribute to firm performance. However, their foundations are fundamentally different

(Hahn et al., 2016). The article of Hahn et al. (2016) described six dimensions on which an

initiative can be classified, in order to measure the level of ambidexterity. i.e. the balance

between moral and instrumental rationales.

The first dimension that classifies moral and instrumental initiatives is moral versus

commercial logic. Moral logic is used as an end in the corporation itself, while commercial

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with a moral logic, might gain strategic relevance over time (Porter & Kramer, 2006). While

commercial logic can generate social benefits for stakeholders (Hahn et al., 2016).

Second, initiatives contain a moral justification when they ensure the moral adequacy in the

light of salient normative stakeholder demands and values. Initiatives with a business case

justification align their activities with business objectives (Hahn et al., 2016).

Central for the third dimension is the ability of the corporation to have a dialogue with a wide

range of stakeholders (Elkington, 1997). Through stakeholder dialogues, the value created

with the initiative is attributable for the wider society, instead of only private interests

(Rodrigue et al., 2013). Initiatives with a moral rationale contain stakeholder engagement in

organizational skills. While initiatives with an instrumental rationale pursue strategic issue

identification and functional integration in organizational skills. The moral rationale

integrates stakeholder engagement in the core business practices of the corporation, which

means that stakeholder engagement is an important factor for production, marketing,

accounting, and product development (Judge & Douglas, 1998). The fourth dimension

classifies an initiative in an intrinsic or extrinsic driver. The moral rationale of social initiatives is based on the moral conviction ‘to do the right thing’, and is intrinsically found in the corporation. While an instrumental rationale is an extrinsic driver, with an economic

incentive (Hahn et al., 2016). The fifth dimension that classifies moral and instrumental initiatives, is the time frame of the initiative. The moral approach ‘emphasizes the long-term nature of the benefit that business is expected to provide to society (Schwartz & Caroll, 2008,

p.163). In contrast with the instrumental approach, where initiatives result in short-term

business benefits (Porter & Kramer, 2011). Finally, the last dimension that classifies moral

and instrumental initiatives is based on moral issues versus strategic issues, referring to the

types of social issues the corporation addresses (Hahn et al., 2016). Table 2 shows the six

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Table 2

Classification Incentives Moral and Instrumental Rationales (Hahn et al., 2016)

The literature of strategic management shows that ambidexterity is a widely

investigated topic for the past 30 years (Raisch & Birkinshaw, 2008). Duncan (1976) was the

first to use this term, and described it as the trade-off between conflicting demands by putting

in place dual structures. The simple idea behind ambidexterity is that ‘the demands on an organization in its task environment are always to some degree in conflict, so there are

always trade-offs to be made’ (Gibson & Birkinshaw, 2004, p. 209). Extensive research has

led to different perspectives of ambidexterity; organizational ambidexterity, structural

ambidexterity, and contextual ambidexterity. Organizational ambidexterity considers the

balance between knowledge exploration and knowledge exploitation. Business groups

focusing on the trade-off between alignment and adaption, deal with structural ambidexterity.

While contextual ambidexterity arises from features of the organizational context, behavioral

Moral initiatives Instrumental Initiatives

Moral logic Commercial logic

Moral case justifications Business case justification

Stakeholder engagement organizational skills

Strategic issue identification and functional integration organizational skills

Intrinsic driver Extrinsic driver

Long term Short term

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Birkinshaw, 2004). Some perspectives of ambidexterity are overlapping. Moreover, all

perspective of ambidexterity have one common outcome: an ambidextrous organization leads

to superior firm performance (Uotila et al., 2009). Although the variety of authors arguing

that successful organizations are ambidextrous, there is still an understudied perspective of

ambidexterity. Engagement in CSR initiatives is a driver of corporations’ success as well.

The rationale behind engagement in CSR initiatives, referring to the balance between moral

and instrumental rationales, is in this research called ‘social ambidexterity’.

2.4. CSR in Emerging Markets

Li et al. (2010) highlighted the need for a better understanding of the importance of

CSR, and what affects CSR in emerging markets. Welford (2004) argues that corporations in

emerging markets adopt CSR practices less than their counterparts in developed markets.

Baughn et al. (2007) assign this effect to a lower level of economic development in emerging

markets. Emerging markets are characterized by their rapid economic growth (Li et al.,

2010). In the literature of international management, those markets are better known as the

BRICs; Brazil, Russia, India, China, and South-Africa. They do not only present almost half

of the worlds’ population, ‘they represent a block of countries with a fresh and investigating approach to global health’ (Marten et al., 2015, p. 2164). In recent years, corporate scandals in emerging markets have drastically increased. The increase of corporate scandals has not

only an impact on the international community, it has an impact on a country’s reputation as

well. The literature has paid much attention on the ‘economic miracles’ of the BRICs, and the

globalization of its corporations (Alon & McIntyre, 2008). Muller & Kolk (2009) argue that

emerging markets deal with a distinct setting for CSR, due to differences in the institutional

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markets deal with differences of engagement in the type of CSR activities. Second, markets

deal with differences in CSR performance. In other words, Muller & Kolk (2009) argue that

EM-MNEs differ from MNEs because they deal with other rationales behind their CSR

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3. Conceptual Model

In this section, the hypotheses of this research are discussed, corresponding with the

conceptual model. Hahn et al. (2016) propose that there is a positive relationship between

social ambidexterity and CSP. However, Hahn et al. (2016) do not provide empirical

evidence for this proposition. Therefore, this research empirically investigates the

relationship between social ambidexterity and CSP, resulting in hypothesis 1.

Hypothesis 1: Social ambidexterity positively affects CSP.

The literature of ambidexterity widely investigated the relationship between ambidexterity

and financial performance. Different authors argued that ambidexterity leads to a higher level

of financial performance (Gibson & Birkinshaw, 2004; Uotila et al., 2009). However, the

relationship between social ambidexterity and financial performance has never been

investigated before. Therefore, this research investigates if social ambidexterity also leads to

financial performance, which results in hypothesis 2.

Hypothesis 2: Social ambidexterity positively affects CFP.

Although, less is known about the CSR practices of EM-MNEs. Extensive research

has been conducted on CSR in developed markets (Li et al., 2010). Engagement in CSR

activities leads to higher level of social and financial performance (McGuire et al., 1988). As

Welford (2004) argues, EM-MNEs are less engaged in CSR activities than their counterparts

in developed markets. Therefore, the proposition arises that financial and social performance

as an outcome of CSR activities is lower in emerging markets than in developed markets,

which results in hypothesis 3, and hypothesis 4.

Hypothesis 3: EM-MNEs weaken the relation between social ambidexterity and CSP. Hypothesis 4: EM-MNEs weaken the relation between social ambidexterity and CFP.

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Hypothesis 1, 2, 3, and 4 result in the following conceptual model.

Figure 1: Conceptual Model

Social Ambidexterity Corporate Social Performance Corporate Financial Performance Emerging Markets

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4. Data and Method

In this section, the method used for this research is discussed. First, the type of

research design is described. After that, the research sample is briefly covered. The final part

of this section describes the data collection for each variable separately.

4.1. Research Design

This research is based on a quantitative data analysis. The data of the variable social

ambidexterity is collected through a manual coding method, with an outcome between 0 and

1. The independent variables, CSP and CFP, are collected through the secondary database ‘Datastream’. The use of secondary databases contains some drawbacks. First, the data in secondary databases is collected for other research purposes. Second, secondary databases

contain a lack of control with regard to the available data (Lewis et al., 2007). However,

many researchers before used the Datastream database to collect the variables CSP and CFP.

Moreover, these variables do not fluctuate for different research purposes (Garcia-Castro et

al., 2010). The data from the manual content analysis and Datastream are used to examine the

potential relationship between the independent and dependent variables, and impact of the

moderator. This potential relationships test the rationales of corporations engaged in social

initiatives and the outcome on CSP and CFP, contingent on emerging markets. Social

ambidexterity, CSP, CFP, and emerging markets are the four variables testing the hypotheses.

There are three control variables included in the research design: Firm size, firm risk, and

industry sector.

The control variables are included in the research design to ensure the validity of the

research, because those variables might drive firm performance as well. Including those

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other variables, that are not tested in the hypotheses. A research sample of 150 corporations

ensures that the results can be tested on consistency and stability, which enhances the

reliability of the research.

In the quantitative data analysis, a multiple hierarchical regression analysis and a

multi group level analysis will be executed. A multiple hierarchical regression analysis is

used, since it predicts how much of the dependent variable is explained by the independent

variables. Furthermore, the multiple hierarchical regression analysis contains different

models in which each model adds more variables. The multiple hierarchical regression

analysis in this research contains three different models. Model 1 is constructed by the

control variables; industry sector, firm size, and firm risk. In model 2, the independent

variable social ambidexterity is added to the model. Model 3 is the last model, where the

moderation variable is included. However, a multiple hierarchical regression analysis can

only have one dependent variable. Therefore, two different multiple hierarchical regression

analyses are executed for the dependent variables CSP, and CFP. The multi group level

analysis measures the effect of social ambidexterity and firm performance in different data

samples. Therefore, two subsamples will be created. The first data sample contains the data

of corporations established in emerging markets, the second data sample contains the data of

corporations established in developed markets. The multi group level analysis is used to

compare the beta values of the relationship between social ambidexterity and firm

performance for MNEs, and EM-MNEs. The beta value is a standardized coefficient, and

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4.2. Research Sample

Nowadays, the key drivers of globalization are MNEs (Rugman & Verbeke, 2004).

The largest 500 MNEs account for over 90% of the world’s stock of foreign direct investment

and conduct about half of the world’s trade (Rugman, 2005). The 500 biggest MNEs of the

world is still a poorly understood topic in the literature of international management

(Rugman, 2005). Therefore, the research sample includes corporations through the Global

Fortune Top 500 list in 2016. The Global Fortune Top 500 represents the largest corporations

of the world. The sample includes 150 corporations based on a top-down level ranking of the

Global Fortune Top 500 in 2016. This means that the corporations are selected beginning at

the top of the list and working towards the end of the list. For instance, in 2016 Walmart is

listed at number 1 in the Global Fortune Top 500. The sample contains 75 corporations

established in an emerging market, and 75 corporations established in a developed market.

Existing databases are used to collect the data, therefore the corporations in the sample are

publicly listed.

4.3. Data Collection

The data collection is described for each variable separately- because they are all

collected differently. First, the independent variable ‘social ambidexterity’ is described.

Second, the dependent variables CSP and CFP are defined. After that, the data collection for

the moderator ‘emerging markets’ is discussed. Finally, the data collection for the control variables is discussed. At the end of this section, an overview is provided in the

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4.3.1. Social Ambidexterity

Social ambidexterity has not been empirically investigated before. There is no existing

method that can be used to collect the data for this variable. Therefore, a new method is

proposed in this work. The unit of measurement is social initiatives. The six dimensions of

Hahn et al. (2016) are used to classify incentives behind the social initiatives undertaken. The

data collection for this variable is organized in different steps.

Existing databases do not have enough detailed information about the incentives of

social initiatives undertaken by corporations. For instance, the Thomson One database offers

information about social initiatives undertaken by corporations, but the database fails in

offering the incentives behind the social initiative. A content analysis in social reporting is

the most common method for measuring social initiatives (Kaplan & Ruffle, 2002). Social

reporting is done by communication in CSR reports. Therefore, this research collected the

CSR reports of all corporations included in the research sample. The CSR reports of the

selected corporations in the research sample are traceable on the internet and are collected of

the year 2014, because the dependent variables are measured on 1 January 2015.

After collecting the CSR reports of all corporations in the research sample, a content

analysis is executed. There are two main methods of doing a content analysis;

computer-based coding and manual coding. A computer-computer-based method is an objective method for doing

a content analysis. Classifying social initiatives requires detailed information of the context

of the text. There is no existing code that can be used to classify the context of the text in

moral and instrumental initiatives. Therefore, computer-based coding is not a suitable

method. This research uses a manual coding method. The drawbacks of manual coding are

that it is very time consuming and it can suffer from a subjective bias of the coder. This

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Next, the different steps undertaken to classify social initiatives in the six dimensions

of Hahn et al. (2016) are described below. First, all social initiatives described in the CSR

report by each corporation are listed. After that, each social initiative is rated among the six

different dimensions of Hahn et al. (2016). The rating is structured by A1, A2, B1, B2, C1,

C2, D1, D2, E1, E2, F1, and F2. Where A, B, C, D, E, and F refer to the six dimensions of

Hahn et al. (2016), 1 refers to moral incentives and 2 refers to instrumental incentives. Table

3 shows how the rating is structured. The manual content analysis is shown in appendix A.

Table 3

Structuration of the Social Initiatives in Content Analysis

Moral Incentives Instrumental Incentives

A1= Moral logic A2= Commercial logic

B1= Moral justification B2= Business case justification

C1= Stakeholder engagement

organizational skills

C2= Strategic issue identification and

functional integration

organizational skills

D1= Intrinsic driver D2= Extrinsic driver

E1= Long term E2= Short term

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After the initiatives for all corporations are coded in, the score on ambidexterity can

be calculated. The outcome of the score on ambidexterity is balanced between moral and

instrumental incentives, and results in a score between 0 – 1. Where,

0 = Total imbalance

1 = Perfectly ambidextrous

For each corporation, the score on ambidexterity is calculated as follows. First, the

score on each dimension (A, B, C, D, E, F) is calculated. The sum of the instrumental

incentive is decreased with sum of the moral incentive, for instance; A1 – A2. After that, the

score of the dimension is divided by the number of initiatives undertaken by the corporation.

The outcome can be any value between -1 and 1. When the incentive score is negative, the

ambidexterity score is computed as 1 plus the incentive score. When the incentive score is

zero or positive, the ambidexterity score is computed as 1 minus the incentive score. The

calculation of the score of ambidexterity for each dimension is shown in equation 1.

Equation 1: 𝐴𝑚𝑏𝑖𝑑𝑒𝑥𝑡𝑒𝑟𝑖𝑡𝑦_𝑥= { 1 + [(𝑥1− 𝑥2) 𝑛 ] if 𝑥1− 𝑥2 < 0 1 − [(𝑥1− 𝑥2) 𝑛 ] if 𝑥1− 𝑥2 ≥ 0

Here, 𝑥₁ and 𝑥₂ refer to the sum of dimensions A1 and A2, B1 and B2, C1 and C2, D1

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The amount of initiatives undertaken per corporation is listed as 𝑛. An example of the calculation of ambidexterity is shown in appendix B.

Now, the score on ambidexterity is calculated separately for each dimension. The next step is to calculate firm’s score on ambidexterity. Firm’s score on ambidexterity is the average score of the six different dimensions. This is calculated by the sum of all scores,

divided by six, as shown in equation 2.

Equation 2:

𝐹𝑖𝑟𝑚 𝑎𝑚𝑏𝑖𝑑𝑒𝑥𝑡𝑒𝑟𝑖𝑡𝑦 = 1

6∑ 𝐴𝑚𝑏𝑖𝑑𝑒𝑥𝑡𝑒𝑟𝑖𝑡𝑦𝑥,𝑦,…

𝑛

𝑖=1

4.3.2. Corporate Social Performance

The literature discusses different methods for measuring CSP. The KLD index is a

widely used measurement for CSP, and evaluates CSP issues each by a number of concern

and strength variables (Chen & Delmas, 2011). Furthermore, Fortune magazine rankings are

widely used in the literature of CSP (Peloza., 2009). Another measurement often used in the

literature of CSP is the ESG scorecard, referring to Environmental, Social and Governmental

scores (Gillan et al., 2010). This research adopts the ESG scorecard for the measurement of

CSP. Specifically, only the social score is used to measure a firm’s corporate social

performance, since environmental and governmental scores can have an influence on the

financial performance as well (Gillan et al., 2010). The social score is available in the Datastream database with the existing code ‘SOCSCORE’. The data of 1 January 2015 measures the social score after corporations have undertaken the social initiatives.

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4.3.3. Corporate Financial Performance

There are different ways to measure CFP as a result of CSR, with different outcomes

as well (Raza et al., 2012). The first measure described by Raza et al. (2012), is Tobin’s Q. When using Tobin’s Q as a financial performance measure, there tends to be a strong positive relation between CSR and CFP. The second measure described by Raza et al. (2012) is

accounting profit ratios. Accounting profit ratios such as return on assets, return on equity,

and return on sales show a positive relationship between CSR and CFP. The last measure

described by Raza et al. (2012), is stock market returns. Studies that make use of stock

market returns as a financial performance measure tend to find a negative relationship

between CSR and CFP (Margolis & Walsh, 2001). This research uses accounting profit ratios

as a measure for CFP, because prior research did not show strongly positive or negative

results by using this measure. Return on assets (ROA) illustrates how well the corporation

uses its total assets to make a profit. Therefore, ROA is used as a measure of CFP, and is

calculated as shown in equation 3.

Equation 3:

𝑅𝑂𝐴 = 𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠

The secondary database ‘Datastream’ is used to collect the data of ROA. Datastream is a global and financial database, providing historical company data. This database consists

of an existing code ‘WC08326’ that already calculated ROA for the selected corporations. The data of the year 2015 is collected to measure CFP, because social ambidexterity is

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4.3.4. Emerging Markets

As described in the research sample, the sample contains 75 corporations established

in an emerging market and 75 corporations established in a developed market. As discussed

in the literature review, emerging countries refer to the BRICs, which stands for: Brazil,

Russia, India, China, and South-Africa. The information whether a country is in a developed

market or an emerging market is provided in the description of the Global Fortune Top 500.

The variable ‘country’ is included in this research as a dummy variable, where: 0 = Developed market

1 = Emerging market.

4.3.5. Control Variables

The control variables firm size, firm risk, and industry are included in the research,

because they might drive firm performance. Stanwick & Stanwick (1998) argued that firm

size is positively related with financial and social performance. Larger firms have greater

resources for social investments and deal with greater pressure to engage in CSP (Margolis et

al., 2007). Firm size is measured by the number of employees, and is retained by the existing

code ‘WC07011’ in the Datastream database.

Additionally, firm performance is negatively related to firm risk (Orlitsky &

Benjamin, 2011). Risk can be measured by the debt of equity ratio. Debt of equity is

calculated by dividing total debt by the total shareholder equity. The Datastream database contains existing codes for total debt ‘WC03255’ and total shareholder equity ‘WC03995’. Equation 4 shows the calculation of the ratio of debt of equity.

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Equation 4:

𝑅𝑎𝑡𝑖𝑜 𝑑𝑒𝑏𝑡 𝑜𝑓 𝑒𝑞𝑢𝑖𝑡𝑦 = 𝑇𝑜𝑡𝑎𝑙 𝑑𝑒𝑏𝑡

𝑇𝑜𝑡𝑎𝑙 𝑠ℎ𝑎𝑟𝑒ℎ𝑜𝑙𝑑𝑒𝑟 𝑒𝑞𝑢𝑖𝑡𝑦

Different industry sectors have an impact on firm performance as well (Hart & Ahuja, 1996). The ‘Global Industry Classification Stands’ (GICS) provides a categorization of 11 industry sectors. The GICS classifies the following industry sectors: technology and

healthcare, consumer, materials, industrials, energy, financials, communications, and utilities.

Each sector contains a two-digit number, which corresponds with the first two letters of the

SIC code. SIC codes are collected with the secondary database ‘Orbis’. Table 4 shows the different industry sectors corporations are participating in, combined with the first two digits

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Table 4

Industry Sector with Corresponding Two Digits

Industry Sector First two digits corresponding to sector

Energy 10 Materials 15 Industrials 20 Consumer Discretionary 25 Consumer Staples 30 Health Care 35 Financials 40 Information Technology 45 Telecommunication Services 50 Utilities 55 Real Estate 60

An overview of the variables participating in the research design is provided in table 5. The

operationalization matrix provides the name of the variable, the indicators, the data collection

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Table 5

Operationalization Matrix

Variable Indicators Data collection + Measurement

Social Ambidexterity The balance between moral and

instrumental initiatives = { 1 + [(𝑥1− 𝑥2) 𝑛 ] if 𝑥1− 𝑥2< 0 1 − [(𝑥1− 𝑥2) 𝑛 ] if 𝑥1− 𝑥2≥ 0

1. Collect CSR reports of the year 2014 of participating corporations on the internet 2. Manual content analysis in CSR reports, code initiatives on six dimensions of Hahn et al. (2015)

3.Calculate ambidexterity score for each dimension by

4. Calculate average score of all dimensions for score firm ambidexterity

Corporate Financial Performance

𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒 𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠

ROA in 2015 Collect data with Datastream by using the

existing code ‘WC08326’

Corporate Social Performance Social score in 2015 Collect data with Datastream by using the existing ‘SOCSCORE’ code

Emerging Markets Firms established in BRICs countries. Dummy indicator.

0: developed market 1: emerging market

Firm size Number of employees Collect data with Datastream by using the

existing ‘WC07011’ code

Firm risk

𝑇𝑜𝑡𝑎𝑙 𝑑𝑒𝑏𝑡 𝑇𝑜𝑡𝑎𝑙 𝑠ℎ𝑎𝑟𝑒ℎ𝑜𝑙𝑑𝑒𝑟 𝑒𝑞𝑢𝑖𝑡𝑦

Ratio debt of equity Collect data with Datastream by using the existing codes and divide ‘WC03255’ by ‘WC03995’

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5. Results

In this section, the results of the quantitative data analysis are shown. First, the

descriptives of the data are analyzed. After that, a correlation matrix of the variables included

in the research is provided. Third, a multiple hierarchical regression analysis is executed for

both the dependent variables, CSP and CFP. In the final part of this section, a multi-group

analysis is provided.

5.1. Descriptives

First, the numeric variables in this research are analyzed in a descriptive analysis. The

results are shown in table 6.

Table 6

Descriptives

N Minimum Maximum Mean Std. Deviation

CSP 150 24.02 96.52 79.38 16.01 CFP 150 -5.50 26.03 3.50 4.54 Ambidexterity 150 .067 .889 .58 .17 Country 150 0 1 .50 .502 Firm Size 150 1000 2 300 000 194 802.67 265 830 Firm Risk 150 .00 20.35 1.71 2.06

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Table 6 shows that the minimum and maximum score of CSP is positive and ranging

between 24.02 and 96.52 with a mean of 79.38. The score on CFP can be negative, and

fluctuates between -5.50 and 26.03 with a mean of 3.50. As discussed in the method, the

score on ambidexterity can vary between 0 and 1, where 0 is total unbalance, and 1 is

perfectly ambidextrous. The mean of the sample is .58, which is just above half. This means

that the mean of the sample tends to be more ambidextrous than to be in unbalance. The

minimum score on ambidexterity is .067 and the maximum is .889. Country is a dummy

variable, where 0 refers to corporations established in a developed market, and 1 refers to

corporations established in an emerging market. The mean is .50 with a standard deviation of

.502, which implicates that half of the sample consists of corporations established in a

developed market, and the other half of the sample consists of corporations established in an

emerging market. Firm size varies between 1000 and 2 300 000 employees, with an average

firm size of 194 803 employees and a standard deviation of 265 830. The sample shows that

firm risk fluctuates between 0.00 and 20.35, with a mean of 1.71 and a standard deviation of

2.06. For all variables, N = 150, indicating that there are no missing values.

Industry sector is a nominal variable, and can’t be analyzed in a descriptive analysis. Therefore, a frequency analysis is provided for industry sector and is shown in table 7.

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Table 7

Frequency Industry Sectors

Frequency Percent Consumer Discretionary 23 15.3 % Consumer Staples 12 8.0 % Energy 19 12.7 % Financials 31 20.7 % Health Care 3 2 % Industrials 21 14 % Information Management 9 6 % Materials 21 14 % Telecommunication Services 10 6.7 % Utilities 1 0.7 %

The frequency analysis shows that there are four major industry sectors included in

the research sample, namely; Financials (20.7%), Consumer Discretionary (15,3%),

Industrials (14%), and Materials (14%). Those industry sectors are transformed to a dummy

variable in order to include them in correlation matrix and regression analysis, where:

0 = Corporation is not engaged in a particular industry sector.

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Thus, four different dummy variables are created for the industry sectors that contain

more than 20 cases. The other industry sectors become the omitted variable.

5.2. Correlation

Table 8 shows the correlation matrix of the variables included in this research. I_Fin,

I_Dis, I_Ind, and I_Mat refer to the four different industries sectors.

Table 8

Correlation Matrix

CSP CFP Amb Country Size Risk I_Fin I_Dis I_Ind I_Mat

CSP CFP .068 Amb .197* .004 Country -.319** -.030 -.045 Size .102 .194* .094 -.153 Risk -.029 -.007 -.022 .118 -.090 I_Fin -.28** -.245** .018 .016 -.072 .205* I_Dis .117 .243** .126 -.204* .160 -.087 -.217** I_Ind -.133 -.088 -.040 .134 .012 .058 -.206* -.172* I_Mat .087 -.009 -.054 .250** -.136 -.104 -.206* -.172* -.163*

* Correlation is significant at the 0.05 level ** Correlation is significant at the 0.01 level

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Ambidexterity and CSP are positively correlated (.197*), while country and CSP are

negatively related (-.319**). Furthermore, CSP is negatively related to the financials industry

sector (-.28**). CFP is positively related to firm size (.194*). CFP has a negative relation

with the financials industry sector (.245**) and a positive relationship with the consumer

discretionary sector (.243**). Country is negatively related to the industrials industry sector

(-.204*) and positively related to the materials industry sector (.250**). Risk is positive

correlated with the financials industry sector (.205*). The last findings in the correlation

matrix show that all industry sectors are negatively related to each other. The financials

industry sector is negatively related to consumer discretionary (-.217), negatively related to

industrials (-.206) and negatively related to materials (-.206*). The consumer discretionary

industry is negative related to industrials (-.172*) and negative related to materials (-.172*).

Industrials is negative related to materials (-.163*).

5.3. Multiple Hierarchical Regression Analysis

As discussed in the method, the multiple hierarchical regression analysis used in this

research contains three models. The first model only contains the control variables. In the

second model, the independent variable social ambidexterity is added to the model. The third

model includes the moderation variable. The moderation variable is composed of the

interaction term of the standardized values of the variables social ambidexterity and country.

A multiple hierarchical regression analysis can have one outcome. Therefore, two regression

analyses are executed in this research. The first regression contains the results of CSP as a

dependent variable- and is shown in table 9. The results of CFP as a dependent variable are

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Table 9 Summary Predictors CSP Variable B Std. Error β t Sig R² R² Change F Change Sig Model 1 .128 .128 3.507 .003 I_Fin -12.994 3.503 -.330 -3.710 .000 I_Dis .076 3.825 .002 .020 .984 I_Ind -9.418 3.937 -.205 -2.392 .018 I_Mat .174 3.962 .004 .044 .965 Size .000 .000 .087 1.083 .281 Risk .459 .626 .059 .732 .465 Model 2 .164 .036 .008 .015 I_Fin -13.337 4.851 -.338 3.872 .000 I_Dis -.925 3.444 -.021 -.245 .807 I_Ind -9.302 3.780 -.202 -2.404 .017 I_Mat .333 3.869 .007 .086 .932 Size .000 3.893 .072 .918 .360 Risk .481 .615 .062 .782 .435 Ambidexterity 18.469 7.470 .192 2.472 .015 Model 3 .172 .008 1.352 .247 I_Fin -13.706 3.455 -.348 -3.967 .000 I_Dis -.810 3.777 -.018 -.215 .830 I_Ind -8.988 3.873 -.195 -2.321 .022 I_Mat -.091 3.905 -.002 -.023 .981 Size .000 .000 .065 .823 .412 Risk .486 .615 .063 .791 .430 Ambidexterity 20.661 7.695 .215 2.685 .008 Interaction -1.501 1.291 -.093 -1.163 .247

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Table 10 Summary Predictors CFP Variable B Std. Error β t Sig R² R² Change F Change Sig Model 1 .137 .137 3.789 .002 I_Fin -2.783 .989 -.249 -2.815 .006 I_Dis 1.811 1.080 .144 1.678 .096 I_Ind -1.629 1.111 -.125 -1.466 .145 I_Mat -.352 1.118 -.027 -.315 .753 Size .000 .000 .158 1.978 .050 Risk .165 .177 .075 .936 .351 Model 2 .138 .001 .148 .701 I_Fin -2.767 .992 -.247 -2.789 .006 I_Dis 1.856 1.089 .148 1.704 .091 I_Ind -1.635 1.115 -.125 -1.467 .145 I_Mat -.360 1.122 -.028 -.321 .749 Size .000 .000 .160 1.995 .048 Risk .164 .177 .075 .928 .355 Ambidexterity -.828 2.152 -.030 -.385 .701 Model 3 .140 .002 .370 .544 I_Fin -2.712 .999 -.243 -2.715 .007 I_Dis 1.839 1.092 .146 1.684 .094 I_Ind -1.682 1.120 -.129 -1.502 .135 I_Mat -.295 1.129 -.023 -.262 .794 Size .000 .000 .164 2.032 .044 Risk .164 .178 .074 .921 .358 Ambidexterity -1.160 2.225 -.043 -.521 .603 Interaction .227 .373 .050 .608 .544

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In table 9, model 1 shows that the control variables explain 12.8% of CSP. The

industry sector financials has a negative impact (-.330***) on CSP. Industrials has a negative

impact (-.205**) on CSP as well. Model 2 explains 16.4 % of CSP, with an increase of 3.6%

due to the inclusion of ambidexterity in the model. The industry sectors financials (-.338***)

and industrials (-.202**) still have a negative impact on CSP. However, ambidexterity has a

positive impact (.192**) on CSP. In model 3, the interaction variable country*ambidexterity

is included. The variance explained in CSP by model 3 is not significant. However, the

industry sector financials (-.348***) and industrials (-.195**) do still have a negative impact

on CSP. Ambidexterity has a positive effect (.215***) on CSP. The moderation effect is not

significant.

In table 10, model 1 shows that the control variables explain 13.7 % of CFP.

Furthermore, the industry sector financials has a negative impact (-.249***) on CFP. Besides,

the industry sector consumer discretion has a positive impact (.144*) on CFP. Firm size

positively influences (.158**) CSP. The variation explained in CFP in model 2 is not

significant. The industry sector financials (-.247***) and consumer discretionary (.148*) still

have an impact on CFP. Firm size still has a positive impact (.160**) on CFP. Model 3, the

interaction variable country*ambidexterity is included. Still, the variables financials

(-.243***), consumer discretionary (.146*), and firm size (.164**) have an impact on CFP.

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5.4. Multi-Group Level Analysis

As discussed in the method, the multi-group level analysis contains two subsamples.

The first subsample contains all corporations established in a developed market, the second

subsample contains all corporations established in an emerging market. By doing this, the

effect of social ambidexterity on firm performance in the two different markets can be

compared. First, a linear regression analysis is provided for MNEs. After that, a linear

regression analysis is provided for EM-MNEs.

5.4.1. Developed Markets

In table 11, the results of the linear regression are shown for the dependent variable

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Table 11 Predictors CSP of MNEs Variable B Std. Error β t Sig R² R² Change F Change Sig Model 1 .181 .181 2.121 .053 I_Fin -1.812 3.362 -.068 -.539 .592 I_Dis -4.020 3.100 -.159 -1.296 .199 I_Ind -3.993 4.379 -.110 -.912 .365 I_Mat 2.027 5.457 .043 .371 .712 Size .000 .000 .116 1.004 .319 Risk .971 .953 .121 1.019 .312 Amb 25.921 8.433 .353 3.074 .003 * P < 0.1 ** P < 0.05 *** P < 0.01

Table 11 shows that this model explains 18.1 % in CSP. None of the variables have a

significant impact on CSP, except ambidexterity. Only the variable ambidexterity has a

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Table 12 Predictors CFP of MNEs Variable B Std. Error β t Sig R² R² Change F Change Sig Model 1 .172 .172 1.986 .070 I_Fin -2.472 1.562 -.202 -1.583 .118 I_Dis 1.481 1.440 .127 1.029 .307 I_Ind -1.723 2.034 -.102 -.847 .400 I_Mat -2.284 2.535 -.105 -.901 .371 Size .000 .000 .241 2.085 .041 Risk .191 .443 .051 .431 .668 Amb -2.451 3.917 -.072 -.626 .534 * P < 0.1 ** P < 0.05 *** P < 0.01

In table 12, the results of the predictors of CFP in developed markets are shown. The

model explains 17.2 % of CFP. However, there is only one significant variable that has an

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5.4.2. Emerging Markets

Table 13 shows the results of the linear regression for CSP in emerging markets. In

table 14, the results of the linear regression for CFP as a dependent variable are shown.

Table 13 Predictors CSP of EM-MNEs Variable B Std. Error β t Sig R² R² Change F Change Sig Model 1 .324 .324 4.586 .000 I_Fin -24.378 5.357 -.537 -4.550 .000 I_Dis 6.349 7.666 .093 .828 .411 I_Ind -9.730 5.536 -.204 -1.758 .083 I_Mat 2.191 5.317 .049 .412 .682 Size .000 .000 .048 .471 .639 Risk .789 .752 .109 .1049 .298 Amb 7.484 10.457 .074 .716 .477 * P < 0.1 ** P < 0.05 *** P < 0.01

Table 13 shows that the model explains 32.4 % of the variance in CSP. However, only

two variables have a significant impact on CSP. The industry sector financials has a negative

impact (-.537***) on CSP. Also the industry sector industrials has a negative impact (-.204*)

Social ambidexterity and firm performance in emerging markets