RENEWABLE ENERGY: GOVERNMENTAL IMPACT ON FIRM’S INVESTMENTS AND THE MODERATING ROLE OF BOARD AND TOP MANAGEMENT DIVERSITY
Master thesis, MSc Supply Chain Management
University of Groningen, Faculty of Economics and Business
June 22, 2020
RIK HEIDEMA Studentnumber: S3769534 e-mail: h.r.heidema@student.rug.nl
Supervisor Dr. S. Boscari Dr. T. Bortolotti
Co-assessor Dr. N. Pulles
Acknowledgement: I would like to thank Dr. Stefania Boscari and Dr. Thomas Bortolotti for all the support and
ABSTRACT
Increasing the share of renewable energy to reduce the carbon emissions remains a key challenge for modern governments and firms. Drawing on instructional theory, this study examines the relationship between countries’ share of renewable energy (CSRE) and firms’
energy investments. This study provides a global perspective on this relationship, by analyzing the data of 227 firms within 21 countries, using CDP data. Moreover, this study takes the moderating role of board of directors (BoD) and top management team (TMT) diversity into account, drawing on stakeholder theory. The analyses yield several interesting findings. First, changing the CSRE positively impacts firms’ energy investments with a one-year time lag, and becomes even stronger in the second and third year after the change in CSRE was made.
Second, some diversity dimensions positively moderate this relationship, while other dimensions have a negative moderating effect. Third, this study found evidence for substantial differences between the moderating effect of the diversity dimensions for BoD and TMT.
Overall, this study provides new insights on what the impact is of changing CSRE on firms’
energy investments and which BoD and TMT diversity structures are most likely to act on it.
INTRODUCTION
Human activities are estimated to have caused approximately between 0.8 °C to 1.2 °C of global warming above pre-industrial levels and is likely to reach 1.5 °C between 2030 and 2052 (IPCC, 2018). The major cause of global warming is the rise in the concentration of gases (e.g.
carbon dioxide) in the atmosphere that contributes to the greenhouse effect (El-Sharkawy, 2014). Currently, the energy industry is the largest contributor to carbon emissions (EEA, 2020) while the demand for energy is still increasing (IPCC, 2014). At the same time, there are alarming energy security issues facing fossil fuel-based energy consumers, since oil is hard to substitute in the short run and is often extracted from political instable regions (Hedenus, Azar and Johansson, 2010). Adopting energy from renewable sources could be a solution to both of these problems since it is a clean, non-polluting source of energy (Ramachandra and Shruthi, 2007).
However, adopting energy from renewable sources is not something that can be done easily on a large scale. Effective mitigation of climate change requires firms to make large investments to transform from high-carbon technologies to low-carbon alternatives (Schmidt, 2014).
Therefore, powerful incentives and visionary energy policies are needed to transform from high-carbon energy sources to renewable energy sources (Mitchell and Connor, 2004).
Governments are able to introduce such incentives and policies to influence corporate behavior (Ayoub and Yuji, 2012). Moreover, many governments are committed to increase their share of renewable energy (Zhang, Li, Zhou and Zhou, 2014). However, there are still large differences between countries regarding the relative share of renewable energy in the total energy consumption (IEA, 2020). Given that firms’ energy investments within a country is a crucial factor for that country to increase its own share of renewable energy (Lewis and Wiser, 2007), it is likely that this country will exert its power to force firms to make larger energy investments. Therefore, the relative change of countries’ share of renewable energy (CSRE) is likely to affect firms’ energy investments. Decision makers within firms, such as the board of directors (BoD) and the top management team (TMT), are capable of influencing these investment decisions within the firm (Harjoto, Laksmana and Lee, 2014; Rao and Tilt, 2016).
Therefore, firms with BoDs or TMTs that are better able to incorporate the demands of the
firm’s environment, could invest more conform its environment interests, and moderate the
relationship between CSRE and firm’s renewable energy investments.
Prior studies found that firms with greater BoD and TMT diversity (in terms of age, gender, nationality, education and experience) are better able to respond to their environment (Bernile, Bhagwat and Yonker, 2018; Rao and Tilt, 2016; Zhu and Shen, 2016). However, these studies did not include the separate dimensions of diversity in their calculations but only took an average index to measure diversity. Therefore, it is not clear yet to what extent the separate dimensions are contributing to the improved responding to the firms’ environment. Moreover, there are contrasting results presented in current literature regarding some of the diversity dimensions (e.g. age diversity). While some scholars found mainly positive effects (Ferrero- Ferrero, Fernandez-Izquierdo and Munoz-Torres, 2015), other scholars found evidence for negative effects (Hafsi and Turgut, 2012; Post, Rahman and Rubow, 2011). Also, prior research mainly studied firm value as an outcome of BoD and TMT diversity. Investments in renewable energy can be a better proxy to measure the effects of BoD and TMT diversity, as those investments are needed to solve the social problem of global warming, rather than just making more profit. In other words, the incentive for a firm to invest in renewable energy is likely to come from outside the firm, while all firms are intrinsically motivated to increase their own firm performance. Scholars that studied the relationship between governmental pressure and sustainable practices often examined the effectiveness of subsidies of a single government in promoting renewable energy (Murray, Cropper, de la Chesnaye and Reilly, 2014; Nicolini and Tavoni, 2017) or compared different subsidiary possibilities of a single government with each other (Shen and Luo, 2015; Zhang, et al. 2014). This study takes a step back and tries to capture the bigger picture by exploring the impact of the share of renewable energy of 21 countries on the investments in renewable energy of 227 firms, within a 5-year timeframe from 2013 until 2017. This study addresses this subject by finding an answer to the following question:
“How does country’s share of renewable energy (CSRE) impacts firm’s investment in renewable energy?”
BoD and TMT diversity is expected to play a moderating role in the effectiveness of this relationship, as the BoD and TMT have the power to impact investment decisions (Rao and Tilt, 2016). Therefore, this study explores the moderating role of BoD and TMT diversity by finding an answer to the question:
“Is the relationship between CSRE and firms’ energy investments moderated by BoD and
TMT diversity?”
This study applies institutional theory to explore the influential role of governments on firm’s investments and stakeholder theory to examine the effect of BoD and TMT on this relationship.
Firms exist in an institutional environment that influence their choices and practices by obligating them to show conformity to institutionalized expectations (Gupta, Dirsmith and Fogarty, 1994; Scott, 1987). Institutional theory explains why firms could invest in renewable energy, even without a clear economic return (Fligstein, 1997; Suddaby, 2010). Stakeholder theory suggests that firms should pursue maximum value for its stakeholders (Freeman et al., 2010) and that cooperation, rather than conflict, should be the primary managerial mindset (Harrison and Wicks, 2013). It offers guidelines on how firms should manage their relationships with stakeholders to ensure sustainable corporate success (Parmer et al., 2010).
As the BoD and TMT are the pinnacle of firms (Zona, 2012), they appear to be extremely important in incorporating stakeholder’s interests onto the firm’s agenda. To generate insights in renewable energy investments of firms, data is retrieved from the Carbon Disclosure Project database. Data about countries’ share of renewable energy is gathered from public databases of the International Energy Agency (IEA). Data about BoD and TMT diversity is obtained from the BoardEx database.
This study extends the current body of literature by contributing to the discussion of governmental policies as influencer of firm’s sustainable investments, using institutional theory. Compared to other studies, this study stands out by taking a global perspective rather than focusing on the effectiveness of policies of a single government (e.g. Murray et al., 2014;
Nicolini and Tavoni, 2017). It makes an empirical contribution to the current literature by not
only showing the impact of CSRE on firms’ energy investments, but also showing how long
this effect will last (i.e. how long the firms’ energy investments will be impacted by this
governmental practice). In addition, this study differentiates from other studies, by taking BoD
and TMT diversity into account, building on stakeholder theory. It adds to the discussion of
the relevance of using greater diverse BoDs and TMTs as an instrument to improve stakeholder
management. The results of this study help to understand the impact of changing the CSRE on
firm’s renewable energy investments and how this relationship is impacted by different levels
of BoD and TMT diversity. Therefore, the results of this study help policy makers at
governments to understand the effects of changing their share of renewable energy and help
firms to recognize the effect of composing greater diverse BoD and TMT.
THEORETICAL BACKGROUND
Country’s share of renewable energy
Renewable energy is energy extracted from a resource that is renewed by nature, that is non- polluting, and whose supply is not affected by the rate of consumption (Ramachandra and Shruthi, 2007). Due to these benefits, many countries committed to improving their share of renewable energy in international environmental agreements (e.g. the Paris Agreement of 2015). Almost all countries have introduced laws and policies to promote the transition to renewable energy (Ayoub and Yuji, 2012). These laws and policies include subsidies, feed-in tariffs, targets for carbon dioxide reductions and targets for renewable energy. Governments set these renewable energy targets to define their future share of renewable energy in their national energy generation (Brand and Zingerle, 2011). However, there are still large differences between countries regarding their development of their share of renewable energy, as can be seen in Table 1. This table shows the year by year change in CSRE (e.g. a renewable energy share of 10% in 2013 and 11% in 2014 will result in a 10% increase for the year 2014).
Table 1: relative change of renewable energy proportion year by year (IEA, 2020)
Country 2014 2015 2016 2017
Austria 2,69% -0,33% -0,53% -0,66%
Belgium 6,88% -0,36% 8,86% 4,04%
Brazil -2,03% 4,65% 4,69% -0,24%
Denmark 7,86% 5,20% 3,25% 9,06%
Finland 5,58% 1,39% -0,79% 4,89%
France 3,83% 2,96% 4,45% 2,11%
Germany 4,50% 3,58% -0,11% 3,94%
Great Britain 22,54% 23,75% 7,72% 8,35%
Ireland 12,86% 5,93% 1,65% 14,37%
Italy 2,04% 2,59% -0,63% 4,89%
Japan 9,62% 10,53% 0,00% 9,52%
Korea 52,63% -6,90% -3,70% 7,69%
Luxembourg 27,78% 11,92% 7,72% 15,55%
Netherlands 15,43% 4,47% 3,01% 10,88%
Norway 3,66% 0,00% 1,40% 2,12%
Singapore 0,00% 16,67% 0,00% 0,00%
Spain 5,26% 0,64% 7,45% 0,72%
Sweden 2,11% 2,19% 0,68% 1,56%
Switzerland 1,84% 8,14% 0,42% 2,92%
Taiwan 10,61% 6,85% 7,69% 5,95%
United states 1,10% -1,09% 4,40% 4,21%
The measures taken by governments to promote renewable energy depends on their economic, social and topological conditions (Ayoub and Yuji, 2012). Table 1 shows the year by year increase (or decrease) of the share of renewable energy for the 21 countries that are included in this study. The increase (or decrease) of the CSRE is a proxy for the commitment of the country regarding renewable energy. Current literature mostly found positive social and economic effects on both the short-term and the long-term regarding carbon dioxide reductions, CSR practices or renewable energy implementation (Ayoub and Yuji, 2012; Mitchell and Connor, 2004; Zhang et al., 2014). However, there are also some negative effects found on the longer term caused by wrong or excessive subsidies, such as low-level technology, high cost and difficulties in grid connection (Shen and Luo, 2015).
Firm’s renewable energy investments
Investments in renewable energy have increased steadily over the past few years. Global investments in renewable energy capacity amounted 272.9 billion dollars in 2018, which was the fifth successive year in which it has exceeded 250 billion dollars (UNEP Centre, 2019).
Despite these large investments, there here are still many opportunities to increase the usage of renewable energy even further. For example, increasing economic growth and demand for energy in emerging economies creates an opportunity for them to increase their investments in renewable energy (Sadorsky, 2009). Several experts identify the opportunities that renewable energy investing can offer including the environmental, social and economic benefits (EEA, 2020; IPCC, 2018). However, many investments in energy efficiency failed despite their appearance to be profitable in the first place (DeCanio, 1993). Therefore, firms are perceiving difficulties when considering investments in renewable energy. Not all cost-effective energy measures will always be implemented by firms because of the existence of these difficulties to energy efficiency, resulting in an energy efficiency gap (Thollander and Ottosson, 2008).
Overcoming these difficulties is necessary to eliminate this efficiency gap.
De Groot, Verhoef and Nijkamp (2001) identified these difficulties as general barriers (e.g.
priority and implementation issues), financial barriers and uncertainty barriers (e.g. concerns
about quality or firms waiting for subsidies). They state that promoting investments in energy-
saving technologies is important to overcome these barriers and help to achieve the
environmental goals. This is also mentioned by Peidong et al (2009), by stating that
governmental stimulation is the key and initial power for developing renewable energy. Past
governmental policies supporting renewable energy investing (e.g. feed-in tariffs and tradable green certificates) are found to be effective, both in the short run and on the longer term (Nicolini and Tavoni, 2017). However, governments need to understand the behavioral context in which investors make decisions to make sure that their policies effectively impact firm’s investment decisions (Masini and Menichetti, 2012).
Institutional Theory
The impact of governmental policies on firm’s investments can be explained by institutional theory. Institutional theory has many faces. One of the earliest versions of the institutional theory describes organizational structure as an adaptive process in reaction to both the influences of participants and constraints from the external environment (Scott, 1987). This early version of institutional theory has a descriptive nature. It describes the process rather than explaining how this phenomenon exactly occurs. Meyer and Rowan (1997) use a more explanatory approach by arguing that organizations whose structures are aligned with the institutional rules decrease their internal coordination and control in order to maintain legitimacy. However, most studies take only a narrow approach for the institutional theory, by stating that organizational survival is determined by the extent to which the organizational structure is aligned with the institutional environment (e.g. Meyer and Rowan, 1977; Powell and DiMaggio, 1991). This narrow approach is less applicable for many multinational companies (MNCs) that are included in this study, because they operate cross-border and in more complex environments than their domestic counterparts (Michel and Shaked, 1986). This results in diverse, fragmented and possible conflicting external environments for MNCs (Kostova, Roth and Dacin, 2008). They state that most challenges regarding the institutional theory for MNCs occur at meso level and opt for a blended institutional perspective, that blends social embeddedness with the ideas of agency, social construction and power and politics. In reaction to this, Phillips and Tracey (2009) proposed that more recent interpretations of institutional theory have stronger interest in agency and change which makes them applicable to MNCs and, therefore, also to this study.
BoD and TMT diversity
Current literature found benefits of BoD and TMT diversity on firm performance and environmental performance (e.g. Bernile et al., 2018; Carter et al., 2003; Goodstein et al., 1994;
Kumar and Paraskevas, 2018). Prior research found a positive effect of gender diverse TMTs,
and TMTs consisting of executives with SCM experience on environmental performance (Kumar and Paraskevas, 2018). Other researchers found that firms with greater BoD diversity invest persistently more in research and development (Bernile et al., 2018) and that BoD diversity is positively associated with CSR performance (Ferrero-Ferrero et al., 2015; Harjoto et al., 2014; Rao and Tilt, 2016). Researchers also found support for a positive relationship between BoD gender diversity and firm’s innovation (Miller and Del Carmen Triana, 2009).
However, some studies also found negative effects for some diversity dimensions. For instance, Hafsi and Turgut (2012) found that age diversity negatively impacts the decision-making process. In addition, Kumar and Parakevas (2018) found that aging TMTs lead to better environmental performance, which implies that TMTs with greater age diversity (i.e. TMTs with a mix of younger and older executives) would not necessarily benefit the environmental performance.
Many of prior scholars focused only on one or two factors to measure BoD or TMT diversity,
while only some scholars used a broader multidimensional measure to define this concept. This
study follows a widely used multidimensional measure of diversity that includes several
dimensions which can be categorized in the clusters experience, educational background and
identity (Bernile et al., 2018; Harjoto et al., 2014; Kumar and Paraskevas, 2018; Zhu and Shen,
2016). The cluster experience contains the dimensions age diversity, diversity in the number
of positions an individual has held, and diversity in the number of years an individual has
worked (i.e. job tenure). The cluster educational background contains the dimensions
qualification diversity (i.e. diversity in the obtained degrees) and whether or not an individual
obtained its degree at an Ivy League school (Zhu and Shen, 2016). Finally, the cluster identity
contains the dimensions gender diversity and diversity in nationality. This study draws on this
multidimensional measure of diversity to study the impact of BoD and TMT diversity on the
relationship between CSRE and firm’s energy. This approach stems from previous studies that
found that group diversity moderates group performance (Foldy, 2004) and that greater diverse
BoDs and TMTs are better able to satisfy the needs of their stakeholders (Harjoto et al., 2014),
because a diverse group of individuals bring different experiences, knowledge bases and
perspectives on society, which improves the management of different types of stakeholders.
Stakeholder theory
The phenomena that greater diverse BoDs and TMTs are better able to respond to their
environment can be explained using stakeholder theory. Early versions of the stakeholder
theory argued that supporting stakeholder’s interests is not necessarily about social
responsibility, but about capitalism (Friedman, 1962). Friedman argued that the purpose of
business is to engage in activities to increase own profits as long as it stays within the rules. A
key difference between this view and later versions of stakeholder theory is the determinant
that make a firm successful. In the early view of stakeholder theory maximizing profits was
the key determinant, while more recent views argue that firms need to engage with customers,
maintain solid relationships with suppliers, and have inspired employees in order to maximize
profits (Freeman et al., 2010). Stakeholder theory provides an instrument linking ethics to
strategy and argues that firms need to serve the interests of a broader group of stakeholders to
create more value over time (Freeman et al., 2010). However, stakeholders seek more than just
economic value. Harrison and Wicks (2013) argue that the notion of value has been
oversimplified and narrowed to focus on profits. They came up with other perspectives that are
important for stakeholders, including organizational affiliation, meaning that stakeholders
expect firms to exhibit behaviors that are consistent with things they value. This reasoning is
also supported by the work of Parmar et al (2010) by stating that value creation must be seen
creating value for stakeholders. Moreover, they state that “understanding the economics of
markets is important, but at the center of starting, managing, and leading a business is a set of
stakeholder relationships that define the business” (Parmar et al., 2010, p. 433). This means
that firms need to provide more than just economic value to their stakeholders to retain their
participation and support.
HYPOTHESIS DEVELOPMENT
CSRE and firm’s energy investments
The central concept of institutional theory is that every institution is influenced by its broader environment (Meyer and Rowan, 1977; Powell and DiMaggio, 1991; Scott, 1987). Therefore, institutional theory could explain why firms could invest in sustainable initiatives, even without clear economic return. Governments can leverage their power to motivate or even force firms to make particular investments. Prior studies in the supply chain management field found that governmental policies forced firms to consider their waste reduction performance and even influenced firm’s investments in waste reduction initiatives (Simpson, 2012). There is also found that governmental pressures significantly explain firm’s investments in security management (Cavusoglu, Cavusoglu, Son and Benbasat, 2015). Renewable energy is a very important topic for governments these days, as countries worldwide are concluding agreements regarding their share of renewable energy (e.g. Paris Agreement). Given the fact that governments need cooperation from firms to meet these agreements (Lewis and Wiser, 2007), it is expected that they will leverage their power to influence firms’ investments in renewable energy. Therefore, the relative change of a country’s share in renewable energy (CSRE) is expected to positively influence firm’s energy investments.
Hypothesis 1: The change in CSRE is positively related to firm’s energy investments.
BoD and TMT Diversity
As mentioned before, greater diverse BoDs and TMTs are better able to act in response to their
stakeholders (Harjoto et al., 2014). One of the most important institution among this group of
stakeholders are governments that can influence firms by pressure (e.g. laws and regulations)
or policies (e.g. subsidies) (Simpson, 2012). Drawing on stakeholder theory, this study
proposes that firms need to comply with the demand of their stakeholders to retain their
participation and support and that firms are better able to do this when they have a greater
diverse BoD and TMT. In other words, greater diverse BoDs and TMTs are better able to
recognize the governmental demand for renewable energy investment than less diverse BoDs
or TMTs. The seven diversity dimensions for both BoD and TMT included in this study are
categorized into three clusters, that will be explained further.
Experience diversity
The experience cluster contains three diversity dimensions: age diversity, diversity in the number of positions an individual has held and diversity in the number of years an individual has worked (Bernile et al., 2018; Zhu and Shen, 2016). These dimensions received a different amount of attention in prior literature. Research on age diversity is much less developed than the other dimensions of BoD and TMT diversity (Ferrero-Ferrero, Fernández-Izquierdo and Muñoz-Torres, 2013). Prior research found that boards whose directors averaged closer to 56 in age were more likely to implement CSR practices (Post, Rahman and Rubow, 2011). This finding was contradictory to their assumption that younger board directors express more concern about the environment than older directors. They gave as explanation that this was the first generation in which environmental issues were included in their educational curricula.
This would imply that there is an optimal range in age for BoDs and TMTs that are most likely to implement CSR practices, rather than a greater age diverse BoD or TMT. Hafsi and Turgut (2012) also found results that were contradictory to their assumptions. They suggested that age diversity was likely to lead to more balanced decision-making that takes a larger share of stakeholders into account. However, they found a significant negative relationship between age diversity and balanced decision-making. Therefore, age diversity is expected to negatively influence the relationship between CSRE and firm’s energy investments.
Prior literature found that individuals that had held job positions in various field of business
are better able to translate the demands of its environment to business practices. For example,
Kumar and Paraskevas (2018) found that executives with SCM experience in the TMT can be
very beneficial for establishing a proactive environmental strategy. Moreover, Zhu and Shen
(2016) found that CEOs that occupied more positions in TMTs of other firms improve the
decision-making process regarding investments. These studies found that firms benefit from
having board directors or top managers that have experience in various positions in a larger
number of firms. These findings suggest that firms should not strive for diversity in the number
of positions an individual has held, but simply for directors and executives that held a higher
number of job positions, in order to be able to recognize the needs and demands of their
environment. A greater diverse BoD or TMT would imply that there are directors or executives
with little or no experience that could harm the decision-making process regarding firm’s
energy investments.
Hafsi and Turgut (2013) describe that directors or executives with more years of board experience generally have more skills and expertise and are, for example, more likely to confront the CEO when necessary. They also argue that directors with less years of board experience might be too cautious to speak up, which could harm the decision-making process.
Harjoto et al (2014) found that directors with more years of board experience are the driving factors of firm’s CSR activities. In addition, Rao and Tilt (2016) found that directors with more years of board experience positively impacts the strategy and decision-making process.
Drawing on these results, a BoD or TMT with directors or executives that have more years of work experience, is expected to be better able to incorporate the demands of its environment and improve the decision-making process, than greater diverse BoDs or TMTs in terms of experience. Therefore, BoD or TMT diversity regarding the number of years of work experience is expected to negatively influence the relationship between CSRE and firms’
energy investments. Given the considerations of these three dimensions, experience diversity is expected to negatively influence the relationship between CSRE and firms’ energy investments.
Hypothesis 2a: The positive effect of CSRE on firms’ energy investments will be weaker for firms having BoDs and TMTs with greater experience diversity.
Educational background diversity
Educational background is the second cluster to measure BoD and TMT diversity in this study.
It contains qualification diversity (diversity in achieved degrees) and Ivy League diversity (whether or not a director or executive received a degree from an Ivy League school).
Qualification can be distinguished into a few main degrees: PhD, Masters, Bachelors and lower
(Zhu and Shen, 2016). Qualification is an important dimension that shapes the way how
directors think and what they stand for when making decisions (Fernández-Gago, Cabeza-
García and Nieto, 2018). Prior research found that diversity in the educational background of
directors has significant impact on firm’s CSR performance (Huang, 2013). Directors develop
several different specialized skills that are based on their education that help them to cope with
interests of different stakeholders (Fernández-Gago et al., 2018). Therefore, diversity in
educational background is expected to positively moderate the relationship between CSRE and
firms’ energy investments.
The second measure within this cluster is Ivy League diversity. This is a characteristic that has been extensively studied in the literature on board diversity (Zhu and Shen, 2016). The Ivy League contains eight private universities in the Northeastern of the United States. These Universities in alphabetical order are Brown University, Columbia University, Cornell University, Dartmouth College, Harvard University, University of Pennsylvania, Princeton University, and Yale University. Prior research found that Ivy League diversity positively influences the CEO-board relationship that will help the decision-making process (Zhu and Shen, 2016). Therefore, it is expected that Ivy League diversity will increase the ability to manage different stakeholders and, therefore, positively influence the relationship between CSRE and the firm’s investment in renewable energy.
Hypothesis 2b: The positive effect of CSRE on firms’ energy investments will be stronger for firms having BoDs and TMTs with greater educational background diversity.
Identity diversity
The last two diversity dimensions are gender diversity and nationality diversity. These dimensions are categorized into the identity cluster. From all the diversity dimensions, gender diversity received the most attention in prior literature and is one of the greatest challenges that modern firms are facing (Carter et al., 2003). Previous studies linked gender diversity with firm performance. There is found that gender diversity is positively related to firm value, because a more gender diverse board might be a more activist board (Carter et al., 2003). In addition, there is found that firms with greater gender diversity in their BoD and TMT, are also better able to enhance the effectiveness of the (investment) decision-making processes (Terjesen, Couto and Francisco, 2015), and that gender diversity improve stakeholder management (Harjoto et al., 2014). Therefore, gender diversity is expected to positively moderate the relationship between CSRE and firms’ energy investments.
The second dimension of this cluster is nationality diversity. Nationality diversity is another
issue that modern firms are facing regarding their BoD and TMT composition (Carter et al.,
2003; Rao and Tilt, 2016). Nationality is one of the most important dimensions of diversity
(Ruigrok, Peck and Tacheva, 2007), as foreign members can add valuable and diverse expertise
to the board which domestic members do not possess (Chen et al., 2008). Miller and Del
Carmen Triana (2009) found that nationality diversity is positively related to the innovation
performance of a firm and, therefore, supports an innovation strategy. Greater diverse BoDs
and TMTs in terms of nationality lead to higher firm value which makes the firm financially stronger, causing it to be able to execute larger investments (Carter et al., 2003). Moreover, prior research found that nationality diversity is positively related to both firm reputation and firms’ innovation investments because firms with greater nationality diversity are better able to incorporate the needs and demands of their environment (Miller and Del Carmen Triana, 2009). Accordingly, it is expected that nationality diversity positively impacts the relationship between CSRE and firms’ energy investments.
Hypothesis 2c: The positive effect of CSRE on firms’ energy investments will be stronger for firms having BoDs and TMTs with greater identity diversity.
Figure 1: Conceptual Model
The discussed hypotheses provided the foundation for the development of the conceptual
model in Figure 1. The model shows the proposed relationship that examines whether CSRE
positively impacts firms’ energy investments, building on institutional theory. Subsequently,
the proposed impact of the BoD and TMT diversity clusters is shown, based on the stakeholder
theory.
METHOD
Data collection and sample
The sample used in this study included 227 firms that responded to the questionnaire of the Carbon Disclosure Project (CDP). The CDP is a non-governmental and non-profit organization, which investigates firms’ responses to climate change and emissions management (Li, Huang, Ren, Chen and Ning, 2016; Luo, Lan and Tang, 2012). The CDP data covers a management section about governance, strategy and sustainable initiatives, a climate change risks & opportunities section and an emissions section (CDP questionnaire 2017). The CDP data is used for a robust number of published articles each year, indicating the relevance of the data (Hahn, Reimsbach and Schiemann, 2015). Data from the CDP was taken from the years 2013 until 2017. Data regarding firms’ renewable energy investments was obtained from the CDP’s database. Firms entered their investment initiatives regarding renewable energy by answering specific questions in the questionnaire. The questions used for this study can be found in appendix A. These investments initiatives regarding renewable energy were added up to derive a total of investments in renewable energy per year for each firm.
Financial data was used to assess the relative size of firms’ energy investments. The firms’
energy investments were compared with their total R&D expenditure to calculate the percentage of the total R&D expenditures that were invested in renewable energy initiatives.
This information was extracted from Compustat’s Capital IQ – Fundamentals Annual database.
The Compustat database provides insights in complex specific industry business sectors from
credible sources (SPGlobal, 2020). The Compustat database is used as secondary data in
several studies that assess financial fundamentals of firms (e.g. Carter et al., 2003; Harjoto et
al., 2014; Sadorsky, 2012). Information about countries’ share of renewable energy was
obtained from the International Energy Agency (IEA) database. The IEA is an autonomous
intergovernmental organization that acts as a policy advisor to governments and has a broad
role in promoting renewable energy. Data about the share of renewable energy was extracted
from the IEA database for the years 2013 until 2017. Relevant countries for this study were
determined based on the headquarter locations of the firms within the sample. Information
about BoD and TMT diversity was obtained from the BoardEx database. BoardEx is a
comprehensive, highly accurate database covering more than 1.8 million organizations and
over 1.3 million individuals that lead them (BoardEx, 2020). The BoardEx data is collected
from credible published sources and cannot be edited by users. The information about BoD
and TMT diversity was also extracted for the years 2013 until 2017 for most of the diversity dimensions (e.g. age and gender diversity). For some diversity dimensions, the relevant data transcends this 5-year timeframe (e.g. number of past positions, years of work experience). A timeframe from 1933 until 2017 was used to obtain the relevant data for these dimensions.
Dependent variable
Firms’ renewable energy investments were reported in different currencies by the firms in the CDP questionnaire. In the final dataset used for this study, all investments were converted to US dollars. The currency in which each firm reported their investments were given by the firms themselves, by answering an additional question of the questionnaire. The investment initiatives were given on a one-year scale, so no exact investment dates were provided.
Therefore, a fairly arbitrary point was taken to determine the exchange rate. For every year, the exchange rate of July 1 was taken, since this point is exactly halfway the year. This means, for instance, that the relevant energy investments of a particular firm for the year 2013, reported in Euros, were converted to US dollars by taking the EUR-USD exchange rate of July 1, 2013.
Subsequently, the total investment in renewable energy of each firm was divided by its total R&D expenditure for that year. By doing so, firms’ energy investments were calculated as a percentage of their R&D expenditures. Given that firms aim for a roughly constant ratio of R&D expenditure to employment or sales (Coad and Rao, 2010), an increase of renewable energy investments would in most cases also lead to a higher percentage.
Independent variable
Data regarding countries’ share of renewable energy was extracted from the IEA database as a
percentage of their total energy consumption. Subsequently, the year by year increase or
decrease was calculated to examine the extent to which a country increased or decreased its
share of renewable energy. The use of relative data for calculations is a common approach in
studies regarding renewable energy subsidies (Shen and Luo, 2015). This approach is adopted
in this research, because the change of the share of renewable energy is a better proxy for the
commitment of a country towards renewable energy than the absolute term. For example, a
country with a high share of renewable energy in absolute terms does not have to be still
pushing firms towards higher energy investments, because the country already reached that
large share of renewable energy. The change in the share of renewable energy does represent
the commitment, as it represents the current activity of the country regarding renewable energy.
Moderator
As explained in the theoretical background, BoD and TMT diversity was measured using the clusters experience, educational background and identity. These clusters containing seven diversity dimensions, that have been extensively studied in prior research: age, gender, nationality, qualification, Ivy League background, positions experience and working experience in years (Bernile et al., 2018; Harjoto et al., 2014; Kumar and Paraskevas, 2018).
These dimensions were coded as follows. Gender was coded as ‘male’ or ‘female’. Nationality was coded based on the work of Rhonen and Shenkar (1985) that reviewed eight highly relevant empirical studies (e.g. the work of Hofstede) that categorized countries based on their employee work attitudes. They presented a comprehensive final synthesis that include eight categories in which the countries were classified: Nordic, Germanic, Anglo, Latin European, Latin American, Far Eastern, Arab, North Eatern and Independent (Rhonen and Shenkar, 1985). These categories are used to classify the countries used in this study and calculate the nationality diversity. The categorization of qualification and Ivy League diversity was based on the work of Zhu and Shen (2016). They classified directors based on qualification as the highest level of degree they obtained. All directors were classified into one of the four categories: PhD, Masters, Bachelors, or lower (Zhu and Shen, 2016). Subsequently, they coded Ivy League diversity binary, by setting it to 1 if a degree was obtained from an Ivy League school, and 0 otherwise (Zhu and Shen, 2016). This study copied these approaches. Experience was measured as the number of positions and the number of years of experience a director or executive has. The age of the directors and executives was calculated separately for each year of the timeframe from 2013 until 2017 used in this study. As age and experience diversity are continuous variables, these were not coded into particular categories.
Each of the mentioned dimensions, except from the continuous variables age and experience,
were measured along the Blau’s diversity index (Blau, 1977), using the formula 1 − ∑(%&)
!,
where Pi equals the proportion of individuals on a given board or TMT in the ith category of a
given dimension. The result of the Blau’s diversity index equals the probability that two entities
randomly taken from a dataset represent a different type. The Blau’s index of diversity is not
suitable for calculations with continuous variables. Therefore, the age and experience
dimensions were measured using the standardized coefficient of variation, as that is widely
used to measure diversity for continuous variables (Zhu and Shen, 2016).
Control variable
The results of this study are controlled for firm size. Larger firms have in general more financial capabilities to make larger investments, which could affect firms’ investments in renewable energy, regardless the environmental pressures that the firm is facing. To control for this phenomenon, the firm size is included into all of the calculations. Based on other scholars, logarithm of the total number of employees a firm has is used as a proxy for firm size (e.g. De Groot, Verhoef and Nijkamp, 2001; Zhu and Shen, 2016). This controls for the possibility that firms may invest significantly more in renewable energy based on their financial capabilities.
This control variable is included in all statistical analysis.
Data analysis
Table 2 shows some summary statistics about the sample. It shows the number of firms that made investments in energy. The table shows that the number of firms that made energy- related investments increased every year. The average investments in renewable energy only decreased in 2015 but went up for the rest of the years. In 2017, investments in renewable energy were widely adopted by the firms within the sample.
Table 2: summary statistics on sample
Because this study focuses on institutional pressure on firms to make certain investments, it is likely that there will be some sort of time lag. Governments that are now deciding to improve their share of renewable energy, cannot exert pressure on firms at the exact same time.
Therefore, data analysis was performed with time-lags of zero until three years, to discover the
strength and the length of the impact of CSRE on firms’ energy investments. Therefore, the
proposed moderating effect of BoD and TMT diversity was also taken with a time lag of one
to three years to discover the strength and the length of the moderating effect. The hypotheses
were tested using hierarchical regression analysis. The independent and moderating variables
were standardized to put them on the same scale before including them in the calculations.
RESULTS
Table 3 contains the main values, standard deviations, and correlation effects for the variables used in this study. Most of the dimensions that are measured within the three clusters (experience, educational background and identity) showed statistically significant correlation.
As shown in Table 3, there are relatively large differences in diversity between the dimensions.
The average diversity for qualification and experience is fairly high, while the average diversity for age is relatively low. Since the diversity variables are measured using the Blau’s Index (except from age and the experience diversity dimensions, which are measured using the standardized coefficient of variation), the minimum value equals 0 for a completely homogeneous BoD or TMT. Conversely, the maximum empirical diversity takes place when the Blau’s Index equals 0.99, for a completely heterogenous BoD or TMT.
Adopting the approach of Zhu and Sarkis (2007), hierarchical moderated regression analysis is used to test the hypotheses of this study. Hierarchical moderated regression analysis is used because the relationship between the variables is fairly linear and the residuals are distributed randomly. Multicollinearity can be a serious issue in moderated regression analysis, as one factor could be highly correlated with other factors and aspects, which might lead to inflated standard errors and misinterpretations of the statistical significance of the regression result (Zhu and Sarkis, 2007). Therefore, the ‘centering’ approach is used by standardizing all variables to mitigate any potential multicollinearity (Tatikonda and Rosenthal, 2000).
Subsequently, the hypotheses were tested for four different time lags, as there is a delay expected between the start of governmental commitment towards renewable energy and the exerted pressure to increase firms’ energy investments. The time frames used in this study starts from direct effect (i.e. a time lag of zero) (T0) up and until a time lag of three years (T-3).
Hierarchical moderated regression analysis is performed for all different points in time.
No significant effect is found for the relationship between CSRE and firms’ energy investments for T0, which is consistent with the prediction of this paper that it costs a certain amount of time to move firms towards larger energy investments. Analysis show that there is evidence for a positive relationship between CSRE and firms’ energy investments for T-1 (coefficient of 0.172, which is significant at P < 0.01), T-2 (coefficient of 0.247, which is significant at P
< 0.001) and T-3 (coefficient of 0.201, which is significant at P < 0.01).
Table 3: Descriptive statistics and Pearson correlation coefficients
Regarding the moderating diversity dimensions, the strongest impacts are found for T-2 and T- 3. From the analysis, it appears that all the diversity dimensions that are significant for T-1, are also significant for T-2 and T-3 and vice versa. Only the qualification diversity dimension for TMT executives appeared to be negatively significant for T-3, while this dimension did not provide significant results for T-1 and T-2. Naturally, there are differences in the coefficients of the variables between the three different lags in time. For clarity reasons, this section will only show tables of the results for T-2, as that appeared the time frame with the strongest significant coefficients. The considerations in this section regarding the time lag of two years will also remain valid for T-1 and T-3 in most cases, as there are no substantial differences in results between these time frames. The tables containing the hierarchical moderating regressions for T-1 and T-3 can be found in appendix B and C.
Table 4 shows the results of the hierarchical regression between CSRE and firms’ energy investments, including the moderating effect of experience on this relationship. As shown in the table, the change of CSRE is positively associated with firms’ energy investments. The coefficient is 0.247, which is significant at P < 0.001. This indicates that an increase of CSRES by one standard deviation, increases firms’ energy investments by 0.247 standard deviation.
Table 4: Hierarchical regression analysis with experience diversity
This finding is consistent with the prediction of this paper that countries that achieve a relative larger proportion of renewable energy, also influence firms located within that country to make larger energy investments. Therefore, hypothesis 1 is supported.
In addition, Table 4 also shows the effects of experience diversity on this relationship.
Interestingly, most diversity dimensions regarding experience seem to negatively influence the relationship of CSRE on firms’ energy investments, and these effects are completely different for BoD and TMT. Although most coefficients are found to be nonsignificant, BoD positions diversity and TMT years diversity are found to significant negatively moderate the relationship between CSRE and firms’ energy investments. The coefficient of BoD positions diversity is
−0.215, which is significant at P < 0.01, while the coefficient of TMT years diversity is −0.179, which is significant at P < 0.10. This means that a board of directors with greater position diversity and a top management team with greater years diversity negatively impacts the relationship between CSRE and firms’ energy investments. Moreover, it shows that the impact of greater BoD positions diversity is larger than the impact of greater TMT years diversity. In addition, the results show that the adjusted R squared increased to 0.078 when including the moderating dimensions. This means that 7.8% of the variance is explained by the included variables in this model. These results are consistent with hypothesis 2a that states that greater experience diversity will have a negative moderating effect on the relationship between CSRE and firms’ energy investments. However, there are no significant effects found for age diversity. Therefore, hypothesis 2a is only partly supported.
Table 5 shows that BoD qualification diversity and TMT Ivy League diversity have a significantly positive effect on the relationship between CSRE and firms’ energy investments.
There are no significant effects found for BoD Ivy League diversity and TMT qualification diversity. The coefficient of BoD qualification diversity is 0.234, which is significant at P <
0.001. The coefficient of TMT Ivy League diversity is 0.434, which is significant at P < 0.001.
Moreover, the adjusted R squared increases substantially after including the interaction effects
of the moderation. As shown in Table 5, the CSRE and diversity dimensions related to
educational background explain 15.8% of the variance of the model. These findings are
consistent with the prediction of this paper that greater diversity in educational background
positively impacts the relationship of CSRE on firms’ energy investments. Therefore,
hypothesis 2b is supported, although the moderation effect only exists for BoD qualification
Table 5: Hierarchical regression analysis with educational background diversity
Interestingly, there is again a large difference between the results for BoD diversity and TMT diversity. BoD qualification diversity positively impacts the relationship of CSRE on firms’
energy investments, while the impact of TMT qualification diversity is nonsignificant. This is
contrariwise for Ivy League diversity. BoD Ivy League diversity has a nonsignificant impact,
while TMT Ivy League diversity significant positively impacts the relationship between CSRE
and firms’ energy investments. For the results of the T-3 time lag, the contrasting results for
BoD and TMT became even larger, as the interaction effect of TMT qualification diversity
became negatively significant. For T-3, the strength of the coefficient for TMT qualification
diversity increased to -0.250, which is significant at P < 0.05. This means that, for a time lag
of 3 years, BoD qualification diversity positively impacts the relationship between CSRE and
firms’ energy investments, while TMT qualification diversity negatively impacts this
relationship. In addition, Table 5 also shows that the impact of TMT Ivy League diversity is
not limited to the interaction effect, as TMT Ivy League diversity also impacts firms’ energy
investments directly as independent variable. As shown in Table 5, the coefficient of this
relationship is 0.353, which is significant at P < 0.001. This direct effect of TMT Ivy League
diversity on firms’ energy investment is also found for the T-3 time lag. For T-1, only the
interaction effect of Ivy League diversity appears to be significant.
Table 6: Hierarchical regression analysis with identity diversity
